WorldWideScience

Sample records for prognostic model based

  1. Distributed Prognostics Based on Structural Model Decomposition

    Data.gov (United States)

    National Aeronautics and Space Administration — Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based...

  2. A Model-Based Prognostics Approach Applied to Pneumatic Valves

    Data.gov (United States)

    National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

  3. A Model-based Prognostics Approach Applied to Pneumatic Valves

    Data.gov (United States)

    National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

  4. Model-based Prognostics under Limited Sensing

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics is crucial to providing reliable condition-based maintenance decisions. To obtain accurate predictions of component life, a variety of sensors are often...

  5. Model-based Prognostics with Concurrent Damage Progression Processes

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics approaches rely on physics-based models that describe the behavior of systems and their components. These models must account for the several...

  6. A Model-based Avionic Prognostic Reasoner (MAPR)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and...

  7. Model-based Prognostics with Fixed-lag Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics exploits domain knowl- edge of the system, its components, and how they fail by casting the underlying physical phenom- ena in a...

  8. Electrochemistry-based Battery Modeling for Prognostics

    Science.gov (United States)

    Daigle, Matthew J.; Kulkarni, Chetan Shrikant

    2013-01-01

    Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.

  9. Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

    Science.gov (United States)

    Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

  10. A Physics-Based Modeling Framework for Prognostic Studies

    Science.gov (United States)

    Kulkarni, Chetan S.

    2014-01-01

    Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable

  11. Physics based Degradation Modeling and Prognostics of Electrolytic Capacitors under Electrical Overstress Conditions

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper proposes a physics based degradation modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors are critical components in...

  12. Prognostics Health Management and Physics based failure Models for Electrolytic Capacitors

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors and MOSFETs are the two major...

  13. Physics Based Modeling and Prognostics of Electrolytic Capacitors

    Science.gov (United States)

    Kulkarni, Chetan; Ceyla, Jose R.; Biswas, Gautam; Goebel, Kai

    2012-01-01

    This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors have become critical components in electronics systems in aeronautics and other domains. Degradations and faults in DC-DC converter unit propagates to the GPS and navigation subsystems and affects the overall solution. Capacitors and MOSFETs are the two major components, which cause degradations and failures in DC-DC converters. This type of capacitors are known for its low reliability and frequent breakdown on critical systems like power supplies of avionics equipment and electrical drivers of electromechanical actuators of control surfaces. Some of the more prevalent fault effects, such as a ripple voltage surge at the power supply output can cause glitches in the GPS position and velocity output, and this, in turn, if not corrected will propagate and distort the navigation solution. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

  14. A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

    Science.gov (United States)

    Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

  15. Modeling for Battery Prognostics

    Science.gov (United States)

    Kulkarni, Chetan S.; Goebel, Kai; Khasin, Michael; Hogge, Edward; Quach, Patrick

    2017-01-01

    For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient

  16. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

    The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...... monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution...

  17. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

    monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

  18. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud

    2017-01-01

    monitoring, fault detection and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

  19. Physics Based Electrolytic Capacitor Degradation Models for Prognostic Studies under Thermal Overstress

    Science.gov (United States)

    Kulkarni, Chetan S.; Celaya, Jose R.; Goebel, Kai; Biswas, Gautam

    2012-01-01

    Electrolytic capacitors are used in several applications ranging from power supplies on safety critical avionics equipment to power drivers for electro-mechanical actuators. This makes them good candidates for prognostics and health management research. Prognostics provides a way to assess remaining useful life of components or systems based on their current state of health and their anticipated future use and operational conditions. Past experiences show that capacitors tend to degrade and fail faster under high electrical and thermal stress conditions that they are often subjected to during operations. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

  20. Enhanced Prognostic Model for Lithium Ion Batteries Based on Particle Filter State Transition Model Modification

    Directory of Open Access Journals (Sweden)

    Buddhi Arachchige

    2017-11-01

    Full Text Available This paper focuses on predicting the End of Life and End of Discharge of Lithium ion batteries using a battery capacity fade model and a battery discharge model. The proposed framework will be able to estimate the Remaining Useful Life (RUL and the Remaining charge through capacity fade and discharge models. A particle filter is implemented that estimates the battery’s State of Charge (SOC and State of Life (SOL by utilizing the battery’s physical data such as voltage, temperature, and current measurements. The accuracy of the prognostic framework has been improved by enhancing the particle filter state transition model to incorporate different environmental and loading conditions without retuning the model parameters. The effect of capacity fade in the reduction of the EOD (End of Discharge time with cycling has also been included, integrating both EOL (End of Life and EOD prediction models in order to get more accuracy in the estimations.

  1. Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

    Science.gov (United States)

    Daigle, Matthew John; Goebel, Kai Frank

    2010-01-01

    Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

  2. A model-based prognostic approach to predict interconnect failure using impedance analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Dae Il; Yoon, Jeong Ah [Dept. of System Design and Control Engineering. Ulsan National Institute of Science and Technology, Ulsan (Korea, Republic of)

    2016-10-15

    The reliability of electronic assemblies is largely affected by the health of interconnects, such as solder joints, which provide mechanical, electrical and thermal connections between circuit components. During field lifecycle conditions, interconnects are often subjected to a DC open circuit, one of the most common interconnect failure modes, due to cracking. An interconnect damaged by cracking is sometimes extremely hard to detect when it is a part of a daisy-chain structure, neighboring with other healthy interconnects that have not yet cracked. This cracked interconnect may seem to provide a good electrical contact due to the compressive load applied by the neighboring healthy interconnects, but it can cause the occasional loss of electrical continuity under operational and environmental loading conditions in field applications. Thus, cracked interconnects can lead to the intermittent failure of electronic assemblies and eventually to permanent failure of the product or the system. This paper introduces a model-based prognostic approach to quantitatively detect and predict interconnect failure using impedance analysis and particle filtering. Impedance analysis was previously reported as a sensitive means of detecting incipient changes at the surface of interconnects, such as cracking, based on the continuous monitoring of RF impedance. To predict the time to failure, particle filtering was used as a prognostic approach using the Paris model to address the fatigue crack growth. To validate this approach, mechanical fatigue tests were conducted with continuous monitoring of RF impedance while degrading the solder joints under test due to fatigue cracking. The test results showed the RF impedance consistently increased as the solder joints were degraded due to the growth of cracks, and particle filtering predicted the time to failure of the interconnects similarly to their actual timesto- failure based on the early sensitivity of RF impedance.

  3. Predicting stabilizing treatment outcomes for complex posttraumatic stress disorder and dissociative identity disorder: an expertise-based prognostic model

    NARCIS (Netherlands)

    Baars, E.W.; van der Hart, O.; Nijenhuis, E.R.S.; Chu, J.A.; Glas, G.; Draaijer, N.

    2011-01-01

    The purpose of this study was to develop an expertise-based prognostic model for the treatment of complex posttraumatic stress disorder (PTSD) and dissociative identity disorder (DID).We developed a survey in 2 rounds: In the first round we surveyed 42 experienced therapists (22 DID and 20 complex

  4. Towards A Model-based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

    Directory of Open Access Journals (Sweden)

    Gautam Biswas

    2012-12-01

    Full Text Available This paper presents a model-driven methodology for predict- ing the remaining useful life of electrolytic capacitors. This methodology adopts a Kalman filter approach in conjunction with an empirical state-based degradation model to predict the degradation of capacitor parameters through the life of the capacitor. Electrolytic capacitors are important components of systems that range from power supplies on critical avion- ics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their critical role in the system, they are good candidates for component level prognostics and health management. Prognostics provides a way to assess remain- ing useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. This paper proposes and empirical degradation model and discusses experimental results for an accelerated aging test performed on a set of identical capacitors subjected to electrical stress. The data forms the basis for developing the Kalman-filter based remaining life prediction algorithm.

  5. Multistream sensor fusion-based prognostics model for systems with single failure modes

    International Nuclear Information System (INIS)

    Fang, Xiaolei; Paynabar, Kamran; Gebraeel, Nagi

    2017-01-01

    Advances in sensor technology have facilitated the capability of monitoring the degradation of complex engineering systems through the analysis of multistream degradation signals. However, the varying levels of correlation with physical degradation process for different sensors, high-dimensionality of the degradation signals and cross-correlation among different signal streams pose significant challenges in monitoring and prognostics of such systems. To address the foregoing challenges, we develop a three-step multi-sensor prognostic methodology that utilizes multistream signals to predict residual useful lifetimes of partially degraded systems. We first identify the informative sensors via the penalized (log)-location-scale regression. Then, we fuse the degradation signals of the informative sensors using multivariate functional principal component analysis, which is capable of modeling the cross-correlation of signal streams. Finally, the third step focuses on utilizing the fused signal features for prognostics via adaptive penalized (log)-location-scale regression. We validate our multi-sensor prognostic methodology using simulation study as well as a case study of aircraft turbofan engines available from NASA repository.

  6. Predicting stabilizing treatment outcomes for complex posttraumatic stress disorder and dissociative identity disorder: an expertise-based prognostic model.

    Science.gov (United States)

    Baars, Erik W; van der Hart, Onno; Nijenhuis, Ellert R S; Chu, James A; Glas, Gerrit; Draijer, Nel

    2011-01-01

    The purpose of this study was to develop an expertise-based prognostic model for the treatment of complex posttraumatic stress disorder (PTSD) and dissociative identity disorder (DID). We developed a survey in 2 rounds: In the first round we surveyed 42 experienced therapists (22 DID and 20 complex PTSD therapists), and in the second round we surveyed a subset of 22 of the 42 therapists (13 DID and 9 complex PTSD therapists). First, we drew on therapists' knowledge of prognostic factors for stabilization-oriented treatment of complex PTSD and DID. Second, therapists prioritized a list of prognostic factors by estimating the size of each variable's prognostic effect; we clustered these factors according to content and named the clusters. Next, concept mapping methodology and statistical analyses (including principal components analyses) were used to transform individual judgments into weighted group judgments for clusters of items. A prognostic model, based on consensually determined estimates of effect sizes, of 8 clusters containing 51 factors for both complex PTSD and DID was formed. It includes the clusters lack of motivation, lack of healthy relationships, lack of healthy therapeutic relationships, lack of other internal and external resources, serious Axis I comorbidity, serious Axis II comorbidity, poor attachment, and self-destruction. In addition, a set of 5 DID-specific items was constructed. The model is supportive of the current phase-oriented treatment model, emphasizing the strengthening of the therapeutic relationship and the patient's resources in the initial stabilization phase. Further research is needed to test the model's statistical and clinical validity.

  7. Model-based prognostics for batteries which estimates useful life and uses a probability density function

    Science.gov (United States)

    Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor)

    2012-01-01

    This invention develops a mathematical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to the internal processes of the battery and validated using experimental data. Effects of temperature and load current have also been incorporated into the model. Subsequently, the model has been used in a Particle Filtering framework to make predictions of remaining useful life for individual discharge cycles as well as for cycle life. The prediction performance was found to be satisfactory as measured by performance metrics customized for prognostics for a sample case. The work presented here provides initial steps towards a comprehensive health management solution for energy storage devices.

  8. Prognostic model based on nailfold capillaroscopy for identifying Raynaud's phenomenon patients at high risk for the development of a scleroderma spectrum disorder: PRINCE (prognostic index for nailfold capillaroscopic examination).

    Science.gov (United States)

    Ingegnoli, Francesca; Boracchi, Patrizia; Gualtierotti, Roberta; Lubatti, Chiara; Meani, Laura; Zahalkova, Lenka; Zeni, Silvana; Fantini, Flavio

    2008-07-01

    To construct a prognostic index based on nailfold capillaroscopic examinations that is capable of predicting the 5-year transition from isolated Raynaud's phenomenon (RP) to RP secondary to scleroderma spectrum disorders (SSDs). The study involved 104 consecutive adult patients with a clinical history of isolated RP, and the index was externally validated in another cohort of 100 patients with the same characteristics. Both groups were followed up for 1-8 years. Six variables were examined because of their potential prognostic relevance (branching, enlarged and giant loops, capillary disorganization, microhemorrhages, and the number of capillaries). The only factors that played a significant prognostic role were the presence of giant loops (hazard ratio [HR] 2.64, P = 0.008) and microhemorrhages (HR 2.33, P = 0.01), and the number of capillaries (analyzed as a continuous variable). The adjusted prognostic role of these factors was evaluated by means of multivariate regression analysis, and the results were used to construct an algorithm-based prognostic index. The model was internally and externally validated. Our prognostic capillaroscopic index identifies RP patients in whom the risk of developing SSDs is high. This model is a weighted combination of different capillaroscopy parameters that allows physicians to stratify RP patients easily, using a relatively simple diagram to deduce the prognosis. Our results suggest that this index could be used in clinical practice, and its further inclusion in prospective studies will undoubtedly help in exploring its potential in predicting treatment response.

  9. A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

    Science.gov (United States)

    Schmidt, Rainer; Gierl, Lothar

    2005-03-01

    Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

  10. An adaptive functional regression-based prognostic model for applications with missing data

    International Nuclear Information System (INIS)

    Fang, Xiaolei; Zhou, Rensheng; Gebraeel, Nagi

    2015-01-01

    Most prognostic degradation models rely on a relatively accurate and comprehensive database of historical degradation signals. Typically, these signals are used to identify suitable degradation trends that are useful for predicting lifetime. In many real-world applications, these degradation signals are usually incomplete, i.e., contain missing observations. Often the amount of missing data compromises the ability to identify a suitable parametric degradation model. This paper addresses this problem by developing a semi-parametric approach that can be used to predict the remaining lifetime of partially degraded systems. First, key signal features are identified by applying Functional Principal Components Analysis (FPCA) to the available historical data. Next, an adaptive functional regression model is used to model the extracted signal features and the corresponding times-to-failure. The model is then used to predict remaining lifetimes and to update these predictions using real-time signals observed from fielded components. Results show that the proposed approach is relatively robust to significant levels of missing data. The performance of the model is evaluated and shown to provide significantly accurate predictions of residual lifetime using two case studies. - Highlights: • We model degradation signals with missing data with the goal of predicting remaining lifetime. • We examine two types of signal characteristics, fragmented and sparse. • We provide framework that updates remaining life predictions by incorporating real-time signal observations. • For the missing data, we show that the proposed model outperforms other benchmark models. • For the complete data, we show that the proposed model performs at least as good as a benchmark model

  11. Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab

    International Nuclear Information System (INIS)

    An, Dawn; Choi, Joo-Ho; Kim, Nam Ho

    2013-01-01

    This paper presents a Matlab-based tutorial for model-based prognostics, which combines a physical model with observed data to identify model parameters, from which the remaining useful life (RUL) can be predicted. Among many model-based prognostics algorithms, the particle filter is used in this tutorial for parameter estimation of damage or a degradation model. The tutorial is presented using a Matlab script with 62 lines, including detailed explanations. As examples, a battery degradation model and a crack growth model are used to explain the updating process of model parameters, damage progression, and RUL prediction. In order to illustrate the results, the RUL at an arbitrary cycle are predicted in the form of distribution along with the median and 90% prediction interval. This tutorial will be helpful for the beginners in prognostics to understand and use the prognostics method, and we hope it provides a standard of particle filter based prognostics. -- Highlights: ► Matlab-based tutorial for model-based prognostics is presented. ► A battery degradation model and a crack growth model are used as examples. ► The RUL at an arbitrary cycle are predicted using the particle filter

  12. A Model-Based Prognostics Methodology For Electrolytic Capacitors Based On Electrical Overstress Accelerated Aging

    Data.gov (United States)

    National Aeronautics and Space Administration — A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical...

  13. A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging

    Data.gov (United States)

    National Aeronautics and Space Administration — A remaining useful life prediction methodology for elec- trolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical...

  14. The strong prognostic value of KELIM, a model-based parameter from CA 125 kinetics in ovarian cancer

    DEFF Research Database (Denmark)

    You, Benoit; Colomban, Olivier; Heywood, Mark

    2013-01-01

    Unexpected results were recently reported about the poor surrogacy of Gynecologic Cancer Intergroup (GCIG) defined CA-125 response in recurrent ovarian cancer (ROC) patients. Mathematical modeling may help describe CA-125 decline dynamically and discriminate prognostic kinetic parameters....

  15. Simple prognostic model for patients with advanced cancer based on performance status.

    Science.gov (United States)

    Jang, Raymond W; Caraiscos, Valerie B; Swami, Nadia; Banerjee, Subrata; Mak, Ernie; Kaya, Ebru; Rodin, Gary; Bryson, John; Ridley, Julia Z; Le, Lisa W; Zimmermann, Camilla

    2014-09-01

    Providing survival estimates is important for decision making in oncology care. The purpose of this study was to provide survival estimates for outpatients with advanced cancer, using the Eastern Cooperative Oncology Group (ECOG), Palliative Performance Scale (PPS), and Karnofsky Performance Status (KPS) scales, and to compare their ability to predict survival. ECOG, PPS, and KPS were completed by physicians for each new patient attending the Princess Margaret Cancer Centre outpatient Oncology Palliative Care Clinic (OPCC) from April 2007 to February 2010. Survival analysis was performed using the Kaplan-Meier method. The log-rank test for trend was employed to test for differences in survival curves for each level of performance status (PS), and the concordance index (C-statistic) was used to test the predictive discriminatory ability of each PS measure. Measures were completed for 1,655 patients. PS delineated survival well for all three scales according to the log-rank test for trend (P statistic was similar for all three scales and ranged from 0.63 to 0.64. We present a simple tool that uses PS alone to prognosticate in advanced cancer, and has similar discriminatory ability to more complex models. Copyright © 2014 by American Society of Clinical Oncology.

  16. A Discussion on Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

    Data.gov (United States)

    National Aeronautics and Space Administration — This article presented a discussion on uncertainty representation and management for model-based prog- nostics methodologies based on the Bayesian tracking framework...

  17. A state-space-based prognostics model for lithium-ion battery degradation

    International Nuclear Information System (INIS)

    Xu, Xin; Chen, Nan

    2017-01-01

    This paper proposes to analyze the degradation of lithium-ion batteries with the sequentially observed discharging profiles. A general state-space model is developed in which the observation model is used to approximate the discharging profile of each cycle, the corresponding parameter vector is treated as the hidden state, and the state-transition model is used to track the evolution of the parameter vector as the battery ages. The EM and EKF algorithms are adopted to estimate and update the model parameters and states jointly. Based on this model, we construct prediction on the end of discharge times for unobserved cycles and the remaining useful cycles before the battery failure. The effectiveness of the proposed model is demonstrated using a real lithium-ion battery degradation data set. - Highlights: • Unifying model for Li-Ion battery SOC and SOH estimation. • Extended Kalman filter based efficient inference algorithm. • Using voltage curves in discharging to have wide validity.

  18. Concordance for prognostic models with competing risks

    DEFF Research Database (Denmark)

    Wolbers, Marcel; Blanche, Paul; Koller, Michael T

    2014-01-01

    The concordance probability is a widely used measure to assess discrimination of prognostic models with binary and survival endpoints. We formally define the concordance probability for a prognostic model of the absolute risk of an event of interest in the presence of competing risks and relate i...

  19. Diagnostic and Prognostic Models for Generator Step-Up Transformers

    Energy Technology Data Exchange (ETDEWEB)

    Vivek Agarwal; Nancy J. Lybeck; Binh T. Pham

    2014-09-01

    In 2014, the online monitoring (OLM) of active components project under the Light Water Reactor Sustainability program at Idaho National Laboratory (INL) focused on diagnostic and prognostic capabilities for generator step-up transformers. INL worked with subject matter experts from the Electric Power Research Institute (EPRI) to augment and revise the GSU fault signatures previously implemented in the Electric Power Research Institute’s (EPRI’s) Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. Two prognostic models were identified and implemented for GSUs in the FW-PHM Suite software. INL and EPRI demonstrated the use of prognostic capabilities for GSUs. The complete set of fault signatures developed for GSUs in the Asset Fault Signature Database of the FW-PHM Suite for GSUs is presented in this report. Two prognostic models are described for paper insulation: the Chendong model for degree of polymerization, and an IEEE model that uses a loading profile to calculates life consumption based on hot spot winding temperatures. Both models are life consumption models, which are examples of type II prognostic models. Use of the models in the FW-PHM Suite was successfully demonstrated at the 2014 August Utility Working Group Meeting, Idaho Falls, Idaho, to representatives from different utilities, EPRI, and the Halden Research Project.

  20. A prognostic model of triple-negative breast cancer based on miR-27b-3p and node status.

    Directory of Open Access Journals (Sweden)

    Songjie Shen

    Full Text Available Triple-negative breast cancer (TNBC is an aggressive but heterogeneous subtype of breast cancer. This study aimed to identify and validate a prognostic signature for TNBC patients to improve prognostic capability and to guide individualized treatment.We retrospectively analyzed the prognostic performance of clinicopathological characteristics and miRNAs in a training set of 58 patients with invasive ductal TNBC diagnosed between 2002 and 2012. A prediction model was developed based on independent clinicopathological and miRNA covariates. The prognostic value of the model was further validated in a separate set of 41 TNBC patients diagnosed between 2007 and 2008.Only lymph node status was marginally significantly associated with poor prognosis of TNBC (P = 0.054, whereas other clinicopathological factors, including age, tumor size, histological grade, lymphovascular invasion, P53 status, Ki-67 index, and type of surgery, were not. The expression levels of miR-27b-3p, miR-107, and miR-103a-3p were significantly elevated in the metastatic group compared with the disease-free group (P value: 0.008, 0.005, and 0.050, respectively. The Cox proportional hazards regression analysis revealed that lymph node status and miR-27b-3p were independent predictors of poor prognosis (P value: 0.012 and 0.027, respectively. A logistic regression model was developed based on these two independent covariates, and the prognostic value of the model was subsequently confirmed in a separate validation set. The two different risk groups, which were stratified according to the model, showed significant differences in the rates of distant metastasis and breast cancer-related death not only in the training set (P value: 0.001 and 0.040, respectively but also in the validation set (P value: 0.013 and 0.012, respectively.This model based on miRNA and node status covariates may be used to stratify TNBC patients into different prognostic subgroups for potentially

  1. A prognostic model for soft tissue sarcoma of the extremities and trunk wall based on size, vascular invasion, necrosis, and growth pattern

    DEFF Research Database (Denmark)

    Carneiro, Ana; Bendahl, Par-Ola; Engellau, Jacob

    2011-01-01

    type, necrosis, and grade. METHODS:: Whole-tumor sections from 239 soft tissue sarcomas of the extremities were reviewed for the following prognostic factors: size, vascular invasion, necrosis, and growth pattern. A new prognostic model, referred to as SING (Size, Invasion, Necrosis, Growth......), was established and compared with other clinically applied systems. RESULTS:: Size, vascular invasion, necrosis, and peripheral tumor growth pattern provided independent prognostic information with hazard ratios of 2.2-2.6 for development of metastases in multivariate analysis. When these factors were combined...... into the prognostic model SING, high risk of metastasis was predicted with a sensitivity of 74% and a specificity of 85%. Moreover, the prognostic performance of SING compared favorably with other widely used systems. CONCLUSIONS:: SING represents a promising prognostic model, and vascular invasion and tumor growth...

  2. A prognostic model for soft tissue sarcoma of the extremities and trunk wall based on size, vascular invasion, necrosis, and growth pattern

    DEFF Research Database (Denmark)

    Carneiro, Ana; Bendahl, Par-Ola; Engellau, Jacob

    2011-01-01

    type, necrosis, and grade. METHODS:: Whole-tumor sections from 239 soft tissue sarcomas of the extremities were reviewed for the following prognostic factors: size, vascular invasion, necrosis, and growth pattern. A new prognostic model, referred to as SING (Size, Invasion, Necrosis, Growth...

  3. Prognostic modelling options for remaining useful life estimation by industry

    Science.gov (United States)

    Sikorska, J. Z.; Hodkiewicz, M.; Ma, L.

    2011-07-01

    Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

  4. Prognostics for Steam Generator Tube Rupture using Markov Chain model

    International Nuclear Information System (INIS)

    Kim, Gibeom; Heo, Gyunyoung; Kim, Hyeonmin

    2016-01-01

    This paper will describe the prognostics method for evaluating and forecasting the ageing effect and demonstrate the procedure of prognostics for the Steam Generator Tube Rupture (SGTR) accident. Authors will propose the data-driven method so called MCMC (Markov Chain Monte Carlo) which is preferred to the physical-model method in terms of flexibility and availability. Degradation data is represented as growth of burst probability over time. Markov chain model is performed based on transition probability of state. And the state must be discrete variable. Therefore, burst probability that is continuous variable have to be changed into discrete variable to apply Markov chain model to the degradation data. The Markov chain model which is one of prognostics methods was described and the pilot demonstration for a SGTR accident was performed as a case study. The Markov chain model is strong since it is possible to be performed without physical models as long as enough data are available. However, in the case of the discrete Markov chain used in this study, there must be loss of information while the given data is discretized and assigned to the finite number of states. In this process, original information might not be reflected on prediction sufficiently. This should be noted as the limitation of discrete models. Now we will be studying on other prognostics methods such as GPM (General Path Model) which is also data-driven method as well as the particle filer which belongs to physical-model method and conducting comparison analysis

  5. A framework for quantifying net benefits of alternative prognostic models.

    Science.gov (United States)

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

    2012-01-30

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd.

  6. Investigating the Effect of Damage Progression Model Choice on Prognostics Performance

    Data.gov (United States)

    National Aeronautics and Space Administration — The success of model-based approaches to systems health management depends largely on the quality of the underly- ing models. In model-based prognostics, it is...

  7. A molecular prognostic model predicts esophageal squamous cell carcinoma prognosis.

    Directory of Open Access Journals (Sweden)

    Hui-Hui Cao

    Full Text Available Esophageal squamous cell carcinoma (ESCC has the highest mortality rates in China. The 5-year survival rate of ESCC remains dismal despite improvements in treatments such as surgical resection and adjuvant chemoradiation, and current clinical staging approaches are limited in their ability to effectively stratify patients for treatment options. The aim of the present study, therefore, was to develop an immunohistochemistry-based prognostic model to improve clinical risk assessment for patients with ESCC.We developed a molecular prognostic model based on the combined expression of axis of epidermal growth factor receptor (EGFR, phosphorylated Specificity protein 1 (p-Sp1, and Fascin proteins. The presence of this prognostic model and associated clinical outcomes were analyzed for 130 formalin-fixed, paraffin-embedded esophageal curative resection specimens (generation dataset and validated using an independent cohort of 185 specimens (validation dataset.The expression of these three genes at the protein level was used to build a molecular prognostic model that was highly predictive of ESCC survival in both generation and validation datasets (P = 0.001. Regression analysis showed that this molecular prognostic model was strongly and independently predictive of overall survival (hazard ratio = 2.358 [95% CI, 1.391-3.996], P = 0.001 in generation dataset; hazard ratio = 1.990 [95% CI, 1.256-3.154], P = 0.003 in validation dataset. Furthermore, the predictive ability of these 3 biomarkers in combination was more robust than that of each individual biomarker.This technically simple immunohistochemistry-based molecular model accurately predicts ESCC patient survival and thus could serve as a complement to current clinical risk stratification approaches.

  8. Towards A Model-Based Prognostics Methodology For Electrolytic Capacitors: A Case Study Based On Electrical Overstress Accelerated Aging

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a model-driven methodology for predict- ing the remaining useful life of electrolytic capacitors. This methodology adopts a Kalman filter...

  9. [A prognostic model of a cholera epidemic].

    Science.gov (United States)

    Boev, B V; Bondarenko, V M; Prokop'eva, N V; San Román, R T; Raygoza-Anaya, M; García de Alba, R

    1994-01-01

    A new model for the prognostication of cholera epidemic on the territory of a large city is proposed. This model reflects the characteristic feature of contacting infection by sensitive individuals due to the preservation of Vibrio cholerae in their water habitat. The mathematical model of the epidemic quantitatively reflects the processes of the spread of infection by kinetic equations describing the interaction of the streams of infected persons, the causative agents and susceptible persons. The functions and parameters of the model are linked with the distribution of individuals according to the duration of the incubation period and infectious process, as well as the period of asymptomatic carrier state. The computer realization of the model by means of IBM PC/AT made it possible to study the cholera epidemic which took place in Mexico in 1833. The verified model of the cholera epidemic was used for the prognostication of the possible spread of this infection in Guadalajara, taking into account changes in the epidemiological situation and the size of the population, as well as improvements in sanitary and hygienic conditions, in the city.

  10. Aircraft Anomaly Prognostics, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Ridgetop Group will leverage its proven Electromechanical Actuator (EMA) prognostics methodology to develop an advanced model-based actuator prognostic reasoner...

  11. Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics has received considerable attention recently as an emerging sub-discipline within SHM. Prognosis is here strictly defined as “predicting the time at...

  12. A framework for quantifying net benefits of alternative prognostic models

    NARCIS (Netherlands)

    Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Feskens, E.J.M.; Kromhout, D.

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit)

  13. Comparison of two prognostic models for acute pulmonary embolism

    Directory of Open Access Journals (Sweden)

    Abd-ElRahim Ibrahim Youssef

    2016-10-01

    Conclusion: (1 There is an agreement to great extent in risk stratification of APE patients by PESI and ESC prognostic models, where mortality rate is increased among high risk classes of both models, (2 ESC prognostic model is more accurate than PESI model in mortality prediction of APE patients especially in the high risk class, (3 echocardiographic evidence of RVD and elevated plasma BNP can help to identify APE patients at increased risk of adverse short-term outcome and (4 integration of RVD assessment by echocardiography and BNP to clinical findings improves the prognostic value of ESC model.

  14. Model Adaptation for Prognostics in a Particle Filtering Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated....

  15. A framework for quantifying net benefits of alternative prognostic models

    OpenAIRE

    Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Ford, I.

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measure...

  16. Degradations analysis and aging modeling for health assessment and prognostics of PEMFC

    International Nuclear Information System (INIS)

    Jouin, Marine; Gouriveau, Rafael; Hissel, Daniel; Péra, Marie-Cécile; Zerhouni, Noureddine

    2016-01-01

    Applying prognostics to Proton Exchange Membrane Fuel Cell (PEMFC) stacks is a good solution to help taking actions extending their lifetime. However, it requires a great understanding of the degradation mechanisms and failures occurring within the stack. This task is not simple when applied to a PEMFC due to the different levels (stack - cells - components), the different scales and the multiple causes that lead to degradation. To overcome this problem, this work proposes a methodology dedicated to the setting of a framework and a modeling of the aging for prognostics. This methodology is based on a deep literature review and degradation analyses of PEMFC stacks. This analysis allows defining a proper vocabulary dedicated to PEMFC's prognostics and health management and a clear limited framework to perform prognostics. Then the degradations review is used to select critical components within the stack, and to define their critical failure mechanisms thanks the proposal of new fault trees. The impact of these critical components and mechanisms on the power loss during aging is included to the model for prognostics. This model is finally validated on four datasets with different mission profiles both for health assessment and prognostics. - Highlights: • A proper framework to perform PHM, particularly prognostics, of PEMFC is proposed. • A degradation analysis is performed. • A completely new model of PEMFC degradation is proposed. • SOH estimation is performed with very high coefficients of determination.

  17. A framework for quantifying net benefits of alternative prognostic models

    DEFF Research Database (Denmark)

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit......) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk...... reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple...

  18. On prognostic models, artificial intelligence and censored observations.

    Science.gov (United States)

    Anand, S S; Hamilton, P W; Hughes, J G; Bell, D A

    2001-03-01

    The development of prognostic models for assisting medical practitioners with decision making is not a trivial task. Models need to possess a number of desirable characteristics and few, if any, current modelling approaches based on statistical or artificial intelligence can produce models that display all these characteristics. The inability of modelling techniques to provide truly useful models has led to interest in these models being purely academic in nature. This in turn has resulted in only a very small percentage of models that have been developed being deployed in practice. On the other hand, new modelling paradigms are being proposed continuously within the machine learning and statistical community and claims, often based on inadequate evaluation, being made on their superiority over traditional modelling methods. We believe that for new modelling approaches to deliver true net benefits over traditional techniques, an evaluation centric approach to their development is essential. In this paper we present such an evaluation centric approach to developing extensions to the basic k-nearest neighbour (k-NN) paradigm. We use standard statistical techniques to enhance the distance metric used and a framework based on evidence theory to obtain a prediction for the target example from the outcome of the retrieved exemplars. We refer to this new k-NN algorithm as Censored k-NN (Ck-NN). This reflects the enhancements made to k-NN that are aimed at providing a means for handling censored observations within k-NN.

  19. Multiplex polymerase chain reaction-based prognostic models in diffuse large B-cell lymphoma patients treated with R-CHOP

    DEFF Research Database (Denmark)

    Green, Tina M; Jensen, Andreas K; Holst, René

    2016-01-01

    We present a multiplex analysis for genes known to have prognostic value in an attempt to design a clinically useful classification model in patients with diffuse large B-cell lymphoma (DLBCL). Real-time polymerase chain reaction was used to measure transcript levels of 28 relevant genes in 194 de...... models. The best model was validated in data from an online available R-CHOP treated cohort. With progression-free survival (PFS) as primary endpoint, the best performing IPI independent model incorporated the LMO2 and HLADQA1 as well as gene interactions for GCSAMxMIB1, GCSAMxCTGF and FOXP1xPDE4B....... This model assigned 33% of patients (n = 60) to poor outcome with an estimated 3-year PFS of 40% vs. 87% for low risk (n = 61) and intermediate (n = 60) risk groups (P model incorporated LMO2 and BCL2 and assigned 33% of the patients with a 3-year PFS of 35% vs...

  20. Application of Prognostic Mesoscale Modeling in the Southeast United States

    International Nuclear Information System (INIS)

    Buckley, R.L.

    1999-01-01

    A prognostic model is being used to provide regional forecasts for a variety of applications at the Savannah River Site (SRS). Emergency response dispersion models available at SRS use the space and time-dependent meteorological data provided by this model to supplement local and regional observations. Output from the model is also used locally to aid in forecasting at SRS, and regionally in providing forecasts of the potential time and location of hurricane landfall within the southeast United States

  1. Risk factors and prognostic models for perinatal asphyxia at term

    NARCIS (Netherlands)

    Ensing, S.

    2015-01-01

    This thesis will focus on the risk factors and prognostic models for adverse perinatal outcome at term, with a special focus on perinatal asphyxia and obstetric interventions during labor to reduce adverse pregnancy outcomes. For the majority of the studies in this thesis we were allowed to use data

  2. Practical options for selecting data-driven or physics-based prognostics algorithms with reviews

    International Nuclear Information System (INIS)

    An, Dawn; Kim, Nam H.; Choi, Joo-Ho

    2015-01-01

    This paper is to provide practical options for prognostics so that beginners can select appropriate methods for their fields of application. To achieve this goal, several popular algorithms are first reviewed in the data-driven and physics-based prognostics methods. Each algorithm’s attributes and pros and cons are analyzed in terms of model definition, model parameter estimation and ability to handle noise and bias in data. Fatigue crack growth examples are then used to illustrate the characteristics of different algorithms. In order to suggest a suitable algorithm, several studies are made based on the number of data sets, the level of noise and bias, availability of loading and physical models, and complexity of the damage growth behavior. Based on the study, it is concluded that the Gaussian process is easy and fast to implement, but works well only when the covariance function is properly defined. The neural network has the advantage in the case of large noise and complex models but only with many training data sets. The particle filter and Bayesian method are superior to the former methods because they are less affected by noise and model complexity, but work only when physical model and loading conditions are available. - Highlights: • Practical review of data-driven and physics-based prognostics are provided. • As common prognostics algorithms, NN, GP, PF and BM are introduced. • Algorithms’ attributes, pros and cons, and applicable conditions are discussed. • This will be helpful to choose the best algorithm for different applications

  3. Systematic review of prognostic models in traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Roberts Ian

    2006-11-01

    Full Text Available Abstract Background Traumatic brain injury (TBI is a leading cause of death and disability world-wide. The ability to accurately predict patient outcome after TBI has an important role in clinical practice and research. Prognostic models are statistical models that combine two or more items of patient data to predict clinical outcome. They may improve predictions in TBI patients. Multiple prognostic models for TBI have accumulated for decades but none of them is widely used in clinical practice. The objective of this systematic review is to critically assess existing prognostic models for TBI Methods Studies that combine at least two variables to predict any outcome in patients with TBI were searched in PUBMED and EMBASE. Two reviewers independently examined titles, abstracts and assessed whether each met the pre-defined inclusion criteria. Results A total of 53 reports including 102 models were identified. Almost half (47% were derived from adult patients. Three quarters of the models included less than 500 patients. Most of the models (93% were from high income countries populations. Logistic regression was the most common analytical strategy to derived models (47%. In relation to the quality of the derivation models (n:66, only 15% reported less than 10% pf loss to follow-up, 68% did not justify the rationale to include the predictors, 11% conducted an external validation and only 19% of the logistic models presented the results in a clinically user-friendly way Conclusion Prognostic models are frequently published but they are developed from small samples of patients, their methodological quality is poor and they are rarely validated on external populations. Furthermore, they are not clinically practical as they are not presented to physicians in a user-friendly way. Finally because only a few are developed using populations from low and middle income countries, where most of trauma occurs, the generalizability to these setting is limited.

  4. Model Adaptation for Prognostics in a Particle Filtering Framework

    Directory of Open Access Journals (Sweden)

    Bhaskar Saha

    2011-01-01

    Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  5. Model Adaptation for Prognostics in a Particle Filtering Framework

    Science.gov (United States)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  6. A copula-based sampling method for data-driven prognostics

    International Nuclear Information System (INIS)

    Xi, Zhimin; Jing, Rong; Wang, Pingfeng; Hu, Chao

    2014-01-01

    This paper develops a Copula-based sampling method for data-driven prognostics. The method essentially consists of an offline training process and an online prediction process: (i) the offline training process builds a statistical relationship between the failure time and the time realizations at specified degradation levels on the basis of off-line training data sets; and (ii) the online prediction process identifies probable failure times for online testing units based on the statistical model constructed in the offline process and the online testing data. Our contributions in this paper are three-fold, namely the definition of a generic health index system to quantify the health degradation of an engineering system, the construction of a Copula-based statistical model to learn the statistical relationship between the failure time and the time realizations at specified degradation levels, and the development of a simulation-based approach for the prediction of remaining useful life (RUL). Two engineering case studies, namely the electric cooling fan health prognostics and the 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology. - Highlights: • We develop a novel mechanism for data-driven prognostics. • A generic health index system quantifies health degradation of engineering systems. • Off-line training model is constructed based on the Bayesian Copula model. • Remaining useful life is predicted from a simulation-based approach

  7. An inflammation-based cumulative prognostic score system in patients with diffuse large B cell lymphoma in rituximab era.

    Science.gov (United States)

    Sun, Feifei; Zhu, Jia; Lu, Suying; Zhen, Zijun; Wang, Juan; Huang, Junting; Ding, Zonghui; Zeng, Musheng; Sun, Xiaofei

    2018-01-02

    Systemic inflammatory parameters are associated with poor outcomes in malignant patients. Several inflammation-based cumulative prognostic score systems were established for various solid tumors. However, there is few inflammation based cumulative prognostic score system for patients with diffuse large B cell lymphoma (DLBCL). We retrospectively reviewed 564 adult DLBCL patients who had received rituximab, cyclophosphamide, doxorubicin, vincristine and prednisolone (R-CHOP) therapy between Nov 1 2006 and Dec 30 2013 and assessed the prognostic significance of six systemic inflammatory parameters evaluated in previous studies by univariate and multivariate analysis:C-reactive protein(CRP), albumin levels, the lymphocyte-monocyte ratio (LMR), the neutrophil-lymphocyte ratio(NLR), the platelet-lymphocyte ratio(PLR)and fibrinogen levels. Multivariate analysis identified CRP, albumin levels and the LMR are three independent prognostic parameters for overall survival (OS). Based on these three factors, we constructed a novel inflammation-based cumulative prognostic score (ICPS) system. Four risk groups were formed: group ICPS = 0, ICPS = 1, ICPS = 2 and ICPS = 3. Advanced multivariate analysis indicated that the ICPS model is a prognostic score system independent of International Prognostic Index (IPI) for both progression-free survival (PFS) (p systemic inflammatory status was associated with clinical outcomes of patients with DLBCL in rituximab era. The ICPS model was shown to classify risk groups more accurately than any single inflammatory prognostic parameters. These findings may be useful for identifying candidates for further inflammation-related mechanism research or novel anti-inflammation target therapies.

  8. A continuous and prognostic convection scheme based on buoyancy, PCMT

    Science.gov (United States)

    Guérémy, Jean-François; Piriou, Jean-Marcel

    2016-04-01

    A new and consistent convection scheme (PCMT: Prognostic Condensates Microphysics and Transport), providing a continuous and prognostic treatment of this atmospheric process, is described. The main concept ensuring the consistency of the whole system is the buoyancy, key element of any vertical motion. The buoyancy constitutes the forcing term of the convective vertical velocity, which is then used to define the triggering condition, the mass flux, and the rates of entrainment-detrainment. The buoyancy is also used in its vertically integrated form (CAPE) to determine the closure condition. The continuous treatment of convection, from dry thermals to deep precipitating convection, is achieved with the help of a continuous formulation of the entrainment-detrainment rates (depending on the convective vertical velocity) and of the CAPE relaxation time (depending on the convective over-turning time). The convective tendencies are directly expressed in terms of condensation and transport. Finally, the convective vertical velocity and condensates are fully prognostic, the latter being treated using the same microphysics scheme as for the resolved condensates but considering the convective environment. A Single Column Model (SCM) validation of this scheme is shown, allowing detailed comparisons with observed and explicitly simulated data. Four cases covering the convective spectrum are considered: over ocean, sensitivity to environmental moisture (S. Derbyshire) non precipitating shallow convection to deep precipitating convection, trade wind shallow convection (BOMEX) and strato-cumulus (FIRE), together with an entire continental diurnal cycle of convection (ARM). The emphasis is put on the characteristics of the scheme which enable a continuous treatment of convection. Then, a 3D LAM validation is presented considering an AMMA case with both observations and a CRM simulation using the same initial and lateral conditions as for the parameterized one. Finally, global

  9. Elements of a unified prognostic model for secondary air contamination by resuspension

    International Nuclear Information System (INIS)

    Besnus, F.; Garger, E.; Gordeev, S.; Hollaender, W.; Kashparov, V.; Martinez-Serrano, J.; Mironov, V.; Nicholson, K.; Tschiersch, J.; Vintersved, I.

    1996-01-01

    Based on results of several joint experimental campaigns and an extensive literature survey, a prognostic model was constructed capable of predicting airborne activity concentrations and size distributions as well as soil surface activity concentrations as a function of time and meteorological conditions. Example scenario calculations show that agricultural practices are of lesser importance to secondary air contamination than dust storms immediately after primary deposition and forest fires

  10. Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

    Science.gov (United States)

    Yu, Jianbo

    2015-12-01

    Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

  11. A prognostic scoring model for survival after locoregional therapy in de novo stage IV breast cancer.

    Science.gov (United States)

    Kommalapati, Anuhya; Tella, Sri Harsha; Goyal, Gaurav; Ganti, Apar Kishor; Krishnamurthy, Jairam; Tandra, Pavan Kumar

    2018-05-02

    The role of locoregional treatment (LRT) remains controversial in de novo stage IV breast cancer (BC). We sought to analyze the role of LRT and prognostic factors of overall survival (OS) in de novo stage IV BC patients treated with LRT utilizing the National Cancer Data Base (NCDB). The objective of the current study is to create and internally validate a prognostic scoring model to predict the long-term OS for de novo stage IV BC patients treated with LRT. We included de novo stage IV BC patients reported to NCDB between 2004 and 2015. Patients were divided into LRT and no-LRT subsets. We randomized LRT subset to training and validation cohorts. In the training cohort, a seventeen-point prognostic scoring system was developed based on the hazard ratios calculated using Cox-proportional method. We stratified both training and validation cohorts into two "groups" [group 1 (0-7 points) and group 2 (7-17 points)]. Kaplan-Meier method and log-rank test were used to compare OS between the two groups. Our prognostic score was validated internally by comparing the OS between the respective groups in both the training and validation cohorts. Among 67,978 patients, LRT subset (21,200) had better median OS as compared to that of no-LRT (45 vs. 24 months; p < 0.0001). The group 1 and group 2 in the training cohort showed a significant difference in the 3-year OS (p < 0.0001) (68 vs. 26%). On internal validation, comparable OS was seen between the respective groups in each cohort (p = 0.77). Our prognostic scoring system will help oncologists to predict the prognosis in de novo stage IV BC patients treated with LRT. Although firm treatment-related conclusions cannot be made due to the retrospective nature of the study, LRT appears to be associated with a better OS in specific subgroups.

  12. Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics.

    Science.gov (United States)

    Kirwan, Alan; Utratna, Marta; O'Dwyer, Michael E; Joshi, Lokesh; Kilcoyne, Michelle

    2015-01-01

    Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques.

  13. Prognostics for Microgrid Components

    Science.gov (United States)

    Saxena, Abhinav

    2012-01-01

    Prognostics is the science of predicting future performance and potential failures based on targeted condition monitoring. Moving away from the traditional reliability centric view, prognostics aims at detecting and quantifying the time to impending failures. This advance warning provides the opportunity to take actions that can preserve uptime, reduce cost of damage, or extend the life of the component. The talk will focus on the concepts and basics of prognostics from the viewpoint of condition-based systems health management. Differences with other techniques used in systems health management and philosophies of prognostics used in other domains will be shown. Examples relevant to micro grid systems and subsystems will be used to illustrate various types of prediction scenarios and the resources it take to set up a desired prognostic system. Specifically, the implementation results for power storage and power semiconductor components will demonstrate specific solution approaches of prognostics. The role of constituent elements of prognostics, such as model, prediction algorithms, failure threshold, run-to-failure data, requirements and specifications, and post-prognostic reasoning will be explained. A discussion on performance evaluation and performance metrics will conclude the technical discussion followed by general comments on open research problems and challenges in prognostics.

  14. Updating and prospective validation of a prognostic model for high sickness absence

    NARCIS (Netherlands)

    Roelen, C.A.M.; Heymans, M.W.; Twisk, J.W.R.; van Rhenen, W.; Pallesen, S.; Bjorvatn, B.; Moen, B.E.; Mageroy, N.

    2015-01-01

    Objectives To further develop and validate a Dutch prognostic model for high sickness absence (SA). Methods Three-wave longitudinal cohort study of 2,059 Norwegian nurses. The Dutch prognostic model was used to predict high SA among Norwegian nurses at wave 2. Subsequently, the model was updated by

  15. Using prognostic models in CLL to personalize approach to clinical care: Are we there yet?

    Science.gov (United States)

    Mina, Alain; Sandoval Sus, Jose; Sleiman, Elsa; Pinilla-Ibarz, Javier; Awan, Farrukh T; Kharfan-Dabaja, Mohamed A

    2018-03-01

    Four decades ago, two staging systems were developed to help stratify CLL into different prognostic categories. These systems, the Rai and the Binet staging, depended entirely on abnormal exam findings and evidence of anemia and thrombocytopenia. Better understanding of biologic, genetic, and molecular characteristics of CLL have contributed to better appreciating its clinical heterogeneity. New prognostic models, the GCLLSG prognostic index and the CLL-IPI, emerged. They incorporate biologic and genetic information related to CLL and are capable of predicting survival outcomes and cases anticipated to need therapy earlier in the disease course. Accordingly, these newer models are helping develop better informed surveillance strategies and ultimately tailor treatment intensity according to presence (or lack thereof) of certain prognostic markers. This represents a step towards personalizing care of CLL patients. We anticipate that as more prognostic factors continue to be identified, the GCLLSG prognostic index and CLL-IPI models will undergo further revisions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Transitions in Prognostic Awareness Among Terminally Ill Cancer Patients in Their Last 6 Months of Life Examined by Multi-State Markov Modeling.

    Science.gov (United States)

    Hsiu Chen, Chen; Wen, Fur-Hsing; Hou, Ming-Mo; Hsieh, Chia-Hsun; Chou, Wen-Chi; Chen, Jen-Shi; Chang, Wen-Cheng; Tang, Siew Tzuh

    2017-09-01

    Developing accurate prognostic awareness, a cornerstone of preference-based end-of-life (EOL) care decision-making, is a dynamic process involving more prognostic-awareness states than knowing or not knowing. Understanding the transition probabilities and time spent in each prognostic-awareness state can help clinicians identify trigger points for facilitating transitions toward accurate prognostic awareness. We examined transition probabilities in distinct prognostic-awareness states between consecutive time points in 247 cancer patients' last 6 months and estimated the time spent in each state. Prognostic awareness was categorized into four states: (a) unknown and not wanting to know, state 1; (b) unknown but wanting to know, state 2; (c) inaccurate awareness, state 3; and (d) accurate awareness, state 4. Transitional probabilities were examined by multistate Markov modeling. Initially, 59.5% of patients had accurate prognostic awareness, whereas the probabilities of being in states 1-3 were 8.1%, 17.4%, and 15.0%, respectively. Patients' prognostic awareness generally remained unchanged (probabilities of remaining in the same state: 45.5%-92.9%). If prognostic awareness changed, it tended to shift toward higher prognostic-awareness states (probabilities of shifting to state 4 were 23.2%-36.6% for patients initially in states 1-3, followed by probabilities of shifting to state 3 for those in states 1 and 2 [9.8%-10.1%]). Patients were estimated to spend 1.29, 0.42, 0.68, and 3.61 months in states 1-4, respectively, in their last 6 months. Terminally ill cancer patients' prognostic awareness generally remained unchanged, with a tendency to become more aware of their prognosis. Health care professionals should facilitate patients' transitions toward accurate prognostic awareness in a timely manner to promote preference-based EOL decisions. Terminally ill Taiwanese cancer patients' prognostic awareness generally remained stable, with a tendency toward developing

  17. A Prognostic Model for Development of Profound Shock among Children Presenting with Dengue Shock Syndrome.

    Directory of Open Access Journals (Sweden)

    Phung Khanh Lam

    Full Text Available To identify risk factors and develop a prediction model for the development of profound and recurrent shock amongst children presenting with dengue shock syndrome (DSS.We analyzed data from a prospective cohort of children with DSS recruited at the Paediatric Intensive Care Unit of the Hospital for Tropical Disease in Ho Chi Minh City, Vietnam. The primary endpoint was "profound DSS", defined as ≥2 recurrent shock episodes (for subjects presenting in compensated shock, or ≥1 recurrent shock episodes (for subjects presenting initially with decompensated/hypotensive shock, and/or requirement for inotropic support. Recurrent shock was evaluated as a secondary endpoint. Risk factors were pre-defined clinical and laboratory variables collected at the time of presentation with shock. Prognostic model development was based on logistic regression and compared to several alternative approaches.The analysis population included 1207 children of whom 222 (18% progressed to "profound DSS" and 433 (36% had recurrent shock. Independent risk factors for both endpoints included younger age, earlier presentation, higher pulse rate, higher temperature, higher haematocrit and, for females, worse hemodynamic status at presentation. The final prognostic model for "profound DSS" showed acceptable discrimination (AUC=0.69 for internal validation and calibration and is presented as a simple score-chart.Several risk factors for development of profound or recurrent shock among children presenting with DSS were identified. The score-chart derived from the prognostic models should improve triage and management of children presenting with DSS in dengue-endemic areas.

  18. Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights

    Science.gov (United States)

    Chatzimavroudis, George P.; Spirka, Thomas A.; Setser, Randolph M.; Myers, Jerry G.

    2004-01-01

    One of NASA's objectives is to be able to perform a complete, pre-flight, evaluation of cardiovascular changes in astronauts scheduled for prolonged space missions. Computational fluid dynamics (CFD) has shown promise as a method for estimating cardiovascular function during reduced gravity conditions. For this purpose, MRI can provide geometrical information, to reconstruct vessel geometries, and measure all spatial velocity components, providing location specific boundary conditions. The objective of this study was to investigate the reliability of MRI-based model reconstruction and measured boundary conditions for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T Siemens MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction (slice thickness 3 and 5 mm; pixel size 1x1 and 0.5x0.5 square millimeters). Velocity acquisitions provided measured inlet boundary conditions and localized three-directional steady-flow velocity data (0.7-3.0 L/min). The vessel walls were isolated using NIH provided software (ImageJ) and lofted to form the geometric surface. Constructed and idealized geometries were imported into a commercial CFD code for meshing and simulation. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with less than 10% differences in the local velocity values. CFD results on models reconstructed from different MRI resolution settings showed insignificant differences (less than 5%). This study illustrated, quantitatively, that reliable CFD simulations can be performed with MRI reconstructed models and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system alteration during space travel is feasible.

  19. Inflammation-based prognostic score and number of lymph node metastases are independent prognostic factors in esophageal squamous cell carcinoma.

    Science.gov (United States)

    Kobayashi, Takashi; Teruya, Masanori; Kishiki, Tomokazu; Kaneko, Susumu; Endo, Daisuke; Takenaka, Yoshiharu; Miki, Kenji; Kobayashi, Kaoru; Morita, Koji

    2010-08-01

    Few studies have investigated whether the Glasgow Prognostic Score (GPS), an inflammation-based prognostic score, is useful for postoperative prognosis of esophageal squamous cell carcinoma. GPS was calculated on the basis of admission data as follows: patients with elevated C-reactive protein level (>10 mg/l) and hypoalbuminemia (l) were assigned to GPS2. Patients with one or no abnormal value were assigned to GPS1 or GPS0. A new scoring system was constructed using independent prognostic variables and was evaluated on whether it could be used to dictate the choice of clinical options. 65 patients with esophageal squamous cell carcinoma were enrolled. GPS and the number of lymph node metastases were found to be independent prognostic variables. The scoring system comprising GPS and the number of lymph node metastases was found to be effective in the prediction of a long-term outcome (p GPS may be useful for postoperative prognosis of patients with esophageal squamous cell carcinoma. GPS and the number of lymph node metastases could be used to identify a subgroup of patients with esophageal squamous cell carcinoma who are eligible for radical resection but show poor prognosis.

  20. Measures to assess the prognostic ability of the stratified Cox proportional hazards model

    DEFF Research Database (Denmark)

    (Tybjaerg-Hansen, A.) The Fibrinogen Studies Collaboration.The Copenhagen City Heart Study; Tybjærg-Hansen, Anne

    2009-01-01

    Many measures have been proposed to summarize the prognostic ability of the Cox proportional hazards (CPH) survival model, although none is universally accepted for general use. By contrast, little work has been done to summarize the prognostic ability of the stratified CPH model; such measures...

  1. Simplified prognostic model for critically ill patients in resource limited settings in South Asia

    NARCIS (Netherlands)

    Haniffa, Rashan; Mukaka, Mavuto; Munasinghe, Sithum Bandara; de Silva, Ambepitiyawaduge Pubudu; Jayasinghe, Kosala Saroj Amarasiri; Beane, Abi; de Keizer, Nicolette; Dondorp, Arjen M.

    2017-01-01

    Background: Current critical care prognostic models are predominantly developed in high-income countries (HICs) and may not be feasible in intensive care units (ICUs) in lower-and middle-income countries (LMICs). Existing prognostic models cannot be applied without validation in LMICs as the

  2. A prognostic pollen emissions model for climate models (PECM1.0

    Directory of Open Access Journals (Sweden)

    M. C. Wozniak

    2017-11-01

    Full Text Available We develop a prognostic model called Pollen Emissions for Climate Models (PECM for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus, evergreen needleleaf trees (Cupressaceae, Pinaceae, grasses (Poaceae; C3, C4, and ragweed (Ambrosia. This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4 over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1 a taxa-specific land cover database, phenology, and emission potential, and (2 a plant functional type (PFT land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions

  3. A points-based algorithm for prognosticating clinical outcome of Chiari malformation Type I with syringomyelia: results from a predictive model analysis of 82 surgically managed adult patients.

    Science.gov (United States)

    Thakar, Sumit; Sivaraju, Laxminadh; Jacob, Kuruthukulangara S; Arun, Aditya Atal; Aryan, Saritha; Mohan, Dilip; Sai Kiran, Narayanam Anantha; Hegde, Alangar S

    2018-01-01

    OBJECTIVE Although various predictors of postoperative outcome have been previously identified in patients with Chiari malformation Type I (CMI) with syringomyelia, there is no known algorithm for predicting a multifactorial outcome measure in this widely studied disorder. Using one of the largest preoperative variable arrays used so far in CMI research, the authors attempted to generate a formula for predicting postoperative outcome. METHODS Data from the clinical records of 82 symptomatic adult patients with CMI and altered hindbrain CSF flow who were managed with foramen magnum decompression, C-1 laminectomy, and duraplasty over an 8-year period were collected and analyzed. Various preoperative clinical and radiological variables in the 57 patients who formed the study cohort were assessed in a bivariate analysis to determine their ability to predict clinical outcome (as measured on the Chicago Chiari Outcome Scale [CCOS]) and the resolution of syrinx at the last follow-up. The variables that were significant in the bivariate analysis were further analyzed in a multiple linear regression analysis. Different regression models were tested, and the model with the best prediction of CCOS was identified and internally validated in a subcohort of 25 patients. RESULTS There was no correlation between CCOS score and syrinx resolution (p = 0.24) at a mean ± SD follow-up of 40.29 ± 10.36 months. Multiple linear regression analysis revealed that the presence of gait instability, obex position, and the M-line-fourth ventricle vertex (FVV) distance correlated with CCOS score, while the presence of motor deficits was associated with poor syrinx resolution (p ≤ 0.05). The algorithm generated from the regression model demonstrated good diagnostic accuracy (area under curve 0.81), with a score of more than 128 points demonstrating 100% specificity for clinical improvement (CCOS score of 11 or greater). The model had excellent reliability (κ = 0.85) and was validated with

  4. A new extranodal scoring system based on the prognostically relevant extranodal sites in diffuse large B-cell lymphoma, not otherwise specified treated with chemoimmunotherapy.

    Science.gov (United States)

    Hwang, Hee Sang; Yoon, Dok Hyun; Suh, Cheolwon; Huh, Jooryung

    2016-08-01

    Extranodal involvement is a well-known prognostic factor in patients with diffuse large B-cell lymphomas (DLBCL). Nevertheless, the prognostic impact of the extranodal scoring system included in the conventional international prognostic index (IPI) has been questioned in an era where rituximab treatment has become widespread. We investigated the prognostic impacts of individual sites of extranodal involvement in 761 patients with DLBCL who received rituximab-based chemoimmunotherapy. Subsequently, we established a new extranodal scoring system based on extranodal sites, showing significant prognostic correlation, and compared this system with conventional scoring systems, such as the IPI and the National Comprehensive Cancer Network-IPI (NCCN-IPI). An internal validation procedure, using bootstrapped samples, was also performed for both univariate and multivariate models. Using multivariate analysis with a backward variable selection, we found nine extranodal sites (the liver, lung, spleen, central nervous system, bone marrow, kidney, skin, adrenal glands, and peritoneum) that remained significant for use in the final model. Our newly established extranodal scoring system, based on these sites, was better correlated with patient survival than standard scoring systems, such as the IPI and the NCCN-IPI. Internal validation by bootstrapping demonstrated an improvement in model performance of our modified extranodal scoring system. Our new extranodal scoring system, based on the prognostically relevant sites, may improve the performance of conventional prognostic models of DLBCL in the rituximab era and warrants further external validation using large study populations.

  5. A novel approach towards fatigue damage prognostics of composite materials utilizing SHM data and stochastic degradation modeling

    NARCIS (Netherlands)

    Loutas, T.; Eleftheroglou, N.

    2016-01-01

    A prognostic framework is proposed in order to estimate the remaining useful life of composite materials under fatigue loading based on acoustic emission data and a sophisticated Non Homogenous Hidden Semi Markov Model. Bayesian neural networks are also utilized as an alternative machine learning

  6. Improvement of PSA Models Using Monitoring and Prognostics

    Energy Technology Data Exchange (ETDEWEB)

    Heo, Gyun Young; Chang, Yoon Suk; Kim, Hyun Dae [Kyung Hee University, Yongin (Korea, Republic of)

    2014-08-15

    Probabilistic Safety Assessment (PSA) has performed a significant role for quantitative decision-making by finding design and operational vulnerability and evaluating cost-benefit in improving such weak points. Especially, it has been widely used as the core methodology for Risk-Informed Applications (RIAs). Even though the nature of PSA seeks realistic results, there are still 'conservative' aspects. The sources for the conservatism come from the assumption of safety analysis and the estimation of failure frequency. Surveillance, Diagnosis, and Prognosis (SDP) utilizing massive database and information technology is worthwhile to be highlighted in terms of the capability of alleviating the conservatism in the conventional PSA. This paper provides enabling techniques to concretize the method to provide time- and condition-dependent risk by integrating a conventional PSA model with condition monitoring and prognostics techniques. We will discuss how to integrate the results with frequency of initiating events (IEs) and failure probability of basic events (BEs). Two illustrative examples will be introduced: how the failure probability of a passive system can be evaluated under different plant conditions and how the IE frequency for Steam Generator Tube Rupture (SGTR) can be updated in terms of operating time. We expect that the proposed PSA model can take a role of annunciator to show the variation of Core Damage Frequency (CDF) in terms of time and operational conditions.

  7. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1994-01-01

    Most of today's general circulation models (GCMs) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, an urgent need for improvements in the treatment of clouds in GCMs has arisen, especially as the clouds relate to radiation. In this paper, we investigate the effects of introducing prognostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the longwave emissivity calculations. Results from several sensitivity simulations show that realistic water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds becomes stronger because of more realistic tropical convection

  8. Maintenance-based prognostics of nuclear plant equipment for long-term operation

    Energy Technology Data Exchange (ETDEWEB)

    Welz, Zachary; Coble, Jamie; Upadhyaya, Belle; Hines, Wes [University of Tennessee, Knoxville (United States)

    2017-08-15

    While industry understands the importance of keeping equipment operational and well maintained, the importance of tracking maintenance information in reliability models is often overlooked. Prognostic models can be used to predict the failure times of critical equipment, but more often than not, these models assume that all maintenance actions are the same or do not consider maintenance at all. This study investigates the influence of integrating maintenance information on prognostic model prediction accuracy. By incorporating maintenance information to develop maintenance-dependent prognostic models, prediction accuracy was improved by more than 40% compared with traditional maintenance-independent models. This study acts as a proof of concept, showing the importance of utilizing maintenance information in modern prognostics for industrial equipment.

  9. Plaque Brachytherapy for Uveal Melanoma: A Vision Prognostication Model

    International Nuclear Information System (INIS)

    Khan, Niloufer; Khan, Mohammad K.; Bena, James; Macklis, Roger; Singh, Arun D.

    2012-01-01

    Purpose: To generate a vision prognostication model after plaque brachytherapy for uveal melanoma. Methods and Materials: All patients with primary single ciliary body or choroidal melanoma treated with iodine-125 or ruthenium-106 plaque brachytherapy between January 1, 2005, and June 30, 2010, were included. The primary endpoint was loss of visual acuity. Only patients with initial visual acuity better than or equal to 20/50 were used to evaluate visual acuity worse than 20/50 at the end of the study, and only patients with initial visual acuity better than or equal to 20/200 were used to evaluate visual acuity worse than 20/200 at the end of the study. Factors analyzed were sex, age, cataracts, diabetes, tumor size (basal dimension and apical height), tumor location, and radiation dose to the tumor apex, fovea, and optic disc. Univariate and multivariable Cox proportional hazards were used to determine the influence of baseline patient factors on vision loss. Kaplan-Meier curves (log rank analysis) were used to estimate freedom from vision loss. Results: Of 189 patients, 92% (174) were alive as of February 1, 2011. At presentation, visual acuity was better than or equal to 20/50 and better than or equal to 20/200 in 108 and 173 patients, respectively. Of these patients, 44.4% (48) had post-treatment visual acuity of worse than 20/50 and 25.4% (44) had post-treatment visual acuity worse than 20/200. By multivariable analysis, increased age (hazard ratio [HR] of 1.01 [1.00-1.03], P=.05), increase in tumor height (HR of 1.35 [1.22-1.48], P<.001), and a greater total dose to the fovea (HR of 1.01 [1.00-1.01], P<.001) were predictive of vision loss. This information was used to develop a nomogram predictive of vision loss. Conclusions: By providing a means to predict vision loss at 3 years after treatment, our vision prognostication model can be an important tool for patient selection and treatment counseling.

  10. Plaque Brachytherapy for Uveal Melanoma: A Vision Prognostication Model

    Energy Technology Data Exchange (ETDEWEB)

    Khan, Niloufer [Department of Radiation Oncology, Taussig Cancer Center, Cleveland Clinic, Cleveland, Ohio (United States); Khan, Mohammad K. [Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia (United States); Bena, James [Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (United States); Macklis, Roger [Department of Radiation Oncology, Taussig Cancer Center, Cleveland Clinic, Cleveland, Ohio (United States); Singh, Arun D., E-mail: singha@ccf.org [Department of Ophthalmic Oncology, Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio (United States)

    2012-11-01

    Purpose: To generate a vision prognostication model after plaque brachytherapy for uveal melanoma. Methods and Materials: All patients with primary single ciliary body or choroidal melanoma treated with iodine-125 or ruthenium-106 plaque brachytherapy between January 1, 2005, and June 30, 2010, were included. The primary endpoint was loss of visual acuity. Only patients with initial visual acuity better than or equal to 20/50 were used to evaluate visual acuity worse than 20/50 at the end of the study, and only patients with initial visual acuity better than or equal to 20/200 were used to evaluate visual acuity worse than 20/200 at the end of the study. Factors analyzed were sex, age, cataracts, diabetes, tumor size (basal dimension and apical height), tumor location, and radiation dose to the tumor apex, fovea, and optic disc. Univariate and multivariable Cox proportional hazards were used to determine the influence of baseline patient factors on vision loss. Kaplan-Meier curves (log rank analysis) were used to estimate freedom from vision loss. Results: Of 189 patients, 92% (174) were alive as of February 1, 2011. At presentation, visual acuity was better than or equal to 20/50 and better than or equal to 20/200 in 108 and 173 patients, respectively. Of these patients, 44.4% (48) had post-treatment visual acuity of worse than 20/50 and 25.4% (44) had post-treatment visual acuity worse than 20/200. By multivariable analysis, increased age (hazard ratio [HR] of 1.01 [1.00-1.03], P=.05), increase in tumor height (HR of 1.35 [1.22-1.48], P<.001), and a greater total dose to the fovea (HR of 1.01 [1.00-1.01], P<.001) were predictive of vision loss. This information was used to develop a nomogram predictive of vision loss. Conclusions: By providing a means to predict vision loss at 3 years after treatment, our vision prognostication model can be an important tool for patient selection and treatment counseling.

  11. Implementation of Remaining Useful Lifetime Transformer Models in the Fleet-Wide Prognostic and Health Management Suite

    International Nuclear Information System (INIS)

    Agarwal, Vivek; Lybeck, Nancy J.; Pham, Binh; Rusaw, Richard; Bickford, Randall

    2015-01-01

    Research and development efforts are required to address aging and reliability concerns of the existing fleet of nuclear power plants. As most plants continue to operate beyond the license life (i.e., towards 60 or 80 years), plant components are more likely to incur age-related degradation mechanisms. To assess and manage the health of aging plant assets across the nuclear industry, the Electric Power Research Institute has developed a web-based Fleet-Wide Prognostic and Health Management (FW-PHM) Suite for diagnosis and prognosis. FW-PHM is a set of web-based diagnostic and prognostic tools and databases, comprised of the Diagnostic Advisor, the Asset Fault Signature Database, the Remaining Useful Life Advisor, and the Remaining Useful Life Database, that serves as an integrated health monitoring architecture. The main focus of this paper is the implementation of prognostic models for generator step-up transformers in the FW-PHM Suite. One prognostic model discussed is based on the functional relationship between degree of polymerization, (the most commonly used metrics to assess the health of the winding insulation in a transformer) and furfural concentration in the insulating oil. The other model is based on thermal-induced degradation of the transformer insulation. By utilizing transformer loading information, established thermal models are used to estimate the hot spot temperature inside the transformer winding. Both models are implemented in the Remaining Useful Life Database of the FW-PHM Suite. The Remaining Useful Life Advisor utilizes the implemented prognostic models to estimate the remaining useful life of the paper winding insulation in the transformer based on actual oil testing and operational data.

  12. Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods.

    Science.gov (United States)

    Parkinson, Craig; Foley, Kieran; Whybra, Philip; Hills, Robert; Roberts, Ashley; Marshall, Chris; Staffurth, John; Spezi, Emiliano

    2018-04-11

    Prognosis in oesophageal cancer (OC) is poor. The 5-year overall survival (OS) rate is approximately 15%. Personalised medicine is hoped to increase the 5- and 10-year OS rates. Quantitative analysis of PET is gaining substantial interest in prognostic research but requires the accurate definition of the metabolic tumour volume. This study compares prognostic models developed in the same patient cohort using individual PET segmentation algorithms and assesses the impact on patient risk stratification. Consecutive patients (n = 427) with biopsy-proven OC were included in final analysis. All patients were staged with PET/CT between September 2010 and July 2016. Nine automatic PET segmentation methods were studied. All tumour contours were subjectively analysed for accuracy, and segmentation methods with segmentation methods studied, clustering means (KM2), general clustering means (GCM3), adaptive thresholding (AT) and watershed thresholding (WT) methods were included for analysis. Known clinical prognostic factors (age, treatment and staging) were significant in all of the developed prognostic models. AT and KM2 segmentation methods developed identical prognostic models. Patient risk stratification was dependent on the segmentation method used to develop the prognostic model with up to 73 patients (17.1%) changing risk stratification group. Prognostic models incorporating quantitative image features are dependent on the method used to delineate the primary tumour. This has a subsequent effect on risk stratification, with patients changing groups depending on the image segmentation method used.

  13. A hybrid prognostic model for multistep ahead prediction of machine condition

    Science.gov (United States)

    Roulias, D.; Loutas, T. H.; Kostopoulos, V.

    2012-05-01

    Prognostics are the future trend in condition based maintenance. In the current framework a data driven prognostic model is developed. The typical procedure of developing such a model comprises a) the selection of features which correlate well with the gradual degradation of the machine and b) the training of a mathematical tool. In this work the data are taken from a laboratory scale single stage gearbox under multi-sensor monitoring. Tests monitoring the condition of the gear pair from healthy state until total brake down following several days of continuous operation were conducted. After basic pre-processing of the derived data, an indicator that correlated well with the gearbox condition was obtained. Consecutively the time series is split in few distinguishable time regions via an intelligent data clustering scheme. Each operating region is modelled with a feed-forward artificial neural network (FFANN) scheme. The performance of the proposed model is tested by applying the system to predict the machine degradation level on unseen data. The results show the plausibility and effectiveness of the model in following the trend of the timeseries even in the case that a sudden change occurs. Moreover the model shows ability to generalise for application in similar mechanical assets.

  14. Moderate Traumatic Brain Injury: Clinical Characteristics and a Prognostic Model of 12-Month Outcome.

    Science.gov (United States)

    Einarsen, Cathrine Elisabeth; van der Naalt, Joukje; Jacobs, Bram; Follestad, Turid; Moen, Kent Gøran; Vik, Anne; Håberg, Asta Kristine; Skandsen, Toril

    2018-03-31

    Patients with moderate traumatic brain injury (TBI) often are studied together with patients with severe TBI, even though the expected outcome of the former is better. Therefore, we aimed to describe patient characteristics and 12-month outcomes, and to develop a prognostic model based on admission data, specifically for patients with moderate TBI. Patients with Glasgow Coma Scale scores of 9-13 and age ≥16 years were prospectively enrolled in 2 level I trauma centers in Europe. Glasgow Outcome Scale Extended (GOSE) score was assessed at 12 months. A prognostic model predicting moderate disability or worse (GOSE score ≤6), as opposed to a good recovery, was fitted by penalized regression. Model performance was evaluated by area under the curve of the receiver operating characteristics curves. Of the 395 enrolled patients, 81% had intracranial lesions on head computed tomography, and 71% were admitted to an intensive care unit. At 12 months, 44% were moderately disabled or worse (GOSE score ≤6), whereas 8% were severely disabled and 6% died (GOSE score ≤4). Older age, lower Glasgow Coma Scale score, no day-of-injury alcohol intoxication, presence of a subdural hematoma, occurrence of hypoxia and/or hypotension, and preinjury disability were significant predictors of GOSE score ≤6 (area under the curve = 0.80). Patients with moderate TBI exhibit characteristics of significant brain injury. Although few patients died or experienced severe disability, 44% did not experience good recovery, indicating that follow-up is needed. The model is a first step in development of prognostic models for moderate TBI that are valid across centers. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  15. Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection.

    Science.gov (United States)

    Van Steen, Kristel; Curran, Desmond; Kramer, Jocelyn; Molenberghs, Geert; Van Vreckem, Ann; Bottomley, Andrew; Sylvester, Richard

    2002-12-30

    Clinical and quality of life (QL) variables from an EORTC clinical trial of first line chemotherapy in advanced breast cancer were used in a prognostic factor analysis of survival and response to chemotherapy. For response, different final multivariate models were obtained from forward and backward selection methods, suggesting a disconcerting instability. Quality of life was measured using the EORTC QLQ-C30 questionnaire completed by patients. Subscales on the questionnaire are known to be highly correlated, and therefore it was hypothesized that multicollinearity contributed to model instability. A correlation matrix indicated that global QL was highly correlated with 7 out of 11 variables. In a first attempt to explore multicollinearity, we used global QL as dependent variable in a regression model with other QL subscales as predictors. Afterwards, standard diagnostic tests for multicollinearity were performed. An exploratory principal components analysis and factor analysis of the QL subscales identified at most three important components and indicated that inclusion of global QL made minimal difference to the loadings on each component, suggesting that it is redundant in the model. In a second approach, we advocate a bootstrap technique to assess the stability of the models. Based on these analyses and since global QL exacerbates problems of multicollinearity, we therefore recommend that global QL be excluded from prognostic factor analyses using the QLQ-C30. The prognostic factor analysis was rerun without global QL in the model, and selected the same significant prognostic factors as before. Copyright 2002 John Wiley & Sons, Ltd.

  16. Enhancement of Physics-of-Failure Prognostic Models with System Level Features

    National Research Council Canada - National Science Library

    Kacprzynski, Gregory

    2002-01-01

    .... The novelty in the current prognostic tool development is that predictions are made through the fusion of stochastic physics-of-failure models, relevant system or component level health monitoring...

  17. Intercomparisons of Prognostic, Diagnostic, and Inversion Modeling Approaches for Estimation of Net Ecosystem Exchange over the Pacific Northwest Region

    Science.gov (United States)

    Turner, D. P.; Jacobson, A. R.; Nemani, R. R.

    2013-12-01

    The recent development of large spatially-explicit datasets for multiple variables relevant to monitoring terrestrial carbon flux offers the opportunity to estimate the terrestrial land flux using several alternative, potentially complimentary, approaches. Here we developed and compared regional estimates of net ecosystem exchange (NEE) over the Pacific Northwest region of the U.S. using three approaches. In the prognostic modeling approach, the process-based Biome-BGC model was driven by distributed meteorological station data and was informed by Landsat-based coverages of forest stand age and disturbance regime. In the diagnostic modeling approach, the quasi-mechanistic CFLUX model estimated net ecosystem production (NEP) by upscaling eddy covariance flux tower observations. The model was driven by distributed climate data and MODIS FPAR (the fraction of incident PAR that is absorbed by the vegetation canopy). It was informed by coarse resolution (1 km) data about forest stand age. In both the prognostic and diagnostic modeling approaches, emissions estimates for biomass burning, harvested products, and river/stream evasion were added to model-based NEP to get NEE. The inversion model (CarbonTracker) relied on observations of atmospheric CO2 concentration to optimize prior surface carbon flux estimates. The Pacific Northwest is heterogeneous with respect to land cover and forest management, and repeated surveys of forest inventory plots support the presence of a strong regional carbon sink. The diagnostic model suggested a stronger carbon sink than the prognostic model, and a much larger sink that the inversion model. The introduction of Landsat data on disturbance history served to reduce uncertainty with respect to regional NEE in the diagnostic and prognostic modeling approaches. The FPAR data was particularly helpful in capturing the seasonality of the carbon flux using the diagnostic modeling approach. The inversion approach took advantage of a global

  18. Prognostic value of the C-reactive protein to albumin ratio: a novel inflammation-based prognostic indicator in osteosarcoma

    Directory of Open Access Journals (Sweden)

    Li YJ

    2017-11-01

    Full Text Available Yong-Jiang Li,1,* Kai Yao,2,* Min-Xun Lu,2 Wen-Biao Zhang,1 Cong Xiao,2 Chong-Qi Tu2 1Department of Oncology, 2Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, People’s Republic of China *These authors contributed equally to this work Abstract: The prognostic role of the C-reactive protein to albumin ratio (CRP/Alb ratio in patients with osteosarcoma has not been investigated. A total of 216 osteosarcoma patients were enrolled in the study. Univariate and multivariate survival analyses between the groups were performed and Kaplan–Meier analysis was conducted to plot the survival curves. Receiver operating characteristic curves were generated and areas under the curve (AUCs were compared to assess the discriminatory ability of the inflammation-based indicators, including CRP/Alb ratio, Glasgow prognostic score (GPS, neutrophil–lymphocyte ratio (NLR, and platelet–lymphocyte ratio (PLR. The optimal cutoff value was 0.210 for CRP/Alb ratio with a Youden index of 0.319. Higher values of CRP/Alb ratio were significantly associated with poorer overall survival in univariate (HR =2.62, 95% CI =1.70–4.03; P<0.001 and multivariate (HR =2.21, 95% CI =1.40–3.49; P=0.001 analyses. In addition, the CRP/Alb ratio had significantly higher AUC values compared with GPS (P=0.003, NLR (P<0.001, and PLR (P<0.001. The study demonstrated that the CRP/Alb ratio is an effective inflammation-based prognostic indicator in osteosarcoma, which potentially has a discriminatory ability superior to that of other inflammatory indicators including GPS, NLR, and PLR. Keywords: osteosarcoma, CRP to albumin ratio, prognosis

  19. Development and validation of logistic prognostic models by predefined SAS-macros

    Directory of Open Access Journals (Sweden)

    Ziegler, Christoph

    2006-02-01

    Full Text Available In medical decision making about therapies or diagnostic procedures in the treatment of patients the prognoses of the course or of the magnitude of diseases plays a relevant role. Beside of the subjective attitude of the clinician mathematical models can help in providing such prognoses. Such models are mostly multivariate regression models. In the case of a dichotomous outcome the logistic model will be applied as the standard model. In this paper we will describe SAS-macros for the development of such a model, for examination of the prognostic performance, and for model validation. The rational for this developmental approach of a prognostic modelling and the description of the macros can only given briefly in this paper. Much more details are given in. These 14 SAS-macros are a tool for setting up the whole process of deriving a prognostic model. Especially the possibility of validating the model by a standardized software tool gives an opportunity, which is not used in general in published prognostic models. Therefore, this can help to develop new models with good prognostic performance for use in medical applications.

  20. Novel Inflammation-Based Prognostic Score for Predicting Survival in Patients with Metastatic Urothelial Carcinoma.

    Directory of Open Access Journals (Sweden)

    Yu-Li Su

    Full Text Available We developed a novel inflammation-based model (NPS, which consisted of a neutrophil to lymphocyte ratio (NLR and platelet count (PC, for assessing the prognostic role in patients with metastatic urothelial carcinoma (UC.We performed a retrospective analysis of patients with metastatic UC who underwent systemic chemotherapy between January 1997 and December 2014 in Kaohsiung Chang Gung Memorial Hospital. The defined cutoff values for the NLR and PC were 3.0 and 400 × 103/μL, respectively. Patients were scored 1 for either an elevated NLR or PC, and 0 otherwise. The NPS was calculated by summing the scores, ranging from 0 to 2. The primary endpoint was overall survival (OS by using Kaplan-Meier analysis. Multivariate Cox regression analysis was used to identify the independent prognostic factors for OS.In total, 256 metastatic UC patients were enrolled. Univariate analysis revealed that patients with either a high NLR or PC had a significantly shorter survival rate compared with those with a low NLR (P = .001 or PC (P < .0001. The median OS in patients with NPS 0, 1, and 2 was 19.0, 12.8, and 9.3 months, respectively (P < .0001. Multivariate analysis revealed that NPS, along with the histologic variant, liver metastasis, age, and white cell count, was an independent factor facilitating OS prediction (hazard ratio 1.64, 95% confidence interval 1.20-2.24, P = .002.The NLR and PC are independent prognostic factors for OS in patients with metastatic UC. The NPS model has excellent discriminant ability for OS.

  1. Development and Validation of a Lifecycle-based Prognostics Architecture with Test Bed Validation

    Energy Technology Data Exchange (ETDEWEB)

    Hines, J. Wesley [Univ. of Tennessee, Knoxville, TN (United States); Upadhyaya, Belle [Univ. of Tennessee, Knoxville, TN (United States); Sharp, Michael [Univ. of Tennessee, Knoxville, TN (United States); Ramuhalli, Pradeep [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Jeffries, Brien [Univ. of Tennessee, Knoxville, TN (United States); Nam, Alan [Univ. of Tennessee, Knoxville, TN (United States); Strong, Eric [Univ. of Tennessee, Knoxville, TN (United States); Tong, Matthew [Univ. of Tennessee, Knoxville, TN (United States); Welz, Zachary [Univ. of Tennessee, Knoxville, TN (United States); Barbieri, Federico [Univ. of Tennessee, Knoxville, TN (United States); Langford, Seth [Univ. of Tennessee, Knoxville, TN (United States); Meinweiser, Gregory [Univ. of Tennessee, Knoxville, TN (United States); Weeks, Matthew [Univ. of Tennessee, Knoxville, TN (United States)

    2014-11-06

    On-line monitoring and tracking of nuclear plant system and component degradation is being investigated as a method for improving the safety, reliability, and maintainability of aging nuclear power plants. Accurate prediction of the current degradation state of system components and structures is important for accurate estimates of their remaining useful life (RUL). The correct quantification and propagation of both the measurement uncertainty and model uncertainty is necessary for quantifying the uncertainty of the RUL prediction. This research project developed and validated methods to perform RUL estimation throughout the lifecycle of plant components. Prognostic methods should seamlessly operate from beginning of component life (BOL) to end of component life (EOL). We term this "Lifecycle Prognostics." When a component is put into use, the only information available may be past failure times of similar components used in similar conditions, and the predicted failure distribution can be estimated with reliability methods such as Weibull Analysis (Type I Prognostics). As the component operates, it begins to degrade and consume its available life. This life consumption may be a function of system stresses, and the failure distribution should be updated to account for the system operational stress levels (Type II Prognostics). When degradation becomes apparent, this information can be used to again improve the RUL estimate (Type III Prognostics). This research focused on developing prognostics algorithms for the three types of prognostics, developing uncertainty quantification methods for each of the algorithms, and, most importantly, developing a framework using Bayesian methods to transition between prognostic model types and update failure distribution estimates as new information becomes available. The developed methods were then validated on a range of accelerated degradation test beds. The ultimate goal of prognostics is to provide an accurate assessment for

  2. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

    Directory of Open Access Journals (Sweden)

    Liu Yufeng

    2011-01-01

    Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

  3. THE MODEL OF UNCLEAR EXPERT SYSTEM OF PROGNOSTICATION THE CONTENT OF EDUCATION

    Directory of Open Access Journals (Sweden)

    Ivan M. Tsidylo

    2012-12-01

    Full Text Available The article deals with the problem of development of the expert system of prognostication of the educational content by means of fuzzy logic. It was the model of making decision by the group of experts in accordance to meaningfulness of the theme in the educational programme on the base of the hierarchical system that combines in itself the use of both unclear and stochastic data. The structure of the unclear system, function and mechanisms of construction of separate blocks of the model are described. The surface of review of the unclear system represents dependence of estimation of the theme meaningfulness on the level of competence of group of experts and size to the point at the permanent value of level’s variation. The testing of the controller on a test selection proves the functional fitness of the developed model.

  4. Inflammation-based prognostic score is a useful predictor of postoperative outcome in patients with extrahepatic cholangiocarcinoma.

    Science.gov (United States)

    Oshiro, Yukio; Sasaki, Ryoko; Fukunaga, Kiyoshi; Kondo, Tadashi; Oda, Tatsuya; Takahashi, Hideto; Ohkohchi, Nobuhiro

    2013-03-01

    Recent studies have revealed that the Glasgow prognostic score (GPS), an inflammation-based prognostic score, is useful for predicting outcome in a variety of cancers. This study sought to investigate the significance of GPS for prognostication of patients who underwent surgery with extrahepatic cholangiocarcinoma. We retrospectively analyzed a total of 62 patients who underwent resection for extrahepatic cholangiocarcinoma. We calculated the GPS as follows: patients with both an elevated C-reactive protein (>10 mg/L) and hypoalbuminemia (L) were allocated a score of 2; patients with one or none of these abnormalities were allocated a s ore of 1 or 0, respectively. Prognostic significance was analyzed by the log-rank test and a Cox proportional hazards model. Overall survival rate was 25.5 % at 5 years for all 62 patients. Venous invasion (p = 0.01), pathological primary tumor category (p = 0.013), lymph node metastasis category (p GPS (p = 0.008) were significantly associated with survival by univariate analysis. A Cox model demonstrated that increased GPS was an independent predictive factor with poor prognosis. The preoperative GPS is a useful predictor of postoperative outcome in patients with extrahepatic cholangiocarcinoma.

  5. Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury.

    Science.gov (United States)

    Ritter, Anne C; Wagner, Amy K; Szaflarski, Jerzy P; Brooks, Maria M; Zafonte, Ross D; Pugh, Mary Jo V; Fabio, Anthony; Hammond, Flora M; Dreer, Laura E; Bushnik, Tamara; Walker, William C; Brown, Allen W; Johnson-Greene, Doug; Shea, Timothy; Krellman, Jason W; Rosenthal, Joseph A

    2016-09-01

    Posttraumatic seizures (PTS) are well-recognized acute and chronic complications of traumatic brain injury (TBI). Risk factors have been identified, but considerable variability in who develops PTS remains. Existing PTS prognostic models are not widely adopted for clinical use and do not reflect current trends in injury, diagnosis, or care. We aimed to develop and internally validate preliminary prognostic regression models to predict PTS during acute care hospitalization, and at year 1 and year 2 postinjury. Prognostic models predicting PTS during acute care hospitalization and year 1 and year 2 post-injury were developed using a recent (2011-2014) cohort from the TBI Model Systems National Database. Potential PTS predictors were selected based on previous literature and biologic plausibility. Bivariable logistic regression identified variables with a p-value models. Multivariable logistic regression modeling with backward-stepwise elimination was used to determine reduced prognostic models and to internally validate using 1,000 bootstrap samples. Fit statistics were calculated, correcting for overfitting (optimism). The prognostic models identified sex, craniotomy, contusion load, and pre-injury limitation in learning/remembering/concentrating as significant PTS predictors during acute hospitalization. Significant predictors of PTS at year 1 were subdural hematoma (SDH), contusion load, craniotomy, craniectomy, seizure during acute hospitalization, duration of posttraumatic amnesia, preinjury mental health treatment/psychiatric hospitalization, and preinjury incarceration. Year 2 significant predictors were similar to those of year 1: SDH, intraparenchymal fragment, craniotomy, craniectomy, seizure during acute hospitalization, and preinjury incarceration. Corrected concordance (C) statistics were 0.599, 0.747, and 0.716 for acute hospitalization, year 1, and year 2 models, respectively. The prognostic model for PTS during acute hospitalization did not

  6. A Comparison of Systemic Inflammation-Based Prognostic Scores in Patients on Regular Hemodialysis

    Directory of Open Access Journals (Sweden)

    Akihiko Kato

    2013-10-01

    Full Text Available Background/Aims: Systemic inflammation-based prognostic scores have prognostic power in patients with cancer, independently of tumor stage and site. Although inflammatory status is associated with mortality in hemodialysis (HD patients, it remains to be determined as to whether these composite scores are useful in predicting clinical outcomes. Methods: We calculated the 6 prognostic scores [Glasgow prognostic score (GPS, modified GPS (mGPS, neutrophil-lymphocyte ratio (NLR, platelet lymphocyte ratio (PLR, prognostic index (PI and prognostic nutritional index (PNI], which have been established as a useful scoring system in cancer patients. We enrolled 339 patients on regular HD (age: 64 ± 13 years; time on HD: 129 ± 114 months; males/females = 253/85 and followed them for 42 months. The area under the receiver-operating characteristics curve was used to determine which scoring system was more predictive of mortality. Results: Elevated GPS, mGPS, NLR, PLR, PI and PNI were all associated with total mortality, independent of covariates. If GPS was raised, mGPS, NLR, PLR and PI were also predictive of all-cause mortality and/or hospitalization. GPS and PNI were associated with poor nutritional status. Using overall mortality as an endpoint, the area under the curve (AUC was significant for a GPS of 0.701 (95% CI: 0.637-0.765; p Conclusion: GPS, based on serum albumin and highly sensitive C-reactive protein, has the most prognostic power for mortality prediction among the prognostic scores in HD patients. However, as the determination of serum albumin reflects mortality similarly to GPS, other composite combinations are needed to provide additional clinical utility beyond that of albumin alone in HD patients.

  7. Mayo Alliance Prognostic Model for Myelodysplastic Syndromes: Integration of Genetic and Clinical Information.

    Science.gov (United States)

    Tefferi, Ayalew; Gangat, Naseema; Mudireddy, Mythri; Lasho, Terra L; Finke, Christy; Begna, Kebede H; Elliott, Michelle A; Al-Kali, Aref; Litzow, Mark R; Hook, C Christopher; Wolanskyj, Alexandra P; Hogan, William J; Patnaik, Mrinal M; Pardanani, Animesh; Zblewski, Darci L; He, Rong; Viswanatha, David; Hanson, Curtis A; Ketterling, Rhett P; Tang, Jih-Luh; Chou, Wen-Chien; Lin, Chien-Chin; Tsai, Cheng-Hong; Tien, Hwei-Fang; Hou, Hsin-An

    2018-06-01

    To develop a new risk model for primary myelodysplastic syndromes (MDS) that integrates information on mutations, karyotype, and clinical variables. Patients with World Health Organization-defined primary MDS seen at Mayo Clinic (MC) from December 28, 1994, through December 19, 2017, constituted the core study group. The National Taiwan University Hospital (NTUH) provided the validation cohort. Model performance, compared with the revised International Prognostic Scoring System, was assessed by Akaike information criterion and area under the curve estimates. The study group consisted of 685 molecularly annotated patients from MC (357) and NTUH (328). Multivariate analysis of the MC cohort identified monosomal karyotype (hazard ratio [HR], 5.2; 95% CI, 3.1-8.6), "non-MK abnormalities other than single/double del(5q)" (HR, 1.8; 95% CI, 1.3-2.6), RUNX1 (HR, 2.0; 95% CI, 1.2-3.1) and ASXL1 (HR, 1.7; 95% CI, 1.2-2.3) mutations, absence of SF3B1 mutations (HR, 1.6; 95% CI, 1.1-2.4), age greater than 70 years (HR, 2.2; 95% CI, 1.6-3.1), hemoglobin level less than 8 g/dL in women or less than 9 g/dL in men (HR, 2.3; 95% CI, 1.7-3.1), platelet count less than 75 × 10 9 /L (HR, 1.5; 95% CI, 1.1-2.1), and 10% or more bone marrow blasts (HR, 1.7; 95% CI, 1.1-2.8) as predictors of inferior overall survival. Based on HR-weighted risk scores, a 4-tiered Mayo alliance prognostic model for MDS was devised: low (89 patients), intermediate-1 (104), intermediate-2 (95), and high (69); respective median survivals (5-year overall survival rates) were 85 (73%), 42 (34%), 22 (7%), and 9 months (0%). The Mayo alliance model was subsequently validated by using the external NTUH cohort and, compared with the revised International Prognostic Scoring System, displayed favorable Akaike information criterion (1865 vs 1943) and area under the curve (0.87 vs 0.76) values. We propose a simple and contemporary risk model for MDS that is based on a limited set of genetic and clinical variables

  8. New prognostic model for extranodal natural killer/T cell lymphoma, nasal type.

    Science.gov (United States)

    Cai, Qingqing; Luo, Xiaolin; Zhang, Guanrong; Huang, Huiqiang; Huang, Hui; Lin, Tongyu; Jiang, Wenqi; Xia, Zhongjun; Young, Ken H

    2014-09-01

    Extranodal natural killer/T cell lymphoma, nasal type (ENKTL) is an aggressive disease with a poor prognosis, requiring risk stratification in affected patients. We designed a new prognostic model specifically for ENKTL to identify high-risk patients who need more aggressive therapy. We retrospectively reviewed 158 patients who were newly diagnosed with ENKTL. The estimated 5-year overall survival rate was 39.4 %. Independent prognostic factors included total protein (TP) 100 mg/dL, and Korean Prognostic Index (KPI) score ≥2. We constructed a new prognostic model by combining these prognostic factors: group 1 (64 cases (41.0 %)), no adverse factors; group 2 (58 cases (37.2 %)), one adverse factor; and group 3 (34 cases (21.8 %)), two or three adverse factors. The 5-year overall survival (OS) rates of these groups were 66.7, 23.0, and 5.9 %, respectively (p KPI model alone (p KPI model alone.

  9. Important prognostic factors in patients with skull base erosion from nasopharyngeal carcinoma after radiotherapy

    International Nuclear Information System (INIS)

    Lu, T.-X.; Mai, W.-Y.; Teh, Bin S.; Hu, Y.-H.; Lu, Hsin H.; Chiu, J. Kam; Carpenter, L. Steven; Woo, Shiao Y.; Butler, E. Brian

    2001-01-01

    Purpose: To evaluate the long-term outcome and prognostic factors in patients with skull base erosion from nasopharyngeal carcinoma after initial radiotherapy (RT). Methods and Materials: From January 1985 to December 1986, 100 patients (71 males, 29 females) with a diagnosis of nasopharyngeal carcinoma were found on computed tomography (CT) to have skull base erosion. The mean age was 41 years (range 16-66). Ninety-six patients had World Health Organization type III undifferentiated carcinoma, and 4 had type I. The metastatic workup, including chest radiography, liver ultrasound scanning, and liver function test was negative. All patients underwent external beam RT (EBRT) alone to 66-80 Gy during 6-8 weeks. A daily fraction size of 2 Gy was delivered using 60 Co or a linear accelerator. No patient received chemotherapy. All patients were followed at regular intervals after irradiation. The median follow-up was 22.3 months (range 2-174). Survival of the cohort was computed by the Kaplan-Meier method. The potential prognostic factors of survival were examined. Multivariate analyses were performed using the Cox regression model. Results: The 1, 2, 5, and 10-year overall survival rate for the cohort was 79%, 41%, 27%, and 13%, respectively. However, the subgroup of patients with both anterior cranial nerve (I-VIII) and posterior cranial nerve (IX-XII) involvement had a 5-year survival of only 7.7%. A difference in the time course of local recurrence and distant metastasis was observed. Both local recurrence and distant metastasis often occurred within the first 2 years after RT. However, local relapse continued to occur after 5 years. In contrast, no additional distant metastases were found after 5 years. The causes of death included local recurrence (n=59), distant metastasis (n=21), both local recurrence and distant metastasis (n = 1), and unrelated causes (n=5). After multivariate analysis, complete recovery of cranial nerve involvement, cranial nerve palsy, and

  10. Prognostics and health management system for hydropower plant based on fog computing and docker container

    Science.gov (United States)

    Xiao, Jian; Zhang, Mingqiang; Tian, Haiping; Huang, Bo; Fu, Wenlong

    2018-02-01

    In this paper, a novel prognostics and health management system architecture for hydropower plant equipment was proposed based on fog computing and Docker container. We employed the fog node to improve the real-time processing ability of improving the cloud architecture-based prognostics and health management system and overcome the problems of long delay time, network congestion and so on. Then Storm-based stream processing of fog node was present and could calculate the health index in the edge of network. Moreover, the distributed micros-service and Docker container architecture of hydropower plants equipment prognostics and health management was also proposed. Using the micro service architecture proposed in this paper, the hydropower unit can achieve the goal of the business intercommunication and seamless integration of different equipment and different manufacturers. Finally a real application case is given in this paper.

  11. Development and validation of a prognostic model for recurrent glioblastoma patients treated with bevacizumab and irinotecan

    DEFF Research Database (Denmark)

    Urup, Thomas; Dahlrot, Rikke Hedegaard; Grunnet, Kirsten

    2016-01-01

    Background Predictive markers and prognostic models are required in order to individualize treatment of recurrent glioblastoma (GBM) patients. Here, we sought to identify clinical factors able to predict response and survival in recurrent GBM patients treated with bevacizumab (BEV) and irinotecan....... Material and methods A total of 219 recurrent GBM patients treated with BEV plus irinotecan according to a previously published treatment protocol were included in the initial population. Prognostic models were generated by means of multivariate logistic and Cox regression analysis. Results In multivariate...

  12. Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

    Science.gov (United States)

    Drier, Yotam; Domany, Eytan

    2011-03-14

    The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

  13. Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

    Directory of Open Access Journals (Sweden)

    Yotam Drier

    2011-03-01

    Full Text Available The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

  14. A clinically based prognostic index for diffuse large B-cell lymphoma with a cut-off at 70 years of age significantly improves prognostic stratification

    DEFF Research Database (Denmark)

    Gang, Anne O.; Pedersen, Michael; d'Amore, Francesco

    2015-01-01

    The introduction of rituximab and generally improved health among elderly patients have increased the survival of patients with diffuse large B-cell lymphoma (DLBCL). The International Prognostic Index (IPI) from 1992 is based on pre-rituximab data from clinical trials including several lymphoma ...... dehydrogenase (LDH), stage and albumin level, and (2) a separate age-adjusted DLBCL-PI for patients 1 extranodal lesion, however excluding stage....... subtypes. We applied IPI factors to a population-based rituximab-treated cohort of 1990 patients diagnosed 2000-2010 and explored new factors and the optimal prognostic age cut-off for DLBCL. Multivariate-analyses (MVA) confirmed the prognostic value of all IPI factors except the presence of > 1 extranodal...... lesion. The optimal age cut-off was 70 years. In a MVA of albumin, lymphocyte count, sex, immunoglobulin G, bulky disease, hemoglobin and B-symptoms, only albumin was prognostic. We propose: (1) a modified DLBCL prognostic index (DLBCL-PI) including: age (70 years), performance status (PS), lactate...

  15. Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM

    Science.gov (United States)

    Zhang, Chaolong; He, Yigang; Yuan, Lifeng; Xiang, Sheng; Wang, Jinping

    2015-01-01

    Lithium-ion batteries are widely used in many electronic systems. Therefore, it is significantly important to estimate the lithium-ion battery's remaining useful life (RUL), yet very difficult. One important reason is that the measured battery capacity data are often subject to the different levels of noise pollution. In this paper, a novel battery capacity prognostics approach is presented to estimate the RUL of lithium-ion batteries. Wavelet denoising is performed with different thresholds in order to weaken the strong noise and remove the weak noise. Relevance vector machine (RVM) improved by differential evolution (DE) algorithm is utilized to estimate the battery RUL based on the denoised data. An experiment including battery 5 capacity prognostics case and battery 18 capacity prognostics case is conducted and validated that the proposed approach can predict the trend of battery capacity trajectory closely and estimate the battery RUL accurately. PMID:26413090

  16. Experimental program for physics-of-failure modeling of electrolytic capacitors towards prognostics and health management

    International Nuclear Information System (INIS)

    Rana, Y.S.; Banerjee, Shantanab; Singh, Tej; Varde, P.V.

    2017-01-01

    Prognostics and Health Management (PHM) is a method used for predicting reliability of a component or system by assessing its current health and future operating conditions. A physics-of-failure (PoF)-based program on PHM for reliability prediction has been initiated at our institute. As part of the program, we aim at developing PoF-based models for degradation of electronic components and their experimental validation. In this direction, a database on existing PoF models for different electronic components has been prepared. We plan to experimentally determine the model constants and propose suitable methodology for PHM. Electrolytic capacitors are one of the most common passive components which find their applications in devices such as power supplies in aircrafts and printed circuit boards (PCBs) for regulation and protection of a nuclear reactor. Experimental studies have established that electrolytic capacitors degrade under electrical and thermal stress and tend to fail before their anticipated useful life at normal operating conditions. Equivalent series resistance (ESR) and capacitance (C) are the two main parameters used for monitoring health of such capacitors. In this paper, we present an experimental program for thermal and electrical overstress studies towards degradation models for electrolytic capacitors. (author)

  17. Prognostic model for chronic hypertension in women with a history of hypertensive pregnancy disorders at term

    NARCIS (Netherlands)

    van der Velde-Visser, S.D.; Hermes, W.; Twisk, J; Franx, A.; Pampus, M.G.; Koopmans, C.; Mol, B. W J; de Groot, J.C.M.J.

    2017-01-01

    Introduction The association between hypertensive pregnancy disorders and cardiovascular disease later in life is well described. In this study we aim to develop a prognostic model from patients characteristics known before, early in, during and after pregnancy to identify women at increased risk of

  18. A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Fernando Sánchez Lasheras

    2015-03-01

    Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

  19. Cancer of the ovary, fallopian tube, and peritoneum: a population-based comparison of the prognostic factors and outcomes.

    Science.gov (United States)

    Rottmann, Miriam; Burges, A; Mahner, S; Anthuber, C; Beck, T; Grab, D; Schnelzer, A; Kiechle, M; Mayr, D; Pölcher, M; Schubert-Fritschle, G; Engel, J

    2017-09-01

    The objective was to compare the prognostic factors and outcomes among primary ovarian cancer (OC), fallopian tube cancer (FC), and peritoneal cancer (PC) patients in a population-based setting. We analysed 5399 OC, 327 FC, and 416 PC patients diagnosed between 1998 and 2014 in the catchment area of the Munich Cancer Registry (meanwhile 4.8 million inhabitants). Tumour site differences were examined by comparing prognostic factors, treatments, the time to progression, and survival. The effect of the tumour site was additionally analysed by a Cox regression model. The median age at diagnosis, histology, and FIGO stage significantly differed among the tumour sites (p < 0.001); PC patients were older, more often diagnosed with a serous subtype, and in FIGO stage III or IV. The time to progression and survival significantly differed among the tumour sites. When stratified by FIGO stage, the differences in time to progression disappeared, and the differences in survival considerably weakened. The differences in the multivariate survival analysis showed an almost identical outcome in PC patients (HR 1.07 [0.91-1.25]) and an improved survival of FC patients (HR 0.63 [0.49-0.81]) compared to that of OC patients. The comparison of OC, FC, and PC patients in this large-scale population-based study showed differences in the prognostic factors. These differences primarily account for the inferior outcome of PC patients, and for the improved survival of FC compared to OC patients.

  20. Prognostics of Power MOSFET

    Science.gov (United States)

    Celaya, Jose Ramon; Saxena, Abhinav; Vashchenko, Vladislay; Saha, Sankalita; Goebel, Kai Frank

    2011-01-01

    This paper demonstrates how to apply prognostics to power MOSFETs (metal oxide field effect transistor). The methodology uses thermal cycling to age devices and Gaussian process regression to perform prognostics. The approach is validated with experiments on 100V power MOSFETs. The failure mechanism for the stress conditions is determined to be die-attachment degradation. Change in ON-state resistance is used as a precursor of failure due to its dependence on junction temperature. The experimental data is augmented with a finite element analysis simulation that is based on a two-transistor model. The simulation assists in the interpretation of the degradation phenomena and SOA (safe operation area) change.

  1. Watershed modeling tools and data for prognostic and diagnostic

    Science.gov (United States)

    Chambel-Leitao, P.; Brito, D.; Neves, R.

    2009-04-01

    's widely used in the world. Watershed models can be characterized by the high number of processes associated simulated. The estimation of these processes is also data intensive, requiring data on topography, land use / land cover, agriculture practices, soil type, precipitation, temperature, relative humidity, wind and radiation. Every year new data is being made available namely by satellite, that has allow to improve the quality of model input and also the calibration of the models (Galvão et. al, 2004b). Tools to cope with the vast amount of data have been developed: data formatting, data retrieving, data bases, metadata bases. The high number of processes simulated in watershed models makes them very wide in terms of output. The SWAT model outputs were modified to produce MOHID compliant result files (time series and HDF). These changes maintained the integrity of the original model, thus guarantying that results remain equal to the original version of SWAT. This allowed to output results in MOHID format, thus making it possible to immediately process it with MOHID visualization and data analysis tools (Chambel-Leitão et. al 2007; Trancoso et. al, 2009). Besides SWAT was modified to produce results files in HDF5 format, this allows the visualization of watershed properties (modeled by SWAT) in animated maps using MOHID GIS. The modified version of SWAT described here has been applied to various national and European projects. Results of the application of this modified version of SWAT to estimate hydrology and nutrients loads to estuaries and water bodies will be shown (Chambel-Leitão, 2008; Yarrow & Chambel-Leitão 2008; Chambel-Leitão et. al 2008; Yarrow & P. Chambel-Leitão, 2007; Yarrow & P. Chambel-Leitão, 2007; Coelho et. al., 2008). Keywords: Watershed models, SWAT, MOHID LAND, Hydrology, Nutrient Loads Arnold, J. G. and Fohrer, N. (2005). SWAT2000: current capabilities and research opportunities in applied watershed modeling. Hydrol. Process. 19, 563

  2. Large-scale external validation and comparison of prognostic models: an application to chronic obstructive pulmonary disease

    NARCIS (Netherlands)

    Guerra, Beniamino; Haile, Sarah R.; Lamprecht, Bernd; Ramírez, Ana S.; Martinez-Camblor, Pablo; Kaiser, Bernhard; Alfageme, Inmaculada; Almagro, Pere; Casanova, Ciro; Esteban-González, Cristóbal; Soler-Cataluña, Juan J.; de-Torres, Juan P.; Miravitlles, Marc; Celli, Bartolome R.; Marin, Jose M.; ter Riet, Gerben; Sobradillo, Patricia; Lange, Peter; Garcia-Aymerich, Judith; Antó, Josep M.; Turner, Alice M.; Han, MeiLan K.; Langhammer, Arnulf; Leivseth, Linda; Bakke, Per; Johannessen, Ane; Oga, Toru; Cosio, Borja; Ancochea-Bermúdez, Julio; Echazarreta, Andres; Roche, Nicolas; Burgel, Pierre-Régis; Sin, Don D.; Soriano, Joan B.; Puhan, Milo A.

    2018-01-01

    External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores

  3. Updating and prospective validation of a prognostic model for high sickness absence.

    Science.gov (United States)

    Roelen, C A M; Heymans, M W; Twisk, J W R; van Rhenen, W; Pallesen, S; Bjorvatn, B; Moen, B E; Magerøy, N

    2015-01-01

    To further develop and validate a Dutch prognostic model for high sickness absence (SA). Three-wave longitudinal cohort study of 2,059 Norwegian nurses. The Dutch prognostic model was used to predict high SA among Norwegian nurses at wave 2. Subsequently, the model was updated by adding person-related (age, gender, marital status, children at home, and coping strategies), health-related (BMI, physical activity, smoking, and caffeine and alcohol intake), and work-related (job satisfaction, job demands, decision latitude, social support at work, and both work-to-family and family-to-work spillover) variables. The updated model was then prospectively validated for predictions at wave 3. 1,557 (77 %) nurses had complete data at wave 2 and 1,342 (65 %) at wave 3. The risk of high SA was under-estimated by the Dutch model, but discrimination between high-risk and low-risk nurses was fair after re-calibration to the Norwegian data. Gender, marital status, BMI, physical activity, smoking, alcohol intake, job satisfaction, job demands, decision latitude, support at the workplace, and work-to-family spillover were identified as potential predictors of high SA. However, these predictors did not improve the model's discriminative ability, which remained fair at wave 3. The prognostic model correctly identifies 73 % of Norwegian nurses at risk of high SA, although additional predictors are needed before the model can be used to screen working populations for risk of high SA.

  4. Novel immunological and nutritional-based prognostic index for gastric cancer.

    Science.gov (United States)

    Sun, Kai-Yu; Xu, Jian-Bo; Chen, Shu-Ling; Yuan, Yu-Jie; Wu, Hui; Peng, Jian-Jun; Chen, Chuang-Qi; Guo, Pi; Hao, Yuan-Tao; He, Yu-Long

    2015-05-21

    To assess the prognostic significance of immunological and nutritional-based indices, including the prognostic nutritional index (PNI), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio in gastric cancer. We retrospectively reviewed 632 gastric cancer patients who underwent gastrectomy between 1998 and 2008. Areas under the receiver operating characteristic curve were calculated to compare the predictive ability of the indices, together with estimating the sensitivity, specificity and agreement rate. Univariate and multivariate analyses were performed to identify risk factors for overall survival (OS). Propensity score analysis was performed to adjust variables to control for selection bias. Each index could predict OS in gastric cancer patients in univariate analysis, but only PNI had independent prognostic significance in multivariate analysis before and after adjustment with propensity scoring (hazard ratio, 1.668; 95% confidence interval: 1.368-2.035). In subgroup analysis, a low PNI predicted a significantly shorter OS in patients with stage II-III disease (P = 0.019, P gastric cancer. Canton score can be a novel preoperative prognostic index in gastric cancer.

  5. Development of a prognostic model for predicting spontaneous singleton preterm birth.

    Science.gov (United States)

    Schaaf, Jelle M; Ravelli, Anita C J; Mol, Ben Willem J; Abu-Hanna, Ameen

    2012-10-01

    To develop and validate a prognostic model for prediction of spontaneous preterm birth. Prospective cohort study using data of the nationwide perinatal registry in The Netherlands. We studied 1,524,058 singleton pregnancies between 1999 and 2007. We developed a multiple logistic regression model to estimate the risk of spontaneous preterm birth based on maternal and pregnancy characteristics. We used bootstrapping techniques to internally validate our model. Discrimination (AUC), accuracy (Brier score) and calibration (calibration graphs and Hosmer-Lemeshow C-statistic) were used to assess the model's predictive performance. Our primary outcome measure was spontaneous preterm birth at model included 13 variables for predicting preterm birth. The predicted probabilities ranged from 0.01 to 0.71 (IQR 0.02-0.04). The model had an area under the receiver operator characteristic curve (AUC) of 0.63 (95% CI 0.63-0.63), the Brier score was 0.04 (95% CI 0.04-0.04) and the Hosmer Lemeshow C-statistic was significant (pvalues of predicted probability. The positive predictive value was 26% (95% CI 20-33%) for the 0.4 probability cut-off point. The model's discrimination was fair and it had modest calibration. Previous preterm birth, drug abuse and vaginal bleeding in the first half of pregnancy were the most important predictors for spontaneous preterm birth. Although not applicable in clinical practice yet, this model is a next step towards early prediction of spontaneous preterm birth that enables caregivers to start preventive therapy in women at higher risk. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  6. Diagnosis and Prognostic of Wastewater Treatment System Based on Bayesian Network

    Science.gov (United States)

    Li, Dan; Yang, Haizhen; Liang, XiaoFeng

    2010-11-01

    Wastewater treatment is a complicated and dynamic process. The treatment effect can be influenced by many variables in microbial, chemical and physical aspects. These variables are always uncertain. Due to the complex biological reaction mechanisms, the highly time-varying and multivariable aspects, the diagnosis and prognostic of wastewater treatment system are still difficult in practice. Bayesian network (BN) is one of the best methods for dealing with uncertainty in the artificial intelligence field. Because of the powerful inference ability and convenient decision mechanism, BN can be employed into the model description and influencing factor analysis of wastewater treatment system with great flexibility and applicability.In this paper, taking modified sequencing batch reactor (MSBR) as an analysis object, BN model was constructed according to the influent water quality, operational condition and effluent effect data of MSBR, and then a novel approach based on BN is proposed to analyze the influencing factors of the wastewater treatment system. The approach presented gives an effective tool for diagnosing and predicting analysis of the wastewater treatment system. On the basis of the influent water quality and operational condition, effluent effect can be predicted. Moreover, according to the effluent effect, the influent water quality and operational condition also can be deduced.

  7. PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

    Science.gov (United States)

    Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

    2010-01-01

    The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

  8. Physical Modeling for Anomaly Diagnostics and Prognostics, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Ridgetop developed an innovative, model-driven anomaly diagnostic and fault characterization system for electromechanical actuator (EMA) systems to mitigate...

  9. Context-Dependent Prognostics and Health Assessment: A Condition-Based Maintenance Approach That Supports Mission Compliance

    Energy Technology Data Exchange (ETDEWEB)

    Allgood, G.O.; Kercel, S.W.

    1999-04-19

    In today's manufacturing environment, plants, systems, and equipment are being asked to perform at levels not thought possible a decade ago. The intent is to improve process operations and equipment reliability, availability, and maintainability without costly upgrades. Of course these gains must be achieved without impacting operational performance. Downsizing is also taking its toll on operations. Loss of personnel, particularly those who represent the corporate history, is depleting US industries of their valuable experiential base which has been relied on so heavily in the past. These realizations are causing companies to rethink their condition-based maintenance policies by moving away from reacting to equipment problems to taking a proactive approach by anticipating needs based on market and customer requirements. This paper describes a different approach to condition-based maintenance-context-dependent prognostics and health assessment. This diagnostic capability is developed around a context-dependent model that provides a capability to anticipate impending failures and determine machine performance over a protracted period of time. This prognostic capability links operational requirements to an economic performance model. In this context, a system may provide 100% operability with less than 100% functionality. This paradigm is used to facilitate optimal logistic supply and support.

  10. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

    Science.gov (United States)

    Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

    2017-05-22

    PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age

  11. Improving Clinical Risk Stratification at Diagnosis in Primary Prostate Cancer: A Prognostic Modelling Study.

    Directory of Open Access Journals (Sweden)

    Vincent J Gnanapragasam

    2016-08-01

    new five-stratum risk stratification system was produced, and its prognostic power was compared against the current system, with PCSM as the outcome. The results were analysed using a Cox hazards model, the log-rank test, Kaplan-Meier curves, competing-risks regression, and concordance indices. In the training set, the new risk stratification system identified distinct subgroups with different risks of PCSM in pair-wise comparison (p < 0.0001. Specifically, the new classification identified a very low-risk group (Group 1, a subgroup of intermediate-risk cancers with a low PCSM risk (Group 2, hazard ratio [HR] 1.62 [95% CI 0.96-2.75], and a subgroup of intermediate-risk cancers with an increased PCSM risk (Group 3, HR 3.35 [95% CI 2.04-5.49] (p < 0.0001. High-risk cancers were also sub-classified by the new system into subgroups with lower and higher PCSM risk: Group 4 (HR 5.03 [95% CI 3.25-7.80] and Group 5 (HR 17.28 [95% CI 11.2-26.67] (p < 0.0001, respectively. These results were recapitulated in the testing set and remained robust after inclusion of competing risks. In comparison to the current risk stratification system, the new system demonstrated improved prognostic performance, with a concordance index of 0.75 (95% CI 0.72-0.77 versus 0.69 (95% CI 0.66-0.71 (p < 0.0001. In an external cohort, the new system achieved a concordance index of 0.79 (95% CI 0.75-0.84 for predicting PCSM versus 0.66 (95% CI 0.63-0.69 (p < 0.0001 for the current NICE risk stratification system. The main limitations of the study were that it was registry based and that follow-up was relatively short.A novel and simple five-stratum risk stratification system outperforms the standard three-stratum risk stratification system in predicting the risk of PCSM at diagnosis in men with primary non-metastatic prostate cancer, even when accounting for competing risks. This model also allows delineation of new clinically relevant subgroups of men who might potentially receive more appropriate

  12. The inflammation-based Glasgow Prognostic Score predicts survival in patients with cervical cancer.

    Science.gov (United States)

    Polterauer, Stephan; Grimm, Christoph; Seebacher, Veronika; Rahhal, Jasmin; Tempfer, Clemens; Reinthaller, Alexander; Hefler, Lukas

    2010-08-01

    The Glasgow Prognostic Score (GPS) is known to reflect the degree of tumor-associated cachexia and inflammation and is associated with survival in various malignancies. We investigated the value of the GPS in patients with cervical cancer. We included 244 consecutive patients with cervical cancer in our study. The pretherapeutic GPS was calculated as follows: patients with elevated C-reactive protein serum levels (>10 mg/L) and hypoalbuminemia (L) were allocated a score of 2, and patients with 1 or no abnormal value were allocated a score of 1 or 0, respectively. The association between GPS and survival was evaluated by univariate log-rank tests and multivariate Cox regression models. The GPS was correlated with clinicopathologic parameters as shown by performing chi2 tests. In univariate analyses, GPS (P GPS (P = 0.03, P = 0.04), FIGO stage (P = 0.006, P = 0.006), and lymph node involvement (P = 0.003, P = 0.002), but not patients' age (P = 0.5, P = 0.5), histological grade (P = 0.7, P = 0.6), and histological type (P = 0.4, P = 0.6) were associated with disease-free and overall survival, respectively. The GPS was associated with FIGO stage (P GPS can be used as an inflammation-based predictor for survival in patients with cervical cancer.

  13. Centrosome-Based Mechanisms, Prognostics and Therapeutics in Prostate Cancer

    Science.gov (United States)

    2006-12-01

    Roberts, J. M. CDK inhibitors: positive and negative regulators of G1- phase progression. Genes Dev. 13, 1501–1512 (1999). 20. La Terra , S. et al. The...centrosome matura - tion because disruption of the tubulin–pericentrin inter- action disrupts spindle pole assembly and possibly centrosome maturation...monitoring. We favor a model in which the check- point senses spindle pole assembly/centrosome matura - tion because disruption of the tubulin

  14. Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

    Directory of Open Access Journals (Sweden)

    Ghosh Debashis

    2004-12-01

    Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

  15. Web Based Prognostics and 24/7 Monitoring

    Science.gov (United States)

    Strautkalns, Miryam; Robinson, Peter

    2013-01-01

    We created a general framework for analysts to store and view data in a way that removes the boundaries created by operating systems, programming languages, and proximity. With the advent of HTML5 and CSS3 with JavaScript the distribution of information is limited to only those who lack a browser. We created a framework based on the methodology: one server, one web based application. Additional benefits are increased opportunities for collaboration. Today the idea of a group in a single room is antiquated. Groups will communicate and collaborate with others from other universities, organizations, as well as other continents across times zones. There are many varieties of data gathering and condition-monitoring software available as well as companies who specialize in customizing software to individual applications. One single group will depend on multiple languages, environments, and computers to oversee recording and collaborating with one another in a single lab. The heterogeneous nature of the system creates challenges for seamless exchange of data and ideas between members. To address these limitations we designed a framework to allow users seamless accessibility to their data. Our framework was deployed using the data feed on the NASA Ames' planetary rover testbed. Our paper demonstrates the process and implementation we followed on the rover.

  16. Prognostic factors and risk stratification in patients with castration-resistant prostate cancer receiving docetaxel-based chemotherapy.

    Science.gov (United States)

    Yamashita, Shimpei; Kohjimoto, Yasuo; Iguchi, Takashi; Koike, Hiroyuki; Kusumoto, Hiroki; Iba, Akinori; Kikkawa, Kazuro; Kodama, Yoshiki; Matsumura, Nagahide; Hara, Isao

    2016-03-22

    While novel drugs have been developed, docetaxel remains one of the standard initial systemic therapies for castration-resistant prostate cancer (CRPC) patients. Despite the excellent anti-tumor effect of docetaxel, its severe adverse effects sometimes distress patients. Therefore, it would be very helpful to predict the efficacy of docetaxel before treatment. The aims of this study were to evaluate the potential value of patient characteristics in predicting overall survival (OS) and to develop a risk classification for CRPC patients treated with docetaxel-based chemotherapy. This study included 79 patients with CRPC treated with docetaxel. The variables, including patient characteristics at diagnosis and at the start of chemotherapy, were retrospectively collected. Prognostic factors predicting OS were analyzed using the Cox proportional hazard model. Risk stratification for overall survival was determined based on the results of multivariate analysis. PSA response ≥50 % was observed in 55 (69.6 %) of all patients, and the median OS was 22.5 months. The multivariate analysis showed that age, serum PSA level at the start of chemotherapy, and Hb were independent prognostic factors for OS. In addition, ECOG performance status (PS) and the CRP-to-albumin ratio were not significant but were considered possible predictors for OS. Risk stratification according to the number of these risk factors could effectively stratify CRPC patients treated with docetaxel in terms of OS. Age, serum PSA level at the start of chemotherapy, and Hb were identified as independent prognostic factors of OS. ECOG PS and the CRP-to-albumin ratio were not significant, but were considered possible predictors for OS in Japanese CRPC patients treated with docetaxel. Risk stratification based on these factors could be helpful for estimating overall survival.

  17. A Novel Prognostic Score, Based on Preoperative Nutritional Status, Predicts Outcomes of Patients after Curative Resection for Gastric Cancer.

    Science.gov (United States)

    Liu, Xuechao; Qiu, Haibo; Liu, Jianjun; Chen, Shangxiang; Xu, Dazhi; Li, Wei; Zhan, Youqing; Li, Yuanfang; Chen, Yingbo; Zhou, Zhiwei; Sun, Xiaowei

    2016-01-01

    PURPOSE: We aimed to determine whether preoperative nutritional status (PNS) was a valuable predictor of outcome in patients with gastric cancer (GC). METHODS: We retrospectively evaluated 1320 patients with GC undergoing curative resection. The PNS score was constructed based on four objective and easily measurable criteria: prognostic nutritional index (PNI) score 1, serum albumin nutritional-based prognostic score, is independently associated with OS in GC. Prospective studies are needed to validate its clinical utility.

  18. Evaluation of Simulated Marine Aerosol Production Using the WaveWatchIII Prognostic Wave Model Coupled to the Community Atmosphere Model within the Community Earth System Model

    Energy Technology Data Exchange (ETDEWEB)

    Long, M. S. [Harvard Univ., Cambridge, MA (United States). School of Engineering and Applied Sciences; Keene, William C. [Univ. of Virginia, Charlottesville, VA (United States). Dept. of Environmental Sciences; Zhang, J. [Univ. of North Dakota, Grand Forks, ND (United States). Dept. of Atmospheric Sciences; Reichl, B. [Univ. of Rhode Island, Narragansett, RI (United States). Graduate School of Oceanography; Shi, Y. [Univ. of North Dakota, Grand Forks, ND (United States). Dept. of Atmospheric Sciences; Hara, T. [Univ. of Rhode Island, Narragansett, RI (United States). Graduate School of Oceanography; Reid, J. S. [Naval Research Lab. (NRL), Monterey, CA (United States); Fox-Kemper, B. [Brown Univ., Providence, RI (United States). Earth, Environmental and Planetary Sciences; Craig, A. P. [National Center for Atmospheric Research, Boulder, CO (United States); Erickson, D. J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division; Ginis, I. [Univ. of Rhode Island, Narragansett, RI (United States). Graduate School of Oceanography; Webb, A. [Univ. of Tokyo (Japan). Dept. of Ocean Technology, Policy, and Environment

    2016-11-08

    Primary marine aerosol (PMA) is emitted into the atmosphere via breaking wind waves on the ocean surface. Most parameterizations of PMA emissions use 10-meter wind speed as a proxy for wave action. This investigation coupled the 3rd generation prognostic WAVEWATCH-III wind-wave model within a coupled Earth system model (ESM) to drive PMA production using wave energy dissipation rate – analogous to whitecapping – in place of 10-meter wind speed. The wind speed parameterization did not capture basin-scale variability in relations between wind and wave fields. Overall, the wave parameterization did not improve comparison between simulated versus measured AOD or Na+, thus highlighting large remaining uncertainties in model physics. Results confirm the efficacy of prognostic wind-wave models for air-sea exchange studies coupled with laboratory- and field-based characterizations of the primary physical drivers of PMA production. No discernible correlations were evident between simulated PMA fields and observed chlorophyll or sea surface temperature.

  19. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1993-01-01

    Most of today's general circulation models (GCMS) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, there has arisen an urgent need for improvements in the treatment of clouds in GCMS, especially as the clouds relate to radiation. In the present paper, we investigate the effects of introducing pregnostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the long wave emissivity calculations. Results from several sensitivity simulations show that realistic cloud water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds become stronger, due to more realistic tropical convection

  20. Accounting for treatment use when validating a prognostic model: a simulation study.

    Science.gov (United States)

    Pajouheshnia, Romin; Peelen, Linda M; Moons, Karel G M; Reitsma, Johannes B; Groenwold, Rolf H H

    2017-07-14

    Prognostic models often show poor performance when applied to independent validation data sets. We illustrate how treatment use in a validation set can affect measures of model performance and present the uses and limitations of available analytical methods to account for this using simulated data. We outline how the use of risk-lowering treatments in a validation set can lead to an apparent overestimation of risk by a prognostic model that was developed in a treatment-naïve cohort to make predictions of risk without treatment. Potential methods to correct for the effects of treatment use when testing or validating a prognostic model are discussed from a theoretical perspective.. Subsequently, we assess, in simulated data sets, the impact of excluding treated individuals and the use of inverse probability weighting (IPW) on the estimated model discrimination (c-index) and calibration (observed:expected ratio and calibration plots) in scenarios with different patterns and effects of treatment use. Ignoring the use of effective treatments in a validation data set leads to poorer model discrimination and calibration than would be observed in the untreated target population for the model. Excluding treated individuals provided correct estimates of model performance only when treatment was randomly allocated, although this reduced the precision of the estimates. IPW followed by exclusion of the treated individuals provided correct estimates of model performance in data sets where treatment use was either random or moderately associated with an individual's risk when the assumptions of IPW were met, but yielded incorrect estimates in the presence of non-positivity or an unobserved confounder. When validating a prognostic model developed to make predictions of risk without treatment, treatment use in the validation set can bias estimates of the performance of the model in future targeted individuals, and should not be ignored. When treatment use is random, treated

  1. Accounting for treatment use when validating a prognostic model: a simulation study

    Directory of Open Access Journals (Sweden)

    Romin Pajouheshnia

    2017-07-01

    Full Text Available Abstract Background Prognostic models often show poor performance when applied to independent validation data sets. We illustrate how treatment use in a validation set can affect measures of model performance and present the uses and limitations of available analytical methods to account for this using simulated data. Methods We outline how the use of risk-lowering treatments in a validation set can lead to an apparent overestimation of risk by a prognostic model that was developed in a treatment-naïve cohort to make predictions of risk without treatment. Potential methods to correct for the effects of treatment use when testing or validating a prognostic model are discussed from a theoretical perspective.. Subsequently, we assess, in simulated data sets, the impact of excluding treated individuals and the use of inverse probability weighting (IPW on the estimated model discrimination (c-index and calibration (observed:expected ratio and calibration plots in scenarios with different patterns and effects of treatment use. Results Ignoring the use of effective treatments in a validation data set leads to poorer model discrimination and calibration than would be observed in the untreated target population for the model. Excluding treated individuals provided correct estimates of model performance only when treatment was randomly allocated, although this reduced the precision of the estimates. IPW followed by exclusion of the treated individuals provided correct estimates of model performance in data sets where treatment use was either random or moderately associated with an individual's risk when the assumptions of IPW were met, but yielded incorrect estimates in the presence of non-positivity or an unobserved confounder. Conclusions When validating a prognostic model developed to make predictions of risk without treatment, treatment use in the validation set can bias estimates of the performance of the model in future targeted individuals, and

  2. A Rest Time-Based Prognostic Framework for State of Health Estimation of Lithium-Ion Batteries with Regeneration Phenomena

    Directory of Open Access Journals (Sweden)

    Taichun Qin

    2016-11-01

    Full Text Available State of health (SOH prognostics is significant for safe and reliable usage of lithium-ion batteries. To accurately predict regeneration phenomena and improve long-term prediction performance of battery SOH, this paper proposes a rest time-based prognostic framework (RTPF in which the beginning time interval of two adjacent cycles is adopted to reflect the rest time. In this framework, SOH values of regeneration cycles, the number of cycles in regeneration regions and global degradation trends are extracted from raw SOH time series and predicted respectively, and then the three sets of prediction results are integrated to calculate the final overall SOH prediction values. Regeneration phenomena can be found by support vector machine and hyperplane shift (SVM-HS model by detecting long beginning time intervals. Gaussian process (GP model is utilized to predict the global degradation trend, and nonlinear models are utilized to predict the regeneration amplitude and the cycle number of each regeneration region. The proposed framework is validated through experimental data from the degradation tests of lithium-ion batteries. The results demonstrate that both the global degradation trend and the regeneration phenomena of the testing batteries can be well predicted. Moreover, compared with the published methods, more accurate SOH prediction results can be obtained under this framework.

  3. Liposarcoma: exploration of clinical prognostic factors for risk based stratification of therapy

    International Nuclear Information System (INIS)

    Kim, Hyo Song; Park, Joon Oh; Kim, Sung Joo; Lee, Jeeyun; Yi, Seong Yoon; Jun, Hyun Jung; Choi, Yoon-La; Ahn, Geung Hwan; Seo, Sung Wook; Lim, Do Hoon; Ahn, Yong Chan

    2009-01-01

    Prognosis and optimal treatment strategies of liposarcoma have not been fully defined. The purpose of this study is to define the distinctive clinical features of liposarcomas by assessing prognostic factors. Between January 1995 and May 2008, 94 liposarcoma patients who underwent surgical resection with curative intent were reviewed. Fifty patients (53.2%) presented with well differentiated, 22 (23.4%) myxoid, 15 (16.0%) dedifferentiated, 5 (5.3%) round cell, and 2 (2.1%) pleomorphic histology. With the median 14 cm sized of tumor burden, about half of the cases were located in the retroperitoneum (46.8%). Seventy two (76.6%) patients remained alive with 78.1%, and 67.5% of the 5- and 10-year overall survival (OS) rates, respectively. Low grade liposarcoma (well differentiated and myxoid) had a significantly prolonged OS and disease free survival (DFS) with adjuvant radiotherapy when compared with those without adjuvant radiotherapy (5-year OS, 100% vs 66.3%, P = 0.03; 1-year DFS, 92.9% vs 50.0%, respectively, P = 0.04). Independent prognostic factors for OS were histologic variant (P = 0.001; HR, 5.1; 95% CI, 2.0 – 12.9), and margin status (P = 0.005; HR, 4.1; 95% CI, 1.6–10.5). We identified three different risk groups: group 1 (n = 66), no adverse factors; group 2, one or two adverse factors (n = 28). The 5-year OS rate for group 1, and 2 were 91.9%, 45.5%, respectively. The histologic subtype, and margin status were independently associated with OS, and adjuvant radiotherapy seems to confer survival benefit in low grade tumors. Our prognostic model for primary liposarcoma demonstrated distinct three groups of patients with good prognostic discrimination

  4. Prognostic factors in breast phyllodes tumors: a nomogram based on a retrospective cohort study of 404 patients.

    Science.gov (United States)

    Zhou, Zhi-Rui; Wang, Chen-Chen; Sun, Xiang-Jie; Yang, Zhao-Zhi; Chen, Xing-Xing; Shao, Zhi-Ming; Yu, Xiao-Li; Guo, Xiao-Mao

    2018-04-01

    The aim of this study was to explore the independent prognostic factors related to postoperative recurrence-free survival (RFS) in patients with breast phyllodes tumors (PTBs). A retrospective analysis was conducted in Fudan University Shanghai Cancer Center. According to histological type, patients with benign PTBs were classified as a low-risk group, while borderline and malignant PTBs were classified as a high-risk group. The Cox regression model was adopted to identify factors affecting postoperative RFS in the two groups, and a nomogram was generated to predict recurrence-free survival at 1, 3, and 5 years. Among the 404 patients, 168 (41.6%) patients had benign PTB, 184 (45.5%) had borderline PTB, and 52 (12.9%) had malignant PTB. Fifty-five patients experienced postoperative local recurrence, including six benign cases, 26 borderline cases, and 22 malignant cases; the three histological types of PTB had local recurrence rates of 3.6%, 14.1%, and 42.3%, respectively. Stromal cell atypia was an independent prognostic factor for RFS in the low-risk group, while the surgical approach and tumor border were independent prognostic factors for RFS in the high-risk group, and patients receiving simple excision with an infiltrative tumor border had a higher recurrence rate. A nomogram developed based on clinicopathologic features and surgical approaches could predict recurrence-free survival at 1, 3, and 5 years. For high-risk patients, this predictive nomogram based on tumor border, tumor residue, mitotic activity, degree of stromal cell hyperplasia, and atypia can be applied for patient counseling and clinical management. The efficacy of adjuvant radiotherapy remains uncertain. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  5. Cutaneous Lymphoma International Consortium Study of Outcome in Advanced Stages of Mycosis Fungoides and Sézary Syndrome: Effect of Specific Prognostic Markers on Survival and Development of a Prognostic Model

    Science.gov (United States)

    Scarisbrick, Julia J.; Prince, H. Miles; Vermeer, Maarten H.; Quaglino, Pietro; Horwitz, Steven; Porcu, Pierluigi; Stadler, Rudolf; Wood, Gary S.; Beylot-Barry, Marie; Pham-Ledard, Anne; Foss, Francine; Girardi, Michael; Bagot, Martine; Michel, Laurence; Battistella, Maxime; Guitart, Joan; Kuzel, Timothy M.; Martinez-Escala, Maria Estela; Estrach, Teresa; Papadavid, Evangelia; Antoniou, Christina; Rigopoulos, Dimitis; Nikolaou, Vassilki; Sugaya, Makoto; Miyagaki, Tomomitsu; Gniadecki, Robert; Sanches, José Antonio; Cury-Martins, Jade; Miyashiro, Denis; Servitje, Octavio; Muniesa, Cristina; Berti, Emilio; Onida, Francesco; Corti, Laura; Hodak, Emilia; Amitay-Laish, Iris; Ortiz-Romero, Pablo L.; Rodríguez-Peralto, Jose L.; Knobler, Robert; Porkert, Stefanie; Bauer, Wolfgang; Pimpinelli, Nicola; Grandi, Vieri; Cowan, Richard; Rook, Alain; Kim, Ellen; Pileri, Alessandro; Patrizi, Annalisa; Pujol, Ramon M.; Wong, Henry; Tyler, Kelly; Stranzenbach, Rene; Querfeld, Christiane; Fava, Paolo; Maule, Milena; Willemze, Rein; Evison, Felicity; Morris, Stephen; Twigger, Robert; Talpur, Rakhshandra; Kim, Jinah; Ognibene, Grant; Li, Shufeng; Tavallaee, Mahkam; Hoppe, Richard T.; Duvic, Madeleine; Whittaker, Sean J.; Kim, Youn H.

    2015-01-01

    Purpose Advanced-stage mycosis fungoides (MF; stage IIB to IV) and Sézary syndrome (SS) are aggressive lymphomas with a median survival of 1 to 5 years. Clinical management is stage based; however, there is wide range of outcome within stages. Published prognostic studies in MF/SS have been single-center trials. Because of the rarity of MF/SS, only a large collaboration would power a study to identify independent prognostic markers. Patients and Methods Literature review identified the following 10 candidate markers: stage, age, sex, cutaneous histologic features of folliculotropism, CD30 positivity, proliferation index, large-cell transformation, WBC/lymphocyte count, serum lactate dehydrogenase, and identical T-cell clone in blood and skin. Data were collected at specialist centers on patients diagnosed with advanced-stage MF/SS from 2007. Each parameter recorded at diagnosis was tested against overall survival (OS). Results Staging data on 1,275 patients with advanced MF/SS from 29 international sites were included for survival analysis. The median OS was 63 months, with 2- and 5-year survival rates of 77% and 52%, respectively. The median OS for patients with stage IIB disease was 68 months, but patients diagnosed with stage III disease had slightly improved survival compared with patients with stage IIB, although patients diagnosed with stage IV disease had significantly worse survival (48 months for stage IVA and 33 months for stage IVB). Of the 10 variables tested, four (stage IV, age > 60 years, large-cell transformation, and increased lactate dehydrogenase) were independent prognostic markers for a worse survival. Combining these four factors in a prognostic index model identified the following three risk groups across stages with significantly different 5-year survival rates: low risk (68%), intermediate risk (44%), and high risk (28%). Conclusion To our knowledge, this study includes the largest cohort of patients with advanced-stage MF/SS and

  6. Comparison of the prognostic values of preoperative inflammation-based parameters in patients with breast cancer.

    Directory of Open Access Journals (Sweden)

    Hideya Takeuchi

    Full Text Available Peripheral blood-derived inflammation-based markers, including C-reactive protein (CRP, neutrophil-to-lymphocyte ratio (NLR, lymphocyte-to-monocyte ratio (LMR, and platelet-to-lymphocyte ratio (PLR are indicators of prognosis in various malignant tumors. The present study aimed to identify the inflammation-based parameters that are most suitable for predicting outcomes in patients with breast cancer. Two hundred ninety-six patients who underwent surgery for localized breast cancer were reviewed retrospectively. The association between clinicopathological factors and inflammation-based parameters were investigated. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic indicators associated with disease-free survival (DFS. The NLR level correlated significantly with tumor size (P<0.05. The PLR level correlated with the expression of estrogen receptor and lymph node involvement (P<0.05. Univariate analysis revealed that lower CRP and PLR values as well as tumor size, lymph node involvement, and nuclear grade were significantly associated with superior DFS (CRP: P<0.01; PLR, tumor size, lymph node involvement, and nuclear grade: P<0.05. On multivariate analysis, CRP (hazard ratio [HR]: 2.85, 95% confidence interval [CI]: 1.03-7.88, P<0.05, PLR (HR: 2.61, 95% CI: 1.07-6.36, P<0.05 and nuclear grade (HR: 3.066, 95% CI: 1.26-7.49, P<0.05 were significant prognostic indicators of DFS in patients with breast cancer. Neither LMR nor NLR significantly predicted DFS. Both preoperative CRP and PLR values were independently associated with poor prognosis in patients with breast carcinoma; these were superior to other inflammation-based scores in terms of prognostic ability.

  7. Prognostic stratification of patients with advanced renal cell carcinoma treated with sunitinib: comparison with the Memorial Sloan-Kettering prognostic factors model

    International Nuclear Information System (INIS)

    Bamias, Aristotelis; Anastasiou, Ioannis; Stravodimos, Kostas; Xanthakis, Ioannis; Skolarikos, Andreas; Christodoulou, Christos; Syrigos, Kostas; Papandreou, Christos; Razi, Evangelia; Dafni, Urania; Fountzilas, George; Karadimou, Alexandra; Dimopoulos, Meletios A; Lampaki, Sofia; Lainakis, George; Malettou, Lia; Timotheadou, Eleni; Papazisis, Kostas; Andreadis, Charalambos; Kontovinis, Loukas

    2010-01-01

    The treatment paradigm in advanced renal cell carcinoma (RCC) has changed in the recent years. Sunitinib has been established as a new standard for first-line therapy. We studied the prognostic significance of baseline characteristics and we compared the risk stratification with the established Memorial Sloan Kettering Cancer Center (MSKCC) model. This is a retrospective analysis of patients treated in six Greek Oncology Units of HECOG. Inclusion criteria were: advanced renal cell carcinoma not amenable to surgery and treatment with Sunitinib. Previous cytokine therapy but no targeted agents were allowed. Overall survival (OS) was the major end point. Significance of prognostic factors was evaluated with multivariate cox regression analysis. A model was developed to stratify patients according to risk. One hundred and nine patients were included. Median follow up has been 15.8 months and median OS 17.1 months (95% CI: 13.7-20.6). Time from diagnosis to the start of Sunitinib (<= 12 months vs. >12 months, p = 0.001), number of metastatic sites (1 vs. >1, p = 0.003) and performance status (PS) (<= 1 vs >1, p = 0.001) were independently associated with OS. Stratification in two risk groups ('low' risk: 0 or 1 risk factors; 'high' risk: 2 or 3 risk factors) resulted in distinctly different OS (median not reached [NR] vs. 10.8 [95% confidence interval (CI): 8.3-13.3], p < 0.001). The application of the MSKCC risk criteria resulted in stratification into 3 groups (low and intermediate and poor risk) with distinctly different prognosis underlying its validity. Nevertheless, MSKCC model did not show an improved prognostic performance over the model developed by this analysis. Studies on risk stratification of patients with advanced RCC treated with targeted therapies are warranted. Our results suggest that a simpler than the MSKCC model can be developed. Such models should be further validated

  8. Prognostic value of normal stress-only myocardial perfusion imaging: a comparison between conventional and CZT-based SPECT

    Energy Technology Data Exchange (ETDEWEB)

    Yokota, Shu; Ottervanger, Jan Paul; Timmer, Jorik R. [Isala Hospital, Department of Cardiology, Zwolle (Netherlands); Mouden, Mohamed; Engbers, Elsemiek [Isala Hospital, Department of Cardiology, Zwolle (Netherlands); Isala Hospital, Department of Nuclear Medicine, Zwolle (Netherlands); Knollema, Siert; Jager, Pieter L. [Isala Hospital, Department of Nuclear Medicine, Zwolle (Netherlands)

    2016-02-15

    Single photon emission computed tomography (SPECT) myocardial perfusion imaging has proven to have prognostic importance in patients with suspected stable coronary artery disease (CAD). The recently introduced ultrafast cadmium zinc telluride (CZT)-based gamma cameras have been associated with less equivocal findings and more normal interpretations, allowing stress-only imaging to be performed more often. However, it is yet unclear whether normal stress-only CZT SPECT has comparable prognostic value as normally interpreted stress-only conventional SPECT. The study population consisted of 1,650 consecutive patients without known CAD with normal stress-only myocardial perfusion results with either conventional (n = 362) or CZT SPECT (n = 1,288). The incidence of major adverse cardiac events (MACE, all-cause death, non-fatal myocardial infarction and/or coronary revascularization) was compared between the conventional SPECT and CZT SPECT groups. Multivariable analyses using the Cox model were used to adjust for differences in baseline variables. Patients scanned with CZT were less often male (33 vs 39 %), had less often hypercholesterolaemia (41 vs 50 %) and had more often a family history of CAD (57 vs 49 %). At a median follow-up time of 37 months (interquartile range 28-45 months) MACE occurred in 68 patients. The incidence of MACE was 1.5 %/year in the CZT group, compared to 2.0 %/year in the conventional group (p = 0.08). After multivariate analyses, there was a trend to a lower incidence of MACE in the CZT SPECT group (hazard ratio 0.61, 95 % confidence interval 0.35-1.04, p = 0.07). The prognostic value of normal stress-only CZT SPECT is at least comparable and may be even better than that of normal conventional stress SPECT. (orig.)

  9. Prognostics and Condition-Based Maintenance: A New Approach to Precursive Metrics

    International Nuclear Information System (INIS)

    Jarrell, Donald B.; Sisk, Daniel R.; Bond, Leonard J.

    2004-01-01

    The assumptions used in the design basis of process equipment have always been as much art as science. The usually imprecise boundaries of the equipments' operational envelope provide opportunities for two major improvements in the operations and maintenance (O and M) of process machinery: (a) the actual versus intended machine environment can be understood and brought into much better alignment and (b) the end goal can define O and M strategies in terms of life cycle and economic management of plant assets.Scientists at the Pacific Northwest National Laboratory (PNNL) have performed experiments aimed at understanding and controlling aging of both safety-specific nuclear plant components and the infrastructure that supports essential plant processes. In this paper we examine the development of aging precursor metrics and their correlation with degradation rate and projected machinery failure.Degradation-specific correlations have been developed at PNNL that will allow accurate physics-based diagnostic and prognostic determinations to be derived from a new view of condition-based maintenance. This view, founded in root cause analysis, is focused on quantifying the primary stressor(s) responsible for degradation in the component of interest and formulating a deterministic relationship between the stressor intensity and the resulting degradation rate. This precursive relationship between the performance, degradation, and underlying stressor set is used to gain a first-principles approach to prognostic determinations. A holistic infrastructure approach, as applied through a conditions-based maintenance framework, will allow intelligent, automated diagnostic and prognostic programming to provide O and M practitioners with an understanding of the condition of their machinery today and an assurance of its operational state tomorrow

  10. VTE Risk assessment - a prognostic Model: BATER Cohort Study of young women.

    Science.gov (United States)

    Heinemann, Lothar Aj; Dominh, Thai; Assmann, Anita; Schramm, Wolfgang; Schürmann, Rolf; Hilpert, Jan; Spannagl, Michael

    2005-04-18

    BACKGROUND: Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE). There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. MATERIALS AND METHODS: A 10-year observation period of the Bavarian Thromboembolic Risk (BATER) study, a cohort study of 4337 women (18-55 years), was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993). The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. RESULTS: Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs). A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI) and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation). Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%), moderate risk (21.1%), high risk (6.0%), very high risk of future VTE (0.9%). In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. CONCLUSION: Our prognostic tool - containing clinical information (and if available also genetic data) - seems to be

  11. VTE Risk assessment – a prognostic Model: BATER Cohort Study of young women

    Directory of Open Access Journals (Sweden)

    Schürmann Rolf

    2005-04-01

    Full Text Available Abstract Background Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE. There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. Materials and methods A 10-year observation period of the Bavarian Thromboembolic Risk (BATER study, a cohort study of 4337 women (18–55 years, was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993. The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. Results Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs. A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation. Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%, moderate risk (21.1%, high risk (6.0%, very high risk of future VTE (0.9%. In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. Conclusion Our prognostic tool – containing clinical information (and if available also genetic data

  12. ANAM4 TBI Reaction Time-Based Tests have Prognostic Utility for Acute Concussion

    Science.gov (United States)

    2013-07-01

    7:767. 2013 ANAM4 TBI Reaction Time-Based Tests Have Prognostic Utility for Acute Concussion LT Jacob N. Norris, MSC USN*; LCDR Waiter Carr, MSC USN...CDR Thomas Herzig, MSC USNf; CDR D. Waiter Labrie, MSC USNf; CDR Richard Sams, MC USN§ ABSTRACT The Concussion Restoration Care Center has used the...Work Unit No. N24LB. REFERENCES 1. Department of Defense: DoD Poiicy Guidance for Management of Mild Traumatic Brain Injury/Concussion in the Deployed

  13. A probabilistic physics-of-failure model for prognostic health management of structures subject to pitting and corrosion-fatigue

    International Nuclear Information System (INIS)

    Chookah, M.; Nuhi, M.; Modarres, M.

    2011-01-01

    A combined probabilistic physics-of-failure-based model for pitting and corrosion-fatigue degradation mechanisms is proposed to estimate the reliability of structures and to perform prognosis and health management. A mechanistic superposition model for corrosion-fatigue mechanism was used as a benchmark model to propose the simple model. The proposed model describes the degradation of the structures as a function of physical and critical environmental stresses, such as amplitude and frequency of mechanical loads (for example caused by the internal piping pressure) and the concentration of corrosive chemical agents. The parameters of the proposed model are represented by the probability density functions and estimated through a Bayesian approach based on the data taken from the experiments performed as part of this research. For demonstrating applications, the proposed model provides prognostic information about the reliability of aging of structures and is helpful in developing inspection and replacement strategies. - Highlights: ► We model an inventory system under static–dynamic uncertainty strategy. ► The demand is stochastic and non-stationary. ► The optimal ordering policy is proven to be a base stock policy. ► A solution algorithm for finding an optimal solution is provided. ► Two heuristics developed produce high quality solutions and scale-up efficiently.

  14. Prognostics and Condition Based Maintenance: A New Approach to Precursive Metrics

    International Nuclear Information System (INIS)

    Jarrell, Donald B.; Sisk, Daniel R.; Bond, Leonard J.

    2002-01-01

    Scientists at the Pacific Northwest National Laboratory (PNNL) have examined the necessity for understanding and controlling the aging process of both safety-specific plant components and the infrastructure that supports these processes. In this paper we examine the preliminary development of aging precursor metrics and their correlation with degradation rate and projected machine failure. Degradation specific correlations are currently being developed at PNNL that will allow accurate physics-based diagnostic and prognostic determinations to be derived from a new view of condition based maintenance. This view, founded in root cause analysis, is focused on quantifying the primary stressor(s) responsible for degradation in the component of interest. The derivative relationship between the performance, degradation and the underlying stressor set is used to gain a first principles approach to prognostic determinations. The assumptions used for the design basis of process equipment have always been as much art as science and for this reason have been misused or relegated into obscurity in all but the nuclear industry. The ability to successfully link degradation and expected equipment life to stressor intensity level is valuable in that it quantifies the degree of machine stress for a given production level. This allows two major improvements in the O and M of process machinery: (1) the actual versus intended machine environment can be understood and brought into much better alignment, and (2) the end goal can define operations and maintenance strategies in terms of life cycle and economic management of plant assets. A holistic infrastructure approach, as applied through a CBM framework, will allow intelligent, automated diagnostic and prognostic programs to provide O and M practitioners with an understanding of the condition of their machinery today and an assurance of its operational state tomorrow

  15. External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study.

    Science.gov (United States)

    Lamain-de Ruiter, Marije; Kwee, Anneke; Naaktgeboren, Christiana A; de Groot, Inge; Evers, Inge M; Groenendaal, Floris; Hering, Yolanda R; Huisjes, Anjoke J M; Kirpestein, Cornel; Monincx, Wilma M; Siljee, Jacqueline E; Van 't Zelfde, Annewil; van Oirschot, Charlotte M; Vankan-Buitelaar, Simone A; Vonk, Mariska A A W; Wiegers, Therese A; Zwart, Joost J; Franx, Arie; Moons, Karel G M; Koster, Maria P H

    2016-08-30

     To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy.  External validation of all published prognostic models in large scale, prospective, multicentre cohort study.  31 independent midwifery practices and six hospitals in the Netherlands.  Women recruited in their first trimester (diabetes mellitus of any type were excluded.  Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots.  3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit.  In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  16. Performance and customization of 4 prognostic models for postoperative onset of nausea and vomiting in ear, nose, and throat surgery.

    Science.gov (United States)

    Engel, Jörg M; Junger, Axel; Hartmann, Bernd; Little, Simon; Schnöbel, Rose; Mann, Valesco; Jost, Andreas; Welters, Ingeborg D; Hempelmann, Gunter

    2006-06-01

    To evaluate the performance of 4 published prognostic models for postoperative onset of nausea and vomiting (PONV) by means of discrimination and calibration and the possible impact of customization on these models. Prospective, observational study. Tertiary care university hospital. 748 adult patients (>18 years old) enrolled in this study. Severe obesity (weight > 150 kg or body mass index > 40 kg/m) was an exclusion criterion. All perioperative data were recorded with an anesthesia information management system. A standardized patient interview was performed on the postoperative morning and afternoon. Individual PONV risk was calculated using 4 original regression equations by Koivuranta et al, Apfel et al, Sinclair et al, and Junger et al Discrimination was assessed using receiver operating characteristic (ROC) curves. Calibration was tested using Hosmer-Lemeshow goodness-of-fit statistics. New predictive equations for the 4 models were derived by means of logistic regression (customization). The prognostic performance of the customized models was validated using the "leaving-one-out" technique. Postoperative onset of nausea and vomiting was observed in 11.2% of the specialized patient population. Discrimination could be demonstrated as shown by areas under the receiver operating characteristic curve of 0.62 for the Koivuranta et al model, 0.63 for the Apfel et al model, 0.70 for the Sinclair et al model, and 0.70 for the Junger et al model. Calibration was poor for all 4 original models, indicated by a P value lower than 0.01 in the C and H statistics. Customization improved the accuracy of the prediction for all 4 models. However, the simplified risk scores of the Koivuranta et al model and the Apfel et al model did not show the same efficiency as those of the Sinclair et al model and the Junger et al model. This is possibly a result of having relatively few patients at high risk for PONV in combination with an information loss caused by too few dichotomous

  17. Prognostic methods in medicine

    NARCIS (Netherlands)

    Lucas, P. J.; Abu-Hanna, A.

    1999-01-01

    Prognosis--the prediction of the course and outcome of disease processes--plays an important role in patient management tasks like diagnosis and treatment planning. As a result, prognostic models form an integral part of a number of systems supporting these tasks. Furthermore, prognostic models

  18. A Distributed Approach to System-Level Prognostics

    Science.gov (United States)

    Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, Indranil

    2012-01-01

    Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key technology for systems health management that leads to improved safety and reliability with reduced costs. The prognostics problem is often approached from a component-centric view. However, in most cases, it is not specifically component lifetimes that are important, but, rather, the lifetimes of the systems in which these components reside. The system-level prognostics problem can be quite difficult due to the increased scale and scope of the prognostics problem and the relative Jack of scalability and efficiency of typical prognostics approaches. In order to address these is ues, we develop a distributed solution to the system-level prognostics problem, based on the concept of structural model decomposition. The system model is decomposed into independent submodels. Independent local prognostics subproblems are then formed based on these local submodels, resul ting in a scalable, efficient, and flexible distributed approach to the system-level prognostics problem. We provide a formulation of the system-level prognostics problem and demonstrate the approach on a four-wheeled rover simulation testbed. The results show that the system-level prognostics problem can be accurately and efficiently solved in a distributed fashion.

  19. Single-gene prognostic signatures for advanced stage serous ovarian cancer based on 1257 patient samples.

    Science.gov (United States)

    Zhang, Fan; Yang, Kai; Deng, Kui; Zhang, Yuanyuan; Zhao, Weiwei; Xu, Huan; Rong, Zhiwei; Li, Kang

    2018-04-16

    We sought to identify stable single-gene prognostic signatures based on a large collection of advanced stage serous ovarian cancer (AS-OvCa) gene expression data and explore their functions. The empirical Bayes (EB) method was used to remove the batch effect and integrate 8 ovarian cancer datasets. Univariate Cox regression was used to evaluate the association between gene and overall survival (OS). The Database for Annotation, Visualization and Integrated Discovery (DAVID) tool was used for the functional annotation of genes for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The batch effect was removed by the EB method, and 1257 patient samples were used for further analysis. We selected 341 single-gene prognostic signatures with FDR matrix organization, focal adhesion and DNA replication which are closely associated with cancer. We used the EB method to remove the batch effect of 8 datasets, integrated these datasets and identified stable prognosis signatures for AS-OvCa.

  20. Prognostics-based qualification of high-power white LEDs using Lévy process approach

    Science.gov (United States)

    Yung, Kam-Chuen; Sun, Bo; Jiang, Xiaopeng

    2017-01-01

    Due to their versatility in a variety of applications and the growing market demand, high-power white light-emitting diodes (LEDs) have attracted considerable attention. Reliability qualification testing is an essential part of the product development process to ensure the reliability of a new LED product before its release. However, the widely used IES-TM-21 method does not provide comprehensive reliability information. For more accurate and effective qualification, this paper presents a novel method based on prognostics techniques. Prognostics is an engineering technology predicting the future reliability or determining the remaining useful lifetime (RUL) of a product by assessing the extent of deviation or degradation from its expected normal operating conditions. A Lévy subordinator of a mixed Gamma and compound Poisson process is used to describe the actual degradation process of LEDs characterized by random sporadic small jumps of degradation degree, and the reliability function is derived for qualification with different distribution forms of jump sizes. The IES LM-80 test results reported by different LED vendors are used to develop and validate the qualification methodology. This study will be helpful for LED manufacturers to reduce the total test time and cost required to qualify the reliability of an LED product.

  1. Few promising multivariable prognostic models exist for recovery of people with non-specific neck pain in musculoskeletal primary care: A systematic review

    NARCIS (Netherlands)

    R.W. Wingbermühle (Roel); E. van Trijffel (Emiel); Nelissen, P.M. (Paul M.); B.W. Koes (Bart); A.P. Verhagen (Arianne)

    2017-01-01

    markdownabstractQuestion: Which multivariable prognostic model(s) for recovery in people with neck pain can be used in primary care? Design: Systematic review of studies evaluating multivariable prognostic models. Participants: People with non-specific neck pain presenting at primary care.

  2. Prognostic model for chronic hypertension in women with a history of hypertensive pregnancy disorders at term.

    Science.gov (United States)

    Visser, V S; Hermes, W; Twisk, J; Franx, A; van Pampus, M G; Koopmans, C; Mol, B W J; de Groot, C J M

    2017-10-01

    The association between hypertensive pregnancy disorders and cardiovascular disease later in life is well described. In this study we aim to develop a prognostic model from patients characteristics known before, early in, during and after pregnancy to identify women at increased risk of cardiovascular disease e.g. chronic hypertension years after pregnancy complicated by hypertension at term. We included women with a history of singleton pregnancy complicated by hypertension at term. Women using antihypertensive medication before pregnancy were excluded. We measured hypertension in these women more than 2years postpartum. Different patients characteristics before, early in, during and after pregnancy were considered to develop a prognostic model of chronic hypertension at 2-years. These included amongst others maternal age, blood pressure at pregnancy intake and blood pressure six weeks post-partum. Univariable analyses followed by a multivariable logistic regression analysis was performed to determine which combination of predictors best predicted chronic hypertension. Model performance was assessed by calibration (graphical plot) and discrimination (area under the receiver operating characteristic (AUC)). Of the 305 women in who blood pressure 2.5years after pregnancy was assessed, 105 women (34%) had chronic hypertension. The following patient characteristics were significant associated with chronic hypertension: higher maternal age, lower education, negative family history on hypertensive pregnancy disorders, higher BMI at booking, higher diastolic blood pressure at pregnancy intake, higher systolic blood pressure during pregnancy and higher diastolic blood pressure at six weeks post-partum. These characteristics were included in the prognostic model for chronic hypertension. Model performance was good as indicated by good calibration and good discrimination (AUC; 0.83 (95% CI 0.75 - 0.92). Chronic hypertension can be expected from patient characteristics

  3. Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables

    NARCIS (Netherlands)

    Roelen, Corne A. M.; Stapelfeldt, Christina M.; Heymans, Martijn W.; van Rhenen, Willem; Labriola, Merete; Nielsen, Claus V.; Bultmann, Ute; Jensen, Chris

    Purpose To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models' risk discrimination was also investigated. Methods 2,562 municipal eldercare

  4. Optimization of a prognostic biosphere model for terrestrial biomass and atmospheric CO2 variability

    International Nuclear Information System (INIS)

    Saito, M.; Ito, A.; Maksyutov, S.

    2014-01-01

    This study investigates the capacity of a prognostic biosphere model to simulate global variability in atmospheric CO 2 concentrations and vegetation carbon dynamics under current environmental conditions. Global data sets of atmospheric CO 2 concentrations, above-ground biomass (AGB), and net primary productivity (NPP) in terrestrial vegetation were assimilated into the biosphere model using an inverse modeling method combined with an atmospheric transport model. In this process, the optimal physiological parameters of the biosphere model were estimated by minimizing the misfit between observed and modeled values, and parameters were generated to characterize various biome types. Results obtained using the model with the optimized parameters correspond to the observed seasonal variations in CO 2 concentration and their annual amplitudes in both the Northern and Southern Hemispheres. In simulating the mean annual AGB and NPP, the model shows improvements in estimating the mean magnitudes and probability distributions for each biome, as compared with results obtained using prior simulation parameters. However, the model is less efficient in its simulation of AGB for forest type biomes. This misfit suggests that more accurate values of input parameters, specifically, grid mean AGB values and seasonal variabilities in physiological parameters, are required to improve the performance of the simulation model. (authors)

  5. Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

    Science.gov (United States)

    Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

    2013-01-01

    In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

  6. External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study.

    NARCIS (Netherlands)

    Lamain-de Ruiter, M.; Kwee, A.; Naaktgeboren, C.A.; Groot, I. de; Evers, I.M.; Groenendaal, F.; Hering, Y.R.; Huisjes, A.J.M.; Kirpestein, C.; Monincx, W.M.; Siljee, J.E.; Zelfde, A. van't; Oirschot, C.M. van; Vankan-Buitelaar, S.A.; Vonk, M.A.A.W.; Wiegers, T.A.; Zwart, J.J.; Franx, A.; Moons, K.G.M.; Koster, M.P.H.

    2016-01-01

    Objective: To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy. Design: External validation of all published prognostic models in

  7. Prognostic Health Monitoring System: Component Selection Based on Risk Criteria and Economic Benefit Assessment

    International Nuclear Information System (INIS)

    Pham, Binh T.; Agarwal, Vivek; Lybeck, Nancy J.; Tawfik, Magdy S.

    2012-01-01

    Prognostic health monitoring (PHM) is a proactive approach to monitor the ability of structures, systems, and components (SSCs) to withstand structural, thermal, and chemical loadings over the SSCs planned service lifespan. The current efforts to extend the operational license lifetime of the aging fleet of U.S. nuclear power plants from 40 to 60 years and beyond can benefit from a systematic application of PHM technology. Implementing a PHM system would strengthen the safety of nuclear power plants, reduce plant outage time, and reduce operation and maintenance costs. However, a nuclear power plant has thousands of SSCs, so implementing a PHM system that covers all SSCs requires careful planning and prioritization. This paper therefore focuses on a component selection that is based on the analysis of a component's failure probability, risk, and cost. Ultimately, the decision on component selection depends on the overall economical benefits arising from safety and operational considerations associated with implementing the PHM system. (author)

  8. A Foundation for Stressor-Based Prognostics for Next Generation Systems

    International Nuclear Information System (INIS)

    Jarrell, Don; Sisk, Daniel; Bond, Leonard

    2002-01-01

    Pacific Northwest National Laboratory (PNNL) scientists are performing research under the Department of Energy Nuclear Energy Research Initiative (NERI) program, to develop a methodology for accurate identification and prediction of equipment faults in critical machinery. The 3-year project, on-line intelligent self-diagnostic monitoring system (SDMS) for next generation nuclear power plants is scheduled for completion at the end of FY 2002. The research involves running machinery to failure in the Laboratory by the introduction of intentional faults. During testing, advanced diagnostic/prognostic sensors and analysis systems monitor the equipment stressor levels, correlate them with expected degradation rates, and predict the resulting machinery performance levels and residual lifetime. Application of a first principles physics-based approach is expected to produce prognostic methodologies of significantly higher accuracies than are currently available. This paper reviews the evolution and current state of the maintenance art. It presents a key measurement philosophy that results from the use of condition based maintenance (CBM) as a fundamental investigative precept, and explains how this approach impacts degradation and failure measurement and prediction accuracy. It then examines how this measurement approach is applied in sensing and correlating pump stressors with regard to degradation rate and time to equipment failure. The specifics are examined on how this approach is being applied at PNNL to cavitation and vibration phenomena in a centrifugal pump. Preliminary vibration analysis results show an excellent correspondence between the (laser) motor position indication, the vibration response, and the dynamic force loading on the bearings. Orbital harmonic vibratory motion of the pump and motor appear to be readily correlated through the FFTs of all three sensing systems. (authors)

  9. Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

    Science.gov (United States)

    Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

    2018-04-01

    The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

  10. Prognostic model for patients treated for colorectal adenomas with regard to development of recurrent adenomas and carcinoma

    DEFF Research Database (Denmark)

    Jensen, P; Krogsgaard, M R; Christiansen, J

    1996-01-01

    -80. INTERVENTIONS: All patients were followed up by rectoscopy and double contrast barium enema. The survival data were analysed by Cox's proportional hazards model. MAIN OUTCOME MEASURES: Variables of significant prognostic importance for recurrence of adenomas and the development of cancer were identified...

  11. Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables

    NARCIS (Netherlands)

    Roelen, C.A.M.; Stapelfeldt, C.M.; Heijmans, M.W.; van Rhenen, W.; Labriola, M.; Nielsen, C.V.; Bultmann, U.; Jensen, C.

    2015-01-01

    Purpose To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models’ risk discrimination was also investigated. Methods 2,562 municipal eldercare

  12. Prognostic Modeling in Pathologic N1 Breast Cancer Without Elective Nodal Irradiation After Current Standard Systemic Management.

    Science.gov (United States)

    Yu, Jeong Il; Park, Won; Choi, Doo Ho; Huh, Seung Jae; Nam, Seok Jin; Kim, Seok Won; Lee, Jeong Eon; Kil, Won Ho; Im, Young-Hyuck; Ahn, Jin Seok; Park, Yeon Hee; Cho, Eun Yoon

    2015-08-01

    This study was conducted to establish a prognostic model in patients with pathologic N1 (pN1) breast cancer who have not undergone elective nodal irradiation (ENI) under the current standard management and to suggest possible indications for ENI. We performed a retrospective study with patients with pN1 breast cancer who received the standard local and preferred adjuvant chemotherapy treatment without neoadjuvant chemotherapy and ENI from January 2005 to June 2011. Most of the indicated patients received endocrine and trastuzumab therapy. In 735 enrolled patients, the median follow-up period was 58.4 months (range, 7.2-111.3 months). Overall, 55 recurrences (7.4%) developed, and locoregional recurrence was present in 27 patients (3.8%). Recurrence-free survival was significantly related to lymphovascular invasion (P = .04, hazard ratio [HR], 1.83; 95% confidence interval [CI], 1.03-2.88), histologic grade (P = .03, HR, 2.57; 95% CI, 1.05-6.26), and nonluminal A subtype (P = .02, HR, 3.04; 95% CI, 1.23-7.49) in multivariate analysis. The prognostic model was established by these 3 prognostic factors. Recurrence-free survival was less than 90% at 5 years in cases with 2 or 3 factors. The prognostic model has stratified risk groups in pN1 breast cancer without ENI. Patients with 2 or more factors should be considered for ENI. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Development Of A Multivariate Prognostic Model For Pain And Activity Limitation In People With Low Back Disorders Receiving Physiotherapy.

    Science.gov (United States)

    Ford, Jon J; Richards BPhysio, Matt C; Surkitt BPhysio, Luke D; Chan BPhysio, Alexander Yp; Slater, Sarah L; Taylor, Nicholas F; Hahne, Andrew J

    2018-05-28

    To identify predictors for back pain, leg pain and activity limitation in patients with early persistent low back disorders. Prospective inception cohort study; Setting: primary care private physiotherapy clinics in Melbourne, Australia. 300 adults aged 18-65 years with low back and/or referred leg pain of ≥6-weeks and ≤6-months duration. Not applicable. Numerical rating scales for back pain and leg pain as well as the Oswestry Disability Scale. Prognostic factors included sociodemographics, treatment related factors, subjective/physical examination, subgrouping factors and standardized questionnaires. Univariate analysis followed by generalized estimating equations were used to develop a multivariate prognostic model for back pain, leg pain and activity limitation. Fifty-eight prognostic factors progressed to the multivariate stage where 15 showed significant (pduration, high multifidus tone, clinically determined inflammation, higher back and leg pain severity, lower lifting capacity, lower work capacity and higher pain drawing percentage coverage). The preliminary model identifying predictors of low back disorders explained up to 37% of the variance in outcome. This study evaluated a comprehensive range of prognostic factors reflective of both the biomedical and psychosocial domains of low back disorders. The preliminary multivariate model requires further validation before being considered for clinical use. Copyright © 2018. Published by Elsevier Inc.

  14. Prognostic model for long-term survival of locally advanced non-small-cell lung cancer patients after neoadjuvant radiochemotherapy and resection integrating clinical and histopathologic factors

    International Nuclear Information System (INIS)

    Pöttgen, Christoph; Stuschke, Martin; Graupner, Britta; Theegarten, Dirk; Gauler, Thomas; Jendrossek, Verena; Freitag, Lutz; Jawad, Jehad Abu; Gkika, Eleni; Wohlschlaeger, Jeremias; Welter, Stefan; Hoiczyk, Matthias; Schuler, Martin; Stamatis, Georgios; Eberhardt, Wilfried

    2015-01-01

    Outcome of consecutive patients with locally advanced non-small cell lung cancer and histopathologically proven mediastional lymph node metastases treated with induction chemotherapy, neoadjuvant radiochemotherapy and thoracotomy at the West German Cancer Center between 08/2000 and 06/2012 was analysed. A clinico-pathological prognostic model for survival was built including partial or complete response according to computed tomography imaging (CT) as clinical parameters as well as pathologic complete remission (pCR) and mediastinal nodal clearance (MNC) as histopathologic factors. Proportional hazard analysis (PHA) and recursive partitioning analysis (RPA) were used to identify prognostic factors for survival. Long-term survival was defined as survival ≥ 36 months. A total of 157 patients were treated, median follow-up was 97 months. Among these patients, pCR and MNC were observed in 41 and 85 patients, respectively. Overall survival was 56 ± 4% and 36 ± 4% at 24 and 60 months, respectively. Sensitivities of pCR and MNC to detect long-term survivors were 38% and 61%, specificities were 84% and 52%, respectively. Multivariable survival analysis revealed pCR, cN3 category, and gender, as prognostic factors at a level of α < 0.05. Considering only preoperative available parameters, CT response became significant. Classifying patients with a predicted hazard above the median as high risk group and the remaining as low risk patients yielded better separation of the survival curves by the inclusion of histopathologic factors than by preoperative factors alone (p < 0.0001, log rank test). Using RPA, pCR was identified as the top prognostic factor above clinical factors (p = 0.0006). No long term survivors were observed in patients with cT3-4 cN3 tumors without pCR. pCR is the dominant histopathologic response parameter and improves prognostic classifiers, based on clinical parameters. The validated prognostic model can be used to estimate individual prognosis and

  15. Cross-national validation of prognostic models predicting sickness absence and the added value of work environment variables.

    Science.gov (United States)

    Roelen, Corné A M; Stapelfeldt, Christina M; Heymans, Martijn W; van Rhenen, Willem; Labriola, Merete; Nielsen, Claus V; Bültmann, Ute; Jensen, Chris

    2015-06-01

    To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models' risk discrimination was also investigated. 2,562 municipal eldercare workers (95% women) participated in the Working in Eldercare Survey. Predictor variables were measured by questionnaire at baseline in 2005. Prognostic models were validated for predictions of high (≥30) SA days and high (≥3) SA episodes retrieved from employer records during 1-year follow-up. The accuracy of predictions was assessed by calibration graphs and the ability of the models to discriminate between high- and low-risk workers was investigated by ROC-analysis. The added value of work environment variables was measured with Integrated Discrimination Improvement (IDI). 1,930 workers had complete data for analysis. The models underestimated the risk of high SA in eldercare workers and the SA episodes model had to be re-calibrated to the Danish data. Discrimination was practically useful for the re-calibrated SA episodes model, but not the SA days model. Physical workload improved the SA days model (IDI = 0.40; 95% CI 0.19-0.60) and psychosocial work factors, particularly the quality of leadership (IDI = 0.70; 95% CI 053-0.86) improved the SA episodes model. The prognostic model predicting high SA days showed poor performance even after physical workload was added. The prognostic model predicting high SA episodes could be used to identify high-risk workers, especially when psychosocial work factors are added as predictor variables.

  16. Model for prognostication of population irradiation dose at the soil way of long-living radionuclides including in food chains

    International Nuclear Information System (INIS)

    Prister, B.S.; Vinogradskaya, V.D.

    2009-01-01

    On the basis of modern pictures of cesium and strontium ion absorption mechanisms a soil taking complex was build the kinetic model of radionuclide migration from soil to plants. Model parameter association with the agricultural chemistry properties of soil, represented by complex estimation of soil properties S e f. The example of model application for prognostication of population internal irradiation dose due to consumption of milk at the soil way of long-living radionuclides including in food chains

  17. A first appraisal of prognostic ocean DMS models and prospects for their use in climate models

    NARCIS (Netherlands)

    Le Clainche, Yvonnick; Vezina, Alain; Levasseur, Maurice; Cropp, Roger A.; Gunson, Jim R.; Vallina, Sergio M.; Vogt, Meike; Lancelot, Christiane; Allen, J. Icarus; Archer, Stephen D.; Bopp, Laurent; Deal, Clara; Elliott, Scott; Jin, Meibing; Malin, Gill; Schoemann, Veronique; Simo, Rafel; Six, Katharina D.; Stefels, Jacqueline

    2010-01-01

    Ocean dimethylsulfide (DMS) produced by marine biota is the largest natural source of atmospheric sulfur, playing a major role in the formation and evolution of aerosols, and consequently affecting climate. Several dynamic process-based DMS models have been developed over the last decade, and work

  18. Model for breast cancer survival: relative prognostic roles of axillary nodal status, TNM stage, estrogen receptor concentration, and tumor necrosis.

    Science.gov (United States)

    Shek, L L; Godolphin, W

    1988-10-01

    The independent prognostic effects of certain clinical and pathological variables measured at the time of primary diagnosis were assessed with Cox multivariate regression analysis. The 859 patients with primary breast cancer, on which the proportional hazards model was based, had a median follow-up of 60 months. Axillary nodal status (categorized as N0, N1-3 or N4+) was the most significant and independent factor in overall survival, but inclusion of TNM stage, estrogen receptor (ER) concentration and tumor necrosis significantly improved survival predictions. Predictions made with the model showed striking subset survival differences within stage: 5-year survival from 36% (N4+, loge[ER] = 0, marked necrosis) to 96% (N0, loge[ER] = 6, no necrosis) in TNM I, and from 0 to 70% for the same categories in TNM IV. Results of the model were used to classify patients into four distinct risk groups according to a derived hazard index. An 8-fold variation in survival was seen with the highest (greater than 3) to lowest index values (less than 1). Each hazard index level included patients with varied combinations of the above factors, but could be considered to denote the same degree of risk of breast cancer mortality. A model with ER concentration, nodal status, and tumor necrosis was found to best predict survival after disease recurrence in 369 patients, thus confirming the enduring biological significance of these factors.

  19. Development and validation of prognostic models in metastatic breast cancer: a GOCS study.

    Science.gov (United States)

    Rabinovich, M; Vallejo, C; Bianco, A; Perez, J; Machiavelli, M; Leone, B; Romero, A; Rodriguez, R; Cuevas, M; Dansky, C

    1992-01-01

    The significance of several prognostic factors and the magnitude of their influence on response rate and survival were assessed by means of uni- and multivariate analyses in 362 patients with stage IV (UICC) breast carcinoma receiving combination chemotherapy as first systemic treatment over an 8-year period. Univariate analyses identified performance status and prior adjuvant radiotherapy as predictors of objective regression (OR), whereas the performance status, prior chemotherapy and radiotherapy (adjuvants), white blood cells count, SGOT and SGPT levels, and metastatic pattern were significantly correlated to survival. In multivariate analyses favorable characteristics associated to OR were prior adjuvant radiotherapy, no prior chemotherapy and postmenopausal status. Regarding survival, the performance status and visceral involvement were selected by the Cox model. The predictive accuracy of the logistic and the proportional hazards models was retrospectively tested in the training sample, and prospectively in a new population of 126 patients also receiving combined chemotherapy as first treatment for metastatic breast cancer. A certain overfitting to data in the training sample was observed with the regression model for response. However, the discriminative ability of the Cox model for survival was clearly confirmed.

  20. Primary radiotherapy or postoperative radiotherapy in patients with head and neck cancer. Comparative analysis of inflammation-based prognostic scoring systems

    International Nuclear Information System (INIS)

    Selzer, Edgar; Grah, Anja; Heiduschka, Gregor; Thurnher, Dietmar; Kornek, Gabriela

    2015-01-01

    Inflammation-based scoring systems have potential value in evaluating the prognosis of cancer patients; however, detailed comparative analyses in well-characterized head and neck cancer patient collectives are missing. We analyzed overall survival (OS) in locally advanced head and neck cancer patients who were treated with curative intent by primary radiotherapy (RT) alone, by RT in combination with cetuximab (RIT) or with cisplatin (RCHT), and by primary surgery followed by postoperative radiotherapy (PORT). The primary RT collective (N = 170) was analyzed separately from the surgery plus RT group (N = 148). OS was estimated using the Kaplan-Meyer method. Cox proportional-hazard regression models were applied to compare the risk of death among patients stratified according to risk factors and the inflammation-based Glasgow Prognostic Score (GPS), the modified GPS (mGPS), the neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the prognostic index (PI). A prognostic relevance of the scoring systems for OS was observed in the primarily irradiated, but not in the PORT collective. OS was 35.5, 18.8, and 15.4 months, respectively, according to GPS 0, 1, and 2. OS according to mGPS 0-2 was identical. The PLR scoring system was not of prognostic relevance, while OS was 27.3 months in the NLR 0 group and 17.3 months in the NLR 1 group. OS was 35.5 months in PI 0, 16.1 months in PI 1, and 22.6 months in PI 2. GPS/mGPS scoring systems are able to discriminate between three risk groups in primarily, but not postoperatively irradiated locally advanced head and neck cancer patients. (orig.) [de

  1. Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.

    Science.gov (United States)

    Tadeo, Irene; Piqueras, Marta; Montaner, David; Villamón, Eva; Berbegall, Ana P; Cañete, Adela; Navarro, Samuel; Noguera, Rosa

    2014-02-01

    Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

  2. Cumulative Intracranial Tumor Volume Augments the Prognostic Value of Diagnosis-Specific Graded Prognostic Assessment Model for Survival in Patients with Melanoma Cerebral Metastases

    DEFF Research Database (Denmark)

    Hirshman, Brian R; Wilson, Bayard R; Ali, Mir Amaan

    2018-01-01

    BACKGROUND: The diagnosis-specific graded prognostic assessment scale (ds-GPA) for patients with melanoma brain metastasis (BM) utilizes only 2 key prognostic variables: Karnofsky performance status and the number of intracranial metastases. We wished to determine whether inclusion of cumulative ...

  3. An Optimization Method for Condition Based Maintenance of Aircraft Fleet Considering Prognostics Uncertainty

    Directory of Open Access Journals (Sweden)

    Qiang Feng

    2014-01-01

    Full Text Available An optimization method for condition based maintenance (CBM of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL distribution of the key line replaceable Module (LRM has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success.

  4. [Preoperative evaluation of surgery for intractable aspiration based on the prognostic nutritional index].

    Science.gov (United States)

    Uchida, Masaya; Hashimoto, Keiko; Mukudai, Shigeyuki; Ushijima, Chihisa; Dejima, Kenji

    2014-12-01

    Because there is no absolute indicator of the nutritional status and prognosis in patients with severe aspiration problems, it is quite difficult to arrive at a true long-time prognosis. By performing surgery for intractable aspiration on such patients, both the prognosis and QOL of the patients could be expected to improve. In our department, we have experienced patients dying within 6 months after surgery. In these cases, the patient's preoperative nutritional status was not good. Therefore, we consider that, when we adopt this procedure, there should be some indicators we should use which could have an effect on the prognosis of such nutritionally-challenged patients. In patients who underwent surgery for intractable aspiration; we examined the relationship between their survival and the prognostic nutritional index (PNI) which is an indicator of the risk of complications such as post-operative events in the surgical field. We investigated the relationship between the prognosis and the postoperative indicators of each of the following: WBC, CRP, serum albumin level, and PNI. Out of a total of 31 cases, the average O-PNI of eight cases in which death occurred was 29.45, and the average of six cases in which death occurred within 6 months after surgery was 28.26. The average O-PNI of the survivors was 36.01. A significant association was noted between the early postoperative deaths and some of the four indicators namely that serum albumin level and O-PNI. Based on the ROC curve, the O-PNI offered higher precision than the albumin level. The cut-off value of the O-PNI value for early postoperative mortality rate was 32. The early postoperative mortality rate was 44.4% in patients with less than 32 O-PNI in the preoperative examination, but if it were O-PNI 32 or more, the early postoperative mortality rate was 9.1%, significantly lower. Therefore, O-PNI could be useful as one of the prognostic evaluation factors in the case of preoperative surgery for intractable

  5. Cytogenetic prognostication within medulloblastoma subgroups.

    Science.gov (United States)

    Shih, David J H; Northcott, Paul A; Remke, Marc; Korshunov, Andrey; Ramaswamy, Vijay; Kool, Marcel; Luu, Betty; Yao, Yuan; Wang, Xin; Dubuc, Adrian M; Garzia, Livia; Peacock, John; Mack, Stephen C; Wu, Xiaochong; Rolider, Adi; Morrissy, A Sorana; Cavalli, Florence M G; Jones, David T W; Zitterbart, Karel; Faria, Claudia C; Schüller, Ulrich; Kren, Leos; Kumabe, Toshihiro; Tominaga, Teiji; Shin Ra, Young; Garami, Miklós; Hauser, Peter; Chan, Jennifer A; Robinson, Shenandoah; Bognár, László; Klekner, Almos; Saad, Ali G; Liau, Linda M; Albrecht, Steffen; Fontebasso, Adam; Cinalli, Giuseppe; De Antonellis, Pasqualino; Zollo, Massimo; Cooper, Michael K; Thompson, Reid C; Bailey, Simon; Lindsey, Janet C; Di Rocco, Concezio; Massimi, Luca; Michiels, Erna M C; Scherer, Stephen W; Phillips, Joanna J; Gupta, Nalin; Fan, Xing; Muraszko, Karin M; Vibhakar, Rajeev; Eberhart, Charles G; Fouladi, Maryam; Lach, Boleslaw; Jung, Shin; Wechsler-Reya, Robert J; Fèvre-Montange, Michelle; Jouvet, Anne; Jabado, Nada; Pollack, Ian F; Weiss, William A; Lee, Ji-Yeoun; Cho, Byung-Kyu; Kim, Seung-Ki; Wang, Kyu-Chang; Leonard, Jeffrey R; Rubin, Joshua B; de Torres, Carmen; Lavarino, Cinzia; Mora, Jaume; Cho, Yoon-Jae; Tabori, Uri; Olson, James M; Gajjar, Amar; Packer, Roger J; Rutkowski, Stefan; Pomeroy, Scott L; French, Pim J; Kloosterhof, Nanne K; Kros, Johan M; Van Meir, Erwin G; Clifford, Steven C; Bourdeaut, Franck; Delattre, Olivier; Doz, François F; Hawkins, Cynthia E; Malkin, David; Grajkowska, Wieslawa A; Perek-Polnik, Marta; Bouffet, Eric; Rutka, James T; Pfister, Stefan M; Taylor, Michael D

    2014-03-20

    Medulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication. Molecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models. Subgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas. Combining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials.

  6. Prognostic value and molecular correlates of a CT image-based quantitative pleural contact index in early stage NSCLC

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Juheon; Cui, Yi; Li, Bailiang; Wu, Jia; Gensheimer, Michael F. [Stanford University School of Medicine, Department of Radiation Oncology, Stanford, CA (United States); Sun, Xiaoli [First Affiliated Hospital of Zhejiang University, Radiotherapy Department, Hangzhou, Zhejiang (China); Li, Dengwang [Stanford University School of Medicine, Department of Radiation Oncology, Stanford, CA (United States); Shandong Normal University, Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, Institute of Biomedical Sciences, School of Physics and Electronics, Jinan Shi (China); Loo, Billy W.; Li, Ruijiang [Stanford University School of Medicine, Department of Radiation Oncology, Stanford, CA (United States); Stanford University School of Medicine, Stanford Cancer Institute, Stanford, CA (United States); Diehn, Maximilian [Stanford University School of Medicine, Department of Radiation Oncology, Stanford, CA (United States); Stanford University School of Medicine, Stanford Cancer Institute, Stanford, CA (United States); Stanford University School of Medicine, Institute for Stem Cell Biology and Regenerative Medicine, Stanford, CA (United States)

    2018-02-15

    To evaluate the prognostic value and molecular basis of a CT-derived pleural contact index (PCI) in early stage non-small cell lung cancer (NSCLC). We retrospectively analysed seven NSCLC cohorts. A quantitative PCI was defined on CT as the length of tumour-pleura interface normalised by tumour diameter. We evaluated the prognostic value of PCI in a discovery cohort (n = 117) and tested in an external cohort (n = 88) of stage I NSCLC. Additionally, we identified the molecular correlates and built a gene expression-based surrogate of PCI using another cohort of 89 patients. To further evaluate the prognostic relevance, we used four datasets totalling 775 stage I patients with publically available gene expression data and linked survival information. At a cutoff of 0.8, PCI stratified patients for overall survival in both imaging cohorts (log-rank p = 0.0076, 0.0304). Extracellular matrix (ECM) remodelling was enriched among genes associated with PCI (p = 0.0003). The genomic surrogate of PCI remained an independent predictor of overall survival in the gene expression cohorts (hazard ratio: 1.46, p = 0.0007) adjusting for age, gender, and tumour stage. CT-derived pleural contact index is associated with ECM remodelling and may serve as a noninvasive prognostic marker in early stage NSCLC. (orig.)

  7. Exploring Stage I non-small-cell lung cancer: development of a prognostic model predicting 5-year survival after surgical resection†.

    Science.gov (United States)

    Guerrera, Francesco; Errico, Luca; Evangelista, Andrea; Filosso, Pier Luigi; Ruffini, Enrico; Lisi, Elena; Bora, Giulia; Asteggiano, Elena; Olivetti, Stefania; Lausi, Paolo; Ardissone, Francesco; Oliaro, Alberto

    2015-06-01

    Despite impressive results in diagnosis and treatment of non-small-cell lung cancer (NSCLC), more than 30% of patients with Stage I NSCLC die within 5 years after surgical treatment. Identification of prognostic factors to select patients with a poor prognosis and development of tailored treatment strategies are then advisable. The aim of our study was to design a model able to define prognosis in patients with Stage I NSCLC, submitted to surgery with curative intent. A retrospective analysis of two surgical registries was performed. Predictors of survival were investigated using the Cox model with shared frailty (accounting for the within-centre correlation). Candidate predictors were: age, gender, smoking habit, morbidity, previous malignancy, Eastern Cooperative Oncology Group performance status, clinical N stage, maximum standardized uptake value (SUV(max)), forced expiratory volume in 1 s, carbon monoxide lung diffusion capacity (DLCO), extent of surgical resection, systematic lymphadenectomy, vascular invasion, pathological T stage, histology and histological grading. The final model included predictors with P model demonstrated that mortality was significantly associated with age, male sex, presence of cardiac comorbidities, DLCO (%), SUV(max), systematic nodal dissection, presence of microscopic vascular invasion, pTNM stage and histological grading. The final model showed a fair discrimination ability (C-statistic = 0.69): the calibration of the model indicated a good agreement between observed and predicted survival. We designed an effective prognostic model based on clinical, pathological and surgical covariates. Our preliminary results need to be refined and validated in a larger patient population, in order to provide an easy-to-use prognostic tool for Stage I NSCLC patients. © The Author 2014. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  8. Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

    Energy Technology Data Exchange (ETDEWEB)

    Louie, Alexander V., E-mail: Dr.alexlouie@gmail.com [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands); Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, Massachusetts (United States); Haasbeek, Cornelis J.A. [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands); Mokhles, Sahar [Department of Cardio-Thoracic Surgery, Erasmus University Medical Center, Rotterdam (Netherlands); Rodrigues, George B. [Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Stephans, Kevin L. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Lagerwaard, Frank J. [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands); Palma, David A. [Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Videtic, Gregory M.M. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Warner, Andrew [Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Takkenberg, Johanna J.M. [Department of Cardio-Thoracic Surgery, Erasmus University Medical Center, Rotterdam (Netherlands); Reddy, Chandana A. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Maat, Alex P.W.M. [Department of Cardio-Thoracic Surgery, Erasmus University Medical Center, Rotterdam (Netherlands); Woody, Neil M. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Slotman, Ben J.; Senan, Suresh [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands)

    2015-09-01

    Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogram for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.

  9. Analysis of acute myocardial infarction occurance in Saratov region using GIS-technologies and prognostic modeling

    Directory of Open Access Journals (Sweden)

    SokolovI.M.

    2012-09-01

    Full Text Available

     

    The research objective: To find estimation tools of incidence of acute myocardial infarction at the regional level and to optimize organization of medical assistance to patients with acute coronary pathology. Materials. With the use of statistics of territorial distribution of acute myocardial infarction incidence in the region and GIS-TECHNOLOGIES the statistical analysis and mathematical modelling of the spatially-organizational data has been carried out. Results. On the basis of the received results the prognostic model of development of acute coronary pathology has been generated. Measures on optimization of organization of medical assistance to patients with an acute coronary pathology have been stated. Conclusion. Methods of intellectual support of the doctor may become effective in formation of organizational structure of the system of stage-by-stage qualified and specialized aid to patients with acute coronary syndrome.

  10. A Modeling Framework for Prognostic Decision Making and its Application to UAV Mission Planning

    Data.gov (United States)

    National Aeronautics and Space Administration — The goal of prognostic decision making (PDM) is to utilize information on anticipated system health changes in selecting future actions. One of the key challenges in...

  11. Evaluating Ice Nucleating Particle Concentrations From Prognostic Dust Minerals in an Earth System Model

    Science.gov (United States)

    Perlwitz, J. P.; Knopf, D. A.; Fridlind, A. M.; Miller, R. L.; Pérez García-Pando, C.; DeMott, P. J.

    2016-12-01

    The effect of aerosol particles on the radiative properties of clouds, the so-called, indirect effect of aerosols, is recognized as one of the largest sources of uncertainty in climate prediction. The distribution of water vapor, precipitation, and ice cloud formation are influenced by the atmospheric ice formation, thereby modulating cloud albedo and thus climate. It is well known that different particle types possess different ice formation propensities with mineral dust being a superior ice nucleating particle (INP) compared to soot particles. Furthermore, some dust mineral types are more proficient INP than others, depending on temperature and relative humidity.In recent work, we have presented an improved dust aerosol module in the NASA GISS Earth System ModelE2 with prognostic mineral composition of the dust aerosols. Thus, there are regional variations in dust composition. We evaluated the predicted mineral fractions of dust aerosols by comparing them to measurements from a compilation of about 60 published literature references. Additionally, the capability of the model to reproduce the elemental composition of the simulated dusthas been tested at Izana Observatory at Tenerife, Canary Islands, which is located off-shore of Africa and where frequent dust events are observed. We have been able to show that the new approach delivers a robust improvement of the predicted mineral fractions and elemental composition of dust.In the current study, we use three-dimensional dust mineral fields and thermodynamic conditions, which are simulated using GISS ModelE, to calculate offline the INP concentrations derived using different ice nucleation parameterizations that are currently discussed. We evaluate the calculated INP concentrations from the different parameterizations by comparing them to INP concentrations from field measurements.

  12. Conditional net survival: Relevant prognostic information for colorectal cancer survivors. A French population-based study.

    Science.gov (United States)

    Drouillard, Antoine; Bouvier, Anne-Marie; Rollot, Fabien; Faivre, Jean; Jooste, Valérie; Lepage, Côme

    2015-07-01

    Traditionally, survival estimates have been reported as survival from the time of diagnosis. A patient's probability of survival changes according to time elapsed since the diagnosis and this is known as conditional survival. The aim was to estimate 5-year net conditional survival in patients with colorectal cancer in a well-defined French population at yearly intervals up to 5 years. Our study included 18,300 colorectal cancers diagnosed between 1976 and 2008 and registered in the population-based digestive cancer registry of Burgundy (France). We calculated conditional 5-year net survival, using the Pohar Perme estimator, for every additional year survived after diagnosis from 1 to 5 years. The initial 5-year net survival estimates varied between 89% for stage I and 9% for advanced stage cancer. The corresponding 5-year net survival for patients alive after 5 years was 95% and 75%. Stage II and III patients who survived 5 years had a similar probability of surviving 5 more years, respectively 87% and 84%. For survivors after the first year following diagnosis, five-year conditional net survival was similar regardless of age class and period of diagnosis. For colorectal cancer survivors, conditional net survival provides relevant and complementary prognostic information for patients and clinicians. Copyright © 2015 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

  13. A comparison of the prognostic value of preoperative inflammation-based scores and TNM stage in patients with gastric cancer

    Directory of Open Access Journals (Sweden)

    Pan QX

    2015-06-01

    Full Text Available Qun-Xiong Pan,* Zi-Jian Su,* Jian-Hua Zhang, Chong-Ren Wang, Shao-Ying KeDepartment of Oncosurgery, Quanzhou First Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, People’s Republic of China*These authors contributed equally to this workBackground: People’s Republic of China is one of the countries with the highest incidence of gastric cancer, accounting for 45% of all new gastric cancer cases in the world. Therefore, strong prognostic markers are critical for the diagnosis and survival of Chinese patients suffering from gastric cancer. Recent studies have begun to unravel the mechanisms linking the host inflammatory response to tumor growth, invasion and metastasis in gastric cancers. Based on this relationship between inflammation and cancer progression, several inflammation-based scores have been demonstrated to have prognostic value in many types of malignant solid tumors.Objective: To compare the prognostic value of inflammation-based prognostic scores and tumor node metastasis (TNM stage in patients undergoing gastric cancer resection.Methods: The inflammation-based prognostic scores were calculated for 207 patients with gastric cancer who underwent surgery. Glasgow prognostic score (GPS, neutrophil lymphocyte ratio (NLR, platelet lymphocyte ratio (PLR, prognostic nutritional index (PNI, and prognostic index (PI were analyzed. Linear trend chi-square test, likelihood ratio chi-square test, and receiver operating characteristic were performed to compare the prognostic value of the selected scores and TNM stage.Results: In univariate analysis, preoperative serum C-reactive protein (P<0.001, serum albumin (P<0.001, GPS (P<0.001, PLR (P=0.002, NLR (P<0.001, PI (P<0.001, PNI (P<0.001, and TNM stage (P<0.001 were significantly associated with both overall survival and disease-free survival of patients with gastric cancer. In multivariate analysis, GPS (P=0.024, NLR (P=0.012, PI (P=0.001, TNM stage (P<0.001, and degree of

  14. The prognostic value of dividing epithelial ovarian cancer into type I and type II tumors based on pathologic characteristics

    DEFF Research Database (Denmark)

    Prahm, Kira Philipsen; Karlsen, Mona Aarenstrup; Høgdall, Estrid

    2015-01-01

    OBJECTIVE: To investigate the prognostic significance of dividing epithelial ovarian cancer (EOC) in type I and type II tumors based on pathologic variables. METHODS: We used the Danish Gynecologic Cancer Database to identify all patients diagnosed with EOC from 2005 to 2012. Information on histo......OBJECTIVE: To investigate the prognostic significance of dividing epithelial ovarian cancer (EOC) in type I and type II tumors based on pathologic variables. METHODS: We used the Danish Gynecologic Cancer Database to identify all patients diagnosed with EOC from 2005 to 2012. Information...... for survival confirmed the increased overall survival for type I tumors after two years of follow-up (hazard ratio: 1.85, 95% confidence interval: 1.35-2.54, Pbased on pathologic variables was associated with an increased risk of death...

  15. Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers.

    Science.gov (United States)

    Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won

    2017-12-12

    Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.

  16. An internally validated prognostic model for success in revision stapes surgery for otosclerosis.

    Science.gov (United States)

    Wegner, Inge; Vincent, Robert; Derks, Laura S M; Rauh, Simone P; Heymans, Martijn W; Stegeman, Inge; Grolman, Wilko

    2018-03-09

    To develop a prediction model that can accurately predict the chance of success following revision stapes surgery in patients with recurrent or persistent otosclerosis at 2- to 6-months follow-up and to validate this model internally. A retrospective cohort study of prospectively gathered data in a tertiary referral center. The associations of 11 prognostic factors with treatment success were tested in 705 cases using multivariable logistic regression analysis with backward selection. Success was defined as a mean air-bone gap closure to 10 dB or less. The most relevant predictors were used to derive a clinical prediction rule to determine the probability of success. Internal validation by means of bootstrapping was performed. Model performance indices, including the Hosmer-Lemeshow test, the area under the receiver operating characteristics curve (AUC), and the explained variance were calculated. Success was achieved in 57.7% of cases at 2- to 6-months follow-up. Certain previous surgical techniques, primary causes of failure leading up to revision stapes surgery, and positions of the prosthesis placed during revision surgery were associated with higher success percentages. The clinical prediction rule performed moderately well in the original dataset (Hosmer-Lemeshow P = .78; AUC = 0.73; explained variance = 22%), which slightly decreased following internal validation by means of bootstrapping (AUC = 0.69; explained variance = 13%). Our study established the importance of previous surgical technique, primary cause of failure, and type of the prosthesis placed during the revision surgery in predicting the probability of success following stapes surgery at 2- to 6-months follow-up. 2b. Laryngoscope, 2018. © 2018 The American Laryngological, Rhinological and Otological Society, Inc.

  17. Incorporating Prognostic Marine Nitrogen Fixers and Related Bio-Physical Feedbacks in an Earth System Model

    Science.gov (United States)

    Paulsen, H.; Ilyina, T.; Six, K. D.

    2016-02-01

    Marine nitrogen fixers play a fundamental role in the oceanic nitrogen and carbon cycles by providing a major source of `new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Furthermore, nitrogen fixers may regionally have a direct impact on ocean physics and hence the climate system as they form extensive surface mats which can increase light absorption and surface albedo and reduce the momentum input by wind. Resulting alterations in temperature and stratification may feed back on nitrogen fixers' growth itself.We incorporate nitrogen fixers as a prognostic 3D tracer in the ocean biogeochemical component (HAMOCC) of the Max Planck Institute Earth system model and assess for the first time the impact of related bio-physical feedbacks on biogeochemistry and the climate system.The model successfully reproduces recent estimates of global nitrogen fixation rates, as well as the observed distribution of nitrogen fixers, covering large parts of the tropical and subtropical oceans. First results indicate that including bio-physical feedbacks has considerable effects on the upper ocean physics in this region. Light absorption by nitrogen fixers leads locally to surface heating, subsurface cooling, and mixed layer depth shoaling in the subtropical gyres. As a result, equatorial upwelling is increased, leading to surface cooling at the equator. This signal is damped by the effect of the reduced wind stress due to the presence of cyanobacteria mats, which causes a reduction in the wind-driven circulation, and hence a reduction in equatorial upwelling. The increase in surface albedo due to nitrogen fixers has only inconsiderable effects. The response of nitrogen fixers' growth to the alterations in temperature and stratification varies regionally. Simulations with the fully coupled Earth system model are in progress to assess the implications of the biologically induced changes in upper ocean physics for the global climate system.

  18. An Integrated Model-Based Diagnostic and Prognostic Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — Systems health monitoring is essential in guar- anteeing the safe, efficient, and correct opera- tion of complex engineered systems. Diagnosis, which consists of...

  19. Prognostic factors in nodular lymphomas: a multivariate analysis based on the Princess Margaret Hospital experience

    International Nuclear Information System (INIS)

    Gospodarowicz, M.K.; Bush, R.S.; Brown, T.C.; Chua, T.

    1984-01-01

    A total of 1,394 patients with non-Hodgkin's lymphoma were treated at the Princess Margaret Hospital between January 1, 1967 and December 31, 1978. Overall actuarial survival of 525 patients with nodular lymphomas was 40% at 12 years; survival of patients with localized (Stage I and III) nodular lymphomas treated with radical radiation therapy was 58%. Significant prognostic factors defined by multivariate analysis included patient's age, stage, histology, tumor bulk, and presence of B symptoms. By combining prognostic factors, distinct prognostic groups have been identified within the overall population. Patients with Stage I and II disease, small or medium bulk, less than 70 years of age achieved 92% 12 year actuarial survival and a 73% relapse-free rate in 12 years of follow-up. These patients represent groups highly curable with irradiation

  20. The prognostic importance of miR-21 in stage II colon cancer: a population-based study

    DEFF Research Database (Denmark)

    Kjaer-Frifeldt, S.; Hansen, T. F.; Nielsen, B. S.

    2012-01-01

    that increasing miR-21 expression levels were significantly correlated to decreasing RF-CSS. Further investigations of the clinical importance of miR-21 in the selection of high-risk stage II colon cancer patients are merited. British Journal of Cancer (2012) 107, 1169-1174. doi:10.1038/bjc.2012.365 www......BACKGROUND: Despite several years of research and attempts to develop prognostic models a considerable fraction of stage II colon cancer patients will experience relapse within few years from their operation. The aim of the present study was to investigate the prognostic importance of miRNA-21 (mi......-free cancer-specific survival (RF-CSS): HR = 1.26; 95% CI: 1.15-1.60; P importance and was found to be significantly related to poor RF-CSS: HR 1.41; 95% CI: 1.19-1.67; P

  1. Prognostic significance of immunohistochemistry-based markers and algorithms in immunochemotherapy-treated diffuse large B cell lymphoma patients.

    Science.gov (United States)

    Culpin, Rachel E; Sieniawski, Michal; Angus, Brian; Menon, Geetha K; Proctor, Stephen J; Milne, Paul; McCabe, Kate; Mainou-Fowler, Tryfonia

    2013-12-01

    To reassess the prognostic validity of immunohistochemical markers and algorithms identified in the CHOP era in immunochemotherapy-treated diffuse large B cell lymphoma patients. The prognostic significance of immunohistochemical markers (CD10, Bcl-6, Bcl-2, MUM1, Ki-67, CD5, GCET1, FoxP1, LMO2) and algorithms (Hans, Hans*, Muris, Choi, Choi*, Nyman, Visco-Young, Tally) was assessed using clinical diagnostic blocks taken from an unselected, population-based cohort of 190 patients treated with R-CHOP. Dichotomizing expression, low CD10 (<10%), low LMO2 (<70%) or high Bcl-2 (≥80%) predicted shorter overall survival (OS; P = 0.033, P = 0.010 and P = 0.008, respectively). High Bcl-2 (≥80%), low Bcl-6 (<60%), low GCET1 (<20%) or low LMO2 (<70%) predicted shorter progression-free survival (PFS; P = 0.001, P = 0.048, P = 0.045 and P = 0.002, respectively). The Hans, Hans* and Muris classifiers predicted OS (P = 0.022, P = 0.037 and P = 0.011) and PFS (P = 0.021, P = 0.020 and P = 0.004). The Choi, Choi* and Tally were associated with PFS (P = 0.049, P = 0.009 and P = 0.023). In multivariate analysis, the International Prognostic Index (IPI) was the only independent predictor of outcome (OS; HR: 2.60, P < 0.001 and PFS; HR: 2.91, P < 0.001). Results highlight the controversy surrounding immunohistochemistry-based algorithms in the R-CHOP era. The need for more robust markers, applicable to the clinic, for incorporation into improved prognostic systems is emphasized. © 2013 John Wiley & Sons Ltd.

  2. Prognostic Factors in Amyotrophic Lateral Sclerosis: A Population-Based Study.

    Science.gov (United States)

    Moura, Mirian Conceicao; Novaes, Maria Rita Carvalho Garbi; Eduardo, Emanoel Junio; Zago, Yuri S S P; Freitas, Ricardo Del Negro Barroso; Casulari, Luiz Augusto

    2015-01-01

    To determine the prognostic factors associated with survival in amyotrophic lateral sclerosis at diagnosis. This retrospective population-based study evaluated 218 patients treated with riluzole between 2005 and 2014 and described their clinical and demographic profiles after the analysis of clinical data and records from the mortality information system in the Federal District, Brazil. Cox multivariate regression analysis was conducted for the parameters found. The study sample consisted of 132 men and 86 women with a mean age at disease onset of 57.2±12.3 years; 77.6% of them were Caucasian. The mean periods between disease onset and diagnosis were 22.7 months among men and 23.5 months among women, and the mean survival periods were 45.7±47.0 months among men and 39.3±29.8 months among women. In addition, 80.3% patients presented non-bulbar-onset amyotrophic lateral sclerosis, and 19.7% presented bulbar-onset. Cox regression analysis indicated worse prognosis for body mass index (BMI) 75 years (RR: 12.47, 95% CI: 3.51-44.26), and bulbar-onset (RR: 4.56, 95% CI: 2.06-10.12). Electromyography did not confirm the diagnosis in 55.6% of the suspected cases and in 27.9% of the bulbar-onset cases. The factors associated with lower survival in amyotrophic lateral sclerosis were age >75 years, BMI <25 kg/m2, and bulbar-onset.

  3. Histology-Based Expression Profiling Yields Novel Prognostic Markers in Human Glioblastoma

    Science.gov (United States)

    Dong, Shumin; Nutt, Catherine L.; Betensky, Rebecca A.; Stemmer-Rachamimov, Anat O.; Denko, Nicholas C.; Ligon, Keith L.; Rowitch, David H.; Louis, David N.

    2006-01-01

    Although the prognosis for patients with glioblastoma is poor, survival is variable, with some patients surviving longer than others. For this reason, there has been longstanding interest in the identi-fication of prognostic markers for glioblastoma. We hypothesized that specific histologic features known to correlate with malignancy most likely express molecules that are directly related to the aggressive behavior of these tumors. We further hypothesized that such molecules could be used as biomarkers to predict behavior in a manner that might add prognostic power to sole histologic observation of the feature. We reasoned that perinecrotic tumor cell palisading, which denotes the most aggressive forms of malignant gliomas, would be a striking histologic feature on which to test this hypothesis. We therefore used laser capture microdissection and oligonucleotide arrays to detect molecules differentially expressed in perinecrotic palisades. A set of RNAs (including POFUT2, PTDSR, PLOD2, ATF5, and HK2) that were differentially expressed in 3 initially studied, micro-dissected glioblastomas also provided prognostic information in an independent set of 28 glioblastomas that did not all have perinecrotic palisades. On validation in a second, larger independent series, this approach could be applied to other human glioma types to derive tissue biomarkers that could offer ancillary prognostic and predictive information alongside standard histopathologic examination. PMID:16254489

  4. Generic Software Architecture for Prognostics (GSAP) User Guide

    Science.gov (United States)

    Teubert, Christopher Allen; Daigle, Matthew John; Watkins, Jason; Sankararaman, Shankar; Goebel, Kai

    2016-01-01

    The Generic Software Architecture for Prognostics (GSAP) is a framework for applying prognostics. It makes applying prognostics easier by implementing many of the common elements across prognostic applications. The standard interface enables reuse of prognostic algorithms and models across systems using the GSAP framework.

  5. Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

    Science.gov (United States)

    Guinney, Justin; Wang, Tao; Laajala, Teemu D; Winner, Kimberly Kanigel; Bare, J Christopher; Neto, Elias Chaibub; Khan, Suleiman A; Peddinti, Gopal; Airola, Antti; Pahikkala, Tapio; Mirtti, Tuomas; Yu, Thomas; Bot, Brian M; Shen, Liji; Abdallah, Kald; Norman, Thea; Friend, Stephen; Stolovitzky, Gustavo; Soule, Howard; Sweeney, Christopher J; Ryan, Charles J; Scher, Howard I; Sartor, Oliver; Xie, Yang; Aittokallio, Tero; Zhou, Fang Liz; Costello, James C

    2017-01-01

    Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a

  6. Real-Time Adaptive Algorithms for Flight Control Diagnostics and Prognostics, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based machinery diagnostic and prognostic techniques depend upon high-quality mathematical models of the plant. Modeling uncertainties and errors decrease...

  7. Mucins as diagnostic and prognostic biomarkers in a fish-parasite model: transcriptional and functional analysis.

    Directory of Open Access Journals (Sweden)

    Jaume Pérez-Sánchez

    Full Text Available Mucins are O-glycosylated glycoproteins present on the apex of all wet-surfaced epithelia with a well-defined expression pattern, which is disrupted in response to a wide range of injuries or challenges. The aim of this study was to identify mucin gene sequences of gilthead sea bream (GSB, to determine its pattern of distribution in fish tissues and to analyse their transcriptional regulation by dietary and pathogenic factors. Exhaustive search of fish mucins was done in GSB after de novo assembly of next-generation sequencing data hosted in the IATS transcriptome database (www.nutrigroup-iats.org/seabreamdb. Six sequences, three categorized as putative membrane-bound mucins and three putative secreted-gel forming mucins, were identified. The transcriptional tissue screening revealed that Muc18 was the predominant mucin in skin, gills and stomach of GSB. In contrast, Muc19 was mostly found in the oesophagus and Muc13 was along the entire intestinal tract, although the posterior intestine exhibited a differential pattern with a high expression of an isoform that does not share a clear orthologous in mammals. This mucin was annotated as intestinal mucin (I-Muc. Its RNA expression was highly regulated by the nutritional background, whereas the other mucins, including Muc2 and Muc2-like, were expressed more constitutively and did not respond to high replacement of fish oil (FO by vegetable oils (VO in plant protein-based diets. After challenge with the intestinal parasite Enteromyxum leei, the expression of a number of mucins was decreased mainly in the posterior intestine of infected fish. But, interestingly, the highest down-regulation was observed for the I-Muc. Overall, the magnitude of the changes reflected the intensity and progression of the infection, making mucins and I-Muc, in particular, reliable markers of prognostic and diagnostic value of fish intestinal health.

  8. Prognostic value of 18F-FDG PET image-based parameters in oesophageal cancer and impact of tumour delineation methodology

    International Nuclear Information System (INIS)

    Hatt, Mathieu; Visvikis, Dimitris; Tixier, Florent; Albarghach, Nidal M.; Pradier, Olivier; Cheze-le Rest, Catherine

    2011-01-01

    18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) image-derived parameters, such as standardized uptake value (SUV), functional tumour length (TL) and tumour volume (TV) or total lesion glycolysis (TLG), may be useful for determining prognosis in patients with oesophageal carcinoma. The objectives of this work were to investigate the prognostic value of these indices in oesophageal cancer patients undergoing combined chemoradiotherapy treatment and the impact of TV delineation strategies. A total of 45 patients were retrospectively analysed. Tumours were delineated on pretreatment 18 F-FDG scans using adaptive threshold and automatic (fuzzy locally adaptive Bayesian, FLAB) methodologies. The maximum standardized uptake value (SUV max ), SUV peak , SUV mean , TL, TV and TLG were computed. The prognostic value of each parameter for overall survival was investigated using Kaplan-Meier and Cox regression models for univariate and multivariate analyses, respectively. Large differences were observed between methodologies (from -140 to +50% for TV). SUV measurements were not significant prognostic factors for overall survival, whereas TV, TL and TLG were, irrespective of the segmentation strategy. After multivariate analysis including standard tumour staging, only TV (p < 0.002) and TL (p = 0.042) determined using FLAB were independent prognostic factors. Whereas no SUV measurement was a significant prognostic factor, TV, TL and TLG were significant prognostic factors for overall survival, irrespective of the delineation methodology. Only functional TV and TL derived using FLAB were independent prognostic factors, highlighting the need for accurate and robust PET tumour delineation tools for oncology applications. (orig.)

  9. Prealbumin/CRP Based Prognostic Score, a New Tool for Predicting Metastasis in Patients with Inoperable Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Ali Esfahani

    2016-01-01

    Full Text Available Background. There is a considerable dissimilarity in the survival duration of the patients with gastric cancer. We aimed to assess the systemic inflammatory response (SIR and nutritional status of these patients before the commencement of chemotherapy to find the appropriate prognostic factors and define a new score for predicting metastasis. Methods. SIR was assessed using Glasgow Prognostic Score (GPS. Then a score was defined as prealbumin/CRP based prognostic score (PCPS to be compared with GPS for predicting metastasis and nutritional status. Results. 71 patients with gastric cancer were recruited in the study. 87% of patients had malnutrition. There was a statistical difference between those with metastatic (n=43 and those with nonmetastatic (n=28 gastric cancer according to levels of prealbumin and CRP; however they were not different regarding patient generated subjective global assessment (PG-SGA and GPS. The best cut-off value for prealbumin was determined at 0.20 mg/dL and PCPS could predict metastasis with 76.5% sensitivity, 63.6% specificity, and 71.4% accuracy. Metastatic and nonmetastatic gastric cancer patients were different in terms of PCPS (P=0.005. Conclusion. PCPS has been suggested for predicting metastasis in patients with gastric cancer. Future studies with larger sample size have been warranted.

  10. Verification of a prognostic meteorological and air pollution model for year-long predictions in the Kwinana industrial region of Western Australia

    International Nuclear Information System (INIS)

    Hurley, P.J.; Blockley, A.; Rayner, K.

    2001-01-01

    A prognostic air pollution model (TAPM) has been used to predict meteorology and sulphur dioxide concentration in the Kwinana industrial region of Western Australia for 1997, with a view to verifying TAPM for use in environmental impact assessments and associated air pollution studies. The regulatory plume model, DISPMOD, developed for the Kwinana region has also been run using both an observationally based meteorological file (denoted DISPMOD-O) and using a TAPM-based meteorological file (denoted DISPMOD-T). TAPM predictions of the meteorology for 1997 compare well with the observed values at each of the five monitoring sites. Root mean square error and index of agreement values for temperature and winds indicate that TAPM performs well at predicting the meteorology, compared to the performance of similar models from other studies. The yearly average, 99.9 percentile, maximum and mean of the top 10 ground-level sulphur dioxide concentrations for 1997 were predicted well by all of the model runs, although DISPMOD-O and DISPMOD-T tended to overpredict extreme statistics at sites furthest from the sources. Overall, TAPM performed better than DISPMOD-O, which in turn performed better than DISPMOD-T, for all statistics considered, but we consider that all three sets of results are sufficiently accurate for regulatory applications. The mean of the top ten concentrations is generally considered to be a robust performance statistic for air pollution applications, and we show that compared to the site-averaged observed value of 95μgm -3 , TAPM predicted 94μgm -3 , DISPMOD-O predicted 111μgm -3 and DISPMOD-T predicted 125μgm -3 . The results indicate that the prognostic meteorological and air pollution approach to regulatory modelling used by TAPM, gives comparable or better results than the current regulatory approach used in the Kwinana region (DISPMOD), and also indicates that the approach of using a currently accepted regulatory model with a prognostically

  11. Proposal of a clinical typing system and generation of a prognostic model in patients with nasopharyngeal carcinoma from Southern China.

    Science.gov (United States)

    Sun, Peng; Chen, Cui; Chen, Xin-Lin; Cheng, Yi-Kan; Zeng, Lei; Zeng, Zhi-Jian; Liu, Li-Zhi; Su, Yong; Gu, Mo-Fa

    2014-01-01

    To propose a novel clinical typing classification focusing on the distinct progression patterns of nasopharyngeal carcinoma (NPC), to supplement our knowledge of the clinical-biological behavior, to provide useful knowledge for treatment planning, and to contribute to basic research in NPC. 632 consecutive patients were retrospectively reviewed and analyzed according to the novel typing system. We considered that NPC can be divided into 5 types as follows: limited (L), ascending (A), descending (D) ascending- descending (mixed) (AD), and distant metastasis types (M). The distribution of these clinical types, their association with Epstein-Barr virus (EBV) serology and prognostic value were explored. 55 (8.70%), 59 (9.34%), 177 (28.01%), 321 (50.79%) and 20 (3.16%) patients were classified as Type L, A, D, AD and M, respectively. EBV (VCA)-IgA titers, EBV early antigen (EA)-IgA serum titers, and capsid antigen lg(EBV DNA) were positively associated with the clinical typing (pTypes L, A, D, AD and M were 100, 100, 95.10, 88.20 and 59.30%, respectively (ptype, which were independent predictors of OS (multivariate Cox proportional model). The prognostic model stratified patients into 4 risk subgroups. The 3-year OS rates of the low, intermediate, high and extremely high risk groups were 99.5, 90.0, 85.5 and 53.2%, respectively (ptyping system and prognostic model can supplement TNM classification, and may help design novel treatment strategies, evaluate risk stratification and investigate the varied biological characteristics of NPC.

  12. Model Updating and Uncertainty Management for Aircraft Prognostic Systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal addresses the integration of physics-based damage propagation models with diagnostic measures of current state of health in a mathematically rigorous...

  13. No prognostic value added by vitamin D pathway SNPs to current prognostic system for melanoma survival.

    Directory of Open Access Journals (Sweden)

    Li Luo

    Full Text Available The prognostic improvement attributed to genetic markers over current prognostic system has not been well studied for melanoma. The goal of this study is to evaluate the added prognostic value of Vitamin D Pathway (VitD SNPs to currently known clinical and demographic factors such as age, sex, Breslow thickness, mitosis and ulceration (CDF. We utilized two large independent well-characterized melanoma studies: the Genes, Environment, and Melanoma (GEM and MD Anderson studies, and performed variable selection of VitD pathway SNPs and CDF using Random Survival Forest (RSF method in addition to Cox proportional hazards models. The Harrell's C-index was used to compare the performance of model predictability. The population-based GEM study enrolled 3,578 incident cases of cutaneous melanoma (CM, and the hospital-based MD Anderson study consisted of 1,804 CM patients. Including both VitD SNPs and CDF yielded C-index of 0.85, which provided slight but not significant improvement by CDF alone (C-index = 0.83 in the GEM study. Similar results were observed in the independent MD Anderson study (C-index = 0.84 and 0.83, respectively. The Cox model identified no significant associations after adjusting for multiplicity. Our results do not support clinically significant prognostic improvements attributable to VitD pathway SNPs over current prognostic system for melanoma survival.

  14. A comparison of prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill: a cohort study.

    Science.gov (United States)

    Ho, Kwok M; Lan, Norris S H; Williams, Teresa A; Harahsheh, Yusra; Chapman, Andrew R; Dobb, Geoffrey J; Magder, Sheldon

    2016-01-01

    This cohort study compared the prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill. The relationships between SIG, lactate, anion gap (AG), anion gap albumin-corrected (AG-corrected), base excess or strong ion difference-effective (SIDe), all obtained within the first hour of intensive care unit (ICU) admission, and the hospital mortality of 6878 patients were analysed. The prognostic significance of each acid-base marker, both alone and in combination with the Admission Mortality Prediction Model (MPM0 III) predicted mortality, were assessed by the area under the receiver operating characteristic curve (AUROC). Of the 6878 patients included in the study, 924 patients (13.4 %) died after ICU admission. Except for plasma chloride concentrations, all acid-base markers were significantly different between the survivors and non-survivors. SIG (with lactate: AUROC 0.631, confidence interval [CI] 0.611-0.652; without lactate: AUROC 0.521, 95 % CI 0.500-0.542) only had a modest ability to predict hospital mortality, and this was no better than using lactate concentration alone (AUROC 0.701, 95 % 0.682-0.721). Adding AG-corrected or SIG to a combination of lactate and MPM0 III predicted risks also did not substantially improve the latter's ability to differentiate between survivors and non-survivors. Arterial lactate concentrations explained about 11 % of the variability in the observed mortality, and it was more important than SIG (0.6 %) and SIDe (0.9 %) in predicting hospital mortality after adjusting for MPM0 III predicted risks. Lactate remained as the strongest predictor for mortality in a sensitivity multivariate analysis, allowing for non-linearity of all acid-base markers. The prognostic significance of SIG was modest and inferior to arterial lactate concentration for the critically ill. Lactate concentration should always be considered regardless whether physiological, base excess or physical-chemical approach

  15. A Distributed Approach to System-Level Prognostics

    Science.gov (United States)

    2012-09-01

    the end of (useful) life ( EOL ) and/or the remaining useful life (RUL) of components, subsystems, or systems. The prognostics problem itself can be...system state estimate, computes EOL and/or RUL. In this paper, we focus on a model-based prognostics approach (Orchard & Vachtse- vanos, 2009; Daigle...been focused on individual components, and determining their EOL and RUL, e.g., (Orchard & Vachtsevanos, 2009; Saha & Goebel, 2009; Daigle & Goebel

  16. Development and internal validation of a prognostic model to predict recurrence free survival in patients with adult granulosa cell tumors of the ovary

    NARCIS (Netherlands)

    van Meurs, Hannah S.; Schuit, Ewoud; Horlings, Hugo M.; van der Velden, Jacobus; van Driel, Willemien J.; Mol, Ben Willem J.; Kenter, Gemma G.; Buist, Marrije R.

    2014-01-01

    Models to predict the probability of recurrence free survival exist for various types of malignancies, but a model for recurrence free survival in individuals with an adult granulosa cell tumor (GCT) of the ovary is lacking. We aimed to develop and internally validate such a prognostic model. We

  17. Computed tomographic findings in dogs with head trauma and development of a novel prognostic computed tomography-based scoring system.

    Science.gov (United States)

    Chai, Orit; Peery, Dana; Bdolah-Abram, Tali; Moscovich, Efrat; Kelmer, Efrat; Klainbart, Sigal; Milgram, Joshua; Shamir, Merav H

    2017-09-01

    OBJECTIVE To characterize CT findings and outcomes in dogs with head trauma and design a prognostic scale. ANIMALS 27 dogs admitted to the Koret School Veterinary Teaching Hospital within 72 hours after traumatic head injury that underwent CT imaging of the head. PROCEDURES Data were extracted from medical records regarding dog signalment, history, physical and neurologic examination findings, and modified Glasgow coma scale scores. All CT images were retrospectively evaluated by a radiologist unaware of dog status. Short-term (10 days after trauma) and long-term (≥ 6 months after trauma) outcomes were determined, and CT findings and other variables were analyzed for associations with outcome. A prognostic CT-based scale was developed on the basis of the results. RESULTS Cranial vault fractures, parenchymal abnormalities, or both were identified via CT in 24 of 27 (89%) dogs. Three (11%) dogs had only facial bone fractures. Intracranial hemorrhage was identified in 16 (59%) dogs, cranial vault fractures in 15 (56%), midline shift in 14 (52%), lateral ventricle asymmetry in 12 (44%), and hydrocephalus in 7 (26%). Hemorrhage and ventricular asymmetry were significantly and negatively associated with short- and long-term survival, respectively. The developed 7-point prognostic scale included points for hemorrhage, midline shift or lateral ventricle asymmetry, cranial vault fracture, and depressed fracture (1 point each) and infratentorial lesion (3 points). CONCLUSIONS AND CLINICAL RELEVANCE The findings reported here may assist in determining prognoses for other dogs with head trauma. The developed scale may be useful for outcome assessment of dogs with head trauma; however, it must be validated before clinical application.

  18. A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis.

    Science.gov (United States)

    Passamonti, F; Giorgino, T; Mora, B; Guglielmelli, P; Rumi, E; Maffioli, M; Rambaldi, A; Caramella, M; Komrokji, R; Gotlib, J; Kiladjian, J J; Cervantes, F; Devos, T; Palandri, F; De Stefano, V; Ruggeri, M; Silver, R T; Benevolo, G; Albano, F; Caramazza, D; Merli, M; Pietra, D; Casalone, R; Rotunno, G; Barbui, T; Cazzola, M; Vannucchi, A M

    2017-12-01

    Polycythemia vera (PV) and essential thrombocythemia (ET) are myeloproliferative neoplasms with variable risk of evolution into post-PV and post-ET myelofibrosis, from now on referred to as secondary myelofibrosis (SMF). No specific tools have been defined for risk stratification in SMF. To develop a prognostic model for predicting survival, we studied 685 JAK2, CALR, and MPL annotated patients with SMF. Median survival of the whole cohort was 9.3 years (95% CI: 8-not reached-NR-). Through penalized Cox regressions we identified negative predictors of survival and according to beta risk coefficients we assigned 2 points to hemoglobin level <11 g/dl, to circulating blasts ⩾3%, and to CALR-unmutated genotype, 1 point to platelet count <150 × 10 9 /l and to constitutional symptoms, and 0.15 points to any year of age. Myelofibrosis Secondary to PV and ET-Prognostic Model (MYSEC-PM) allocated SMF patients into four risk categories with different survival (P<0.0001): low (median survival NR; 133 patients), intermediate-1 (9.3 years, 95% CI: 8.1-NR; 245 patients), intermediate-2 (4.4 years, 95% CI: 3.2-7.9; 126 patients), and high risk (2 years, 95% CI: 1.7-3.9; 75 patients). Finally, we found that the MYSEC-PM represents the most appropriate tool for SMF decision-making to be used in clinical and trial settings.

  19. Prognostic table for predicting major cardiac events based on J-ACCESS investigation

    International Nuclear Information System (INIS)

    Nakajima, Kenichi; Nishimura, Tsunehiko

    2008-01-01

    The event risk of patients with coronary heart disease may be estimated by a large-scale prognostic database in a Japanese population. The aim of this study was to create a heart risk table for predicting the major cardiac event rate. Using the Japanese-assessment of cardiac event and survival study (J-ACCESS) database created by a prognostic investigation involving 117 hospitals and >4000 patients in Japan, multivariate logistic regression analysis was performed. The major event rate over a 3-year period that included cardiac death, non-fatal myocardial infarction, and severe heart failure requiring hospitalization was predicted by the logistic regression equation. The algorithm for calculating the event rate was simplified for creating tables. Two tables were created to calculate cardiac risk by age, perfusion score category, and ejection fraction with and without the presence of diabetes. A relative risk table comparing age-matched control subjects was also made. When the simplified tables were compared with the results from the original logistic regression analysis, both risk values and relative risks agreed well (P<0.0001 for both). The Heart Risk Table was created for patients suspected of having ischemic heart disease and who underwent myocardial perfusion gated single-photon emission computed tomography. The validity of risk assessment using a J-ACCESS database should be validated in a future study. (author)

  20. Computerized three-class classification of MRI-based prognostic markers for breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Bhooshan, Neha; Giger, Maryellen; Edwards, Darrin; Yuan Yading; Jansen, Sanaz; Li Hui; Lan Li; Newstead, Gillian [Department of Radiology, University of Chicago, Chicago, IL 60637 (United States); Sattar, Husain, E-mail: bhooshan@uchicago.edu [Department of Pathology, University of Chicago, Chicago, IL 60637 (United States)

    2011-09-21

    The purpose of this study is to investigate whether computerized analysis using three-class Bayesian artificial neural network (BANN) feature selection and classification can characterize tumor grades (grade 1, grade 2 and grade 3) of breast lesions for prognostic classification on DCE-MRI. A database of 26 IDC grade 1 lesions, 86 IDC grade 2 lesions and 58 IDC grade 3 lesions was collected. The computer automatically segmented the lesions, and kinetic and morphological lesion features were automatically extracted. The discrimination tasks-grade 1 versus grade 3, grade 2 versus grade 3, and grade 1 versus grade 2 lesions-were investigated. Step-wise feature selection was conducted by three-class BANNs. Classification was performed with three-class BANNs using leave-one-lesion-out cross-validation to yield computer-estimated probabilities of being grade 3 lesion, grade 2 lesion and grade 1 lesion. Two-class ROC analysis was used to evaluate the performances. We achieved AUC values of 0.80 {+-} 0.05, 0.78 {+-} 0.05 and 0.62 {+-} 0.05 for grade 1 versus grade 3, grade 1 versus grade 2, and grade 2 versus grade 3, respectively. This study shows the potential for (1) applying three-class BANN feature selection and classification to CADx and (2) expanding the role of DCE-MRI CADx from diagnostic to prognostic classification in distinguishing tumor grades.

  1. Prognostics and health management of engineering systems an introduction

    CERN Document Server

    Kim, Nam-Ho; Choi, Joo-Ho

    2017-01-01

    This book introduces the methods for predicting the future behavior of a system’s health and the remaining useful life to determine an appropriate maintenance schedule. The authors introduce the history, industrial applications, algorithms, and benefits and challenges of PHM (Prognostics and Health Management) to help readers understand this highly interdisciplinary engineering approach that incorporates sensing technologies, physics of failure, machine learning, modern statistics, and reliability engineering. It is ideal for beginners because it introduces various prognostics algorithms and explains their attributes, pros and cons in terms of model definition, model parameter estimation, and ability to handle noise and bias in data, allowing readers to select the appropriate methods for their fields of application. Among the many topics discussed in-depth are: • Prognostics tutorials using least-squares • Bayesian inference and parameter estimation • Physics-based prognostics algorithms including non...

  2. Accelerated Aging with Electrical Overstress and Prognostics for Power MOSFETs

    Science.gov (United States)

    Saha, Sankalita; Celaya, Jose Ramon; Vashchenko, Vladislav; Mahiuddin, Shompa; Goebel, Kai F.

    2011-01-01

    Power electronics play an increasingly important role in energy applications as part of their power converter circuits. Understanding the behavior of these devices, especially their failure modes as they age with nominal usage or sudden fault development is critical in ensuring efficiency. In this paper, a prognostics based health management of power MOSFETs undergoing accelerated aging through electrical overstress at the gate area is presented. Details of the accelerated aging methodology, modeling of the degradation process of the device and prognostics algorithm for prediction of the future state of health of the device are presented. Experiments with multiple devices demonstrate the performance of the model and the prognostics algorithm as well as the scope of application. Index Terms Power MOSFET, accelerated aging, prognostics

  3. Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals

    DEFF Research Database (Denmark)

    Smith, Todd; Muller, David C; Moons, Karel G M

    2018-01-01

    in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted......-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained....

  4. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  5. Survey on Prognostics Techniques for Updating Initiating Event Frequency in PSA

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyeonmin; Heo, Gyunyoung [Kyung Hee University, Yongin (Korea, Republic of)

    2015-05-15

    One of the applications using PSA is a risk monito. The risk monitoring is real-time analysis tool to decide real-time risk based on real state of components and systems. In order to utilize more effective, the methodologies that manipulate the data from Prognostics was suggested. Generally, Prognostic comprehensively includes not only prognostic but also monitoring and diagnostic. The prognostic method must need condition monitoring. In case of applying PHM to a PSA model, the latest condition of NPPs can be identified more clearly. For reducing the conservatism and uncertainties, we suggested the concept that updates the initiating event frequency in a PSA model by using Bayesian approach which is one of the prognostics techniques before. From previous research, the possibility that PSA is updated by using data more correctly was found. In reliability theory, the Bathtub curve divides three parts (infant failure, constant and random failure, wareout failure). In this paper, in order to investigate the applicability of prognostic methods in updating quantitative data in a PSA model, the OLM acceptance criteria from NUREG, the concept of how to using prognostic in PSA, and the enabling prognostic techniques are suggested. The prognostic has the motivation that improved the predictive capabilities using existing monitoring systems, data, and information will enable more accurate equipment risk assessment for improved decision-making.

  6. Survey on Prognostics Techniques for Updating Initiating Event Frequency in PSA

    International Nuclear Information System (INIS)

    Kim, Hyeonmin; Heo, Gyunyoung

    2015-01-01

    One of the applications using PSA is a risk monito. The risk monitoring is real-time analysis tool to decide real-time risk based on real state of components and systems. In order to utilize more effective, the methodologies that manipulate the data from Prognostics was suggested. Generally, Prognostic comprehensively includes not only prognostic but also monitoring and diagnostic. The prognostic method must need condition monitoring. In case of applying PHM to a PSA model, the latest condition of NPPs can be identified more clearly. For reducing the conservatism and uncertainties, we suggested the concept that updates the initiating event frequency in a PSA model by using Bayesian approach which is one of the prognostics techniques before. From previous research, the possibility that PSA is updated by using data more correctly was found. In reliability theory, the Bathtub curve divides three parts (infant failure, constant and random failure, wareout failure). In this paper, in order to investigate the applicability of prognostic methods in updating quantitative data in a PSA model, the OLM acceptance criteria from NUREG, the concept of how to using prognostic in PSA, and the enabling prognostic techniques are suggested. The prognostic has the motivation that improved the predictive capabilities using existing monitoring systems, data, and information will enable more accurate equipment risk assessment for improved decision-making

  7. Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

    Science.gov (United States)

    Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

    2011-05-15

    There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

  8. Prognostic Health Management System: Component Selection Based on Risk Criteria and Economic Benefit Assessment

    International Nuclear Information System (INIS)

    Pham, B.T.; Agarwal, V.; Lybeck, N.J.; Tawfik, M.S.

    2012-01-01

    Long-term operation (LTO), i.e., beyond 60 years, of the current fleet of nuclear power plants (NPPs) is an important element in the overall energy stability of the United States in coming decades. Problem Statement and Proposed Approach: - For LTO of NPPs, early and proactive diagnosis of degradation at systems, structures, and components (SSCs) level is required; - Periodic maintenance versus Proactive maintenance; - Prognostic Health Monitoring (PHM) can be used to better manage aging and degradation mechanisms, including emerging mechanisms; - Selection of components is crucial for implementing the PHM system; - Approach is to develop a quantitative framework that aids systematic identification of plant components that are selected for cost-effective PHM.

  9. Rough Set Theory based prognostication of life expectancy for terminally ill patients.

    Science.gov (United States)

    Gil-Herrera, Eleazar; Yalcin, Ali; Tsalatsanis, Athanasios; Barnes, Laura E; Djulbegovic, Benjamin

    2011-01-01

    We present a novel knowledge discovery methodology that relies on Rough Set Theory to predict the life expectancy of terminally ill patients in an effort to improve the hospice referral process. Life expectancy prognostication is particularly valuable for terminally ill patients since it enables them and their families to initiate end-of-life discussions and choose the most desired management strategy for the remainder of their lives. We utilize retrospective data from 9105 patients to demonstrate the design and implementation details of a series of classifiers developed to identify potential hospice candidates. Preliminary results confirm the efficacy of the proposed methodology. We envision our work as a part of a comprehensive decision support system designed to assist terminally ill patients in making end-of-life care decisions.

  10. Condition Based Prognostics of Passive Components - A New Era for Nuclear Power Plant Life Management

    International Nuclear Information System (INIS)

    Bakhtiari, S.; Mohanty, S.; Prokofiev, I.; Tregoning, R.

    2012-01-01

    As part of a research project sponsored by the U.S. NRC, Argonne National Laboratory (ANL) conducted scoping studies to identify viable and promising sensors and techniques for in-situ inspection and real-time monitoring of degradation in nuclear power plant (NPP) systems, structures, and components (SSC). Significant advances have been made over the past two decades toward development of online monitoring (OLM) techniques for detection, diagnostics, and prognostics of degradation in active nuclear power plant (NPP) components (e.g., pumps, valves). However, early detection of damage and degradation in safety-critical passive components, (e.g. piping, tubing pressure vessel), is challenging, and will likely remain so for the foreseeable future. Ensuring the structural integrity of the reactor pressure vessel (RPV) and piping systems in particular is a prerequisite to long term safe operation of NPPs. The current practice is to implement inservice inspection (ISI) and preventive maintenance programs. While these programs have generally been successful, they are limited in that information is only obtained during plant outages. Additionally, these inspections, often the critical path in the outage schedule, are costly, time consuming, and involve potentially high dose to nondestructive examination/evaluation (NDE) personnel. A viable plant-wide on-line structural health monitoring program for continuous and automatic monitoring of critical SSCs could be a more effective approach for guarding against unexpected failures. Specifically, OLM information about the current condition of the SSCs could be input to an online prognostics (OLP) system to forecast their remaining useful life in real time. This paper provides an overview of scoping studies performed at ANL on assessing the viability of OLM and OLP systems for real time and automated monitoring and remaining of condition and the remaining useful life of passive components in NPPs. (author)

  11. Technology of prognostication of sporting achievements of badminton players on the stage of preliminary base preparation.

    Directory of Open Access Journals (Sweden)

    Shyyan V.N.

    2011-08-01

    Full Text Available In the article the technology of evaluation of potential capabilities of badminton players is displayed 12-14 years. The functional, pedagogical and psychophysiological criteria which became a component parts of the developed analytical models of sportsmen-badminton players are explored. The criterion for the quantitative estimation of perspective is offered, which allows on the 9-ti point scale to estimate perspective of badminton players on the stage of preliminary base preparation.

  12. p53 nuclear accumulation and multiploidy are adverse prognostic factors in surgically resected stage II colorectal cancers independent of fluorouracil-based adjuvant therapy.

    Science.gov (United States)

    Buglioni, S; D'Agnano, I; Vasselli, S; Perrone Donnorso, R; D'Angelo, C; Brenna, A; Benevolo, M; Cosimelli, M; Zupi, G; Mottolese, M

    2001-09-01

    To identify the prognostically highest risk patients, DNA content and p53 nuclear or cytoplasmic accumulation, evaluated by monoclonal antibody DO7 and polyclonal antibody CM1, were determined in 94 surgically resected stage II (Dukes B2) colorectal cancers, treated or not with adjuvant 5-fluorouracil-based chemotherapy. Sixty-one (65%) of the tumors were aneuploid, 16 (17%) of which had a multiploid DNA content; 50 (53%) displayed DO7 nuclear p53 accumulation, and 44 (47%) showed cytoplasmic CM1 positivity. In multivariate analysis, only multiploidy and p53 nuclear positivity emerged as independent prognostic indicators of a poorer outcome. Positivity for p53 was associated with shorter survival in 5-fluorouracil-treated and untreated patients. Therefore, in patients with Dukes B2 colorectal cancer, a biologic profile based on the combined evaluation of DNA multiploidy and p53 status can provide valuable prognostic information, identifying patients to be enrolled in alternative, more aggressive therapeutic trials.

  13. Validation of the prognostic value of lymph node ratio in patients with cutaneous melanoma: a population-based study of 8,177 cases.

    Science.gov (United States)

    Mocellin, Simone; Pasquali, Sandro; Rossi, Carlo Riccardo; Nitti, Donato

    2011-07-01

    The proportion of positive among examined lymph nodes (lymph node ratio [LNR]) has been recently proposed as an useful and easy-to-calculate prognostic factor for patients with cutaneous melanoma. However, its independence from the standard prognostic system TNM has not been formally proven in a large series of patients. Patients with histologically proven cutaneous melanoma were identified from the Surveillance Epidemiology End Results database. Disease-specific survival was the clinical outcome of interest. The prognostic ability of conventional factors and LNR was assessed by multivariable survival analysis using the Cox regression model. Eligible patients (n = 8,177) were diagnosed with melanoma between 1998 and 2006. Among lymph node-positive cases (n = 3,872), most LNR values ranged from 1% to 10% (n = 2,187). In the whole series (≥5 lymph nodes examined) LNR significantly contributed to the Cox model independently of the TNM effect on survival (hazard ratio, 1.28; 95% confidence interval, 1.23-1.32; P < .0001). On subgroup analysis, the significant and independent prognostic value of LNR was confirmed both in patients with ≥10 lymph nodes examined (n = 4,381) and in those with TNM stage III disease (n = 3,658). In all cases, LNR increased the prognostic accuracy of the survival model. In this large series of patients, the LNR independently predicted disease-specific survival, improving the prognostic accuracy of the TNM system. Accordingly, the LNR should be taken into account for the stratification of patients' risk, both in clinical and research settings. Copyright © 2011 Mosby, Inc. All rights reserved.

  14. Implementation and evaluation of prognostic representations of the optical diameter of snow in the SURFEX/ISBA-Crocus detailed snowpack model

    Science.gov (United States)

    Carmagnola, C. M.; Morin, S.; Lafaysse, M.; Domine, F.; Lesaffre, B.; Lejeune, Y.; Picard, G.; Arnaud, L.

    2014-03-01

    In the SURFEX/ISBA-Crocus multi-layer snowpack model, the snow microstructure has up to now been characterised by the grain size and by semi-empirical shape variables which cannot be measured easily in the field or linked to other relevant snow properties. In this work we introduce a new formulation of snow metamorphism directly based on equations describing the rate of change of the optical diameter (dopt). This variable is considered here to be equal to the equivalent sphere optical diameter, which is inversely proportional to the specific surface area (SSA). dopt thus represents quantitatively some of the geometric characteristics of a porous medium. Different prognostic rate equations of dopt, including a re-formulation of the original Crocus scheme and the parameterisations from Taillandier et al. (2007) and Flanner and Zender (2006), were evaluated by comparing their predictions to field measurements carried out at Summit Camp (Greenland) in May and June 2011 and at Col de Porte (French Alps) during the 2009/10 and 2011/12 winter seasons. We focused especially on results in terms of SSA. In addition, we tested the impact of the different formulations on the simulated density profile, the total snow height, the snow water equivalent (SWE) and the surface albedo. Results indicate that all formulations perform well, with median values of the RMSD between measured and simulated SSA lower than 10 m2 kg-1. Incorporating the optical diameter as a fully fledged prognostic variable is an important step forward in the quantitative description of the snow microstructure within snowpack models, because it opens the way to data assimilation of various electromagnetic observations.

  15. Implementation and evaluation of prognostic representations of the optical diameter of snow in the detailed snowpack model SURFEX/ISBA-Crocus

    Science.gov (United States)

    Carmagnola, C. M.; Morin, S.; Lafaysse, M.; Domine, F.; Lesaffre, B.; Lejeune, Y.; Picard, G.; Arnaud, L.

    2013-09-01

    In the SURFEX/ISBA-Crocus multi-layer snowpack model, the snow microstructure was up to now characterized by the grain size and by semi-empirical shape variables which cannot be measured easily in the field or linked to other relevant snow properties. In this work we introduce a new formulation of snow metamorphism directly based on equations describing the rate of change of the optical diameter (dopt). This variable is considered here to be equal to the equivalent sphere optical diameter, which is inversely proportional to the specific surface area (SSA). dopt thus represents quantitatively some of the geometric characteristics of a porous medium. Different prognostic rate equations of dopt, including a re-formulation of the original Crocus scheme and the parametrizations from Taillandier et al. (2007) and Flanner and Zender (2006), were evaluated by comparing their predictions to field measurements carried out at Summit Camp (Greenland) in May and June 2011 and at Col de Porte (French Alps) during the 2009/10 and 2011/12 winter seasons. We focused especially on results in terms of SSA. In addition, we tested the impact of the different formulations on the simulated density profile, the total snow height, the snow water equivalent (SWE) and the surface albedo. Results indicate that all formulations perform well, with median values of the RMSD between measured and simulated SSA lower than 10 m2 kg-1. Incorporating the optical diameter as a fully-fledged prognostic variable is an important step forward in the quantitative description of the snow microstructure within snowpack models, because it opens the way to data assimilation of various electromagnetic observations.

  16. Prognostic role of serum prostatic acid phosphatase for 103Pd-based radiation for prostatic carcinoma

    International Nuclear Information System (INIS)

    Dattoli, Michael; Wallner, Kent; True, Lawrence; Sorace, Richard; Koval, John; Cash, Jennifer; Acosta, Rudolph; Biswas, Mohendra; Binder, Michael; Sullivan, Brent; Lastarria, Emilio; Kirwan, Novelle; Stein, Douglas

    1999-01-01

    Purpose: To establish the prognostic role of serum enzymatic prostatic acid phosphatase (PAP) in patients treated with palladium ( 103 Pd) and supplemental external beam irradiation (EBRT) for clinically localized, high-risk prostate carcinoma. Methods and Materials: One hundred twenty-four consecutive patients with Stage T2a-T3 prostatic carcinoma were treated from 1992 through 1995. Each patient had at least one of the following risk factors for extracapsular disease extension: Stage T2b or greater (100 patients), Gleason score 7-10 (40 patients), pretreatment prostate specific antigen (PSA) > 15 ng/ml (32 patients), or elevated serum PAP (25 patients). Patients received 41 Gy conformal EBRT to a limited pelvic field, followed 4 weeks later by a 103 Pd boost (prescription dose 80 Gy). Biochemical failure was defined as a PSA greater than 1 ng/ml (normal < 4 ng/ml). Results: The overall, actuarial freedom from biochemical failure at 4 years after treatment was 79%. In Cox-proportional hazard multivariate analysis, the strongest predictor of failure was elevated pretreatment acid phosphatase (p = 0.02), followed by Gleason score (p = 0.1), and PSA (p = 0.14). Conclusion: PAP was the strongest predictor of long-term biochemical failure. It may be a more accurate indicator of micrometastatic disease than PSA, and as such, we suggest that it be reconsidered for general use in radiation-treated patients

  17. Integrating Tenascin-C protein expression and 1q25 copy number status in pediatric intracranial ependymoma prognostication: A new model for risk stratification.

    Science.gov (United States)

    Andreiuolo, Felipe; Le Teuff, Gwénaël; Bayar, Mohamed Amine; Kilday, John-Paul; Pietsch, Torsten; von Bueren, André O; Witt, Hendrik; Korshunov, Andrey; Modena, Piergiorgio; Pfister, Stefan M; Pagès, Mélanie; Castel, David; Giangaspero, Felice; Chimelli, Leila; Varlet, Pascale; Rutkowski, Stefan; Frappaz, Didier; Massimino, Maura; Grundy, Richard; Grill, Jacques

    2017-01-01

    Despite multimodal therapy, prognosis of pediatric intracranial ependymomas remains poor with a 5-year survival rate below 70% and frequent late deaths. This multicentric European study evaluated putative prognostic biomarkers. Tenascin-C (TNC) immunohistochemical expression and copy number status of 1q25 were retained for a pooled analysis of 5 independent cohorts. The prognostic value of TNC and 1q25 on the overall survival (OS) was assessed using a Cox model adjusted to age at diagnosis, tumor location, WHO grade, extent of resection, radiotherapy and stratified by cohort. Stratification on a predictor that did not satisfy the proportional hazards assumption was considered. Model performance was evaluated and an internal-external cross validation was performed. Among complete cases with 5-year median follow-up (n = 470; 131 deaths), TNC and 1q25 gain were significantly associated with age at diagnosis and posterior fossa tumor location. 1q25 status added independent prognostic value for death beyond the classical variables with a hazard ratio (HR) = 2.19 95%CI = [1.29; 3.76] (p = 0.004), while TNC prognostic relation was tumor location-dependent with HR = 2.19 95%CI = [1.29; 3.76] (p = 0.004) in posterior fossa and HR = 0.64 [0.28; 1.48] (p = 0.295) in supratentorial (interaction p value = 0.015). The derived prognostic score identified 3 different robust risk groups. The omission of upfront RT was not associated with OS for good and intermediate prognostic groups while the absence of upfront RT was negatively associated with OS in the poor risk group. Integrated TNC expression and 1q25 status are useful to better stratify patients and to eventually adapt treatment regimens in pediatric intracranial ependymoma.

  18. Integrating Tenascin-C protein expression and 1q25 copy number status in pediatric intracranial ependymoma prognostication: A new model for risk stratification.

    Directory of Open Access Journals (Sweden)

    Felipe Andreiuolo

    Full Text Available Despite multimodal therapy, prognosis of pediatric intracranial ependymomas remains poor with a 5-year survival rate below 70% and frequent late deaths.This multicentric European study evaluated putative prognostic biomarkers. Tenascin-C (TNC immunohistochemical expression and copy number status of 1q25 were retained for a pooled analysis of 5 independent cohorts. The prognostic value of TNC and 1q25 on the overall survival (OS was assessed using a Cox model adjusted to age at diagnosis, tumor location, WHO grade, extent of resection, radiotherapy and stratified by cohort. Stratification on a predictor that did not satisfy the proportional hazards assumption was considered. Model performance was evaluated and an internal-external cross validation was performed.Among complete cases with 5-year median follow-up (n = 470; 131 deaths, TNC and 1q25 gain were significantly associated with age at diagnosis and posterior fossa tumor location. 1q25 status added independent prognostic value for death beyond the classical variables with a hazard ratio (HR = 2.19 95%CI = [1.29; 3.76] (p = 0.004, while TNC prognostic relation was tumor location-dependent with HR = 2.19 95%CI = [1.29; 3.76] (p = 0.004 in posterior fossa and HR = 0.64 [0.28; 1.48] (p = 0.295 in supratentorial (interaction p value = 0.015. The derived prognostic score identified 3 different robust risk groups. The omission of upfront RT was not associated with OS for good and intermediate prognostic groups while the absence of upfront RT was negatively associated with OS in the poor risk group.Integrated TNC expression and 1q25 status are useful to better stratify patients and to eventually adapt treatment regimens in pediatric intracranial ependymoma.

  19. Inflammation-based prognostic score, prior to neoadjuvant chemoradiotherapy, predicts postoperative outcome in patients with esophageal squamous cell carcinoma.

    Science.gov (United States)

    Kobayashi, Takashi; Teruya, Masanori; Kishiki, Tomokazu; Endo, Daisuke; Takenaka, Yoshiharu; Tanaka, Hozumi; Miki, Kenji; Kobayashi, Kaoru; Morita, Koji

    2008-11-01

    Recent studies have revealed that Glasgow prognostic score (GPS), an inflammation-based prognostic score, is associated with poor outcome in a variety of tumors. However, few studies have investigated whether GPS measured prior to neoadjuvant chemoradiotherapy (nCRT) is useful for postoperative prognosis of patients with advanced esophageal squamous cell carcinoma (ESCC). GPS was calculated on the basis of admission data as follows: patients with both an elevated C-reactive protein (>10 mg/L) and hypoalbuminaemia (L) were allocated a GPS score of 2. Patients in whom only 1 of these biochemical abnormalities was present were allocated a GPS score of 1, and patients with a normal C-reactive protein and albumin were allocated a score of 0. All patients underwent radical en-bloc resection 3-4 weeks after nCRT. A total of 48 patients with clinical TNM stage II/III were enrolled. Univariate analyses revealed that there were significant differences in cancer-specific survival in relation to grade of response to nCRT (P = .004), lymph node status (P = .0065), lymphatic invasion (P = .0002), venous invasion (P = .0001), pathological TNM classification (P = .015), and GPS (P GPS classification showed a close relationship with lymphatic invasion, venous invasion, and number of lymph node (P = .0292, .0473, and .0485, respectively). GPS was found to be the only independent predictor of cancer-specific survival (odds ratio, 0.17; 95% confidence interval, 0.06-0.52; P = .0019). GPS, measured prior to nCRT, is an independent novel predictor of postoperative outcome in patients with advanced ESCC.

  20. Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data—a preliminary study

    Science.gov (United States)

    Xia, Wei; Chen, Ying; Zhang, Rui; Yan, Zhuangzhi; Zhou, Xiaobo; Zhang, Bo; Gao, Xin

    2018-02-01

    Our objective was to identify prognostic imaging biomarkers for hepatocellular carcinoma in contrast-enhanced computed tomography (CECT) with biological interpretations by associating imaging features and gene modules. We retrospectively analyzed 371 patients who had gene expression profiles. For the 38 patients with CECT imaging data, automatic intra-tumor partitioning was performed, resulting in three spatially distinct subregions. We extracted a total of 37 quantitative imaging features describing intensity, geometry, and texture from each subregion. Imaging features were selected after robustness and redundancy analysis. Gene modules acquired from clustering were chosen for their prognostic significance. By constructing an association map between imaging features and gene modules with Spearman rank correlations, the imaging features that significantly correlated with gene modules were obtained. These features were evaluated with Cox’s proportional hazard models and Kaplan-Meier estimates to determine their prognostic capabilities for overall survival (OS). Eight imaging features were significantly correlated with prognostic gene modules, and two of them were associated with OS. Among these, the geometry feature volume fraction of the subregion, which was significantly correlated with all prognostic gene modules representing cancer-related interpretation, was predictive of OS (Cox p  =  0.022, hazard ratio  =  0.24). The texture feature cluster prominence in the subregion, which was correlated with the prognostic gene module representing lipid metabolism and complement activation, also had the ability to predict OS (Cox p  =  0.021, hazard ratio  =  0.17). Imaging features depicting the volume fraction and textural heterogeneity in subregions have the potential to be predictors of OS with interpretable biological meaning.

  1. Local Recurrence of Hepatocellular Carcinoma after Segmental Transarterial Chemoembolization: Risk Estimates Based on Multiple Prognostic Factors

    International Nuclear Information System (INIS)

    Park, Seung Hyun; Cho, Yun Ku; Ahn, Yong Sik; Park, Yoon Ok; Kim, Jae Kyun; Chung, Jin Wook

    2007-01-01

    To determine the prognostic factors for local recurrence of nodular hepatocellular carcinoma after segmental transarterial chemoembolization. Seventy-four nodular hepatocellular carcinoma tumors ≤5 cm were retrospectively analyzed for local recurrence after segmental transarterial chemoembolization using follow-up CT images (median follow-up of 17 months, 4 77 months in range). The tumors were divided into four groups (IA, IB, IIA, and IIB) according to whether the one-month follow-up CT imaging, after segmental transarterial chemoembolization, showed homogeneous (Group I) or inhomogeneous (Group II) iodized oil accumulation, or whether the tumors were located within the liver segment (Group A) or in a segmental border zone (Group B). Comparison of tumor characteristics between Group IA and the other three groups was performed using the chi-square test. Local recurrence rates were compared among the groups using the Kaplan-Meier estimation and log rank test. Local tumor recurrence occurred in 19 hepatocellular carcinoma tumors (25.7%). There were: 28, 18, 17, and 11 tumors in Group IA, IB, IIA, and IIB, respectively. One of 28 (3.6%) tumors in Group IA, and 18 of 46 (39.1%) tumors in the other three groups showed local recurrence. Comparisons between Group IA and the other three groups showed that the tumor characteristics were similar. One-, two-, and three-year estimated local recurrence rates in Group IA were 0%, 11.1%, and 11.1%, respectively. The difference between Group IA and the other three groups was statistically significant (p 0.000). An acceptably low rate of local recurrence was observed for small or intermediate nodular tumors located within the liver segment with homogeneous iodized oil accumulation

  2. Product quality management based on CNC machine fault prognostics and diagnosis

    Science.gov (United States)

    Kozlov, A. M.; Al-jonid, Kh M.; Kozlov, A. A.; Antar, Sh D.

    2018-03-01

    This paper presents a new fault classification model and an integrated approach to fault diagnosis which involves the combination of ideas of Neuro-fuzzy Networks (NF), Dynamic Bayesian Networks (DBN) and Particle Filtering (PF) algorithm on a single platform. In the new model, faults are categorized in two aspects, namely first and second degree faults. First degree faults are instantaneous in nature, and second degree faults are evolutional and appear as a developing phenomenon which starts from the initial stage, goes through the development stage and finally ends at the mature stage. These categories of faults have a lifetime which is inversely proportional to a machine tool's life according to the modified version of Taylor’s equation. For fault diagnosis, this framework consists of two phases: the first one is focusing on fault prognosis, which is done online, and the second one is concerned with fault diagnosis which depends on both off-line and on-line modules. In the first phase, a neuro-fuzzy predictor is used to take a decision on whether to embark Conditional Based Maintenance (CBM) or fault diagnosis based on the severity of a fault. The second phase only comes into action when an evolving fault goes beyond a critical threshold limit called a CBM limit for a command to be issued for fault diagnosis. During this phase, DBN and PF techniques are used as an intelligent fault diagnosis system to determine the severity, time and location of the fault. The feasibility of this approach was tested in a simulation environment using the CNC machine as a case study and the results were studied and analyzed.

  3. Primary radiotherapy or postoperative radiotherapy in patients with head and neck cancer. Comparative analysis of inflammation-based prognostic scoring systems

    Energy Technology Data Exchange (ETDEWEB)

    Selzer, Edgar; Grah, Anja [Medical University of Vienna, Department of Radiotherapy, Vienna (Austria); Heiduschka, Gregor; Thurnher, Dietmar [Medical University of Vienna, Otorhinolaryngology - Head and Neck Surgery, Vienna (Austria); Kornek, Gabriela [Medical University of Vienna, Medicine I - Division of Clinical Oncology, Vienna (Austria)

    2015-01-13

    Inflammation-based scoring systems have potential value in evaluating the prognosis of cancer patients; however, detailed comparative analyses in well-characterized head and neck cancer patient collectives are missing. We analyzed overall survival (OS) in locally advanced head and neck cancer patients who were treated with curative intent by primary radiotherapy (RT) alone, by RT in combination with cetuximab (RIT) or with cisplatin (RCHT), and by primary surgery followed by postoperative radiotherapy (PORT). The primary RT collective (N = 170) was analyzed separately from the surgery plus RT group (N = 148). OS was estimated using the Kaplan-Meyer method. Cox proportional-hazard regression models were applied to compare the risk of death among patients stratified according to risk factors and the inflammation-based Glasgow Prognostic Score (GPS), the modified GPS (mGPS), the neutrophil-lymphocyte ratio (NLR), the platelet-lymphocyte ratio (PLR), and the prognostic index (PI). A prognostic relevance of the scoring systems for OS was observed in the primarily irradiated, but not in the PORT collective. OS was 35.5, 18.8, and 15.4 months, respectively, according to GPS 0, 1, and 2. OS according to mGPS 0-2 was identical. The PLR scoring system was not of prognostic relevance, while OS was 27.3 months in the NLR 0 group and 17.3 months in the NLR 1 group. OS was 35.5 months in PI 0, 16.1 months in PI 1, and 22.6 months in PI 2. GPS/mGPS scoring systems are able to discriminate between three risk groups in primarily, but not postoperatively irradiated locally advanced head and neck cancer patients. (orig.) [German] Entzuendungsbasierte Bewertungssysteme haben eine potenzielle Bedeutung fuer die Beurteilung der Prognose von Krebspatienten. Derzeit fehlen jedoch ausreichend detailliert durchgefuehrte Analysen in Kollektiven von Patienten mit Kopf-Hals-Tumoren. Untersucht wurde das Gesamtueberleben (''overall survival'', OS) von Patienten mit lokal

  4. Gene Expression of the EGF System-a Prognostic Model in Non-Small Cell Lung Cancer Patients Without Activating EGFR Mutations

    DEFF Research Database (Denmark)

    Sandfeld-Paulsen, Birgitte; Folkersen, Birgitte Holst; Rasmussen, Torben Riis

    2016-01-01

    OBJECTIVES: Contradicting results have been demonstrated for the expression of the epidermal growth factor receptor (EGFR) as a prognostic marker in non-small cell lung cancer (NSCLC). The complexity of the EGF system with four interacting receptors and more than a dozen activating ligands is a l.......17-6.47], P model that takes the complexity of the EGF system into account and shows that this model is a strong prognostic marker in NSCLC patients.......OBJECTIVES: Contradicting results have been demonstrated for the expression of the epidermal growth factor receptor (EGFR) as a prognostic marker in non-small cell lung cancer (NSCLC). The complexity of the EGF system with four interacting receptors and more than a dozen activating ligands...... is a likely explanation. The aim of this study is to demonstrate that the combined network of receptors and ligands from the EGF system is a prognostic marker. MATERIAL AND METHODS: Gene expression of the receptors EGFR, HER2, HER3, HER4, and the ligands AREG, HB-EGF, EPI, TGF-α, and EGF was measured...

  5. Survival in pediatric medulloblastoma: a population-based observational study to improve prognostication.

    Science.gov (United States)

    Weil, Alexander G; Wang, Anthony C; Westwick, Harrison J; Ibrahim, George M; Ariani, Rojine T; Crevier, Louis; Perreault, Sebastien; Davidson, Tom; Tseng, Chi-Hong; Fallah, Aria

    2017-03-01

    Medulloblastoma is the most common form of brain malignancy of childhood. The mainstay of epidemiological data regarding childhood medulloblastoma is derived from case series, hence population-based studies are warranted to improve the accuracy of survival estimates. To utilize a big-data approach to update survival estimates in a contemporary cohort of children with medulloblastoma. We performed a population-based retrospective observational cohort study utilizing the Surveillance, Epidemiology, and End Results Program database that captures all children, less than 20 years of age, between 1973 and 2012 in 18 geographical regions representing 28% of the US population. We included all participants with a presumed or histologically diagnosis of medulloblastoma. The main outcome of interest is survivors at 1, 5 and 10 years following diagnosis. A cohort of 1735 children with a median (interquartile range) age at diagnosis of 7 (4-11) years, with a diagnosis of medulloblastoma were identified. The incidence and prevalence of pediatric medulloblastoma has remained stable over the past 4 decades. There is a critical time point at 1990 when the overall survival has drastically improved. In the contemporary cohort (1990 onwards), the percentage of participants alive was 86, 70 and 63% at 1, 5 and 10 years, respectively. Multivariate Cox-Regression model demonstrated Radiation (HR 0.37; 95% CI 0.30-0.46, p < 0.001) and Surgery (HR 0.42; 95% CI 0.30-0.58, p < 0.001) independently predict survival. The probability of mortality from a neurological cause is <5% in patients who are alive 8 years following diagnosis. The SEER cohort analysis demonstrates significant improvements in pediatric medulloblastoma survival. In contrast to previous reports, the majority of patients survive in the modern era, and those alive 8 years following initial diagnosis are likely a long-term survivor. The importance of minimizing treatment-related toxicity is increasingly apparent given

  6. Development and External Validation of Prognostic Model for 2-Year Survival of Non-Small-Cell Lung Cancer Patients Treated With Chemoradiotherapy

    International Nuclear Information System (INIS)

    Dehing-Oberije, Cary; Yu Shipeng; De Ruysscher, Dirk; Meersschout, Sabine; Van Beek, Karen; Lievens, Yolande; Van Meerbeeck, Jan; De Neve, Wilfried; Rao, Bharat Ph.D.; Weide, Hiska van der; Lambin, Philippe

    2009-01-01

    Purpose: Radiotherapy, combined with chemotherapy, is the treatment of choice for a large group of non-small-cell lung cancer (NSCLC) patients. Recent developments in the treatment of these patients have led to improved survival. However, the clinical TNM stage is highly inaccurate for the prediction of survival, and alternatives are lacking. The objective of this study was to develop and validate a prediction model for survival of NSCLC patients, treated with chemoradiotherapy. Patients and Methods: The clinical data from 377 consecutive inoperable NSCLC patients, Stage I-IIIB, treated radically with chemoradiotherapy were collected. A prognostic model for 2-year survival was developed, using 2-norm support vector machines. The performance of the model was expressed as the area under the curve of the receiver operating characteristic and assessed using leave-one-out cross-validation, as well as two external data sets. Results: The final multivariate model consisted of gender, World Health Organization performance status, forced expiratory volume in 1 s, number of positive lymph node stations, and gross tumor volume. The area under the curve, assessed by leave-one-out cross-validation, was 0.74, and application of the model to the external data sets yielded an area under the curve of 0.75 and 0.76. A high- and low-risk group could be clearly identified using a risk score based on the model. Conclusion: The multivariate model performed very well and was able to accurately predict the 2-year survival of NSCLC patients treated with chemoradiotherapy. The model could support clinicians in the treatment decision-making process.

  7. Prognostic relevance of motor talent predictors in early adolescence: A group- and individual-based evaluation considering different levels of achievement in youth football.

    Science.gov (United States)

    Höner, Oliver; Votteler, Andreas

    2016-12-01

    In the debate about the usefulness of motor diagnostics in the talent identification process, the prognostic validity for tests conducted in early adolescence is of critical interest. Using a group- and individual-based statistical approach, this prospective cohort study evaluated a nationwide assessment of speed abilities and technical skills regarding its relevance for future achievement levels. The sample consisted of 22,843 U12-players belonging to the top 4% in German football. The U12-results in five tests served as predictors for players' selection levels in U16-U19 (youth national team, regional association, youth academy, not selected). Group-mean differences proved the prognostic relevance for all predictors. Low individual selection probabilities demonstrated limited predictive values, while excellent test results proved their particular prognostic relevance. Players scoring percentile ranks (PRs) ≥ 99 had a 12 times higher chance to become youth national team players than players scoring PR talents) but also led to lower sensitivity (loss of talents). Extending the current research, these different approaches revealed the ambiguity of the diagnostics' prognostic relevance, representing both the usefulness and several pitfalls of nationwide diagnostics. Therefore, the present diagnostics can support but not substitute for coaches' subjective decisions for talent identification, and multidisciplinary designs are required.

  8. Radiation therapy for chordoma and chondrosarcoma of the skull base and the cervical spine. Prognostic factors and patterns of failure

    International Nuclear Information System (INIS)

    Noel, G.; Jauffret, E.; Mammar, H.; Ferrand, R.; Habrand, J.L.; Crevoisier, R. de; Haie-Meder, C.; Beaudre, A.; Dederke, S.; Hasboun, D.; Boisserie, G.; Pontvert, D.; Gaboriaud, G.; Guedea, F.; Petriz, L.; Mazeron, J.J.

    2003-01-01

    Background: Prospective analysis of local tumor control, survival and treatment complications in 67 consecutive patients treated with fractionated photon and proton radiation for chordoma or chondrosarcoma of the base of the skull and the cervical spine. Patients and Methods: Between December 1995 and January 2000, 67 patients with a median age of 52 years (range: 14-85 years), were treated at the Centre de Protontherapie d'Orsay (CPO), France, using the 201-MeV proton beam, 49 for chordoma and 18 for chondrosarcoma. Irradiation combined high-energy photons and protons. Photons represented two thirds of the total dose and protons one third. The median total dose delivered within gross tumor volume (GTV) was 67 cobalt gray equivalents (CGE; range: 60-70 CGE). Results: Within a median follow-up of 29 months (range: 4-71 months), the 3-year local control rates were 71% and 85% for chordomas and chondrosarcomas, respectively, and the 3-year overall survival rates 88% and 75%, respectively. 14 tumors (21.5%) failed locally (eight within the GTV, four within the clinical target volume [CTV], and two without further assessment). Seven patients died from their tumor and another one from a nonrelated condition (pulmonary embolism). The maximum tumor diameter and, similarly, the GTV were larger in relapsing patients, compared with the rest of the population: 56 mm vs 44 mm (p = 0.024) and 50 ml vs 22 ml (p = 0.0083), respectively. In univariate analysis, age ≤ 52 years at the time of radiotherapy (p = 0.002), maximum diameter < 45 mm (p = 0.02), and GTV < 28 ml (p = 0.02) impacted positively on local control. On multivariate analysis, only age was an independent prognostic factor of local control. Conclusion: In chordomas and chondrosarcomas of the skull base and cervical spine, combined photon and proton radiation therapy offers excellent chances of cure. In two thirds of the cases, relapses are located in the GTV. Maximum diameter, GTV, and age are prognostic indicators

  9. Differential evolution-based multi-objective optimization for the definition of a health indicator for fault diagnostics and prognostics

    Science.gov (United States)

    Baraldi, P.; Bonfanti, G.; Zio, E.

    2018-03-01

    The identification of the current degradation state of an industrial component and the prediction of its future evolution is a fundamental step for the development of condition-based and predictive maintenance approaches. The objective of the present work is to propose a general method for extracting a health indicator to measure the amount of component degradation from a set of signals measured during operation. The proposed method is based on the combined use of feature extraction techniques, such as Empirical Mode Decomposition and Auto-Associative Kernel Regression, and a multi-objective Binary Differential Evolution (BDE) algorithm for selecting the subset of features optimal for the definition of the health indicator. The objectives of the optimization are desired characteristics of the health indicator, such as monotonicity, trendability and prognosability. A case study is considered, concerning the prediction of the remaining useful life of turbofan engines. The obtained results confirm that the method is capable of extracting health indicators suitable for accurate prognostics.

  10. Distinct distribution and prognostic significance of molecular subtypes of breast cancer in Chinese women: a population-based cohort study

    Directory of Open Access Journals (Sweden)

    Cai Qiuyin

    2011-07-01

    Full Text Available Abstract Background Molecular classification of breast cancer is an important prognostic factor. The distribution of molecular subtypes of breast cancer and their prognostic value has not been well documented in Asians. Methods A total of 2,791 breast cancer patients recruited for a population-based cohort study were evaluated for molecular subtypes of breast cancer by immunohistochemical assays. Data on clinicopathological characteristics were confirmed by centralized pathology review. The average follow-up of the patients was 53.4 months. Overall and disease-free survival by molecular subtypes of breast cancer were evaluated. Results The prevalence of the luminal A, luminal B, human epidermal growth factor receptor 2 (HER2, and triple-negative subtypes were 48.6%, 16.7%, 13.7%, and 12.9%, respectively. The luminal A subtype was more likely to be diagnosed in older women (P = 0.03 and had a stronger correlation with favorable clinicopathological factors (smaller tumor size, lower histologic grade, and earlier TNM stage than the triple-negative or HER2 subtypes. Women with triple-negative breast cancer had a higher frequency of family history of breast cancer than women with other subtypes (P = 0.048. The 5-year overall/disease-free survival percentages for the luminal A, luminal B, HER2, and triple-negative subtypes were 92.9%/88.6%, 88.6%/85.1%, 83.2%/79.1%, and 80.7%/76.0%, respectively. A similar pattern was observed in multivariate analyses. Immunotherapy was associated with improved overall and disease-free survival for luminal A breast cancer, but reduced disease-free survival (HR = 2.21, 95% CI, 1.09-4.48 for the HER2 subtype of breast cancer. Conclusions The triple-negative and HER2 subtypes were associated with poorer outcomes compared with the luminal A subtype among these Chinese women. The HER2 subtype was more prevalent in this Chinese population compared with Western populations, suggesting the importance of standardized HER2

  11. PROGNOSTIC FACTORS FOR PRIMARY CENTRAL NERVOUS SYSTEM LYMPHOMAS TREATED WITH HIGH-DOSE METHOTREXATE-BASED CHEMO-RADIOTHERAPY

    Science.gov (United States)

    Nagane, Motoo; Lee, Jeunghun; Shishido-Hara, Yukiko; Suzuki, Kaori; Shimizu, Saki; Umino, Michiru; Kobayashi, Keiichi; Shiokawa, Yoshiaki

    2014-01-01

    BACKGROUND: Chemotherapy with high-dose methotrexate (HD-MTX) followed by whole brain radiotherapy (WBRT) is a conventional approach to treat primary central nervous system lymphomas (PCNSL), but some tumors relapse early leading to unfavorable outcome. Several biomarkers have been identified as prognostic factors in PCNSL, however, the correlation of both clinical factors including those related to MTX metabolism and B-cell differentiation and oncogenic biomarkers with response to and outcome by therapy is yet unclear. METHODS: We investigated 32 immunocompetent patients (19 males, 13 females) with PCNSL (all diffuse large B-cell type) treated with HD-MTX based therapy with or without WBRT since 2000 in our institution. Paraffin-embedded formalin-fixed tumor tissue sections were stained immunohistochemically with antibodies against following factors: B-cell differentiation markers (CD10, Bcl-6, Mum-1, CD138); MTX metabolism-related (MRP family, LRP, DHFR); cell cycle-related (p27KIP1, MIB-1); drug resistance-related (MGMT, MLH1, MSH2, MSH6, PMS2); and oncogenes (Myc, Bcl-2). Correlation between positivity of these factors and clinical outcomes were evaluated using logrank test and cox regression analysis. RESULTS: Among these factors, complete response to HD-MTX was significantly associated with longer progression-free survival (PFS)(P = 0.0012), while Bcl-6 expression as well as histological subtype (non-germinal center B-cell, non-GCB) was closely correlated with shorter PFS. Age (>60) (P = 0.006) and MSH2 expression (P = 0.017) were found to be better predictor for overall survival (OS), but in multivariate analysis, they were no longer significant. Other factors involved in MTX metabolism, DNA repair enzymes, and oncogenes did not affect outcome. CONCLUSIONS: Non-GCB subtype and Bcl-6 expression may be associated with worse outcome in patients with PCNSL treated with HD-MTX, while MTX-metabolism related factors did not influence prognosis. Further

  12. Prognostic Value of Volume-Based {sup 18}F-Fluorodeoxyglucose PET/CT Parameters in Patients with Clinically Node-Negative Oral Tongue Squamous Cell Carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Su Jin [Dept. of Nuclear Medicine, Ajou University School of Medicine, Suwon (Korea, Republic of); Choi, Joon Young; Lee, Hwan Joo; Hyun, Seung Hyup; Moon, Seung Hwan; Kim, Byung Tae [Dept. of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of); Baek, Chung Hwan; Son, Young Ik [Dept. of Otorhinolaryngology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

    2012-11-15

    To evaluate the prognostic value of volume-based metabolic parameters measured with {sup 18}F-fluorodeoxyglucose ({sup 18}F-FDG) positron emission tomography (PET) in patients with clinically node-negative (cN0) oral tongue squamous cell carcinoma (OTSCC) as compared with other prognostic factors. In this study, we included a total of 57 patients who had been diagnosed with cN0 tongue cancer by radiologic, ({sup 18}F-FDG PET/CT, and physical examinations. The maximum standardized uptake value (SUVmax), average SUV (SUVavg), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) for primary tumors were measured with ({sup 18}F-FDG PET. The prognostic significances of these parameters and other clinical variables were assessed by Cox proportional hazards regression analysis. In the univariate analysis, pathological node (pN) stage, American Joint Committee on Cancer (AJCC) stage, SUVmax, SUVavg, MTV, and TLG were significant predictors for survival. On a multivariate analysis, pN stage (hazard ratio = 10.555, p = 0.049), AJCC stage (hazard ratio = 13.220, p = 0.045), and MTV (hazard ratio = 2.698, p 0.033) were significant prognostic factors in cN0 OTSCC patients. The patients with MTV {>=} 7.78 cm{sup 3} showed a worse prognosis than those with MTV < 7.78 cm{sup 3} (p = 0.037). The MTV of primary tumor as a volumetric parameter of ({sup 18}F-FDG PET, in addition to pN stage and AJCC stage, is an independent prognostic factor for survival in cN0 OTSCC.

  13. MRI-detected skull-base invasion. Prognostic value and therapeutic implication in intensity-modulated radiotherapy treatment for nasopharyngeal carcinoma

    International Nuclear Information System (INIS)

    Cheng, Yi-Kan; Jiang, Ning; Yue, Dan; Tang, Ling-Long; Zhang, Fan; Lin, Li; Liu, Xu; Chen, Lei; Ma, Jun; Liu, Li-Zhi

    2014-01-01

    With advances in imaging and radiotherapy, the prognostic value of skull-base invasion in nasopharyngeal carcinoma (NPC) needs to be reassessed. We aimed to define a classification system and evaluate the prognostic value of the classification of magnetic resonance imaging (MRI)-detected skull-base invasion in NPC treated with intensity-modulated radiotherapy (IMRT). We retrospectively reviewed 749 patients who underwent MRI and were subsequently histologically diagnosed with nondisseminated NPC and treated with IMRT. MRI-detected skull-base invasion was not found to be an independent prognostic factor for overall survival (OS), distant metastasis-free survival (DMFS), local relapse-free survival (LRFS), or disease-free survival (DFS; p > 0.05 for all). Skull-base invasion was classified according to the incidence of each site (type I sites inside pharyngobasilar fascia and clivus vs. type II sites outside pharyngobasilar fascia). The 5-year OS, DMFS, LRFS, and DFS rates in the classification of skull-base invasion in NPC were 83 vs. 67 %, 85 vs.75 %, 95 vs. 88 %, and 76 vs. 62 %, respectively (p [de

  14. Using Enthalpy as a Prognostic Variable in Atmospheric Modelling with Variable Composition

    Science.gov (United States)

    2016-04-14

    Sela, personal communication, 2005). These terms are also routinely neglected in models. In models with a limited number of gaseous tracers, such as...so-called energy- exchange term (second term on the left- hand side) in Equation (5). The finite-difference schemes in existing atmospheric models have...equation for the sum of enthalpy and kinetic energy of horizontal motion is solved. This eliminates the energy- exchange term and automatically

  15. Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Foley, Kieran G. [Cardiff University, Division of Cancer and Genetics, Cardiff (United Kingdom); Hills, Robert K. [Cardiff University, Haematology Clinical Trials Unit, Cardiff (United Kingdom); Berthon, Beatrice; Marshall, Christopher [Wales Research and Diagnostic PET Imaging Centre, Cardiff (United Kingdom); Parkinson, Craig; Spezi, Emiliano [Cardiff University, School of Engineering, Cardiff (United Kingdom); Lewis, Wyn G. [University Hospital of Wales, Department of Upper GI Surgery, Cardiff (United Kingdom); Crosby, Tom D.L. [Department of Oncology, Velindre Cancer Centre, Cardiff (United Kingdom); Roberts, Stuart Ashley [University Hospital of Wales, Department of Clinical Radiology, Cardiff (United Kingdom)

    2018-01-15

    This retrospective cohort study developed a prognostic model incorporating PET texture analysis in patients with oesophageal cancer (OC). Internal validation of the model was performed. Consecutive OC patients (n = 403) were chronologically separated into development (n = 302, September 2010-September 2014, median age = 67.0, males = 227, adenocarcinomas = 237) and validation cohorts (n = 101, September 2014-July 2015, median age = 69.0, males = 78, adenocarcinomas = 79). Texture metrics were obtained using a machine-learning algorithm for automatic PET segmentation. A Cox regression model including age, radiological stage, treatment and 16 texture metrics was developed. Patients were stratified into quartiles according to a prognostic score derived from the model. A p-value < 0.05 was considered statistically significant. Primary outcome was overall survival (OS). Six variables were significantly and independently associated with OS: age [HR =1.02 (95% CI 1.01-1.04), p < 0.001], radiological stage [1.49 (1.20-1.84), p < 0.001], treatment [0.34 (0.24-0.47), p < 0.001], log(TLG) [5.74 (1.44-22.83), p = 0.013], log(Histogram Energy) [0.27 (0.10-0.74), p = 0.011] and Histogram Kurtosis [1.22 (1.04-1.44), p = 0.017]. The prognostic score demonstrated significant differences in OS between quartiles in both the development (X{sup 2} 143.14, df 3, p < 0.001) and validation cohorts (X{sup 2} 20.621, df 3, p < 0.001). This prognostic model can risk stratify patients and demonstrates the additional benefit of PET texture analysis in OC staging. (orig.)

  16. Base Station Performance Model

    OpenAIRE

    Walsh, Barbara; Farrell, Ronan

    2005-01-01

    At present the testing of power amplifiers within base station transmitters is limited to testing at component level as opposed to testing at the system level. While the detection of catastrophic failure is possible, that of performance degradation is not. This paper proposes a base station model with respect to transmitter output power with the aim of introducing system level monitoring of the power amplifier behaviour within the base station. Our model reflects the expe...

  17. Structural Health and Prognostics Management for Offshore Wind Turbines: Sensitivity Analysis of Rotor Fault and Blade Damage with O&M Cost Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Myrent, Noah J. [Vanderbilt Univ., Nashville, TN (United States). Lab. for Systems Integrity and Reliability; Barrett, Natalie C. [Vanderbilt Univ., Nashville, TN (United States). Lab. for Systems Integrity and Reliability; Adams, Douglas E. [Vanderbilt Univ., Nashville, TN (United States). Lab. for Systems Integrity and Reliability; Griffith, Daniel Todd [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Wind Energy Technology Dept.

    2014-07-01

    Operations and maintenance costs for offshore wind plants are significantly higher than the current costs for land-based (onshore) wind plants. One way to reduce these costs would be to implement a structural health and prognostic management (SHPM) system as part of a condition based maintenance paradigm with smart load management and utilize a state-based cost model to assess the economics associated with use of the SHPM system. To facilitate the development of such a system a multi-scale modeling and simulation approach developed in prior work is used to identify how the underlying physics of the system are affected by the presence of damage and faults, and how these changes manifest themselves in the operational response of a full turbine. This methodology was used to investigate two case studies: (1) the effects of rotor imbalance due to pitch error (aerodynamic imbalance) and mass imbalance and (2) disbond of the shear web; both on a 5-MW offshore wind turbine in the present report. Sensitivity analyses were carried out for the detection strategies of rotor imbalance and shear web disbond developed in prior work by evaluating the robustness of key measurement parameters in the presence of varying wind speeds, horizontal shear, and turbulence. Detection strategies were refined for these fault mechanisms and probabilities of detection were calculated. For all three fault mechanisms, the probability of detection was 96% or higher for the optimized wind speed ranges of the laminar, 30% horizontal shear, and 60% horizontal shear wind profiles. The revised cost model provided insight into the estimated savings in operations and maintenance costs as they relate to the characteristics of the SHPM system. The integration of the health monitoring information and O&M cost versus damage/fault severity information provides the initial steps to identify processes to reduce operations and maintenance costs for an offshore wind farm while increasing turbine availability

  18. Peripheral T cell lymphoma, not otherwise specified (PTCL-NOS). A new prognostic model developed by the International T cell Project Network.

    Science.gov (United States)

    Federico, Massimo; Bellei, Monica; Marcheselli, Luigi; Schwartz, Marc; Manni, Martina; Tarantino, Vittoria; Pileri, Stefano; Ko, Young-Hyeh; Cabrera, Maria E; Horwitz, Steven; Kim, Won S; Shustov, Andrei; Foss, Francine M; Nagler, Arnon; Carson, Kenneth; Pinter-Brown, Lauren C; Montoto, Silvia; Spina, Michele; Feldman, Tatyana A; Lechowicz, Mary J; Smith, Sonali M; Lansigan, Frederick; Gabus, Raul; Vose, Julie M; Advani, Ranjana H

    2018-04-19

    Different models to investigate the prognosis of peripheral T cell lymphoma not otherwise specified (PTCL-NOS) have been developed by means of retrospective analyses. Here we report on a new model designed on data from the prospective T Cell Project. Twelve covariates collected by the T Cell Project were analysed and a new model (T cell score), based on four covariates (serum albumin, performance status, stage and absolute neutrophil count) that maintained their prognostic value in multiple Cox proportional hazards regression analysis was proposed. Among patients registered in the T Cell Project, 311 PTCL-NOS were retained for study. At a median follow-up of 46 months, the median overall survival (OS) and progression-free survival (PFS) was 20 and 10 months, respectively. Three groups were identified at low risk (LR, 48 patients, 15%, score 0), intermediate risk (IR, 189 patients, 61%, score 1-2), and high risk (HiR, 74 patients, 24%, score 3-4), having a 3-year OS of 76% [95% confidence interval 61-88], 43% [35-51], and 11% [4-21], respectively (P < 0·001). Comparing the performance of the T cell score on OS to that of each of the previously developed models, it emerged that the new score had the best discriminant power. The new T cell score, based on clinical variables, identifies a group with very unfavourable outcomes. © 2018 The Authors British Journal of Haematology published by British Society for Haematology and John Wiley & Sons Ltd.

  19. The prognostic value of FET PET at radiotherapy planning in newly diagnosed glioblastoma

    Energy Technology Data Exchange (ETDEWEB)

    Hoejklint Poulsen, Sidsel [The Finsen Center, Rigshospitalet, Department of Radiation Biology, Copenhagen (Denmark); Center of Diagnostic Investigation, Rigshospitalet, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen (Denmark); Urup, Thomas; Grunnet, Kirsten; Skovgaard Poulsen, Hans [The Finsen Center, Rigshospitalet, Department of Radiation Biology, Copenhagen (Denmark); The Finsen Center, Rigshospitalet, Department of Oncology, Copenhagen (Denmark); Jarle Christensen, Ib [University of Copenhagen, Hvidovre Hospital, Laboratory of Gastroenterology, Copenhagen (Denmark); Larsen, Vibeke Andree [Center of Diagnostic Investigation, Rigshospitalet, Department of Radiology, Copenhagen (Denmark); Lundemann Jensen, Michael; Munck af Rosenschoeld, Per [The Finsen Center, Rigshospitalet, Department of Oncology, Copenhagen (Denmark); The Finsen Center, Rigshospitalet, Section of Radiotherapy, Copenhagen (Denmark); Law, Ian [Center of Diagnostic Investigation, Rigshospitalet, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen (Denmark)

    2017-03-15

    Glioblastoma patients show a great variability in progression free survival (PFS) and overall survival (OS). To gain additional pretherapeutic information, we explored the potential of O-(2-{sup 18}F-fluoroethyl)-L-tyrosine (FET) PET as an independent prognostic biomarker. We retrospectively analyzed 146 consecutively treated, newly diagnosed glioblastoma patients. All patients were treated with temozolomide and radiation therapy (RT). CT/MR and FET PET scans were obtained postoperatively for RT planning. We used Cox proportional hazards models with OS and PFS as endpoints, to test the prognostic value of FET PET biological tumor volume (BTV). Median follow-up time was 14 months, and median OS and PFS were 16.5 and 6.5 months, respectively. In the multivariate analysis, increasing BTV (HR = 1.17, P < 0.001), poor performance status (HR = 2.35, P < 0.001), O(6)-methylguanine-DNA methyltransferase protein status (HR = 1.61, P = 0.024) and higher age (HR = 1.32, P = 0.013) were independent prognostic factors of poor OS. For poor PFS, only increasing BTV (HR = 1.18; P = 0.002) was prognostic. A prognostic index for OS was created based on the identified prognostic factors. Large BTV on FET PET is an independent prognostic factor of poor OS and PFS in glioblastoma patients. With the introduction of FET PET, we obtain a prognostic index that can help in glioblastoma treatment planning. (orig.)

  20. A framework for quantifying net benefits of alternative prognostic models‡

    Science.gov (United States)

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21905066

  1. Performance and evaluation of a coupled prognostic model TAPM over a mountainous complex terrain industrial area

    Science.gov (United States)

    Matthaios, Vasileios N.; Triantafyllou, Athanasios G.; Albanis, Triantafyllos A.; Sakkas, Vasileios; Garas, Stelios

    2018-05-01

    Atmospheric modeling is considered an important tool with several applications such as prediction of air pollution levels, air quality management, and environmental impact assessment studies. Therefore, evaluation studies must be continuously made, in order to improve the accuracy and the approaches of the air quality models. In the present work, an attempt is made to examine the air pollution model (TAPM) efficiency in simulating the surface meteorology, as well as the SO2 concentrations in a mountainous complex terrain industrial area. Three configurations under different circumstances, firstly with default datasets, secondly with data assimilation, and thirdly with updated land use, ran in order to investigate the surface meteorology for a 3-year period (2009-2011) and one configuration applied to predict SO2 concentration levels for the year of 2011.The modeled hourly averaged meteorological and SO2 concentration values were statistically compared with those from five monitoring stations across the domain to evaluate the model's performance. Statistical measures showed that the surface temperature and relative humidity are predicted well in all three simulations, with index of agreement (IOA) higher than 0.94 and 0.70 correspondingly, in all monitoring sites, while an overprediction of extreme low temperature values is noted, with mountain altitudes to have an important role. However, the results also showed that the model's performance is related to the configuration regarding the wind. TAPM default dataset predicted better the wind variables in the center of the simulation than in the boundaries, while improvement in the boundary horizontal winds implied the performance of TAPM with updated land use. TAPM assimilation predicted the wind variables fairly good in the whole domain with IOA higher than 0.83 for the wind speed and higher than 0.85 for the horizontal wind components. Finally, the SO2 concentrations were assessed by the model with IOA varied from 0

  2. Implicit coupling of turbulent diffusion with chemical reaction mechanisms for prognostic atmospheric dispersion models

    Energy Technology Data Exchange (ETDEWEB)

    Berlowitz, D.R.

    1996-11-01

    In the last few decades the negative impact by humans on the thin atmospheric layer enveloping the earth, the basis for life on this planet, has increased steadily. In order to halt, or at least slow down this development, the knowledge and study of these anthropogenic influence has to be increased and possible remedies have to be suggested. An important tool for these studies are computer models. With their help the atmospheric system can be approximated and the various processes, which have led to the current situation can be quantified. They also serve as an instrument to assess short or medium term strategies to reduce this human impact. However, to assure efficiency as well as accuracy, a careful analysis of the numerous processes involved in the dispersion of pollutants in the atmosphere is called for. This should help to concentrate on the essentials and also prevent excessive usage of sometimes scarce computing resources. The basis of the presented work is the EUMAC Zooming Model (ETM), and particularly the component calculating the dispersion of pollutants in the atmosphere, the model MARS. The model has two main parts: an explicit solver, where the advection and the horizontal diffusion of pollutants are calculated, and an implicit solution mechanism, allowing the joint computation of the change of concentration due to chemical reactions, coupled with the respective influence of the vertical diffusion of the species. The aim of this thesis is to determine particularly the influence of the horizontal components of the turbulent diffusion on the existing implicit solver of the model. Suggestions for a more comprehensive inclusion of the full three dimensional diffusion operator in the implicit solver are made. This is achieved by an appropriate operator splitting. A selection of numerical approaches to tighten the coupling of the diffusion processes with the calculation of the applied chemical reaction mechanisms are examined. (author) figs., tabs., refs.

  3. Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication

    Directory of Open Access Journals (Sweden)

    Kilpinen Sami

    2010-05-01

    Full Text Available Abstract Background Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s. Results In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42% neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis and to those with no MYCN amplification or 12q24.31 gain (good prognosis (P = 0.001. Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC

  4. A Novel Inflammation-Based Prognostic Score: The Fibrinogen/Albumin Ratio Predicts Prognoses of Patients after Curative Resection for Hepatocellular Carcinoma

    Directory of Open Access Journals (Sweden)

    Qiaodong Xu

    2018-01-01

    Full Text Available Background. Inflammation is an important hallmark of cancer. Fibrinogen and albumin are both vital factors in systemic inflammation. This study investigated the prognostic value of the fibrinogen/albumin ratio in HCC patients who underwent curative resection. Methods. HCC patients (n=151 who underwent curative resection were evaluated retrospectively. The optimal cutoff value for the fibrinogen/albumin ratio was selected by receiver operating characteristic (ROC curve analysis. Correlations between preoperative fibrinogen/albumin ratios and clinicopathologic characteristics were analyzed by χ2 test. The area under the receiver operating characteristic curve (AUC was calculated to compare the prognostic value of the fibrinogen/albumin ratio with other prognostic scores (neutrophil to lymphocyte ratio (NLR, platelet to lymphocyte ratio (PLR, and albumin-bilirubin (ALBI score. The overall survival (OS and time to recurrence (TTR were assessed by the log-rank test and the Cox proportional hazard regression model. Results. An optimal cutoff value of the preoperative fibrinogen/albumin ratio (0.062 was determined for 151 patients who underwent curative resection for HCC via a ROC curve analysis. Fibrinogen/albumin ratio > 0.062 was significantly associated with microvascular invasion, an advanced BCLC stage, and ALBI grade. Multivariate analyses revealed that fibrinogen/albumin ratio was an independent predictor for OS (P=0.003 and TTR (P=0.035. The prognostic ability of fibrinogen/albumin ratio was comparable to other prognostic scores (NLR, PLR, and ALBI score by AUC analysis. Patients with a fibrinogen/albumin ratio > 0.062 had lower 1-, 3-, and 5-year OS rates (66.0%, 41.8%, and 28.2% versus 81.9%, 69.3%, and 56.1%, resp., P<0.001 and higher 1-, 3-, and 5-year recurrence rates (60.9%, 79.2%, and 90.5% versus 49.5%, 69.1%, and 77.1%, resp., P=0.008 compared with patients with fibrinogen/albumin ratio ≤ 0.062. Conclusion. The

  5. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Sarfraz, M.

    2004-01-01

    Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

  6. Prognostic Value of Electrocardiographic Left Ventricular Hypertrophy on Cardiovascular Risk in a Non-hypertensive Community-based Population.

    Science.gov (United States)

    Tanaka, Kentaro; Tanaka, Fumitaka; Onoda, Toshiyuki; Tanno, Kozo; Ohsawa, Masaki; Sakata, Kiyomi; Omama, Shinichi; Ogasawara, Kuniaki; Ishibashi, Yasuhiro; Itai, Kazuyoshi; Kuribayashi, Toru; Okayama, Akira; Nakamura, Motoyuki

    2018-04-06

    The appearance of left ventricular hypertrophy on 12-lead electrocardiography (ECG-LVH) has been clarified to be associated with the risk of incidence of cardiovascular events (CVEs) in hypertensive individuals and the general population, but not enough in non-hypertensive individuals. A total of 4,927 non-hypertensive individuals ≥ 40 years of age who were free of CVE in the general population were followed for the incidence of CVE. ECG-LVH was defined according to criteria of the Sokolow-Lyon (SL) voltage, Cornell voltage (CV), or Cornell voltage product (CP). During the average 9.8 ± 2.0 years of follow-up, 267 individuals (5.4%) had their first CVE. The hazard ratio (HR) for the incidence of CVE after full adjustment by potential confounders significantly increased in the individuals with ECG-LVH by any criteria of the SL voltage, CV, and CP (HR = 1.77, p < 0.001) compared to those with no ECG-LVH. This association was significant also in individuals without any of obesity, dyslipidemia, and diabetes mellitus or those with systolic BP <120 mmHg and diastolic BP < 80mmHg. Furthermore, ECG-LVH by each criteria provided the reclassification improvement for the CVE risk prediction model by the Framingham 10-year risk score (the net reclassification improvement = 0.17 to 0.22, each p value < 0.010). In the absence of hypertension, ECG-LVH parameters are associated with the increased risk of developed CVEs independent of the established risk factors and provide the additional prognostic value in an assessment of the CVE risk using the traditional risk factors.

  7. GC-MS based Gestational Diabetes Mellitus longitudinal study: Identification of 2-and 3-hydroxybutyrate as potential prognostic biomarkers.

    Science.gov (United States)

    Dudzik, Danuta; Zorawski, Marcin; Skotnicki, Mariusz; Zarzycki, Wieslaw; García, Antonia; Angulo, Santiago; Lorenzo, M Paz; Barbas, Coral; Ramos, M Pilar

    2017-09-10

    Gestational Diabetes Mellitus (GDM) causes severe short- and long-term complications for the mother, fetus and neonate, including type 2-diabetes (T2DM) later in life. In this pilot study, GC-Q/MS analysis was applied for plasma metabolomics fingerprinting of 24 healthy and 24 women with GDM at different stages of gestation (second and third trimester) and postpartum (one and three months). Multivariate (unsupervised and supervised) statistical analysis was performed to investigate variance in the data, identify outliers and for unbiased assessment of data quality. Plasma fingerprints allowed for the discrimination of GDM pregnant women from controls both in the 2nd and 3rd trimesters of gestation. However, metabolic profiles tended to be similar after delivery. Follow up of these women revealed that 4 of them developed T2DM within 2 years postpartum. Multivariate PLS-DA models limited to women with GDM showed clear separation 3 months postpartum. In the 2nd trimester of gestation there was also a clear separation between GDM women that were normoglycemic after pregnancy and those with recognized postpartum T2DM. Metabolites that had the strongest discriminative power between these groups in the 2nd trimester of gestation were 2-hydroxybutyrate, 3-hydroxybutyrate, and stearic acid. We have described, that early GDM comprises metabotypes that are associated with the risk of future complications, including postpartum T2DM. In this pilot study, we provide evidence that 2-hydroxybutyrate and 3-hydroxybutyrate may be considered as future prognostic biomarkers to predict the onset of diabetic complications in women with gestational diabetes after delivery. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Few promising multivariable prognostic models exist for recovery of people with non-specific neck pain in musculoskeletal primary care: a systematic review.

    Science.gov (United States)

    Wingbermühle, Roel W; van Trijffel, Emiel; Nelissen, Paul M; Koes, Bart; Verhagen, Arianne P

    2018-01-01

    Which multivariable prognostic model(s) for recovery in people with neck pain can be used in primary care? Systematic review of studies evaluating multivariable prognostic models. People with non-specific neck pain presenting at primary care. Baseline characteristics of the participants. Recovery measured as pain reduction, reduced disability, or perceived recovery at short-term and long-term follow-up. Fifty-three publications were included, of which 46 were derivation studies, four were validation studies, and three concerned combined studies. The derivation studies presented 99 multivariate models, all of which were at high risk of bias. Three externally validated models generated usable models in low risk of bias studies. One predicted recovery in non-specific neck pain, while two concerned participants with whiplash-associated disorders (WAD). Discriminative ability of the non-specific neck pain model was area under the curve (AUC) 0.65 (95% CI 0.59 to 0.71). For the first WAD model, discriminative ability was AUC 0.85 (95% CI 0.79 to 0.91). For the second WAD model, specificity was 99% (95% CI 93 to 100) and sensitivity was 44% (95% CI 23 to 65) for prediction of non-recovery, and 86% (95% CI 73 to 94) and 55% (95% CI 41 to 69) for prediction of recovery, respectively. Initial Neck Disability Index scores and age were identified as consistent prognostic factors in these three models. Three externally validated models were found to be usable and to have low risk of bias, of which two showed acceptable discriminative properties for predicting recovery in people with neck pain. These three models need further validation and evaluation of their clinical impact before their broad clinical use can be advocated. PROSPERO CRD42016042204. [Wingbermühle RW, van Trijffel E, Nelissen PM, Koes B, Verhagen AP (2018) Few promising multivariable prognostic models exist for recovery of people with non-specific neck pain in musculoskeletal primary care: a systematic review

  9. Unavailability of thymidine kinase does not preclude the use of German comprehensive prognostic index: results of an external validation analysis in early chronic lymphocytic leukemia and comparison with MD Anderson Cancer Center model.

    Science.gov (United States)

    Molica, Stefano; Giannarelli, Diana; Mirabelli, Rosanna; Levato, Luciano; Russo, Antonio; Linardi, Maria; Gentile, Massimo; Morabito, Fortunato

    2016-01-01

    A comprehensive prognostic index that includes clinical (i.e., age, sex, ECOG performance status), serum (i.e., ß2-microglobulin, thymidine kinase [TK]), and molecular (i.e., IGVH mutational status, del 17p, del 11q) markers developed by the German CLL Study Group (GCLLSG) was externally validated in a prospective, community-based cohort consisting of 338 patients with early chronic lymphocytic leukemia (CLL) using as endpoint the time to first treatment (TTFT). Because serum TK was not available, a slightly modified version of the model based on seven instead of eight prognostic variables was used. By German index, 62.9% of patients were scored as having low-risk CLL (score 0-2), whereas 37.1% had intermediate-risk CLL (score 3-5). This stratification translated into a significant difference in the TTFT [HR = 4.21; 95% C.I. (2.71-6.53); P reliability [HR = 2.73; 95% C.I. (1.79-4.17); P German score. The c-statistic of the MDACC model was 0.65 (range, 0.53-0.78) a level below that of the German index [0.71 (range, 0.60-0.82)] and below the accepted 0.7 threshold necessary to have value at the individual patient level. Results of this external comparative validation analysis strongly support the German score as the benchmark for comparison of any novel prognostic scheme aimed at evaluating the TTFT in patients with early CLL even when a modified version which does not include TK is utilized. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  10. Distributed Prognostics System Implementation on Wireless Embedded Devices

    Data.gov (United States)

    National Aeronautics and Space Administration — Distributed prognostics is the next step in the evolution of prognostic methodologies. It is an important enabling technology for the emerging Condition Based...

  11. Development and validation of a prognostic model to predict death in patients with traumatic bleeding, and evaluation of the effect of tranexamic acid on mortality according to baseline risk: a secondary analysis of a randomised controlled trial.

    Science.gov (United States)

    Perel, P; Prieto-Merino, D; Shakur, H; Roberts, I

    2013-06-01

    prognostic models we included predictors for death in hospital within 4 weeks of injury. For the stratified analysis we reported ORs for all causes of death, death due to bleeding, and fatal and non-fatal thrombotic events associated with the use of TXA according to baseline risk. A total of 3076 (15%) patients died in the CRASH-2 trial and 1705 (12%) in the TARN data set. Glasgow Coma Scale score, age and systolic blood pressure were the strongest predictors of mortality. Discrimination and calibration were satisfactory, with C-statistics > 0.80 in both CRASH-2 trial and TARN data sets. A simple chart was constructed to readily provide the probability of death at the point of care, while a web-based calculator is available for a more detailed risk assessment. TXA reduced all-cause mortality and death due to bleeding in each stratum of baseline risk. There was no evidence of heterogeneity in the effect of TXA on all-cause mortality (p-value for interaction = 0.96) or death due to bleeding (p= 0.98). There was a significant reduction in the odds of fatal and non-fatal thrombotic events with TXA (OR = 0.69, 95% confidence interval 0.53 to 0.89; p= 0.005). There was no evidence of heterogeneity in the effect of TXA on the risk of thrombotic events (p= 0.74). This prognostic model can be used to obtain valid predictions of mortality in patients with traumatic bleeding. TXA can be administered safely to a wide spectrum of bleeding trauma patients and should not be restricted to the most severely injured. Future research should evaluate whether or not the use of this prognostic model in clinical practice has an impact on the management and outcomes of trauma patients.

  12. Identification and prognostic value of anterior gradient protein 2 expression in breast cancer based on tissue microarray.

    Science.gov (United States)

    Guo, Jilong; Gong, Guohua; Zhang, Bin

    2017-07-01

    Breast cancer has attracted substantial attention as one of the major cancers causing death in women. It is crucial to find potential biomarkers of prognostic value in breast cancer. In this study, the expression pattern of anterior gradient protein 2 in breast cancer was identified based on the main molecular subgroups. Through analysis of 69 samples from the Gene Expression Omnibus database, we found that anterior gradient protein 2 expression was significantly higher in non-triple-negative breast cancer tissues compared with normal tissues and triple-negative breast cancer tissues (p gradient protein 2 expression pattern. Furthermore, we performed immunohistochemical analysis. The quantification results revealed that anterior gradient protein 2 is highly expressed in non-triple-negative breast cancer (grade 3 excluded) and grade 1 + 2 (triple-negative breast cancer excluded) tumours compared with normal tissues. Anterior gradient protein 2 was significantly highly expressed in non-triple-negative breast cancer (grade 3 excluded) and non-triple-negative breast cancer tissues compared with triple-negative breast cancer tissues (p gradient protein 2 was significantly highly expressed in grade 1 + 2 (triple-negative breast cancer excluded) and grade 1 + 2 tissues compared with grade 3 tissues (p gradient protein 2 expression was significantly associated with histologic type, histological grade, oestrogen status and progesterone status. Univariate analysis of clinicopathological variables showed that anterior gradient protein 2 expression, tumour size and lymph node status were significantly correlated with overall survival in patients with grade 1 and 2 tumours. Cox multivariate analysis revealed anterior gradient protein 2 as a putative independent indicator of unfavourable outcomes (p = 0.031). All these data clearly showed that anterior gradient protein 2 is highly expressed in breast cancer and can be regarded as a putative biomarker for

  13. The association between mammographic calcifications and breast cancer prognostic factors in a population-based registry cohort.

    Science.gov (United States)

    Nyante, Sarah J; Lee, Sheila S; Benefield, Thad S; Hoots, Tiffany N; Henderson, Louise M

    2017-01-01

    Mammographic calcifications can be a marker of malignancy, but their association with prognosis is less well established. In the current study, the authors examined the relationship between calcifications and breast cancer prognostic factors in the population-based Carolina Mammography Registry. The current study included 8472 invasive breast cancers diagnosed in the Carolina Mammography Registry between 1996 and 2011 for which information regarding calcifications occurring within 2 years of diagnosis was reported. Calcification-specific Breast Imaging Reporting and Data System (BI-RADS) assessments were reported prospectively by a radiologist. Tumor characteristic data were obtained from the North Carolina Central Cancer Registry and/or pathology reports. Multivariable-adjusted associations between the presence of calcifications in the breast affected by cancer and tumor characteristics were estimated using logistic regression. Statistical tests were 2-sided. The presence of calcifications was found to be positively associated with tumors that were high grade (vs low grade: odds ratio [OR], 1.43; 95% confidence interval [95% CI], 1.10-1.88) or had an in situ component (vs without: OR, 2.15; 95% CI, 1.81-2.55). Calcifications were found to be inversely associated with hormone receptor-negative status (vs positive status: OR, 0.73; 95% CI, 0.57-0.93), size >35 mm (vs ≤8 mm: OR, 0.47; 95% CI, 0.37-0.61), and lobular tumors (vs ductal: OR, 0.39; 95% CI, 0.22-0.69). The association between the presence of calcifications and an in situ component was limited to BI-RADS category 4 and 5 calcifications and was absent for BI-RADS category 2 or 3 calcifications (P for heterogeneity Cancer 2017;123:219-227. © 2016 American Cancer Society. © 2016 American Cancer Society.

  14. Prognostic classification with laboratory parameters or imaging techniques in small-cell lung cancer

    NARCIS (Netherlands)

    de Jong, Wouter K.; Fidler, Vaclav; Groen, Harry J. M.

    PURPOSE: Our aim in this study was to compare prognostic models based on laboratory tests with a model including imaging information in small-cell lung cancer. PATIENTS AND METHODS: A retrospective analysis was performed on 156 consecutive patients. Three existing models based on laboratory tests

  15. Surface Prognostic Charts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Surface Prognostic Charts are historical surface prognostic (forecast) charts created by the United States Weather Bureau. They include fronts, isobars, cloud, and...

  16. Prognostic Impact of Array-based Genomic Profiles in Esophageal Squamous Cell Cancer

    International Nuclear Information System (INIS)

    Carneiro, Ana; Isinger, Anna; Karlsson, Anna; Johansson, Jan; Jönsson, Göran; Bendahl, Pär-Ola; Falkenback, Dan; Halvarsson, Britta; Nilbert, Mef

    2008-01-01

    Esophageal squamous cell carcinoma (ESCC) is a genetically complex tumor type and a major cause of cancer related mortality. Although distinct genetic alterations have been linked to ESCC development and prognosis, the genetic alterations have not gained clinical applicability. We applied array-based comparative genomic hybridization (aCGH) to obtain a whole genome copy number profile relevant for identifying deranged pathways and clinically applicable markers. A 32 k aCGH platform was used for high resolution mapping of copy number changes in 30 stage I-IV ESCC. Potential interdependent alterations and deranged pathways were identified and copy number changes were correlated to stage, differentiation and survival. Copy number alterations affected median 19% of the genome and included recurrent gains of chromosome regions 5p, 7p, 7q, 8q, 10q, 11q, 12p, 14q, 16p, 17p, 19p, 19q, and 20q and losses of 3p, 5q, 8p, 9p and 11q. High-level amplifications were observed in 30 regions and recurrently involved 7p11 (EGFR), 11q13 (MYEOV, CCND1, FGF4, FGF3, PPFIA, FAD, TMEM16A, CTTS and SHANK2) and 11q22 (PDFG). Gain of 7p22.3 predicted nodal metastases and gains of 1p36.32 and 19p13.3 independently predicted poor survival in multivariate analysis. aCGH profiling verified genetic complexity in ESCC and herein identified imbalances of multiple central tumorigenic pathways. Distinct gains correlate with clinicopathological variables and independently predict survival, suggesting clinical applicability of genomic profiling in ESCC

  17. Real-Time Prognostics of a Rotary Valve Actuator

    Science.gov (United States)

    Daigle, Matthew

    2015-01-01

    Valves are used in many domains and often have system-critical functions. As such, it is important to monitor the health of valves and their actuators and predict remaining useful life. In this work, we develop a model-based prognostics approach for a rotary valve actuator. Due to limited observability of the component with multiple failure modes, a lumped damage approach is proposed for estimation and prediction of damage progression. In order to support the goal of real-time prognostics, an approach to prediction is developed that does not require online simulation to compute remaining life, rather, a function mapping the damage state to remaining useful life is found offline so that predictions can be made quickly online with a single function evaluation. Simulation results demonstrate the overall methodology, validating the lumped damage approach and demonstrating real-time prognostics.

  18. Prognostic impact of nomogram based on whole tumour size, tumour disappearance ratio on CT and SUVmax on PET in lung adenocarcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Song, So Hee; Lee, Ho Yun; Kim, Eun Young; Lee, Kyung Soo [Sungkyunkwan University School of Medicine, Department of Radiology and Center for Imaging Science, Samsung Medical Center, Gangnam-Gu, Seoul (Korea, Republic of); Ahn, Joong Hyun [Samsung Biomedical Research Institute, Biostatistics Team, Seoul (Korea, Republic of); Lee, Geewon [Pusan National University Hospital, Pusan National University School of Medicine, Department of Radiology and Medical Research Institute, Busan (Korea, Republic of); Choi, Joon Young [Sungkyunkwan University School of Medicine, Departments of Nuclear Medicine, Samsung Medical Center, Seoul (Korea, Republic of); Kang, Jun [Catholic University of Korea, Department of Pathology, Inchun St. Mary' s Hospital, College of Medicine, Inchun (Korea, Republic of); Han, Joungho [Sungkyunkwan University School of Medicine, Department of Pathology, Samsung Medical Center, Seoul (Korea, Republic of); Kwon, O.J. [Sungkyunkwan University School of Medicine, Division of Respiratory and Critical Medicine of the Department of Internal Medicine, Samsung Medical Center, Seoul (Korea, Republic of); Kim, Hong Kwan; Choi, Yong Soo; Kim, Jhingook; Shim, Young Mog [Sungkyunkwan University School of Medicine, Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Seoul (Korea, Republic of)

    2016-06-15

    Lung adenocarcinoma frequently manifests as subsolid nodules, and the solid portion and ground-glass-opacity (GGO) portion on CT have different prognostic significance. Therefore, current T descriptor, defined as the whole tumour diameter without discrimination between solid and GGO, is insufficient. We aimed to determine the prognostic significance of solid tumour size and attempt to include prognostic factors such as tumour disappearance rate (TDR) on CT and SUVmax on PET/CT. Five hundred and ninety-five patients with completely resected lung adenocarcinoma were analyzed. We developed a nomogram using whole tumour size, TDR, and SUVmax. External validation was performed in another 102 patients. In patients with tumours measuring ≤2 cm and >2 to 3 cm, disease free survival (DFS) was significantly associated with solid tumour size (P < 0.001), but not with whole tumour size (P = 0.052). Developed nomogram was significantly superior to the conventional T stage (area under the curve of survival ROC; P = 0.013 by net reclassification improvement) in stratification of patient survival. In the external validation group, significant difference was noted in DFS according to proposed T stage (P = 0.009). Nomogram-based T descriptors provide better prediction of survival and assessment of individual risks than conventional T descriptors. (orig.)

  19. Utility of Inflammatory Marker- and Nutritional Status-based Prognostic Factors for Predicting the Prognosis of Stage IV Gastric Cancer Patients Undergoing Non-curative Surgery.

    Science.gov (United States)

    Mimatsu, Kenji; Fukino, Nobutada; Ogasawara, Yasuo; Saino, Yoko; Oida, Takatsugu

    2017-08-01

    The present study aimed to compare the utility of various inflammatory marker- and nutritional status-based prognostic factors, including many previous established prognostic factors, for predicting the prognosis of stage IV gastric cancer patients undergoing non-curative surgery. A total of 33 patients with stage IV gastric cancer who had undergone palliative gastrectomy and gastrojejunostomy were included in the study. Univariate and multivariate analyses were performed to evaluate the relationships between the mGPS, PNI, NLR, PLR, the CONUT, various clinicopathological factors and cancer-specific survival (CS). Among patients who received non-curative surgery, univariate analysis of CS identified the following significant risk factors: chemotherapy, mGPS and NLR, and multivariate analysis revealed that the mGPS was independently associated with CS. The mGPS was a more useful prognostic factor than the PNI, NLR, PLR and CONUT in patients undergoing non-curative surgery for stage IV gastric cancer. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  20. Prognostic factors and scoring system for survival in colonic perforation.

    Science.gov (United States)

    Komatsu, Shuhei; Shimomatsuya, Takumi; Nakajima, Masayuki; Amaya, Hirokazu; Kobuchi, Taketsune; Shiraishi, Susumu; Konishi, Sayuri; Ono, Susumu; Maruhashi, Kazuhiro

    2005-01-01

    No ideal and generally accepted prognostic factors and scoring systems exist to determine the prognosis of peritonitis associated with colonic perforation. This study was designed to investigate prognostic factors and evaluate the various scoring systems to allow identification of high-risk patients. Between 1996 and 2003, excluding iatrogenic and trauma cases, 26 consecutive patients underwent emergency operations for colorectal perforation and were selected for this retrospective study. Several clinical factors were analyzed as possible predictive factors, and APACHE II, SOFA, MPI, and MOF scores were calculated. The overall mortality was 26.9%. Compared with the survivors, non-survivors were found more frequently in Hinchey's stage III-IV, a low preoperative marker of pH, base excess (BE), and a low postoperative marker of white blood cell count, PaO2/FiO2 ratio, and renal output (24h). According to the logistic regression model, BE was a significant independent variable. Concerning the prognostic scoring systems, an APACHE II score of 19, a SOFA score of 8, an MPI score of 30, and an MOF score of 7 or more were significantly related to poor prognosis. Preoperative BE and postoperative white blood cell count were reliable prognostic factors and early classification using prognostic scoring systems at specific points in the disease process are useful to improve our understanding of the problems involved.

  1. Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

    Science.gov (United States)

    Avissar, Roni; Chen, Fei

    1993-01-01

    Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes

  2. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

  3. SYNTAX score based on coronary computed tomography angiography may have a prognostic value in patients with complex coronary artery disease: An observational study from a retrospective cohort.

    Science.gov (United States)

    Suh, Young Joo; Han, Kyunghwa; Chang, Suyon; Kim, Jin Young; Im, Dong Jin; Hong, Yoo Jin; Lee, Hye-Jeong; Hur, Jin; Kim, Young Jin; Choi, Byoung Wook

    2017-09-01

    The SYNergy between percutaneous coronary intervention with TAXus and cardiac surgery (SYNTAX) score is an invasive coronary angiography (ICA)-based score for quantifying the complexity of coronary artery disease (CAD). Although the SYNTAX score was originally developed based on ICA, recent publications have reported that coronary computed tomography angiography (CCTA) is a feasible modality for the estimation of the SYNTAX score.The aim of our study was to investigate the prognostic value of the SYNTAX score, based on CCTA for the prediction of major adverse cardiac and cerebrovascular events (MACCEs) in patients with complex CAD.The current study was approved by the institutional review board of our institution, and informed consent was waived for this retrospective cohort study. We included 251 patients (173 men, mean age 66.0 ± 9.29 years) who had complex CAD [3-vessel disease or left main (LM) disease] on CCTA. SYNTAX score was obtained on the basis of CCTA. Follow-up clinical outcome data regarding composite MACCEs were also obtained. Cox proportional hazards models were developed to predict the risk of MACCEs based on clinical variables, treatment, and computed tomography (CT)-SYNTAX scores.During the median follow-up period of 1517 days, there were 48 MACCEs. Univariate Cox hazards models demonstrated that MACCEs were associated with advanced age, low body mass index (BMI), and dyslipidemia (P < .2). In patients with LM disease, MACCEs were associated with a higher SYNTAX score. In patients with CT-SYNTAX score ≥23, patients who underwent coronary artery bypass graft surgery (CABG) and percutaneous coronary intervention had significantly lower hazard ratios than patients who were treated with medication alone. In multivariate Cox hazards model, advanced age, low BMI, and higher SYNTAX score showed an increased hazard ratio for MACCE, while treatment with CABG showed a lower hazard ratio (P < .2).On the basis of our results, CT-SYNTAX score

  4. Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325).

    Science.gov (United States)

    Dehing-Oberije, Cary; Aerts, Hugo; Yu, Shipeng; De Ruysscher, Dirk; Menheere, Paul; Hilvo, Mika; van der Weide, Hiska; Rao, Bharat; Lambin, Philippe

    2011-10-01

    Currently, prediction of survival for non-small-cell lung cancer patients treated with (chemo)radiotherapy is mainly based on clinical factors. The hypothesis of this prospective study was that blood biomarkers related to hypoxia, inflammation, and tumor load would have an added prognostic value for predicting survival. Clinical data and blood samples were collected prospectively (NCT00181519, NCT00573040, and NCT00572325) from 106 inoperable non-small-cell lung cancer patients (Stages I-IIIB), treated with curative intent with radiotherapy alone or combined with chemotherapy. Blood biomarkers, including lactate dehydrogenase, C-reactive protein, osteopontin, carbonic anhydrase IX, interleukin (IL) 6, IL-8, carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1, were measured. A multivariate model, built on a large patient population (N = 322) and externally validated, was used as a baseline model. An extended model was created by selecting additional biomarkers. The model's performance was expressed as the area under the curve (AUC) of the receiver operating characteristic and assessed by use of leave-one-out cross validation as well as a validation cohort (n = 52). The baseline model consisted of gender, World Health Organization performance status, forced expiratory volume, number of positive lymph node stations, and gross tumor volume and yielded an AUC of 0.72. The extended model included two additional blood biomarkers (CEA and IL-6) and resulted in a leave-one-out AUC of 0.81. The performance of the extended model was significantly better than the clinical model (p = 0.004). The AUC on the validation cohort was 0.66 and 0.76, respectively. The performance of the prognostic model for survival improved markedly by adding two blood biomarkers: CEA and IL-6. Copyright © 2011 Elsevier Inc. All rights reserved.

  5. Accelerated Aging in Electrolytic Capacitors for Prognostics

    Science.gov (United States)

    Celaya, Jose R.; Kulkarni, Chetan; Saha, Sankalita; Biswas, Gautam; Goebel, Kai Frank

    2012-01-01

    The focus of this work is the analysis of different degradation phenomena based on thermal overstress and electrical overstress accelerated aging systems and the use of accelerated aging techniques for prognostics algorithm development. Results on thermal overstress and electrical overstress experiments are presented. In addition, preliminary results toward the development of physics-based degradation models are presented focusing on the electrolyte evaporation failure mechanism. An empirical degradation model based on percentage capacitance loss under electrical overstress is presented and used in: (i) a Bayesian-based implementation of model-based prognostics using a discrete Kalman filter for health state estimation, and (ii) a dynamic system representation of the degradation model for forecasting and remaining useful life (RUL) estimation. A leave-one-out validation methodology is used to assess the validity of the methodology under the small sample size constrain. The results observed on the RUL estimation are consistent through the validation tests comparing relative accuracy and prediction error. It has been observed that the inaccuracy of the model to represent the change in degradation behavior observed at the end of the test data is consistent throughout the validation tests, indicating the need of a more detailed degradation model or the use of an algorithm that could estimate model parameters on-line. Based on the observed degradation process under different stress intensity with rest periods, the need for more sophisticated degradation models is further supported. The current degradation model does not represent the capacitance recovery over rest periods following an accelerated aging stress period.

  6. MRI-detected skull-base invasion. Prognostic value and therapeutic implication in intensity-modulated radiotherapy treatment for nasopharyngeal carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Yi-Kan; Jiang, Ning; Yue, Dan; Tang, Ling-Long; Zhang, Fan; Lin, Li; Liu, Xu; Chen, Lei; Ma, Jun [Sun Yat-sen University Cancer Center, Department of Radiation Oncology, Guangzhou (China); Liu, Li-Zhi [Sun Yat-sen University Cancer Center, Department of Radiology, Guangzhou (China)

    2014-10-15

    With advances in imaging and radiotherapy, the prognostic value of skull-base invasion in nasopharyngeal carcinoma (NPC) needs to be reassessed. We aimed to define a classification system and evaluate the prognostic value of the classification of magnetic resonance imaging (MRI)-detected skull-base invasion in NPC treated with intensity-modulated radiotherapy (IMRT). We retrospectively reviewed 749 patients who underwent MRI and were subsequently histologically diagnosed with nondisseminated NPC and treated with IMRT. MRI-detected skull-base invasion was not found to be an independent prognostic factor for overall survival (OS), distant metastasis-free survival (DMFS), local relapse-free survival (LRFS), or disease-free survival (DFS; p > 0.05 for all). Skull-base invasion was classified according to the incidence of each site (type I sites inside pharyngobasilar fascia and clivus vs. type II sites outside pharyngobasilar fascia). The 5-year OS, DMFS, LRFS, and DFS rates in the classification of skull-base invasion in NPC were 83 vs. 67 %, 85 vs.75 %, 95 vs. 88 %, and 76 vs. 62 %, respectively (p < 0.05 for all). Multivariate analysis indicated the classification of skull-base invasion was an independent prognostic factor. MRI-detected skull-base invasion is not an independent prognostic factor in patients with NPC treated with IMRT. However, classification according to the site of invasion has prognostic value. Therefore, patients with various subclassifications of stage T3 disease may receive treatment with different intensities; however, further studies are warranted to prove this. (orig.) [German] Aufgrund der Fortschritte der bildgebenden Verfahren und der Strahlentherapie muss der prognostische Wert der Invasion des nasopharyngealen Karzinoms (NPC) in die Schaedelbasis erneut bewertet werden. Unser Ziel ist die Definition eines Klassifikationssystems und die Untersuchung des prognostischen Werts der Klassifikation der MRT-ermittelten Invasion des mit

  7. Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation

    Science.gov (United States)

    2012-09-01

    interpreting the state vector as the health indicator and a threshold is used on this variable in order to compute EOL (end-of-life) and RUL. Here, we...End-of-life ( EOL ) would match the true spread and would not change from one experiment to another. This is, however, in practice impossible to achieve

  8. Skull base tumor model.

    Science.gov (United States)

    Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

    2010-11-01

    Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

  9. Remaining useful life estimation based on stochastic deterioration models: A comparative study

    International Nuclear Information System (INIS)

    Le Son, Khanh; Fouladirad, Mitra; Barros, Anne; Levrat, Eric; Iung, Benoît

    2013-01-01

    Prognostic of system lifetime is a basic requirement for condition-based maintenance in many application domains where safety, reliability, and availability are considered of first importance. This paper presents a probabilistic method for prognostic applied to the 2008 PHM Conference Challenge data. A stochastic process (Wiener process) combined with a data analysis method (Principal Component Analysis) is proposed to model the deterioration of the components and to estimate the RUL on a case study. The advantages of our probabilistic approach are pointed out and a comparison with existing results on the same data is made

  10. Prognostics Approach for Power MOSFET Under Thermal-Stress

    Science.gov (United States)

    Galvan, Jose Ramon Celaya; Saxena, Abhinav; Kulkarni, Chetan S.; Saha, Sankalita; Goebel, Kai

    2012-01-01

    The prognostic technique for a power MOSFET presented in this paper is based on accelerated aging of MOSFET IRF520Npbf in a TO-220 package. The methodology utilizes thermal and power cycling to accelerate the life of the devices. The major failure mechanism for the stress conditions is dieattachment degradation, typical for discrete devices with leadfree solder die attachment. It has been determined that dieattach degradation results in an increase in ON-state resistance due to its dependence on junction temperature. Increasing resistance, thus, can be used as a precursor of failure for the die-attach failure mechanism under thermal stress. A feature based on normalized ON-resistance is computed from in-situ measurements of the electro-thermal response. An Extended Kalman filter is used as a model-based prognostics techniques based on the Bayesian tracking framework. The proposed prognostics technique reports on preliminary work that serves as a case study on the prediction of remaining life of power MOSFETs and builds upon the work presented in [1]. The algorithm considered in this study had been used as prognostics algorithm in different applications and is regarded as suitable candidate for component level prognostics. This work attempts to further the validation of such algorithm by presenting it with real degradation data including measurements from real sensors, which include all the complications (noise, bias, etc.) that are regularly not captured on simulated degradation data. The algorithm is developed and tested on the accelerated aging test timescale. In real world operation, the timescale of the degradation process and therefore the RUL predictions will be considerable larger. It is hypothesized that even though the timescale will be larger, it remains constant through the degradation process and the algorithm and model would still apply under the slower degradation process. By using accelerated aging data with actual device measurements and real

  11. A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Wen-An Yang

    2016-01-01

    Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

  12. Comparison of an inflammation-based prognostic score (GPS) with performance status (ECOG-ps) in patients receiving palliative chemotherapy for gastroesophageal cancer.

    Science.gov (United States)

    Crumley, Andrew B C; Stuart, Robert C; McKernan, Margaret; McDonald, Alexander C; McMillan, Donald C

    2008-08-01

    The aim of the present study was to compare an inflammation-based prognostic score (Glasgow Prognostic Score, GPS) with performance status (ECOG-ps) in patients receiving platinum-based chemotherapy for palliation of gastroesophageal cancer. Sixty-five patients presenting with gastroesophageal carcinoma to the Royal Infirmary, Glasgow between January 1999 and December 2005 and who received palliative chemotherapy or chemo-radiotherapy were studied. ECOG-ps, C-reactive protein, and albumin were recorded at diagnosis. Patients with both an elevated C-reactive protein (>10 mg/L) and hypoalbuminemia (L) were allocated a GPS of 2. Patients in whom only one of these biochemical abnormalities was present were allocated a GPS of 1 and patients with a normal C-reactive protein and albumin were allocated a score of 0. Toxicity was recorded using the Common Toxicity Criteria. The minimum follow up was 14 months. During the follow-up period, 59 (91%) of the patients died. On univariate and multivariate survival analysis, only the GPS (hazard ratios 1.65, 95% CI 1.10-2.47, P GPS of 0, those patients with a GPS of 1 or 2 required more frequent chemotherapy dose reduction (P GPS, appears to be superior to the subjective assessment of performance status (ECOG-ps) in predicting the response to platinum-based chemotherapy in patients with advanced gastroesophageal cancer.

  13. Idiopathic linear IgA bullous dermatosis: prognostic factors based on a case series of 72 adults.

    Science.gov (United States)

    Gottlieb, J; Ingen-Housz-Oro, S; Alexandre, M; Grootenboer-Mignot, S; Aucouturier, F; Sbidian, E; Tancrede, E; Schneider, P; Regnier, E; Picard-Dahan, C; Begon, E; Pauwels, C; Cury, K; Hüe, S; Bernardeschi, C; Ortonne, N; Caux, F; Wolkenstein, P; Chosidow, O; Prost-Squarcioni, C

    2017-07-01

    Linear IgA bullous dermatosis (LABD) is a clinically and immunologically heterogeneous, subepidermal, autoimmune bullous disease (AIBD), for which the long-term evolution is poorly described. To investigate the clinical and immunological characteristics, follow-up and prognostic factors of adult idiopathic LABD. This retrospective study, conducted in our AIBD referral centre, included adults, diagnosed between 1995 and 2012, with idiopathic LABD, defined as pure or predominant IgA deposits by direct immunofluorescence. Clinical, histological and immunological findings were collected from charts. Standard histology was systematically reviewed, and indirect immunofluorescence (IIF) on salt-split skin (SSS) and immunoblots (IBs) on amniotic membrane extracts using anti-IgA secondary antibodies were performed, when biopsies and sera obtained at diagnosis were available. Prognostic factors for complete remission (CR) were identified using univariate and multivariate analyses. Of the 72 patients included (median age 54 years), 60% had mucous membrane (MM) involvement. IgA IIF on SSS was positive for 21 of 35 patients tested; 15 had epidermal and dermal labellings. Immunoelectron microscopy performed on the biopsies of 31 patients labelled lamina lucida (LL) (26%), lamina densa (23%), anchoring-fibril zone (AFz) (19%) and LL+AFz (23%). Of the 34 IgA IBs, 22 were positive, mostly for LAD-1/LABD97 (44%) and full-length BP180 (33%). The median follow-up was 39 months. Overall, 24 patients (36%) achieved sustained CR, 19 (29%) relapsed and 35% had chronic disease. CR was significantly associated with age > 70 years or no MM involvement. No prognostic immunological factor was identified. Patients with LABD who are < 70 years old and have MM involvement are at risk for chronic evolution. © 2017 British Association of Dermatologists.

  14. Integration of prognostic aerosol-cloud interactions in a chemistry transport model coupled offline to a regional climate model

    Science.gov (United States)

    Thomas, M. A.; Kahnert, M.; Andersson, C.; Kokkola, H.; Hansson, U.; Jones, C.; Langner, J.; Devasthale, A.

    2015-06-01

    To reduce uncertainties and hence to obtain a better estimate of aerosol (direct and indirect) radiative forcing, next generation climate models aim for a tighter coupling between chemistry transport models and regional climate models and a better representation of aerosol-cloud interactions. In this study, this coupling is done by first forcing the Rossby Center regional climate model (RCA4) with ERA-Interim lateral boundaries and sea surface temperature (SST) using the standard cloud droplet number concentration (CDNC) formulation (hereafter, referred to as the "stand-alone RCA4 version" or "CTRL" simulation). In the stand-alone RCA4 version, CDNCs are constants distinguishing only between land and ocean surface. The meteorology from this simulation is then used to drive the chemistry transport model, Multiple-scale Atmospheric Transport and Chemistry (MATCH), which is coupled online with the aerosol dynamics model, Sectional Aerosol module for Large Scale Applications (SALSA). CDNC fields obtained from MATCH-SALSA are then fed back into a new RCA4 simulation. In this new simulation (referred to as "MOD" simulation), all parameters remain the same as in the first run except for the CDNCs provided by MATCH-SALSA. Simulations are carried out with this model setup for the period 2005-2012 over Europe, and the differences in cloud microphysical properties and radiative fluxes as a result of local CDNC changes and possible model responses are analysed. Our study shows substantial improvements in cloud microphysical properties with the input of the MATCH-SALSA derived 3-D CDNCs compared to the stand-alone RCA4 version. This model setup improves the spatial, seasonal and vertical distribution of CDNCs with a higher concentration observed over central Europe during boreal summer (JJA) and over eastern Europe and Russia during winter (DJF). Realistic cloud droplet radii (CD radii) values have been simulated with the maxima reaching 13 μm, whereas in the stand

  15. Prognostic Performance Metrics

    Data.gov (United States)

    National Aeronautics and Space Administration — This chapter presents several performance metrics for offline evaluation of prognostics algorithms. A brief overview of different methods employed for performance...

  16. Prognostic Value of Quantitative Stress Perfusion Cardiac Magnetic Resonance.

    Science.gov (United States)

    Sammut, Eva C; Villa, Adriana D M; Di Giovine, Gabriella; Dancy, Luke; Bosio, Filippo; Gibbs, Thomas; Jeyabraba, Swarna; Schwenke, Susanne; Williams, Steven E; Marber, Michael; Alfakih, Khaled; Ismail, Tevfik F; Razavi, Reza; Chiribiri, Amedeo

    2018-05-01

    This study sought to evaluate the prognostic usefulness of visual and quantitative perfusion cardiac magnetic resonance (CMR) ischemic burden in an unselected group of patients and to assess the validity of consensus-based ischemic burden thresholds extrapolated from nuclear studies. There are limited data on the prognostic value of assessing myocardial ischemic burden by CMR, and there are none using quantitative perfusion analysis. Patients with suspected coronary artery disease referred for adenosine-stress perfusion CMR were included (n = 395; 70% male; age 58 ± 13 years). The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction, aborted sudden death, and revascularization after 90 days. Perfusion scans were assessed visually and with quantitative analysis. Cross-validated Cox regression analysis and net reclassification improvement were used to assess the incremental prognostic value of visual or quantitative perfusion analysis over a baseline clinical model, initially as continuous covariates, then using accepted thresholds of ≥2 segments or ≥10% myocardium. After a median 460 days (interquartile range: 190 to 869 days) follow-up, 52 patients reached the primary endpoint. At 2 years, the addition of ischemic burden was found to increase prognostic value over a baseline model of age, sex, and late gadolinium enhancement (baseline model area under the curve [AUC]: 0.75; visual AUC: 0.84; quantitative AUC: 0.85). Dichotomized quantitative ischemic burden performed better than visual assessment (net reclassification improvement 0.043 vs. 0.003 against baseline model). This study was the first to address the prognostic benefit of quantitative analysis of perfusion CMR and to support the use of consensus-based ischemic burden thresholds by perfusion CMR for prognostic evaluation of patients with suspected coronary artery disease. Quantitative analysis provided incremental prognostic value to visual assessment and

  17. Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

    Energy Technology Data Exchange (ETDEWEB)

    Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

    2012-08-24

    Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

  18. Metrics for Evaluating Performance of Prognostics Techniques

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics is an emerging concept in condition based maintenance (CBM) of critical systems. Along with developing the fundamentals of being able to confidently...

  19. Evaluating Algorithm Performance Metrics Tailored for Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics has taken center stage in Condition Based Maintenance (CBM) where it is desired to estimate Remaining Useful Life (RUL) of a system so that remedial...

  20. Distributed Prognostic Health Management with Gaussian Process Regression

    Science.gov (United States)

    Saha, Sankalita; Saha, Bhaskar; Saxena, Abhinav; Goebel, Kai Frank

    2010-01-01

    Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. A major challenge encountered in such design is formulation of optimal distributed prognostics algorithms. In this paper. we present a distributed GPR based prognostics algorithm whose target platform is a wireless sensor network. In addition to challenges encountered in a distributed implementation, a wireless network poses constraints on communication patterns, thereby making the problem more challenging. The prognostics application that was used to demonstrate our new algorithms is battery prognostics. In order to present trade-offs within different prognostic approaches, we present comparison with the distributed implementation of a particle filter based prognostics for the same battery data.

  1. Prognostic significance of gastrointestinal symptoms and diagnosis in relation to the acute radiation syndrome. A retrospective analysis based on the data base SEARCH

    International Nuclear Information System (INIS)

    Hoebbel, Mathias Niklaus Johannes

    2016-01-01

    The following thesis explores the prognostic significance of gastrointestinal symptoms and diagnoses in relation to acute radiation syndrome. This is a retrospective analysis based on the SEARCH (System of Evaluation and Archiving of Radiation Accidents based on Case Histories) database, which was created by a team of researchers in Ulm in 1998. The SEARCH database compiled health status data of individuals involved in a total of 78 ionized radiation accidents between 1945 and 2003. In the past changes in bloodbuilding systems were considered the defining factor in determining a prognosis regarding survival times. Treatment decisions were made in line with these findings, including stem-cell transplants. In recent history, especially after the nuclear disaster in Chernobyl in 1986, the focus shifted onto other organ systems. As a result it has been proven that significant cutaneous damages present an important influence on survival regardless of haematopoiesis. Several researchers have looked at changes in the gastrointestinal tract and possible correlations with radiation induced multiple organ failure. In this paper, all of the data recorded in SEARCH in regards to gastrointestinal symptoms have been analyzed. These include symptoms such as nausea, vomiting and changes in bowel movement as well as their onset and severity. Radiation-induced oral mucositis was also further investigated. Despite the occasional gaps in data in SEARCH, results from the analysis proved that the occurrence of certain symptoms, their severity and their onset were directly correlated to life expectancy, regardless of the dose estimation, and the pending blood test results. An immediate triage of these patients by skilled medical professionals is imperative to accurate categorization.

  2. Health-related quality of life is a prognostic factor for survival in older patients after colorectal cancer diagnosis: A population-based study.

    Science.gov (United States)

    Fournier, Evelyne; Jooste, Valérie; Woronoff, Anne-Sophie; Quipourt, Valérie; Bouvier, Anne-Marie; Mercier, Mariette

    2016-01-01

    Studies carried out in the context of clinical trials have shown a relationship between survival and health-related quality of life in colorectal cancer patients. We assessed the prognostic value of health-related quality of life at diagnosis and of its longitudinal evolution on survival in older colorectal cancer patients. All patients aged ≥65 years, diagnosed with new colorectal cancer between 2003 and 2005 and registered in the Digestive Cancer Registry of Burgundy were eligible. Patients were asked to complete the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 at inclusion, three, six and twelve months after. Multivariate regression models were used to evaluate the prognostic value of health-related quality of life scores at diagnosis and their deterioration on relative survival. In multivariate analysis, a role functioning dimension lower than median was predictive of lower survival (hazard ratio=3.1, p=0.015). After three and six months of follow-up, patients with greater appetite loss were more likely to die, with hazard ratios of 4.7 (p=0.013) and 3.7 (p=0.002), respectively. Health-related quality of life assessments at diagnosis are independently associated with older colorectal cancer patients' survival. Its preservation should be a major management goal for older cancer patients. Copyright © 2015 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

  3. Early Metabolome Profiling and Prognostic Value in Paraquat-Poisoned Patients: Based on Ultraperformance Liquid Chromatography Coupled To Quadrupole Time-of-Flight Mass Spectrometry.

    Science.gov (United States)

    Hu, Lufeng; Hong, Guangliang; Tang, Yahui; Wang, Xianqin; Wen, Congcong; Lin, Feiyan; Lu, Zhongqiu

    2017-12-18

    Paraquat (PQ) has caused countless deaths throughout the world. There remains no effective treatment for PQ poisoning. Here we study the blood metabolome of PQ-poisoned patients using ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS). Patients were divided into groups according to blood PQ concentration. Healthy subjects served as controls. Metabolic features were statistically analyzed using multivariate pattern-recognition techniques to identify the most important metabolites. Selected metabolites were further compared with a series of clinical indexes to assess the prognostic value. PQ-poisoned patients showed substantial differences compared with healthy subjects. Based on variable of importance in the project (VIP) values and statistical analysis, 17 metabolites were selected and identified. These metabolites well-classified low PQ-poisoned patients, high PQ-poisoned patients, and healthy subjects, which was better than that of a complete blood count (CBC). Among the 17 metabolites, 20:3/18:1-PC (PC), LPA (0:0/16:0) (LPA), 19-oxo-deoxycorticosterone (19-oxo-DOC), and eicosapentaenoic acid (EPA) had prognostic value. In particular, EPA was the most sensitive one. Besides, the levels of EPA was correlated with LPA and 19-oxo-DOC. If EPA was excessively consumed, then prognosis was poor. In conclusion, the serum metabolome is substantially perturbed by PQ poisoning. EPA is the most important biomarker in early PQ poisoning.

  4. Serum C-reactive protein (CRP) as a simple and independent prognostic factor in extranodal natural killer/T-cell lymphoma, nasal type.

    Science.gov (United States)

    Li, Ya-Jun; Li, Zhi-Ming; Xia, Yi; Huang, Jia-Jia; Huang, Hui-Qiang; Xia, Zhong-Jun; Lin, Tong-Yu; Li, Su; Cai, Xiu-Yu; Wu-Xiao, Zhi-Jun; Jiang, Wen-Qi

    2013-01-01

    C-reactive protein (CRP) is a biomarker of the inflammatory response, and it shows significant prognostic value for several types of solid tumors. The prognostic significance of CRP for lymphoma has not been fully examined. We evaluated the prognostic role of baseline serum CRP levels in patients with extranodal natural killer (NK)/T-cell lymphoma (ENKTL). We retrospectively analyzed 185 patients with newly diagnosed ENKTL. The prognostic value of the serum CRP level was evaluated for the low-CRP group (CRP≤10 mg/L) versus the high-CRP group (CRP>10 mg/L). The prognostic value of the International Prognostic Index (IPI) and the Korean Prognostic Index (KPI) were evaluated and compared with the newly developed prognostic model. Patients in the high-CRP group tended to display increased adverse clinical characteristics, lower rates of complete remission (P60 years, hypoalbuminemia, and elevated lactate dehydrogenase levels were independent adverse predictors of OS. Based on these four independent predictors, we constructed a new prognostic model that identified 4 groups with varying OS: group 1, no adverse factors; group 2, 1 factor; group 3, 2 factors; and group 4, 3 or 4 factors (PKPI in distinguishing between the low- and intermediate-low-risk groups, the intermediate-low- and high-intermediate-risk groups, and the high-intermediate- and high-risk groups. Our results suggest that pretreatment serum CRP levels represent an independent predictor of clinical outcome for patients with ENKTL. The prognostic value of the new prognostic model is superior to both IPI and KPI.

  5. A Comparison of the Prognostic Value of Early PSA Test-Based Variables Following External Beam Radiotherapy, With or Without Preceding Androgen Deprivation: Analysis of Data From the TROG 96.01 Randomized Trial

    International Nuclear Information System (INIS)

    Lamb, David S.; Denham, James W.; Joseph, David; Matthews, John; Atkinson, Chris; Spry, Nigel A.; Duchesne, Gillian; Ebert, Martin; Steigler, Allison; Delahunt, Brett; D'Este, Catherine

    2011-01-01

    Purpose: We sought to compare the prognostic value of early prostate-specific antigen (PSA) test-based variables for the 802 eligible patients treated in the Trans-Tasman Radiation Oncology Group 96.01 randomized trial. Methods and Materials: Patients in this trial had T2b, T2c, T3, and T4 N0 prostate cancer and were randomized to 0, 3, or 6 months of neoadjuvant androgen deprivation therapy (NADT) prior to and during radiation treatment at 66 Gy to the prostate and seminal vesicles. The early PSA test-based variables evaluated were the pretreatment initial PSA (iPSA) value, PSA values at 2 and 4 months into NADT, the PSA nadir (nPSA) value after radiation in all patients, and PSA response signatures in men receiving radiation. Comparisons of endpoints were made using Cox models of local progression-free survival, distant failure-free survival, biochemical failure-free survival, and prostate cancer-specific survival. Results: The nPSA value was a powerful predictor of all endpoints regardless of whether NADT was given before radiation. PSA response signatures also predicted all endpoints in men treated by radiation alone. iPSA and PSA results at 2 and 4 months into NADT predicted biochemical failure-free survival but not any of the clinical endpoints. nPSA values correlated with those of iPSA, Gleason grade, and T stage and were significantly higher in men receiving radiation alone than in those receiving NADT. Conclusions: The postradiation nPSA value is the strongest prognostic indicator of all early PSA-based variables. However, its use as a surrogate endpoint needs to take into account its dependence on pretreatment variables and treatment method.

  6. Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3)

    Science.gov (United States)

    Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike

    2018-04-01

    A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and raindrops. The unique aspect of the new scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice by a single category that predicts bulk particle properties (P3). This method has already been applied in a regional model and most recently also in the Community Atmosphere Model 5 (CAM5). A single cloud ice category does not rely on heuristic conversion rates from one category to another. Therefore, it is conceptually easier and closer to first principles. This work shows that a single category is a viable approach to describe cloud ice in climate models. Prognostic representation of sedimentation is achieved by a nested approach for sub-stepping the cloud microphysics scheme. This yields good results in terms of accuracy and performance as compared to simulations with high temporal resolution. Furthermore, the new scheme allows for a competition between various cloud processes and is thus able to unbiasedly represent the ice formation pathway from nucleation to growth by vapor deposition and collisions to sedimentation. Specific aspects of the P3 method are evaluated. We could not produce a purely stratiform cloud where rime growth dominates growth by vapor deposition and conclude that the lack of appropriate conditions renders the prognostic parameters associated with the rime properties unnecessary. Limitations inherent in a single category are examined.

  7. Serum prognostic biomarkers in head and neck cancer patients.

    Science.gov (United States)

    Lin, Ho-Sheng; Siddiq, Fauzia; Talwar, Harvinder S; Chen, Wei; Voichita, Calin; Draghici, Sorin; Jeyapalan, Gerald; Chatterjee, Madhumita; Fribley, Andrew; Yoo, George H; Sethi, Seema; Kim, Harold; Sukari, Ammar; Folbe, Adam J; Tainsky, Michael A

    2014-08-01

    A reliable estimate of survival is important as it may impact treatment choice. The objective of this study is to identify serum autoantibody biomarkers that can be used to improve prognostication for patients affected with head and neck squamous cell carcinoma (HNSCC). Prospective cohort study. A panel of 130 serum biomarkers, previously selected for cancer detection using microarray-based serological profiling and specialized bioinformatics, were evaluated for their potential as prognostic biomarkers in a cohort of 119 HNSCC patients followed for up to 12.7 years. A biomarker was considered positive if its reactivity to the particular patient's serum was greater than one standard deviation above the mean reactivity to sera from the other 118 patients, using a leave-one-out cross-validation model. Survival curves were estimated according to the Kaplan-Meier method, and statistically significant differences in survival were examined using the log rank test. Independent prognostic biomarkers were identified following analysis using multivariate Cox proportional hazards models. Poor overall survival was associated with African Americans (hazard ratio [HR] for death = 2.61; 95% confidence interval [CI]: 1.58-4.33; P = .000), advanced stage (HR = 2.79; 95% CI: 1.40-5.57; P = .004), and recurrent disease (HR = 6.66; 95% CI: 2.54-17.44; P = .000). On multivariable Cox analysis adjusted for covariates (race and stage), six of the 130 markers evaluated were found to be independent prognosticators of overall survival. The results shown here are promising and demonstrate the potential use of serum biomarkers for prognostication in HNSCC patients. Further clinical trials to include larger samples of patients across multiple centers may be warranted. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

  8. Addressing the challenges of obtaining functional outcomes in traumatic brain injury research: missing data patterns, timing of follow-up, and three prognostic models.

    Science.gov (United States)

    Zelnick, Leila R; Morrison, Laurie J; Devlin, Sean M; Bulger, Eileen M; Brasel, Karen J; Sheehan, Kellie; Minei, Joseph P; Kerby, Jeffrey D; Tisherman, Samuel A; Rizoli, Sandro; Karmy-Jones, Riyad; van Heest, Rardi; Newgard, Craig D

    2014-06-01

    Traumatic brain injury (TBI) is common and debilitating. Randomized trials of interventions for TBI ideally assess effectiveness by using long-term functional neurological outcomes, but such outcomes are difficult to obtain and costly. If there is little change between functional status at hospital discharge versus 6 months, then shorter-term outcomes may be adequate for use in future clinical trials. Using data from a previously published multi-center, randomized, placebo-controlled TBI clinical trial, we evaluated patterns of missing outcome data, changes in functional status between hospital discharge and 6 months, and three prognostic models to predict long-term functional outcome from covariates available at hospital discharge (functional measures, demographics, and injury characteristics). The Resuscitation Outcomes Consortium Hypertonic Saline trial enrolled 1282 TBI patients, obtaining the primary outcome of 6-month Glasgow Outcome Score Extended (GOSE) for 85% of patients, but missing the primary outcome for the remaining 15%. Patients with missing outcomes had less-severe injuries, higher neurological function at discharge (GOSE), and shorter hospital stays than patients whose GOSE was obtained. Of 1066 (83%) patients whose GOSE was obtained both at hospital discharge and at 6-months, 71% of patients had the same dichotomized functional status (severe disability/death vs. moderate/no disability) after 6 months as at discharge, 28% had an improved functional status, and 1% had worsened. Performance was excellent (C-statistic between 0.88 and 0.91) for all three prognostic models and calibration adequate for two models (p values, 0.22 and 0.85). Our results suggest that multiple imputation of the standard 6-month GOSE may be reasonable in TBI research when the primary outcome cannot be obtained through other means.

  9. Discovery of a Novel Immune Gene Signature with Profound Prognostic Value in Colorectal Cancer: A Model of Cooperativity Disorientation Created in the Process from Development to Cancer.

    Directory of Open Access Journals (Sweden)

    Ning An

    Full Text Available Immune response-related genes play a major role in colorectal carcinogenesis by mediating inflammation or immune-surveillance evasion. Although remarkable progress has been made to investigate the underlying mechanism, the understanding of the complicated carcinogenesis process was enormously hindered by large-scale tumor heterogeneity. Development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. The association between embryonic development and carcinogenesis makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Here we proposed that the immune genes, responsible for intra-immune cooperativity disorientation (defined in this study as disruption of developmental expression correlation patterns during carcinogenesis, probably contain untapped prognostic resource of colorectal cancer. In this study, we determined the mRNA expression profile of 137 human biopsy samples, including samples from different stages of human colonic development, colorectal precancerous progression and colorectal cancer samples, among which 60 were also used to generate miRNA expression profile. We originally established Spearman correlation transition model to quantify the cooperativity disorientation associated with the transition from normal to precancerous to cancer tissue, in conjunction with miRNA-mRNA regulatory network and machine learning algorithm to identify genes with prognostic value. Finally, a 12-gene signature was extracted, whose prognostic value was evaluated using Kaplan-Meier survival analysis in five independent datasets. Using the log-rank test, the 12-gene signature was closely related to overall survival in four datasets (GSE17536, n = 177, p = 0.0054; GSE17537, n = 55, p = 0.0039; GSE39582, n = 562, p = 0.13; GSE39084, n = 70, p = 0.11, and significantly associated with disease

  10. A Prognostic Method for Fault Detection in Wind Turbine Drivetrains

    DEFF Research Database (Denmark)

    Nejada, Amir R.; Odgaard, Peter Fogh; Gao, Zhen

    2014-01-01

    In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermedi......In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors...... bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from...

  11. Volume-Based F-18 FDG PET/CT Imaging Markers Provide Supplemental Prognostic Information to Histologic Grading in Patients With High-Grade Bone or Soft Tissue Sarcoma

    DEFF Research Database (Denmark)

    Andersen, Kim Francis; Fuglo, Hanna Maria; Rasmussen, Sine Hvid

    2015-01-01

    analysis. Kaplan-Meier survival estimates and log-rank test were used to compare the degree of equality of survival distributions. Prognostic variables with related hazard ratios (HR) were assessed using Cox proportional hazards regression analysis.Forty-one of 92 patients died during follow-up (45%; 12 BS.......05, HR 3.37 [95% CI 1.02-11.11]). No significant results were demonstrated for MTV40%.Volume-based F-18 FDG PET/CT imaging markers in terms of pretreatment estimation of TLG provide supplemental prognostic information to histologic grading, with significant independent properties for prediction...

  12. Prognostic factors in patients with advanced transitional cell carcinoma of the urothelial tract experiencing treatment failure with platinum-containing regimens

    DEFF Research Database (Denmark)

    Bellmunt, Joaquim; Choueiri, Toni K; Fougeray, Ronan

    2010-01-01

    analysis was used to identify independent prognostic factors, and bootstrap analysis was performed for internal validation, forming a prognostic model. External validation was performed on the phase II vinflunine study CA183001. RESULTS Multivariate analysis and the internal validation identified Eastern......, or three prognostic factors; the median OS times for these groups were 14.2, 7.3, 3.8, and 1.7 months (P internally and externally validated three adverse risk factors (PS, hemoglobin level, and liver metastasis) that predict for OS and developed...... Cooperative Oncology Group performance status (PS) more than 0, hemoglobin level less than 10 g/dL, and the presence of liver metastasis as the main adverse prognostic factors for OS. External validation confirmed these prognostic factors. Four subgroups were formed based on the presence of zero, one, two...

  13. Prognostics of Power MOSFET

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper demonstrates how to apply prognostics to power MOSFETs (metal oxide field effect transistor). The methodology uses thermal cycling to age devices and...

  14. Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties

    Directory of Open Access Journals (Sweden)

    Jialin Cai

    2017-05-01

    Full Text Available Many molecular classification and prognostic gene signatures for hepatocellular carcinoma (HCC patients have been established based on genome-wide gene expression profiling; however, their generalizability is unclear. Herein, we systematically assessed the prognostic effects of these gene signatures and identified valuable prognostic biomarkers by integrating these gene signatures. With two independent HCC datasets (GSE14520, N = 242 and GSE54236, N = 78, 30 published gene signatures were evaluated, and 11 were significantly associated with the overall survival (OS of postoperative HCC patients in both datasets. The random survival forest models suggested that the gene signatures were superior to clinical characteristics for predicting the prognosis of the patients. Based on the 11 gene signatures, a functional protein-protein interaction (PPI network with 1406 nodes and 10,135 edges was established. With tissue microarrays of HCC patients (N = 60, we determined the prognostic values of the core genes in the network and found that RAD21, CDK1, and HDAC2 expression levels were negatively associated with OS for HCC patients. The multivariate Cox regression analyses suggested that CDK1 was an independent prognostic factor, which was validated in an independent case cohort (N = 78. In cellular models, inhibition of CDK1 by siRNA or a specific inhibitor, RO-3306, reduced cellular proliferation and viability for HCC cells. These results suggest that the prognostic predictive capacities of these gene signatures are reproducible and that CDK1 is a potential prognostic biomarker or therapeutic target for HCC patients.

  15. An Aircraft Lifecycle Approach for the Cost-Benefit Analysis of Prognostics and Condition-Based Maintenance-Based on Discrete-Event Simulation

    Science.gov (United States)

    2014-10-02

    MPD. This manufacturer documentation contains maintenance tasks with specification of intervals and required man-hours that are to be carried out...failures, without consideration of false alarms and missed failures (see also section 4.1.3). The task redundancy rate is the percentage of preventive...Prognostics and Health Management ROI return on investment RUL remaining useful life TCG task code group SB Service Bulletin XML Extensible Markup

  16. Prognostic Value of Abnormal p53 Expression in Locally Advanced Prostate Cancer Treated With Androgen Deprivation and Radiotherapy: A Study Based on RTOG 9202

    International Nuclear Information System (INIS)

    Che Mingxin; DeSilvio, Michelle; Pollack, Alan; Grignon, David J.; Venkatesan, Varagur Mohan; Hanks, Gerald E.; Sandler, Howard M.

    2007-01-01

    Purpose: The goal of this study was to verify the significance of p53 as a prognostic factor in Radiation Therapy Oncology Group 9202, which compared short-term androgen deprivation (STAD) with radiation therapy (RT) to long-term androgen deprivation + RT in men with locally advanced prostate cancer (Pca). Methods and Materials: Tumor tissue was sufficient for p53 analysis in 777 cases. p53 status was determined by immunohistochemistry. Abnormal p53 expression was defined as 20% or more tumor cells with positive nuclei. Univariate and multivariate Cox proportional hazards models were used to evaluate the relationships of p53 status to patient outcomes. Results: Abnormal p53 was detected in 168 of 777 (21.6%) cases, and was significantly associated with cause-specific mortality (adjusted hazard ratio [HR] = 1.89; 95% confidence interval (CI) 1.14 - 3.14; p = 0.014) and distant metastasis (adjusted HR = 1.72; 95% CI 1.13-2.62; p = 0.013). When patients were divided into subgroups according to assigned treatment, only the subgroup of patients who underwent STAD + RT showed significant correlation between p53 status and cause-specific mortality (adjusted HR = 2.43; 95% CI = 1.32-4.49; p = 0.0044). When patients were divided into subgroups according to p53 status, only the subgroup of patients with abnormal p53 showed significant association between assigned treatment and cause-specific mortality (adjusted HR = 3.81; 95% CI 1.40-10.37; p = 0.0087). Conclusions: Abnormal p53 is a significant prognostic factor for patients with prostate cancer who undergo short-term androgen deprivation and radiotherapy. Long-term androgen deprivation may significantly improve the cause-specific survival for those with abnormal p53

  17. Model-Based Reasoning

    Science.gov (United States)

    Ifenthaler, Dirk; Seel, Norbert M.

    2013-01-01

    In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper…

  18. Evaluation of a prognostic scoring system based on the systemic inflammatory and nutritional status of patients with locally advanced non-small-cell lung cancer treated with chemoradiotherapy

    International Nuclear Information System (INIS)

    Mitsuyoshi, Takamasa; Matsuo, Yukinori; Itou, Hitoshi; Shintani, Takashi; Iizuka, Yusuke; Kim, Young Hak; Mizowaki, Takashi

    2018-01-01

    Systemic inflammation and poor nutritional status have a negative effect on the outcomes of cancer. Here, we analyzed the effects of the pretreatment inflammatory and nutritional status on clinical outcomes of locally advanced non-small-cell lung cancer (NSCLC) patients treated with chemoradiotherapy. We retrospectively reviewed 89 patients with locally advanced NSCLC treated with chemoradiotherapy between July 2006 and June 2013. Serum C-reactive protein (CRP) was assessed as an inflammatory marker, and serum albumin, body mass index (BMI) and skeletal mass index were assessed as nutritional status markers. The relationships between these markers and overall survival (OS) were assessed. The median OS was 24.6 months [95% confidence interval (CI): 19.4–39.3 months]. During follow-up, 58 patients (65%) had disease recurrence and 52 patients (58%) died. In multivariate Cox hazard analysis, CRP levels and BMI approached but did not achieve a significant association with OS (P = 0.062 and 0.094, respectively). Recursive partitioning analysis identified three prognostic groups based on hazard similarity (CRP-BMI scores): 0 = CRP < 0.3 mg/dl, 1 = CRP ≥ 0.3 mg/dl and BMI ≥ 18.5 kg/m 2 , and 2 = CRP ≥ 0.3 mg/dl and BMI < 18.5 kg/m 2 . The CRP-BMI score was significantly associated with OS (P = 0.023). Patients with scores of 0, 1 and 2 had median OS of 39.3, 24.5 and 14.5 months, respectively, and the scores also predicted the probability of receiving salvage treatment after recurrence. The CRP-BMI score is thus a simple and useful prognostic marker of clinical outcome for patients with locally advanced NSCLC treated with chemoradiotherapy.

  19. Adjuvant therapy decisions based on magnetic resonance imaging of extramural venous invasion and other prognostic factors in colorectal cancer

    Science.gov (United States)

    Swift, RI; Chau, I; Heald, RJ; Tekkis, PP; Brown, G

    2014-01-01

    Introduction There remains a lack of high quality randomised trial evidence for the use of adjuvant chemotherapy in stage II rectal cancer, particularly in the presence of high risk features such as extramural venous invasion (EMVI). The aim of this study was to explore this issue through a survey of colorectal surgeons and gastrointestinal oncologists. Methods An electronic survey was sent to a group of colorectal surgeons who were members of the Association of Coloproctology of Great Britain and Ireland. The survey was also sent to a group of gastrointestinal oncologists through the Pelican Cancer Foundation. Reminder emails were sent at 4 and 12 weeks. Results A total of 142 surgeons (54% response rate) and 99 oncologists (68% response rate) responded to the survey. The majority in both groups of clinicians thought EMVI was an important consideration in adjuvant treatment decision making and commented routinely on this in their multidisciplinary team meeting. Although both would consider treating patients on the basis of EMVI detected by magnetic resonance imaging, oncologists were more selective. Both surgeons and oncologists were prepared to offer patients with EMVI adjuvant chemotherapy but there was lack of consensus on the benefit. Conclusions This survey reinforces the evolution in thinking with regard to adjuvant therapy in stage II disease. Factors such as EMVI should be given due consideration and the prognostic information we offer patients must be more accurate. Historical data may not accurately reflect today’s practice and it may be time to consider an appropriately designed trial to address this contentious issue. PMID:25245736

  20. Can metabolic tumor parameters on primary staging 18F-FDG PET/CT aid in risk stratification of primary central nervous system lymphomas for patient management as a prognostic model?

    Science.gov (United States)

    Okuyucu, K; Alagoz, E; Ince, S; Ozaydin, S; Arslan, N

    Primary central nervous system (CNS) lymphoma is an aggressive and fatal extranodal non-Hodgkin lymphoma jailed in CNS at initial diagnosis. Its prognosis is poor and the disease has a fatal outcome when compared with systemic non-Hodgkin lymphoma. A few baseline risk stratification scoring systems have been suggested to estimate the prognosis mainly based on serum lactate dehydrogenase level,age, Karnofsky performance score, involvement of deep brain structures and cerebrospinal fluid protein concentration. 18 F-FDG PET/CT has a high prognostic value with respect to overall survival and disease-free survival in many cancers and lymphomas. We aimed to investigate metabolic tumor indexes on primary staging 18 F-FDG PET/CT as prognostic markers in primary CNS lymphoma. Fourteen patients with primary CNS diffuse large B-cell lymphoma (stage i) were enrolled in this retrospective cohort study. Primary staging 18 F-FDG PET/CT was performed and quantitative parameters like maximum standardized uptake value, average standardized uptake value, metabolic tumor volume and total lesion glycolysis (TLG) were calculated for all patients before the treatment. Cox regression models were performed to determine their relation with survival time. In the evaluation of all potential risk factors impacting recurrence/metastases (age, sex, serum lactate dehydrogenase, involvement of deep brain structures, maximum standardized uptake value, average standardized uptake value, metabolic tumor volume, and TLG) with univariate analysis, TLG remained statistically significant (P=.02). Metabolic tumor parameters are useful in prognosis estimation of primary CNS lymphomas, especially TLG, which is the most important one and may play a role in patient management. Copyright © 2017 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

  1. Model-based Software Engineering

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2010-01-01

    The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...

  2. Principles of models based engineering

    Energy Technology Data Exchange (ETDEWEB)

    Dolin, R.M.; Hefele, J.

    1996-11-01

    This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.

  3. Evaluation of meteorological fields generated by a prognostic mesoscale model using data collected during the 1993 GMAQS/COAST field study

    International Nuclear Information System (INIS)

    Lolk, N.K.; Douglas, S.G.

    1996-01-01

    In 1993, the US Interior Department's Minerals Management Service (MMS) sponsored the Gulf of Mexico Air Quality Study (GMAQS). Its purpose was to assess potential impacts of offshore petrochemical development on ozone concentrations in nonattainment areas in the Texas/Louisiana Gulf Coast region as mandated by the 1990 Clean Air Act Amendments. The GMAQS comprised data collection, data analysis, and applications of an advanced photochemical air quality model, the variable-grid Urban Airshed Model (UAM-V), and a prognostic mesoscale meteorological model (SAIMM -- Systems Applications International Mesoscale Model) to simulate two ozone episodes that were captured during the summer field study. The primary purpose of this paper is to evaluate the SAIMM-simulated meteorological fields using graphical analysis that utilize the comprehensive GMAQS/COAST (Gulf of Mexico Air Quality Study/Coastal Oxidant Assessment for Southeast Texas) database and to demonstrate the ability of the SAIMM to simulate the day-to-day variations in the evolution and structure of the gulf breeze and the mixed layer

  4. Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques

    Science.gov (United States)

    Saha, Bhaskar; Goebel, kai

    2007-01-01

    Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to the modern Condition- Based Maintenance (CBM)/Prognostic Health Management (PHM) paradigm. The application of the Bayesian techniques to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation as in Particle Filters (PF), provides a powerful tool to integrate the diagnosis and prognosis of battery health. The RVM, which is a Bayesian treatment of the Support Vector Machine (SVM), is used for model identification, while the PF framework uses the learnt model, statistical estimates of noise and anticipated operational conditions to provide estimates of remaining useful life (RUL) in the form of a probability density function (PDF). This type of prognostics generates a significant value addition to the management of any operation involving electrical systems.

  5. Risk based modelling

    International Nuclear Information System (INIS)

    Chapman, O.J.V.; Baker, A.E.

    1993-01-01

    Risk based analysis is a tool becoming available to both engineers and managers to aid decision making concerning plant matters such as In-Service Inspection (ISI). In order to develop a risk based method, some form of Structural Reliability Risk Assessment (SRRA) needs to be performed to provide a probability of failure ranking for all sites around the plant. A Probabilistic Risk Assessment (PRA) can then be carried out to combine these possible events with the capability of plant safety systems and procedures, to establish the consequences of failure for the sites. In this way the probability of failures are converted into a risk based ranking which can be used to assist the process of deciding which sites should be included in an ISI programme. This paper reviews the technique and typical results of a risk based ranking assessment carried out for nuclear power plant pipework. (author)

  6. Naples Prognostic Score, Based on Nutritional and Inflammatory Status, is an Independent Predictor of Long-term Outcome in Patients Undergoing Surgery for Colorectal Cancer.

    Science.gov (United States)

    Galizia, Gennaro; Lieto, Eva; Auricchio, Annamaria; Cardella, Francesca; Mabilia, Andrea; Podzemny, Vlasta; Castellano, Paolo; Orditura, Michele; Napolitano, Vincenzo

    2017-12-01

    The existing scores reflecting the patient's nutritional and inflammatory status do not include all biomarkers and have been poorly studied in colorectal cancers. The purpose of this study was to assess a new prognostic tool, the Naples prognostic score, comparing it with the prognostic nutritional index, controlling nutritional status score, and systemic inflammation score. This was an analysis of patients undergoing surgery for colorectal cancer. The study was conducted at a university hospital. A total of 562 patients who underwent surgery for colorectal cancer in July 2004 through June 2014 and 468 patients undergoing potentially curative surgery were included. MaxStat analysis dichotomized neutrophil:lymphocyte ratio, lymphocyte:monocyte ratio, prognostic nutritional index, and the controlling nutritional status score. The Naples prognostic scores were divided into 3 groups (group 0, 1, and 2). The receiver operating characteristic curve for censored survival data compared the prognostic performance of the scoring systems. Overall survival and complication rates in all patients, as well as recurrence and disease-free survival rates in radically resected patients, were measured. The Naples prognostic score correlated positively with the other scoring systems (p cancer. See Video Abstract at http://links.lww.com/DCR/A469.

  7. A Retrospective Survival Analysis of Anatomic and Prognostic Stage Group Based on the American Joint Committee on Cancer 8th Edition Cancer Staging Manual in Luminal B Human Epidermal Growth Factor Receptor 2-negative Breast Cancer.

    Science.gov (United States)

    Xu, Ling; Li, Jiang-Hong; Ye, Jing-Ming; Duan, Xue-Ning; Cheng, Yuan-Jia; Xin, Ling; Liu, Qian; Zhou, Bin; Liu, Yin-Hua

    2017-08-20

    Current understanding of tumor biology suggests that breast cancer is a group of diseases with different intrinsic molecular subtypes. Anatomic staging system alone is insufficient to provide future outcome information. The American Joint Committee on Cancer (AJCC) expert panel updated the 8th edition of the staging manual with prognostic stage groups by incorporating biomarkers into the anatomic stage groups. In this study, we retrospectively analyzed the data from our center in China using the anatomic and prognostic staging system based on the AJCC 8th edition staging manual. We reviewed the data from January 2008 to December 2014 for cases with Luminal B Human Epidermal Growth Factor Receptor 2 (HER2)-negative breast cancer in our center. All cases were restaged using the AJCC 8th edition anatomic and prognostic staging system. The Kaplan-Meier method and log-rank test were used to compare the survival differences between different subgroups. SPSS software version 19.0 (IBM Corp., Armonk, NY, USA) was used for the statistical analyses. This study consisted of 796 patients with Luminal B HER-negative breast cancer. The 5-year disease-free survival (DFS) of 769 Stage I-III patients was 89.7%, and the 5-year overall survival (OS) of all 796 patients was 91.7%. Both 5-year DFS and 5-year OS were significantly different in the different anatomic and prognostic stage groups. There were 372 cases (46.7%) assigned to a different group. The prognostic Stage II and III patients restaged from anatomic Stage III had significant differences in 5-year DFS (χ2 = 11.319, P= 0.001) and 5-year OS (χ2 = 5.225, P= 0.022). In addition, cases restaged as prognostic Stage I, II, or III from the anatomic Stage II group had statistically significant differences in 5-year DFS (χ2 = 6.510, P= 0.039) but no significant differences in 5-year OS (χ2 = 5.087, P= 0.079). However, the restaged prognostic Stage I and II cases from anatomic Stage I had no statistically significant

  8. Model-based consensus

    NARCIS (Netherlands)

    Boumans, M.; Martini, C.; Boumans, M.

    2014-01-01

    The aim of the rational-consensus method is to produce "rational consensus", that is, "mathematical aggregation", by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  9. Model-based consensus

    NARCIS (Netherlands)

    Boumans, Marcel

    2014-01-01

    The aim of the rational-consensus method is to produce “rational consensus”, that is, “mathematical aggregation”, by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  10. TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

    Science.gov (United States)

    Lin, Frank Po-Yen; Pokorny, Adrian; Teng, Christina; Epstein, Richard J

    2017-07-31

    Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical narratives, we have built a novel computational pipeline termed Text-based Exploratory Pattern Analyser for Prognosticator and Associator discovery (TEPAPA). This pipeline combines semantic-free natural language processing (NLP), regular expression induction, and statistical association testing to identify conserved text patterns associated with outcome variables of clinical interest. When we applied TEPAPA to a cohort of head and neck squamous cell carcinoma patients, plausible concepts known to be correlated with human papilloma virus (HPV) status were identified from the EMR text, including site of primary disease, tumour stage, pathologic characteristics, and treatment modalities. Similarly, correlates of other variables (including gender, nodal status, recurrent disease, smoking and alcohol status) were also reliably recovered. Using highly-associated patterns as covariates, a patient's HPV status was classifiable using a bootstrap analysis with a mean area under the ROC curve of 0.861, suggesting its predictive utility in supporting EMR-based phenotyping tasks. These data support using this integrative approach to efficiently identify disease-associated factors from unstructured EMR narratives, and thus to efficiently generate testable hypotheses.

  11. Prognostics and Health Management of Wind Turbines: Current Status and Future Opportunities

    Energy Technology Data Exchange (ETDEWEB)

    Sheng, Shuangwen

    2015-12-14

    Prognostics and health management is not a new concept. It has been used in relatively mature industries, such as aviation and electronics, to help improve operation and maintenance (O&M) practices. In the wind industry, prognostics and health management is relatively new. The level for both wind industry applications and research and development (R&D) has increased in recent years because of its potential for reducing O&M cost of wind power, especially for turbines installed offshore. The majority of wind industry application efforts has been focused on diagnosis based on various sensing and feature extraction techniques. For R&D, activities are being conducted in almost all areas of a typical prognostics and health management framework (i.e., sensing, data collection, feature extraction, diagnosis, prognosis, and maintenance scheduling). This presentation provides an overview of the current status of wind turbine prognostics and health management that focuses on drivetrain condition monitoring through vibration, oil debris, and oil condition analysis techniques. It also discusses turbine component health diagnosis through data mining and modeling based on supervisory control and data acquisition system data. Finally, it provides a brief survey of R&D activities for wind turbine prognostics and health management, along with future opportunities.

  12. Activity-based DEVS modeling

    DEFF Research Database (Denmark)

    Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

    2018-01-01

    architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number......Use of model-driven approaches has been increasing to significantly benefit the process of building complex systems. Recently, an approach for specifying model behavior using UML activities has been devised to support the creation of DEVS models in a disciplined manner based on the model driven...... of the artifacts of the UML 2.5 activities and actions, from the vantage point of DEVS behavioral modeling, is covered in details. Their semantics are discussed to the extent of time-accurate requirements for simulation. We characterize them in correspondence with the specification of the atomic model behavior. We...

  13. Local-Level Prognostics Health Management Systems Framework for Passive AdvSMR Components. Interim Report

    Energy Technology Data Exchange (ETDEWEB)

    Ramuhalli, Pradeep [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Roy, Surajit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hirt, Evelyn H. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pardini, Allan F. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Jones, Anthony M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Deibler, John E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States; Pitman, Stan G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States; Tucker, Joseph C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States; Prowant, Matthew S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States; Suter, Jonathan D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States

    2014-09-12

    This report describes research results to date in support of the integration and demonstration of diagnostics technologies for prototypical AdvSMR passive components (to establish condition indices for monitoring) with model-based prognostics methods. The focus of the PHM methodology and algorithm development in this study is at the localized scale. Multiple localized measurements of material condition (using advanced nondestructive measurement methods), along with available measurements of the stressor environment, enhance the performance of localized diagnostics and prognostics of passive AdvSMR components and systems.

  14. Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

    Science.gov (United States)

    Corbetta, M.; Sbarufatti, C.; Saxena, A.; Giglio, M.; Goebel, K.

    2016-01-01

    Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model

  15. Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Liao X

    2018-04-01

    Full Text Available Xiwen Liao,1 Guangzhi Zhu,1 Rui Huang,2 Chengkun Yang,1 Xiangkun Wang,1 Ketuan Huang,1 Tingdong Yu,1 Chuangye Han,1 Hao Su,1 Tao Peng1 1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China Background: The aim of the present study was to identify potential prognostic microRNA (miRNA biomarkers for hepatocellular carcinoma (HCC prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA. Materials and methods: A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs, and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results: Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394, and time-dependent receiver–operating characteristic (ROC analysis showed an area under the curve (AUC of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration

  16. Physics Based Electrolytic Capacitor Degradation Models for Prognostic Studies under Thermal Overstress

    Data.gov (United States)

    National Aeronautics and Space Administration — Electrolytic capacitors are used in several applications rang- ing from power supplies on safety critical avionics equipment to power drivers for electro-mechanical...

  17. Application of Model Based Prognostics to Pneumatic Valves in a Cryogenic Propellant Loading Testbed

    Data.gov (United States)

    National Aeronautics and Space Administration — Pneumatic-actuated valves are critical components in many applications, including cryogenic propellant loading for space operations. For these components, failures...

  18. Validation of Model-Based Prognostics for Pneumatic Valves in a Demonstration Testbed

    Science.gov (United States)

    2014-10-02

    predict end of life ( EOL ) and remaining useful life (RUL). The approach still follows the general estimation-prediction framework devel- oped in the...atmosphere, with linearly increasing leak area. kA2leak = Cleak (16) We define valve end of life ( EOL ) through open/close time limits of the valves, as in...represents end of life ( EOL ), and ∆kE represents remaining useful life (RUL). For valves, timing requirements are provided that de- fine the maximum

  19. Prognostic factors and survival of colorectal cancer in Kurdistan province, Iran: A population-based study (2009-2014).

    Science.gov (United States)

    Rasouli, Mohammad Aziz; Moradi, Ghobad; Roshani, Daem; Nikkhoo, Bahram; Ghaderi, Ebrahim; Ghaytasi, Bahman

    2017-02-01

    Colorectal cancer (CRC) survival varies at individual and geographically level. This population-based study aimed to evaluating various factors affecting the survival rate of CRC patients in Kurdistan province.In a retrospective cohort study, patients diagnosed as CRC were collected through a population-based study from March 1, 2009 to 2014. The data were collected from Kurdistan's Cancer Registry database. Additional information and missing data were collected reference to patients' homes, medical records, and pathology reports. The CRC survival was calculated from the date of diagnosis to the date of cancer-specific death or the end of follow-up (cutoff date: October 2015). Kaplan-Meier method and log-rank test were used for the univariate analysis of survival in various subgroups. The proportional-hazard model Cox was also used in order to consider the effects of different factors on survival including age at diagnosis, place of residence, marital status, occupation, level of education, smoking, economic status, comorbidity, tumor stage, and tumor grade.A total number of 335 patients affected by CRC were assessed and the results showed that 1- and 5-year survival rate were 87% and 33%, respectively. According to the results of Cox's multivariate analysis, the following factors were significantly related to CRC survival: age at diagnosis (≥65 years old) (HR 2.08, 95% CI: 1.17-3.71), single patients (HR 1.62, 95% CI: 1.10-2.40), job (worker) (HR 2.09, 95% CI: 1.22-3.58), educational level: diploma or below (HR 0.61, 95% CI: 0.39-0.92), wealthy economic status (HR 0.51, 95% CI: 0.31-0.82), tumor grade in poorly differentiated (HR 2.25, 95% CI: 1.37-3.69), and undifferentiated/anaplastic grade (HR 2.90, 95% CI: 1.67-4.98).We found that factors such as low education, inappropriate socioeconomic status, and high tumor grade at the time of disease diagnosis were effective in the poor survival of CRC patients in Kurdistan province; this, which need more attention.

  20. Prognostic value of baseline seric Syndecan-1 in initially unresectable metastatic colorectal cancer patients: a simple biological score.

    Science.gov (United States)

    Jary, Marine; Lecomte, Thierry; Bouché, Olivier; Kim, Stefano; Dobi, Erion; Queiroz, Lise; Ghiringhelli, Francois; Etienne, Hélène; Léger, Julie; Godet, Yann; Balland, Jérémy; Lakkis, Zaher; Adotevi, Olivier; Bonnetain, Franck; Borg, Christophe; Vernerey, Dewi

    2016-11-15

    In first-line metastatic colorectal cancer (mCRC), baseline prognostic factors allowing death risk and treatment strategy stratification are lacking. Syndecan-1 (CD138) soluble form was never described as a prognostic biomarker in mCRC. We investigated its additional prognostic value for overall survival (OS). mCRC patients with unresectable disease at diagnosis were treated with bevacizumab-based chemotherapy in two independent prospective clinical trials (development set: n = 126, validation set: n = 51, study NCT00489697 and study NCT00544011, respectively). Serums were collected at baseline for CD138 measurement. OS determinants were assessed and, based on the final multivariate model, a prognostic score was proposed. Two independent OS prognostic factors were identified: Lactate Dehydrogenase (LDH) high level (p = 0.0066) and log-CD138 high level (p = 0.0190). The determination of CD138 binary information (cutoff: 75 ng/mL) allowed the assessment of a biological prognostic score with CD138 and LDH values, identifying three risk groups for death (median OS= 38.9, 30.1 and 19.8 months for the low, intermediate and high risk groups, respectively; p value for OS, in mCRC patients. A simple biological scoring system is proposed including LDH and CD138 binary status values. © 2016 UICC.

  1. A simulation study on estimating biomarker-treatment interaction effects in randomized trials with prognostic variables.

    Science.gov (United States)

    Haller, Bernhard; Ulm, Kurt

    2018-02-20

    To individualize treatment decisions based on patient characteristics, identification of an interaction between a biomarker and treatment is necessary. Often such potential interactions are analysed using data from randomized clinical trials intended for comparison of two treatments. Tests of interactions are often lacking statistical power and we investigated if and how a consideration of further prognostic variables can improve power and decrease the bias of estimated biomarker-treatment interactions in randomized clinical trials with time-to-event outcomes. A simulation study was performed to assess how prognostic factors affect the estimate of the biomarker-treatment interaction for a time-to-event outcome, when different approaches, like ignoring other prognostic factors, including all available covariates or using variable selection strategies, are applied. Different scenarios regarding the proportion of censored observations, the correlation structure between the covariate of interest and further potential prognostic variables, and the strength of the interaction were considered. The simulation study revealed that in a regression model for estimating a biomarker-treatment interaction, the probability of detecting a biomarker-treatment interaction can be increased by including prognostic variables that are associated with the outcome, and that the interaction estimate is biased when relevant prognostic variables are not considered. However, the probability of a false-positive finding increases if too many potential predictors are included or if variable selection is performed inadequately. We recommend undertaking an adequate literature search before data analysis to derive information about potential prognostic variables and to gain power for detecting true interaction effects and pre-specifying analyses to avoid selective reporting and increased false-positive rates.

  2. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...... of information structures. The general event concept can be used to guide systems analysis and design and to improve modeling approaches....

  3. Joint System Prognostics For Increased Efficiency And Risk Mitigation In Advanced Nuclear Reactor Instrumentation and Control

    Energy Technology Data Exchange (ETDEWEB)

    Donald D. Dudenhoeffer; Tuan Q. Tran; Ronald L. Boring; Bruce P. Hallbert

    2006-08-01

    The science of prognostics is analogous to a doctor who, based on a set of symptoms and patient tests, assesses a probable cause, the risk to the patient, and a course of action for recovery. While traditional prognostics research has focused on the aspect of hydraulic and mechanical systems and associated failures, this project will take a joint view in focusing not only on the digital I&C aspect of reliability and risk, but also on the risks associated with the human element. Model development will not only include an approximation of the control system physical degradation but also on human performance degradation. Thus the goal of the prognostic system is to evaluate control room operation; to identify and potentially take action when performance degradation reduces plant efficiency, reliability or safety.

  4. [Prognostic scores for pulmonary embolism].

    Science.gov (United States)

    Junod, Alain

    2016-03-23

    Nine prognostic scores for pulmonary embolism (PE), based on retrospective and prospective studies, published between 2000 and 2014, have been analyzed and compared. Most of them aim at identifying PE cases with a low risk to validate their ambulatory care. Important differences in the considered outcomes: global mortality, PE-specific mortality, other complications, sizes of low risk groups, exist between these scores. The most popular score appears to be the PESI and its simplified version. Few good quality studies have tested the applicability of these scores to PE outpatient care, although this approach tends to already generalize in the medical practice.

  5. HMM-based Trust Model

    DEFF Research Database (Denmark)

    ElSalamouny, Ehab; Nielsen, Mogens; Sassone, Vladimiro

    2010-01-01

    Probabilistic trust has been adopted as an approach to taking security sensitive decisions in modern global computing environments. Existing probabilistic trust frameworks either assume fixed behaviour for the principals or incorporate the notion of ‘decay' as an ad hoc approach to cope...... with their dynamic behaviour. Using Hidden Markov Models (HMMs) for both modelling and approximating the behaviours of principals, we introduce the HMM-based trust model as a new approach to evaluating trust in systems exhibiting dynamic behaviour. This model avoids the fixed behaviour assumption which is considered...... the major limitation of existing Beta trust model. We show the consistency of the HMM-based trust model and contrast it against the well known Beta trust model with the decay principle in terms of the estimation precision....

  6. Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions

    Science.gov (United States)

    2012-09-01

    make end of life ( EOL ) and remaining useful life (RUL) estimations. Model-based prognostics approaches perform these tasks with the help of first...in parameters Degradation Modeling Parameter estimation Prediction Thermal / Electrical Stress Experimental Data State Space model RUL EOL ...distribution at given single time point kP , and use this for multi-step predictions to EOL . There are several methods which exits for selecting the sigma

  7. Mode of detection: an independent prognostic factor for women with breast cancer.

    Science.gov (United States)

    Hofvind, Solveig; Holen, Åsne; Román, Marta; Sebuødegård, Sofie; Puig-Vives, Montse; Akslen, Lars

    2016-06-01

    To investigate breast cancer survival and risk of breast cancer death by detection mode (screen-detected, interval, and detected outside the screening programme), adjusting for prognostic and predictive tumour characteristics. Information about detection mode, prognostic (age, tumour size, histologic grade, lymph node status) and predictive factors (molecular subtypes based on immunohistochemical analyses of hormone receptor status (estrogen and progesterone) and Her2 status) were available for 8344 women in Norway aged 50-69 at diagnosis of breast cancer, 2005-2011. A total of 255 breast cancer deaths were registered by the end of 2011. Kaplan-Meier method was used to estimate six years breast cancer specific survival and Cox proportional hazard model to estimate hazard ratio (HR) for breast cancer death by detection mode, adjusting for prognostic and predictive factors. Women with screen-detected cancer had favourable prognostic and predictive tumour characteristics compared with interval cancers and those detected outside the screening programme. The favourable characteristics were present for screen-detected cancers, also within the subtypes. Adjusted HR of dying from breast cancer was two times higher for women with symptomatic breast cancer (interval or outside the screening), using screen-detected tumours as the reference. Detection mode is an independent prognostic factor for women diagnosed with breast cancer. Information on detection mode might be relevant for patient management to avoid overtreatment. © The Author(s) 2015.

  8. Applicability of RFID in the prognostics of logistic systems

    NARCIS (Netherlands)

    Lopez De La Cruz, A.M.; Veeke, H.P.M.; Lodewijks, G.

    2007-01-01

    The objective of this paper is to investigate the applicability of RFID in prognostic logistics. Starting from a general introduction of prognostic logistics, the system structure, and technical requirements are discussed. Based on this discussion the issues and concerns regarding the applicability

  9. Modeling Guru: Knowledge Base for NASA Modelers

    Science.gov (United States)

    Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

    2009-05-01

    Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the

  10. Prognostic factors in oligodendrogliomas

    DEFF Research Database (Denmark)

    Westergaard, L; Gjerris, F; Klinken, L

    1997-01-01

    An outcome analysis was performed on 96 patients with pure cerebral oligodendrogliomas operated in the 30-year period 1962 to 1991. The most important predictive prognostic factors were youth and no neurological deficit, demonstrated as a median survival for the group younger than 20 years of 17...

  11. Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment

    Directory of Open Access Journals (Sweden)

    Carolina Rosswog

    2017-12-01

    Full Text Available BACKGROUND: Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. METHODS: A cohort of 695 neuroblastoma patients was divided into a discovery set (n = 75 for multigene predictor generation, a training set (n = 411 for risk score development, and a validation set (n = 209. Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. RESULTS: The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9 ± 3.4 vs 63.6 ± 14.5 vs 31.0 ± 5.4; P < .001, and its prognostic value was validated by multivariable analysis. CONCLUSION: We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients.

  12. Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

    Science.gov (United States)

    Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

    2017-12-01

    Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Structure-Based Turbulence Model

    National Research Council Canada - National Science Library

    Reynolds, W

    2000-01-01

    .... Maire carried out this work as part of his Phi) research. During the award period we began to explore ways to simplify the structure-based modeling so that it could be used in repetitive engineering calculations...

  14. Predictive accuracy of model for end stage liver disease (meld) as a prognostic marker for cirrhosis in comparison with child - pugh score

    International Nuclear Information System (INIS)

    Zubair, U.B.; Alam, M.M.; Saeed, F.

    2015-01-01

    To compare Model for End Stage Liver Disease (MELD) and Child-Turcott-Pugh (CTG) scoring as predictors of survival in cirrhotic patients. Study Design: Observational prospective study. Place and Duration of Study: Military Hospital, Rawalpindi from 1st Dec 2008 to 30th April 2009. Material and Methods: The study was carried out at Military Hospital, Rawalpindi a tertiary care hospital of Pakistan. Study included 55 patients suffering from cirrhosis of both genders being above 12 years of age, admitted in medical wards during the period from 1st December, 2008 to 30th April 2009. Each patient was assigned a MELD and CTP score. On discharge, these patients were followed up at 03 months, 06 months and 1 year duration through telephone. Results: Thirty seven (67.3%) patients were male while 18 (32.7%) were female patients, with age ranging from 27 years to 75 years (mean 53). Fourteen (25.4%) patients were dead at 3-months, 22 patients (40%) were dead at 6-months and 29 (52.7%) patients were dead at 1 year follow up. MELD score proved to be a better indicator of survival than CTP score over a period of 01 year follow-up. Conclusion: MELD score is a better prognostic marker for cirrhotic patients as compared to CTP score. (author)

  15. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2009-01-01

    The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

  16. Computer Based Modelling and Simulation

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 6; Issue 3. Computer Based Modelling and Simulation - Modelling Deterministic Systems. N K Srinivasan. General Article Volume 6 Issue 3 March 2001 pp 46-54. Fulltext. Click here to view fulltext PDF. Permanent link:

  17. A Novel UAV Electric Propulsion Testbed for Diagnostics and Prognostics

    Science.gov (United States)

    Gorospe, George E., Jr.; Kulkarni, Chetan S.

    2017-01-01

    This paper presents a novel hardware-in-the-loop (HIL) testbed for systems level diagnostics and prognostics of an electric propulsion system used in UAVs (unmanned aerial vehicle). Referencing the all electric, Edge 540T aircraft used in science and research by NASA Langley Flight Research Center, the HIL testbed includes an identical propulsion system, consisting of motors, speed controllers and batteries. Isolated under a controlled laboratory environment, the propulsion system has been instrumented for advanced diagnostics and prognostics. To produce flight like loading on the system a slave motor is coupled to the motor under test (MUT) and provides variable mechanical resistance, and the capability of introducing nondestructive mechanical wear-like frictional loads on the system. This testbed enables the verification of mathematical models of each component of the propulsion system, the repeatable generation of flight-like loads on the system for fault analysis, test-to-failure scenarios, and the development of advanced system level diagnostics and prognostics methods. The capabilities of the testbed are extended through the integration of a LabVIEW-based client for the Live Virtual Constructive Distributed Environment (LVCDC) Gateway which enables both the publishing of generated data for remotely located observers and prognosers and the synchronization the testbed propulsion system with vehicles in the air. The developed HIL testbed gives researchers easy access to a scientifically relevant portion of the aircraft without the overhead and dangers encountered during actual flight.

  18. Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model

    OpenAIRE

    Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

    2017-01-01

    Purpose The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. Materials and Methods This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC m...

  19. The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study.

    Science.gov (United States)

    Gnanapragasam, V J; Bratt, O; Muir, K; Lee, L S; Huang, H H; Stattin, P; Lophatananon, A

    2018-02-28

    The purpose of this study is to validate a new five-tiered prognostic classification system to better discriminate cancer-specific mortality in men diagnosed with primary non-metastatic prostate cancer. We applied a recently described five-strata model, the Cambridge Prognostic Groups (CPGs 1-5), in two international cohorts and tested prognostic performance against the current standard three-strata classification of low-, intermediate- or high-risk disease. Diagnostic clinico-pathological data for men obtained from the Prostate Cancer data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality. The PCBaSe cohort included 72,337 men, of whom 7162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk regression confirming significant intergroup distinction (p study of nearly 75,000 men confirms that the CPG five-tiered prognostic model has superior discrimination compared to the three-tiered model in predicting prostate cancer death across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes. We therefore propose adoption of the CPG model as a simple-to-use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer.

  20. Prognostics Health Management of Electronic Systems Under Mechanical Shock and Vibration Using Kalman Filter Models and Metrics

    Data.gov (United States)

    National Aeronautics and Space Administration — Structural damage to ball grid array interconnects incurred during vibration testing has been monitored in the prefailure space using resistance spectroscopy-based...

  1. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  2. Prognostic risk stratification derived from individual patient level data for men with advanced penile squamous cell carcinoma receiving first-line systemic therapy.

    Science.gov (United States)

    Pond, Gregory R; Di Lorenzo, Giuseppe; Necchi, Andrea; Eigl, Bernhard J; Kolinsky, Michael P; Chacko, Raju T; Dorff, Tanya B; Harshman, Lauren C; Milowsky, Matthew I; Lee, Richard J; Galsky, Matthew D; Federico, Piera; Bolger, Graeme; DeShazo, Mollie; Mehta, Amitkumar; Goyal, Jatinder; Sonpavde, Guru

    2014-05-01

    Prognostic factors in men with penile squamous cell carcinoma (PSCC) receiving systemic therapy are unknown. A prognostic classification system in this disease may facilitate interpretation of outcomes and guide rational drug development. We performed a retrospective analysis to identify prognostic factors in men with PSCC receiving first-line systemic therapy for advanced disease. Individual patient level data were obtained from 13 institutions to study prognostic factors in the context of first-line systemic therapy for advanced PSCC. Cox proportional hazards regression analysis was conducted to examine the prognostic effect of these candidate factors on progression-free survival (PFS) and overall survival (OS): age, stage, hemoglobin, neutrophil count, lymphocyte count, albumin, site of metastasis (visceral or nonvisceral), smoking, circumcision, regimen, ECOG performance status (PS), lymphovascular invasion, precancerous lesion, and surgery following chemotherapy. The effect of different treatments was then evaluated adjusting for factors in the prognostic model. The study included 140 eligible men. Mean age across all men was 57.0 years. Among them, 8.6%, 21.4%, and 70.0% of patients had stage 2, 3, and 4 diseases, respectively; 40.7% had ECOG PS ≥ 1, 47.4% had visceral metastases, and 73.6% received cisplatin-based chemotherapy. The multivariate model of poor prognostic factors included visceral metastases (Pstatistic of 0.657 and 0.677 for OS and PFS, respectively). The median OS for the entire population was 9 months. Median OS was not reached, 8, and 7 months for those with 0, 1, and both risk factors, respectively. Cisplatin-based regimens were associated with better OS (P = 0.017) but not PFS (P = 0.37) compared with noncisplatin-based regimens after adjusting for the 2 prognostic factors. In men with advanced PSCC receiving first-line systemic therapy, visceral metastases and ECOG PS ≥ 1 were poor prognostic factors. A prognostic model including

  3. Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication in Terminally Ill Patients

    Science.gov (United States)

    2016-03-01

    indicates that, when making their choices, the people tend to be regret averse: they anticipate regret to avoid post-decisional regret . In the...visual analogue scales for elicitation of regret , elicitation of acceptable regret , incorporation of treatment effects in the decision making...calculations. The details of the CDSS-EBM are published in a peer-reviewed journal manuscript (See appendix: Extensions to Regret -based Decision Curve Analysis

  4. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  5. Building and validation of a prognostic model for predicting extracorporeal circuit clotting in patients with continuous renal replacement therapy.

    Science.gov (United States)

    Fu, Xia; Liang, Xinling; Song, Li; Huang, Huigen; Wang, Jing; Chen, Yuanhan; Zhang, Li; Quan, Zilin; Shi, Wei

    2014-04-01

    To develop a predictive model for circuit clotting in patients with continuous renal replacement therapy (CRRT). A total of 425 cases were selected. 302 cases were used to develop a predictive model of extracorporeal circuit life span during CRRT without citrate anticoagulation in 24 h, and 123 cases were used to validate the model. The prediction formula was developed using multivariate Cox proportional-hazards regression analysis, from which a risk score was assigned. The mean survival time of the circuit was 15.0 ± 1.3 h, and the rate of circuit clotting was 66.6 % during 24 h of CRRT. Five significant variables were assigned a predicting score according to the regression coefficient: insufficient blood flow, no anticoagulation, hematocrit ≥0.37, lactic acid of arterial blood gas analysis ≤3 mmol/L and APTT R (2) = 0.232; P = 0.301). A risk score that includes the five above-mentioned variables can be used to predict the likelihood of extracorporeal circuit clotting in patients undergoing CRRT.

  6. Mammographic Density Reduction as a Prognostic Marker for Postmenopausal Breast Cancer: Results Using a Joint Longitudinal-Survival Modeling Approach.

    Science.gov (United States)

    Andersson, Therese M-L; Crowther, Michael J; Czene, Kamila; Hall, Per; Humphreys, Keith

    2017-11-01

    Previous studies have linked reductions in mammographic density after a breast cancer diagnosis to an improved prognosis. These studies focused on short-term change, using a 2-stage process, treating estimated change as a fixed covariate in a survival model. We propose the use of a joint longitudinal-survival model. This enables us to model long-term trends in density while accounting for dropout as well as for measurement error. We studied the change in mammographic density after a breast cancer diagnosis and its association with prognosis (measured by cause-specific mortality), overall and with respect to hormone replacement therapy and tamoxifen treatment. We included 1,740 women aged 50-74 years, diagnosed with breast cancer in Sweden during 1993-1995, with follow-up until 2008. They had a total of 6,317 mammographic density measures available from the first 5 years of follow-up, including baseline measures. We found that the impact of the withdrawal of hormone replacement therapy on density reduction was larger than that of tamoxifen treatment. Unlike previous studies, we found that there was an association between density reduction and survival, both for tamoxifen-treated women and women who were not treated with tamoxifen. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

  7. PML expression in soft tissue sarcoma: prognostic and predictive value in alkylating agents/antracycline-based first line therapy.

    Science.gov (United States)

    Vincenzi, Bruno; Santini, Daniele; Schiavon, Gaia; Frezza, Anna Maria; Silletta, Marianna; Crucitti, Pierfilippo; Casali, Paolo; Dei Tos, Angelo P; Rossi, Sabrina; Rizzo, Sergio; Badalamenti, Giuseppe; Tomasino, Rosa Maria; Russo, Antonio; Butrynski, James E; Tonini, Giuseppe

    2012-04-01

    Soft tissue sarcomas are aggressive tumors representing alkylating agents/antracycline-based first line therapy. One hundred eleven patients affected by locally advanced and metastatic soft tissue sarcoma were selected. PML expression was evaluated by immunohistochemical analysis in pathological samples and in the corresponding normal tissue from each case. PML immunohistochemical results were correlated with prognosis and with radiological response to alkylating agents/antracycline-based first line therapy. PML expression was significantly reduced in synovial sarcomas (P < 0.0001), in myofibroblastic sarcomas (P < 0.0001), angiosarcomas (P < 0.0001), in leiomyosarcomas (P = 0.003), in mixoid liposarcomas (P < 0.0001), and in dedifferentiated liposarcomas (P < 0.0001). No significant difference was found for pleomorphic sarcoma [31.8 (95% CI: 16.7-41.0); P = 0.21]. and pleomorphic liposarcomas (P = 0.51). Loss of PML expression was found to be statistically correlated with TTP (P < 0.0001), median duration of response (P = 0.007), and OS (P = 0.02). No correlation was observed between PML expression and treatment efficacy. PML IHC expression is down-regulated in synovial sarcomas, myofibroblastic sarcomas, angiosarcomas, liposarcoma, and leiomyosarcomas and its expression correlated with prognosis. Copyright © 2011 Wiley Periodicals, Inc.

  8. Evaluating the quality of Websites related to Hospital-Based Home Care: The Credibility Indicator as a prognostic factor

    Directory of Open Access Journals (Sweden)

    María Sanz-Lorente

    2017-04-01

    Full Text Available Objective: To evaluate the documental quality of websites related to Home Care Services. Method: This is a descriptive cross-sectional study of websites based on Home Care Services, using searches on Google to access the study population. The “fallacy sample” of this search engine was take into account. The quality was studied thought the 8 variables of the Credibility Indicator (CI. Results: A total of 215 active websites, mainly belonging to the media, were evaluated. None of the websites met all 8 items in the CI. Mean of 2,12 ± 0,07; Minimum of 0 and Maximum of 5; Median equal to 3. Within the studied websites, 74 (34,42% presented both authorship and affiliation. There was an association between the CI accomplishment and websites that had these 2 variables (p <0.001. Conclusions: The quality of websites covering issues of Hospital-Based Home Care services is still poor. It is confirmed that identifying authorship and affiliation is an important factor in predicting the quality of the information. The Credibility Indicator is a useful aid when determining the quality of a website.

  9. MICRONUCLEI: A PROGNOSTIC TOOL

    OpenAIRE

    Ankit; Rinky; Manisha; Sonalika; Anand; Sanyog

    2014-01-01

    Squamous cell carcinoma is one the most common oral mucosal malignant tumor, diagnosis of oral squamous cell carcinoma rarely presents difficulty, it is the cancer staging and histo pathological grading that are more important for prognosis, micronuclei are good prognostic indicator. Micronuclei screening can be done easily by exfoliative cytology, one of the most valuable diagnostic method other than routine histopathology (H and E-stained sections) and immunohistochemist...

  10. Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study.

    Directory of Open Access Journals (Sweden)

    Maarten O Blanken

    Full Text Available This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV hospitalization in preterm infants 33-35 weeks gestational age (WGA.The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy preterm infants 33-35 WGA. All hospitalizations for respiratory tract infection were screened for proven RSV infection by immunofluorescence or polymerase chain reaction. Multivariate logistic regression analysis was used to update an existing prediction model in the derivation cohort (n = 1,227. In the validation cohort (n = 1,194, predicted versus actual RSV hospitalization rates were compared to determine validity of the model.RSV hospitalization risk in both cohorts was comparable (5.7% versus 4.9%. In the derivation cohort, a prediction rule to determine probability of RSV hospitalization was developed using 4 predictors: family atopy (OR 1.9; 95%CI, 1.1-3.2, birth period (OR 2.6; 1.6-4.2, breastfeeding (OR 1.7; 1.0-2.7 and siblings or daycare attendance (OR 4.7; 1.7-13.1. The model showed good discrimination (c-statistic 0.703; 0.64-0.76, 0.702 after bootstrapping. External validation showed good discrimination and calibration (c-statistic 0.678; 0.61-0.74.Our prospectively validated prediction rule identifies infants at increased RSV hospitalization risk, who may benefit from targeted preventive interventions. This prediction rule can facilitate country-specific, cost-effective use of RSV prophylaxis in late preterm infants.

  11. Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations

    Directory of Open Access Journals (Sweden)

    Cunji Zhang

    2016-05-01

    Full Text Available Tool breakage causes losses of surface polishing and dimensional accuracy for machined part, or possible damage to a workpiece or machine. Tool Condition Monitoring (TCM is considerably vital in the manufacturing industry. In this paper, an indirect TCM approach is introduced with a wireless triaxial accelerometer. The vibrations in the three vertical directions (x, y and z are acquired during milling operations, and the raw signals are de-noised by wavelet analysis. These features of de-noised signals are extracted in the time, frequency and time–frequency domains. The key features are selected based on Pearson’s Correlation Coefficient (PCC. The Neuro-Fuzzy Network (NFN is adopted to predict the tool wear and Remaining Useful Life (RUL. In comparison with Back Propagation Neural Network (BPNN and Radial Basis Function Network (RBFN, the results show that the NFN has the best performance in the prediction of tool wear and RUL.

  12. Performance of three prognostic models in patients with cancer in need of intensive care in a medical center in China.

    Directory of Open Access Journals (Sweden)

    XueZhong Xing

    Full Text Available The aim of this study was to evaluate the performance of Acute Physiology and Chronic Health Evaluation II (APACHE II, Simplified Acute Physiology Score 3 (SAPS 3, and Acute Physiology and Chronic Health Evaluation IV (APACHE IV in patients with cancer admitted to intensive care unit (ICU in a single medical center in China.This is a retrospective observational cohort study including nine hundred and eighty one consecutive patients over a 2-year period.The hospital mortality rate was 4.5%. When all 981 patients were evaluated, the area under the receiver operating characteristic curve (AUROC, 95% Confidential Intervals of the three models in predicting hospital mortality were 0.948 (0.914-0.982, 0.863 (0.804-0.923, and 0.873 (0.813-0.934 for SAPS 3, APACHE II and APACHE IV respectively. The p values of Hosmer-Lemeshow statistics for the models were 0.759, 0.900 and 0.878 for SAPS 3, APACHE II and APACHE IV respectively. However, SAPS 3 and APACHE IV underestimated the in-hospital mortality with standardized mortality ratio (SMR of 1.5 and 1.17 respectively, while APACHE II overestimated the in-hospital mortality with SMR of 0.72. Further analysis showed that discrimination power was better with SAPS 3 than with APACHE II and APACHE IV whether for emergency surgical and medical patients (AUROC of 0.912 vs 0.866 and 0.857 or for scheduled surgical patients (AUROC of 0.945 vs 0.834 and 0.851. Calibration was good for all models (all p > 0.05 whether for scheduled surgical patients or emergency surgical and medical patients. However, in terms of SMR, SAPS 3 was both accurate in predicting the in-hospital mortality for emergency surgical and medical patients and for scheduled surgical patients, while APACHE IV and APACHE II were not.In this cohort, we found that APACHE II, APACHE IV and SAPS 3 models had good discrimination and calibration ability in predicting in-hospital mortality of critically ill patients with cancer in need of intensive care. Of

  13. The Prognostic Value of a Four-Dimensional CT Angiography-Based Collateral Grading Scale for Reperfusion Therapy in Acute Ischemic Stroke Patients.

    Science.gov (United States)

    Zhang, Sheng; Chen, Weili; Tang, Huan; Han, Quan; Yan, Shenqiang; Zhang, Xiaocheng; Chen, Qingmeng; Parsons, Mark; Wang, Shaoshi; Lou, Min

    2016-01-01

    Leptomeningeal collaterals, which affects tissue fate, are still challenging to assess. Four-dimensional CT angiography (4D CTA) originated from CT perfusion (CTP) provides the possibility of non-invasive and time-resolved assessment of leptomeningeal collateral flow. We sought to develop a comprehensive rating system to integrate the speed and extent of collateral flow on 4D CTA, and investigate its prognostic value for reperfusion therapy in acute ischemic stroke (AIS) patients. We retrospectively studied 80 patients with M1 ± internal carotid artery (ICA) occlusion who had baseline CTP before intravenous thrombolysis. The velocity and extent of collaterals were evaluated by regional leptomeningeal collateral score on peak phase (rLMC-P) and temporally fused intensity projections (tMIP) (rLMC-M) on 4D CTA, respectively. The cutoffs of rLMC-P and rLMC-M score for predicting good outcome (mRS score ≤ 2) were integrated to develop the collateral grading scale (CGS) (rating from 0-2). The CGS score was correlated with 3-months mRS score (non-recanalizers: ρ = -0.495, p = 0.01; recanalizers: ρ = -0.671, p < 0.001). Patients with intermediate or good collaterals (CGS score of 1 and 2) who recanalized were more likely to have good outcome than those without recanalization (p = 0.038, p = 0.018), while there was no significant difference in outcome in patients with poor collaterals (CGS score of 0) stratified by recanalization (p = 0.227). Identification of collaterals based on CGS may help to select good responders to reperfusion therapy in patients with large artery occlusion.

  14. Early prognostication markers in cardiac arrest patients treated with hypothermia.

    Science.gov (United States)

    Karapetkova, M; Koenig, M A; Jia, X

    2016-03-01

    Established prognostication markers, such as clinical findings, electroencephalography (EEG) and biochemical markers, used by clinicians to predict neurological outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. MEDLINE and Embase were searched for evidence on the current standards for neurological outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers and multimodal approaches for prognostication are included and reviewed. Whilst the prognostic accuracy of various tests after TH has been questioned, pupillary light reflexes and somatosensory evoked potentials are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 h after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as magnetic resonance imaging and computed tomography, can identify functional and structural brain injury but are not readily available at the patient's bedside because of limited availability and high costs. A multimodal algorithm composed of neurological examination, EEG-based quantitative testing and somatosensory evoked potentials, in conjunction with newer magnetic resonance imaging sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed more than 72 h after CA. © 2015 EAN.

  15. SERPINB3 in the chicken model of ovarian cancer: a prognostic factor for platinum resistance and survival in patients with epithelial ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Whasun Lim

    Full Text Available Serine protease inhibitors (SERPINs appear to be ubiquitously expressed in a variety of species and play important roles in pivotal physiological processes such as angiogenesis, immune responses, blood coagulation and fibronolysis. Of these, squamous cell carcinoma antigen 1 (SCCA1, also known as a SERPINB3, was first identified in squamous cell carcinoma tissue from the cervix of women. However, there is little known about the SERPINB3 expression in human epithelial ovarian cancer (EOC. Therefore, in the present study, we investigated the functional role of SERPINB3 gene in human EOC using chickens, the most relevant animal model. In 136 chickens, EOC was found in 10 (7.4%. SERPINB3 mRNA was induced in cancerous, but not normal ovaries of chickens (P<0.01, and it was abundant only in the glandular epithelium of cancerous ovaries of chickens. Further, several microRNAs, specifically miR-101, miR-1668 and miR-1681 were discovered to influence SERPINB3 expression via its 3'-UTR which suggests that post-transcriptional regulation influences SERPINB3 expression in chickens. SERPINB3 protein was localized predominantly to the glandular epithelium in cancerous ovaries of chickens, and it was abundant in the nucleus of both chicken and human ovarian cancer cell lines. In 109 human patients with EOC, 15 (13.8%, 66 (60.6% and 28 (25.7% patients showed weak, moderate and strong expression of SERPINB3 protein, respectively. Strong expression of SERPINB3 protein was a prognostic factor for platinum resistance (adjusted OR; odds ratio, 5.94; 95% Confidence Limits, 1.21-29.15, and for poor progression-free survival (PFS; adjusted HR; hazard ratio, 2.07; 95% CI; confidence interval, 1.03-4.41. Therefore, SERPINB3 may play an important role in ovarian carcinogenesis and be a novel biomarker for predicting platinum resistance and a poor prognosis for survival in patients with EOC.

  16. 12 A multi-centre randomised feasibility study evaluating the impact of a prognostic model for management of blunt chest wall trauma patients: stumbl trial.

    Science.gov (United States)

    Battle, Ceri; Hutchings, Hayley; Abbott, Zoe; O'neill, Claire; Groves, Sam; Watkins, Alan; Lecky, Fiona; Jones, Sally; Gagg, James; Body, Rick; Evans, Phillip

    2017-12-01

    A new prognostic model has been developed and externally validated, the aim of which is to assist in the management of the blunt chest wall trauma patient in the Emergency Department (ED). A definitive randomised controlled trial (impact trial), is required to assess the clinical and cost effectiveness of the new model, before it can be accepted in clinical practice. The purpose of this trial is to assess the feasibility and acceptability of such a definitive trial and inform its design. This feasibility trial is designed to test the methods of a multi-centre, cluster-randomised (stepped wedge) trial, with a substantial qualitative component. Four EDs in England and Wales will collect data for all blunt chest wall trauma patients over a five month period; in the initial period acting as the controls (normal care) and the second period, acting as the interventions (in which the new model will be used). Baseline measurements including completion of the SF-12v2 will be obtained on initial assessment in the ED. Patient outcome data will then be collected for any subsequent hospitalisations. Data collection will conclude with a six week follow-up completion of two surveys (SF-12v2 and Client Services Receipt Inventory).Analysis of outcomes will focus on feasibility, acceptability and trial processes and will include recruitment and retention rates, attendance at clinician training rates and use of model in the ED. Qualitative feedback will be obtained through clinician interviews and a research nurse focus group. An evaluation of the feasibility of health economics outcomes data will be completed. Wales Research Ethics Committee 6 granted approval for the trial in September 2016. Health Care Research Wales Research Permissions and the HRA have granted approval for the study. Patient recruitment commenced in February 2017. Planned dissemination is through publication in a peer-reviewed Emergency Medicine Journal, presentation at appropriate conferences and to

  17. Protocol for a multicentre randomised feasibility STUdy evaluating the impact of a prognostic model for Management of BLunt chest wall trauma patients: STUMBL trial.

    Science.gov (United States)

    Battle, Ceri; Abbott, Zoe; Hutchings, Hayley A; O'Neill, Claire; Groves, Sam; Watkins, Alan; Lecky, Fiona E; Jones, Sally; Gagg, James; Body, Richard; Evans, Philip A

    2017-07-10

    A new prognostic model has been developed and externally validated, the aim of which is to assist in the management of the blunt chest wall trauma patient in the emergency department (ED). A definitive randomised controlled trial (impact trial) is required to assess the clinical and cost effectiveness of the new model before it can be accepted in clinical practice. The purpose of this trial is to assess the feasibility and acceptability of such a definitive trial and inform its design. This feasibility trial is designed to test the methods of a multicentre, cluster-randomised (stepped- wedge) trial, with a substantial qualitative component. Four EDs in England and Wales will collect data for all blunt chest wall trauma patients over a 5-month period; in the initial period acting as the controls (normal care), and in the second period acting as the interventions (in which the new model will be used). Baseline measurements including completion of the SF-12v2 will be obtained on initial assessment in the ED. Patient outcome data will then be collected for any subsequent hospitalisations. Data collection will conclude with a 6-week follow-up completion of two surveys (SF-12v2 and Client Services Receipt Inventory). Analysis of outcomes will focus on feasibility, acceptability and trial processes and will include recruitment and retention rates, attendance at clinician training rates and use of model in the ED. Qualitative feedback will be obtained through clinician interviews and a research nurse focus group. An evaluation of the feasibility of health economics outcomes data will be completed. Wales Research Ethics Committee 6 granted approval for the trial in September 2016. Patient recruitment will commence in February 2017. Planned dissemination is through publication in a peer-reviewed Emergency Medicine Journal , presentation at appropriate conferences and to stakeholders at professional meetings. ISRCTN95571506; Pre-results. © Article author(s) (or their

  18. Morpho-molecular analysis as a prognostic model for repulsive feedback of the medicinal plant "Andrographis paniculata" to allogamy.

    Science.gov (United States)

    Valdiani, Alireza; Talei, Daryush; Javanmard, Arash; Tan, Soon Guan; Kadir, Mihdzar Abdul; Maziah, Mahmood

    2014-06-01

    Andrographis paniculata Nees. (AP) is a self-pollinated medicinal herb with a wide range of pharmaceutical properties, facing a low diversity in Malaysia. Cross-pollination of AP accessions leads to considerable rates of heterosis in the agro-morphological characteristics and anticancer phytochemicals of this eminent medicinal herb. However, the poor crossability of the plant at the interpopulation or intraspecific levels is an obstacle from the evolutionary and breeding points of view as an average of 4.56% crossability was recorded for AP in this study. Hence, this research aimed to elicit the impact of parental genetic distances (GDs) on the rate of crossability of AP using seven accessions in 21 possible cross combinations. To this end, a set of 55 randomly amplified polymorphic DNA (RAPD) primers and a total of 13 agro-morphological markers were employed to test the hypothesis. Twenty-two out of the 55 RAPD primers amplified a total of 257 bands of which 107 bands were found to be polymorphic. The principal component analysis (PCA) based on the RAPD markers revealed that the studied AP accessions were distributed to three distinct groups. Furthermore, it was noticed that even a minor increase in GD between two parents can cause a decline in their crossability. Unlike, the morphological-based GDs acted neutrally to crossability. This finding suggests that, despite the low genetic diversity among the Malaysian APs, a population prescreening using RAPD markers would be useful to enhance the rate of fruit set through selecting the genetically adjacent parents. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Comparison of Two Probabilistic Fatigue Damage Assessment Approaches Using Prognostic Performance Metrics

    Directory of Open Access Journals (Sweden)

    Xuefei Guan

    2011-01-01

    Full Text Available In this paper, two probabilistic prognosis updating schemes are compared. One is based on the classical Bayesian approach and the other is based on newly developed maximum relative entropy (MRE approach. The algorithm performance of the two models is evaluated using a set of recently developed prognostics-based metrics. Various uncertainties from measurements, modeling, and parameter estimations are integrated into the prognosis framework as random input variables for fatigue damage of materials. Measures of response variables are then used to update the statistical distributions of random variables and the prognosis results are updated using posterior distributions. Markov Chain Monte Carlo (MCMC technique is employed to provide the posterior samples for model updating in the framework. Experimental data are used to demonstrate the operation of the proposed probabilistic prognosis methodology. A set of prognostics-based metrics are employed to quantitatively evaluate the prognosis performance and compare the proposed entropy method with the classical Bayesian updating algorithm. In particular, model accuracy, precision, robustness and convergence are rigorously evaluated in addition to the qualitative visual comparison. Following this, potential development and improvement for the prognostics-based metrics are discussed in detail.

  20. Graph Model Based Indoor Tracking

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin

    2009-01-01

    The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...

  1. Computer Based Modelling and Simulation

    Indian Academy of Sciences (India)

    GENERAL I ARTICLE. Computer Based ... universities, and later did system analysis, ... sonal computers (PC) and low cost software packages and tools. They can serve as useful learning experience through student projects. Models are .... Let us consider a numerical example: to calculate the velocity of a trainer aircraft ...

  2. Prognostic factors of breast cancer

    International Nuclear Information System (INIS)

    Gonzalez Ortega, Jose Maria; Morales Wong, Mario Miguel; Lopez Cuevas, Zoraida; Diaz Valdez, Marilin

    2011-01-01

    The prognostic factors must to be differentiated of the predictive ones. A prognostic factor is any measurement used at moment of the surgery correlated with the free interval of disease or global survival in the absence of the systemic adjuvant treatment and as result is able to correlate with the natural history of the disease. In contrast, a predictive factor is any measurement associated with the response to a given treatment. Among the prognostic factors of the breast cancer are included the clinical, histological, biological, genetic and psychosocial factors. In present review of psychosocial prognostic factors has been demonstrated that the stress and the depression are negative prognostic factors in patients presenting with breast cancer. It is essential to remember that the assessment of just one prognostic parameter is a help but it is not useful to clinical and therapeutic management of the patient.(author)

  3. Component-Level Prognostics Health Management Framework for Passive Components - Advanced Reactor Technology Milestone: M2AT-15PN2301043

    Energy Technology Data Exchange (ETDEWEB)

    Ramuhalli, Pradeep; Roy, Surajit; Hirt, Evelyn H.; Prowant, Matthew S.; Pitman, Stan G.; Tucker, Joseph C.; Dib, Gerges; Pardini, Allan F.

    2015-06-19

    This report describes research results to date in support of the integration and demonstration of diagnostics technologies for prototypical advanced reactor passive components (to establish condition indices for monitoring) with model-based prognostics methods. Achieving this objective will necessitate addressing several of the research gaps and technical needs described in previous technical reports in this series.

  4. State of the art and taxonomy of prognostics approaches, trends of prognostics applications and open issues towards maturity at different technology readiness levels

    Science.gov (United States)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine

    2017-09-01

    Integrating prognostics to a real application requires a certain maturity level and for this reason there is a lack of success stories about development of a complete Prognostics and Health Management system. In fact, the maturity of prognostics is closely linked to data and domain specific entities like modeling. Basically, prognostics task aims at predicting the degradation of engineering assets. However, practically it is not possible to precisely predict the impending failure, which requires a thorough understanding to encounter different sources of uncertainty that affect prognostics. Therefore, different aspects crucial to the prognostics framework, i.e., from monitoring data to remaining useful life of equipment need to be addressed. To this aim, the paper contributes to state of the art and taxonomy of prognostics approaches and their application perspectives. In addition, factors for prognostics approach selection are identified, and new case studies from component-system level are discussed. Moreover, open challenges toward maturity of the prognostics under uncertainty are highlighted and scheme for an efficient prognostics approach is presented. Finally, the existing challenges for verification and validation of prognostics at different technology readiness levels are discussed with respect to open challenges.

  5. Model-based sensor diagnosis

    International Nuclear Information System (INIS)

    Milgram, J.; Dormoy, J.L.

    1994-09-01

    Running a nuclear power plant involves monitoring data provided by the installation's sensors. Operators and computerized systems then use these data to establish a diagnostic of the plant. However, the instrumentation system is complex, and is not immune to faults and failures. This paper presents a system for detecting sensor failures using a topological description of the installation and a set of component models. This model of the plant implicitly contains relations between sensor data. These relations must always be checked if all the components are functioning correctly. The failure detection task thus consists of checking these constraints. The constraints are extracted in two stages. Firstly, a qualitative model of their existence is built using structural analysis. Secondly, the models are formally handled according to the results of the structural analysis, in order to establish the constraints on the sensor data. This work constitutes an initial step in extending model-based diagnosis, as the information on which it is based is suspect. This work will be followed by surveillance of the detection system. When the instrumentation is assumed to be sound, the unverified constraints indicate errors on the plant model. (authors). 8 refs., 4 figs

  6. Physics-of-Failure Approach to Prognostics

    Science.gov (United States)

    Kulkarni, Chetan S.

    2017-01-01

    As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of the electrical components present in the system. In case of electric vehicles, computing remaining battery charge is safety-critical. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. In this presentation our approach to develop a system level health monitoring safety indicator for different electronic components is presented which runs estimation and prediction algorithms to determine state-of-charge and estimate remaining useful life of respective components. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

  7. A Prognostic Model for Estimating the Time to Virologic Failure in HIV-1 Infected Patients Undergoing a New Combination Antiretroviral Therapy Regimen

    Directory of Open Access Journals (Sweden)

    Micheli Valeria

    2011-06-01

    Full Text Available Abstract Background HIV-1 genotypic susceptibility scores (GSSs were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed. Methods We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90th day after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems (Rega, ANRS and HIVdb and other covariates by means of Cox regression and random survival forests (RSF. Prediction models were validated via the bootstrap and c-index measure. Results The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70, while RSF showed a better performance (c-index≈0.73, p Conclusions GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART.

  8. Serum levels of LDH, CEA, and CA19-9 have prognostic roles on survival in patients with metastatic pancreatic cancer receiving gemcitabine-based chemotherapy.

    Science.gov (United States)

    Tas, Faruk; Karabulut, Senem; Ciftci, Rumeysa; Sen, Fatma; Sakar, Burak; Disci, Rian; Duranyildiz, Derya

    2014-06-01

    Serum LDH, CEA, and CA19-9 levels are important tumor markers in pancreatic cancer. The purpose of this study was to evaluate the clinical significance of serum LDH, CEA, and CA19-9 levels in metastatic pancreatic cancer (MPC) receiving gemcitabine-based chemotherapy. In this retrospective study, we analyzed the outcome of 196 MPC patients who are treated with gemcitabine-based chemotherapy in our clinic. Positivity rates of serum LDH, CEA, and CA19-9 were 22, 40, and 83 %, respectively. Likewise, the rates of very high serum levels of tumor markers were correlated with these positivity rates (9 % for LDH, 30 % for CEA, and 55 % for CA19-9). The serum LDH levels were significantly higher in older patients (p = 0.05) and also in the patients with large tumors (p = 0.05), hepatic metastasis (p = 0.01), hypoalbuminemia (p = 0.01), and unresponsive to chemotherapy (p = 0.04). However, no correlation was found between both serum CEA and CA19-9 levels and possible prognostic factors (p > 0.05). The significant relationships were found between the serum levels of CEA and CA19-9 (r s = 0.24, p = 0.004), and serum LDH and CEA (r(s) = 0.193, p = 0.02). But, there was no correlation between serum LDH and CA19-9 levels (p = 0.39). One-year overall survival rate was 12.8 % (95 % CI 8-18). Increased serum levels of all the tumor markers significantly had adverse affect on survival (p = 0.001 for LDH, p = 0.002 for CEA, and p = 0.007 for CA19-9). However, no difference was observed in between high levels and very high levels of serum markers for all tumor markers (p > 0.05). Patients with normal serum levels of all three tumor markers had better outcome than others (p = 0.002) and those with normal serum LDH and CEA levels (whatever CA19-9) levels had associated with better survival compared with other possible alternatives (p CEA, and CA19-9 had significant affect on survival in MPC patients.

  9. Prognostic value of admission plasma glucose in non-diabetic ...

    African Journals Online (AJOL)

    Prognostic value of admission plasma glucose in non-diabetic Nigerians with stroke. ... International Journal of Medicine and Health Development ... Outcome was measured using the Modified Rankin scale based on the last score of each ...

  10. Prognostic factors for medulloblastoma

    International Nuclear Information System (INIS)

    Jenkin, Derek; Al Shabanah, Mohamed; Al Shail, Essam; Gray, Alan; Hassounah, Maher; Khafaga, Yasser; Kofide, Amani; Mustafa, Mahmoud; Schultz, Henrik

    2000-01-01

    Purpose: To evaluate prognostic factors for medulloblastoma. Methods and Materials: One hundred and seventy-three consecutive patients with medulloblastoma, treated at King Faisal Specialist Hospital (KFSH) from 1988-1997, were reviewed. Eighty-four percent were children less than 15 years old. From 1988-1994, treatment was at the discretion of the investigator. From 1994-1998, patients entered a single-arm best practice protocol in which, in staged patients, the surgical intent was total resection, standard radiation treatment was defined, and adjuvant chemotherapy was given to a 'high-risk' subset. Results: For 150 patients who completed surgical and radiation treatment, the 5-year survival rate was 58%, compared with 0% for 16 patients who were unable to start or complete radiation treatment. For staged patients, the 5-year survival was M0 + M1, 78% and M2 + M3, 21% (p 14 years and gross cystic/necrotic features in the primary tumor. The size of the primary tumor, the degree of hydrocephalus at diagnosis, the presence of residual tumor in the post-operative CT/MRI, and the functional status of the patient prior to radiation treatment were not significant factors. Conclusions: Stage M0 + M1 was the most powerful favorable prognostic factor. In Saudi Arabia more patients present with advanced disseminated disease, 41% M2 + M3, than in the West, and this impacts adversely on overall survival. Total resection and standard radiation treatment were not sensitive prognostic factors in a treatment environment in which 78% of patients underwent at least 90% tumor resection and 60% received standard radiation treatment. In order to improve the proportion of patients able to complete radiation treatment, consideration should be given to limiting resection when the attainment of total resection is likely to be morbid, and to delaying rather than omitting radiation treatment in the patient severely compromised postoperatively

  11. [Prognostic value of JAK2, MPL and CALR mutations in Chinese patients with primary myelofibrosis].

    Science.gov (United States)

    Xu, Z F; Li, B; Liu, J Q; Li, Y; Ai, X F; Zhang, P H; Qin, T J; Zhang, Y; Wang, J Y; Xu, J Q; Zhang, H L; Fang, L W; Pan, L J; Hu, N B; Qu, S Q; Xiao, Z J

    2016-07-01

    .7, respectively). The impact of the CALR type- 2 mutations or no detectable driver mutation on survival was independent of current prognostic scoring systems. The DIPSS- Chinese molecular prognostic model based on the molecular features of Chinese patients was proposed and worked well for prognostic indication.

  12. Systematic review of renal carcinoma prognostic factors.

    Science.gov (United States)

    Lorente, D; Trilla, E; Meseguer, A; Planas, J; Placer, J; Celma, A; Salvador, C; Regis, L; Morote, J

    2017-05-01

    The natural history of renal cell carcinoma is heterogeneous. Some scenarios can be found in terms of clinical presentation, clinical evolution or type of recurrence (local/metastatic). The aim of this publication is to analyze the most important prognostic factors published in the literature. A literature review ob published papers was performed using the Pubmed, from first Motzer's classification published in 1999 to 2015, according to PRISMA declaration. Search was done using the following keywords: kidney neoplasm, kidney cancer, renal cell carcinoma, prognostic factors, mortality, survival and disease progression. Papers were classified according to level of evidence, the number of patients included and the type of study performed. The evolution in the knowledge of molecular pathways related to renal oncogenesis and the new targeted therapies has left to remain obsolete the old prognostic models. It's necessary to perform a continuous review to actualize nomograms and to adapt them to the new scenarios. Is necessary to perform a proper external validation of existing prognostic factors using prospective and multicentric studies to add them into the daily urologist clinical practice. Copyright © 2016 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

  13. Model-based security testing

    OpenAIRE

    Schieferdecker, Ina; Großmann, Jürgen; Schneider, Martin

    2012-01-01

    Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security...

  14. Requirements Flowdown for Prognostics and Health Management

    Science.gov (United States)

    Goebel, Kai; Saxena, Abhinav; Roychoudhury, Indranil; Celaya, Jose R.; Saha, Bhaskar; Saha, Sankalita

    2012-01-01

    Prognostics and Health Management (PHM) principles have considerable promise to change the game of lifecycle cost of engineering systems at high safety levels by providing a reliable estimate of future system states. This estimate is a key for planning and decision making in an operational setting. While technology solutions have made considerable advances, the tie-in into the systems engineering process is lagging behind, which delays fielding of PHM-enabled systems. The derivation of specifications from high level requirements for algorithm performance to ensure quality predictions is not well developed. From an engineering perspective some key parameters driving the requirements for prognostics performance include: (1) maximum allowable Probability of Failure (PoF) of the prognostic system to bound the risk of losing an asset, (2) tolerable limits on proactive maintenance to minimize missed opportunity of asset usage, (3) lead time to specify the amount of advanced warning needed for actionable decisions, and (4) required confidence to specify when prognosis is sufficiently good to be used. This paper takes a systems engineering view towards the requirements specification process and presents a method for the flowdown process. A case study based on an electric Unmanned Aerial Vehicle (e-UAV) scenario demonstrates how top level requirements for performance, cost, and safety flow down to the health management level and specify quantitative requirements for prognostic algorithm performance.

  15. Model-Based Security Testing

    Directory of Open Access Journals (Sweden)

    Ina Schieferdecker

    2012-02-01

    Full Text Available Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing, and the usage of security test patterns. This paper provides a survey on MBST techniques and the related models as well as samples of new methods and tools that are under development in the European ITEA2-project DIAMONDS.

  16. CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas

    International Nuclear Information System (INIS)

    Ganeshan, B.; Miles, K.A.; Shortman, R.; Afaq, A.; Ardeshna, K.M.; Groves, A.M.; Kayani, I.; Babikir, S.

    2017-01-01

    The purpose of this study was to investigate the ability of computed tomography texture analysis (CTTA) to provide additional prognostic information in patients with Hodgkin's lymphoma (HL) and high-grade non-Hodgkin's lymphoma (NHL). This retrospective, pilot-study approved by the IRB comprised 45 lymphoma patients undergoing routine 18F-FDG-PET-CT. Progression-free survival (PFS) was determined from clinical follow-up (mean-duration: 40 months; range: 10-62 months). Non-contrast-enhanced low-dose CT images were submitted to CTTA comprising image filtration to highlight features of different sizes followed by histogram-analysis using kurtosis. Prognostic value of CTTA was compared to PET FDG-uptake value, tumour-stage, tumour-bulk, lymphoma-type, treatment-regime, and interim FDG-PET (iPET) status using Kaplan-Meier analysis. Cox regression analysis determined the independence of significantly prognostic imaging and clinical features. A total of 27 patients had aggressive NHL and 18 had HL. Mean PFS was 48.5 months. There was no significant difference in pre-treatment CTTA between the lymphoma sub-types. Kaplan-Meier analysis found pre-treatment CTTA (medium feature scale, p=0.010) and iPET status (p<0.001) to be significant predictors of PFS. Cox analysis revealed that an interaction between pre-treatment CTTA and iPET status was the only independent predictor of PFS (HR: 25.5, 95% CI: 5.4-120, p<0.001). Specifically, pre-treatment CTTA risk stratified patients with negative iPET. CTTA can potentially provide prognostic information complementary to iPET for patients with HL and aggressive NHL. (orig.)

  17. Prognostic factors in lupus nephritis

    DEFF Research Database (Denmark)

    Faurschou, Mikkel; Starklint, Henrik; Halberg, Poul

    2006-01-01

    To evaluate the prognostic significance of clinical and renal biopsy findings in an unselected cohort of patients with systemic lupus erythematosus (SLE) and nephritis.......To evaluate the prognostic significance of clinical and renal biopsy findings in an unselected cohort of patients with systemic lupus erythematosus (SLE) and nephritis....

  18. Prognostic and survival analysis of presbyopia: The healthy twin study

    Science.gov (United States)

    Lira, Adiyani; Sung, Joohon

    2015-12-01

    Presbyopia, a vision condition in which the eye loses its flexibility to focus on near objects, is part of ageing process which mostly perceptible in the early or mid 40s. It is well known that age is its major risk factor, while sex, alcohol, poor nutrition, ocular and systemic diseases are known as common risk factors. However, many other variables might influence the prognosis. Therefore in this paper we developed a prognostic model to estimate survival from presbyopia. 1645 participants which part of the Healthy Twin Study, a prospective cohort study that has recruited Korean adult twins and their family members based on a nation-wide registry at public health agencies since 2005, were collected and analyzed by univariate analysis as well as Cox proportional hazard model to reveal the prognostic factors for presbyopia while survival curves were calculated by Kaplan-Meier method. Besides age, sex, diabetes, and myopia; the proposed model shows that education level (especially engineering program) also contribute to the occurrence of presbyopia as well. Generally, at 47 years old, the chance of getting presbyopia becomes higher with the survival probability is less than 50%. Furthermore, our study shows that by stratifying the survival curve, MZ has shorter survival with average onset time about 45.8 compare to DZ and siblings with 47.5 years old. By providing factors that have more effects and mainly associate with presbyopia, we expect that we could help to design an intervention to control or delay its onset time.

  19. Elevated neutrophil and monocyte counts in peripheral blood are associated with poor survival in patients with metastatic melanoma: a prognostic model

    DEFF Research Database (Denmark)

    Schmidt, H; Bastholt, L; Geertsen, P

    2005-01-01

    factors in univariate analyses. Subsequently, a multivariate Cox's regression analysis identified elevated LDH (Pperformance status of 2 (P=0.008, hazard ratio 1.6) as independent prognostic factors for poor survival...... of several phase II protocols and the majority received treatment with intermediate dose subcutaneous IL-2 and interferon-alpha. Neutrophil and monocyte counts, lactate dehydrogenase (LDH), number of metastatic sites, location of metastases and performance status were all statistically significant prognostic...... survival of 12.6 months (95% confidence interval (CI), 11.4-13.8), 6.0 months (95% CI, 4.8-7.2) and 3.4 months (95% CI, 1.2-5.6), respectively. The low-risk group encompassed the majority of long-term survivors, whereas the patients in the high-risk group with a very poor prognosis should probably...

  20. Towards A Model-based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

    Data.gov (United States)

    National Aeronautics and Space Administration — A remaining useful life prediction methodology for elec- trolytic capacitors is presented. This methodology adopts a Kalman filter approach in conjunction with an...

  1. Crowdsourcing Based 3d Modeling

    Science.gov (United States)

    Somogyi, A.; Barsi, A.; Molnar, B.; Lovas, T.

    2016-06-01

    Web-based photo albums that support organizing and viewing the users' images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

  2. CROWDSOURCING BASED 3D MODELING

    Directory of Open Access Journals (Sweden)

    A. Somogyi

    2016-06-01

    Full Text Available Web-based photo albums that support organizing and viewing the users’ images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

  3. Skull base chordomas: treatment outcome and prognostic factors in adult patients following conformal treatment with 3D planning and high dose fractionated combined proton and photon radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Munzenrider, J E; Hug, E; McManus, P; Adams, J; Efird, J; Liebsch, N J

    1995-07-01

    Purpose: To report treatment outcome and prognostic factors for local recurrence-free survival and overall survival in adult patients with skull base chordomas treated with 3D planning and high dose fractionated combined proton and photon radiation therapy. Methods and Materials: From 1975 through 1993, 132 adult patients with skull base chordomas were treated with fractionated combined proton and photon radiation therapy. Seventy five patients (57%) were male and 57 (43%) female. Age ranged from 19 to 80 years (median 45.5 years). All pathology was verified at MGH by a single pathologist. Ninety six had non-chondroid (NCC) and 36 chondroid chordomas (CC), respectively. Median prescribed dose was 68.7 CGE (CGE, Cobalt Gray-equivalent: proton Gy X RBE 1.1 + photon Gy), ranging from 36 to 79.2 CGE; 95% received {>=} 66.6 CGE. Between 70 and 100% of the dose was given with the 160 MeV proton beam at the Harvard Cyclotron. 3D CT-based treatment planning has been employed in all patients treated since 1980. Median follow-up was 46 months (range 2-158 months). Results: Treatment outcome was evaluated in terms of local recurrence-free survival (LRFS) and disease specific survival (DSS), as well as treatment-related morbidity. Local failure (LF), defined as progressive neurological deficit with definite increase in tumor volume on CT or MRI scan, occurred in 39 patients (29.5%). LF was more common among women than among men:(26(57)) (46%) vs (13(75)) (17%), respectively. Thirty three of the 39 LF were seen in non-chondroid chordoma patients, with 6 occurring in patients with the chondroid variant (34% of NCC and 17% of CC), respectively. Distant metastasis was documented in 8 patients. LRFS was 81 {+-} 5.8%, 59 {+-} 8.3%, and 43 {+-} 10.4%, and DSS was 94 {+-} 3.6%, 80 {+-} 6.7%, and 50 {+-} 10.7% at 36, 60, and 96 months, respectively, for the total group. LRFS and DSS were not significantly different for patients with NCC than those with CC (p > .05). Gender was

  4. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    OpenAIRE

    Inti eZlobec; Inti eZlobec; Michel P Bihl; Anja eFoerster; Alex eRufle; Luigi eTerracciano; Alessandro eLugli; Alessandro eLugli

    2012-01-01

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related pro...

  5. A novel prognostic six-CpG signature in glioblastomas.

    Science.gov (United States)

    Yin, An-An; Lu, Nan; Etcheverry, Amandine; Aubry, Marc; Barnholtz-Sloan, Jill; Zhang, Lu-Hua; Mosser, Jean; Zhang, Wei; Zhang, Xiang; Liu, Yu-He; He, Ya-Long

    2018-03-01

    We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM). A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation. An integrative analysis of multidimensional TCGA data was performed to molecularly characterize different risk tumors. The six-CpG risk-score signature robustly predicted overall survival (OS) in all discovery and validation cohorts and in a treatment-independent manner. It also predicted progression-free survival (PFS) in available patients. The multimarker epigenetic signature was demonstrated as an independent prognosticator and had better performance than known molecular indicators such as glioma-CpG island methylator phenotype (G-CIMP) and proneural subtype. The defined risk subgroups were molecularly distinct; high-risk tumors were biologically more aggressive with concordant activation of proangiogenic signaling at multimolecular levels. Accordingly, we observed better OS benefits of bevacizumab-contained therapy to high-risk patients in independent sets, supporting its implication in guiding usage of antiangiogenic therapy. Finally, the six-CpG signature refined the risk classification based on G-CIMP and MGMT methylation status. The novel six-CpG signature is a robust and independent prognostic indicator for GBMs and is of promising value to improve personalized management. © 2018 John Wiley & Sons Ltd.

  6. Prognostic indices for brain metastases – usefulness and challenges

    Directory of Open Access Journals (Sweden)

    Nieder Carsten

    2009-03-01

    Full Text Available Abstract Background This review addresses the strengths and weaknesses of 6 different prognostic indices, published since the Radiation Therapy Oncology Group (RTOG developed and validated the widely used 3-tiered prognostic index known as recursive partitioning analysis (RPA classes, i.e. between 1997 and 2008. In addition, other analyses of prognostic factors in groups of patients, which typically are underrepresented in large trials or databases, published in the same time period are reviewed. Methods Based on a systematic literature search, studies with more than 20 patients were included. The methods and results of prognostic factor analyses were extracted and compared. The authors discuss why current data suggest a need for a more refined index than RPA. Results So far, none of the indices has been derived from analyses of all potential prognostic factors. The 3 most recently published indices, including the RTOG's graded prognostic assessment (GPA, all expanded from the primary 3-tiered RPA system to a 4-tiered system. The authors' own data confirm the results of the RTOG GPA analysis and support further evaluation of this tool. Conclusion This review provides a basis for further refinement of the current prognostic indices by identifying open questions regarding, e.g., performance of the ideal index, evaluation of new candidate parameters, and separate analyses for different cancer types. Unusual primary tumors and their potential differences in biology or unique treatment approaches are not well represented in large pooled analyses.

  7. Cluster-based analysis of multi-model climate ensembles

    Science.gov (United States)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models.

  8. Prognostic value of platelet-to-lymphocyte ratio in pancreatic cancer: a comprehensive meta-analysis of 17 cohort studies.

    Science.gov (United States)

    Zhou, Yongping; Cheng, Sijin; Fathy, Abdel Hamid; Qian, Haixin; Zhao, Yongzhao

    2018-01-01

    Several studies were conducted to explore the prognostic value of platelet-to-lymphocyte ratio (PLR) in pancreatic cancer and have reported contradictory results. This study aims to summarize the prognostic role of PLR in pancreatic cancer. Embase, PubMed and Cochrane Library were completely searched. The cohort studies focusing on the prognostic role of PLR in pancreatic cancer were eligible. The overall survival (OS) and progression-free survival (PFS) were analyzed. Fifteen papers containing 17 cohort studies with pancreatic cancer were identified. The results showed patients that with low PLR might have longer OS when compared to the patients with high PLR (hazard ratio=1.28, 95% CI=1.17-1.40, P analysis model, ethnicity, sample size and cut-off value. Further analyses based on the adjusted potential confounders were conducted, including CA199, neutrophil-to-lymphocyte ratio, modified Glasgow Prognostic Score, albumin, C-reactive protein, Eastern Cooperative Oncology Group, stage, tumor size, nodal involvement, tumor differentiation, margin status, age and gender, which confirmed that low PLR was a protective factor in pancreatic cancer. In addition, low PLR was significantly associated with longer PFS when compared to high PLR in pancreatic cancer (hazard ratio=1.27, 95% CI=1.03-1.57, P =0.03; I 2 =33%). In conclusion, it was found that high PLR is an unfavorable predictor of OS and PFS in patients with pancreatic cancer, and PLR is a promising prognostic biomarker for pancreatic cancer.

  9. Development and Validation of a New Prognostic System for Patients with Hepatocellular Carcinoma.

    Directory of Open Access Journals (Sweden)

    Fabio Farinati

    2016-04-01

    Full Text Available Prognostic assessment in patients with hepatocellular carcinoma (HCC remains controversial. Using the Italian Liver Cancer (ITA.LI.CA database as a training set, we sought to develop and validate a new prognostic system for patients with HCC.Prospective collected databases from Italy (training cohort, n = 3,628; internal validation cohort, n = 1,555 and Taiwan (external validation cohort, n = 2,651 were used to develop the ITA.LI.CA prognostic system. We first defined ITA.LI.CA stages (0, A, B1, B2, B3, C using only tumor characteristics (largest tumor diameter, number of nodules, intra- and extrahepatic macroscopic vascular invasion, extrahepatic metastases. A parametric multivariable survival model was then used to calculate the relative prognostic value of ITA.LI.CA tumor stage, Eastern Cooperative Oncology Group (ECOG performance status, Child-Pugh score (CPS, and alpha-fetoprotein (AFP in predicting individual survival. Based on the model results, an ITA.LI.CA integrated prognostic score (from 0 to 13 points was constructed, and its prognostic power compared with that of other integrated systems (BCLC, HKLC, MESIAH, CLIP, JIS. Median follow-up was 58 mo for Italian patients (interquartile range, 26-106 mo and 39 mo for Taiwanese patients (interquartile range, 12-61 mo. The ITA.LI.CA integrated prognostic score showed optimal discrimination and calibration abilities in Italian patients. Observed median survival in the training and internal validation sets was 57 and 61 mo, respectively, in quartile 1 (ITA.LI.CA score ≤ 1, 43 and 38 mo in quartile 2 (ITA.LI.CA score 2-3, 23 and 23 mo in quartile 3 (ITA.LI.CA score 4-5, and 9 and 8 mo in quartile 4 (ITA.LI.CA score > 5. Observed and predicted median survival in the training and internal validation sets largely coincided. Although observed and predicted survival estimations were significantly lower (log-rank test, p < 0.001 in Italian than in Taiwanese patients, the ITA.LI.CA score maintained

  10. Model-Based Diagnosis and Prognosis of a Water Recycling System

    Science.gov (United States)

    Roychoudhury, Indranil; Hafiychuk, Vasyl; Goebel, Kai Frank

    2013-01-01

    A water recycling system (WRS) deployed at NASA Ames Research Center s Sustainability Base (an energy efficient office building that integrates some novel technologies developed for space applications) will serve as a testbed for long duration testing of next generation spacecraft water recycling systems for future human spaceflight missions. This system cleans graywater (waste water collected from sinks and showers) and recycles it into clean water. Like all engineered systems, the WRS is prone to standard degradation due to regular use, as well as other faults. Diagnostic and prognostic applications will be deployed on the WRS to ensure its safe, efficient, and correct operation. The diagnostic and prognostic results can be used to enable condition-based maintenance to avoid unplanned outages, and perhaps extend the useful life of the WRS. Diagnosis involves detecting when a fault occurs, isolating the root cause of the fault, and identifying the extent of damage. Prognosis involves predicting when the system will reach its end of life irrespective of whether an abnormal condition is present or not. In this paper, first, we develop a physics model of both nominal and faulty system behavior of the WRS. Then, we apply an integrated model-based diagnosis and prognosis framework to the simulation model of the WRS for several different fault scenarios to detect, isolate, and identify faults, and predict the end of life in each fault scenario, and present the experimental results.

  11. Colorectal Cancer: Prognostic Values

    Directory of Open Access Journals (Sweden)

    Suzana Manxhuka-Kerliu

    2009-02-01

    Full Text Available After lung cancer colorectal cancer (Cc is ranked the second, as a cause of cancer-related death. The purpose of this study was to analyze the Cc cases in our material with respect to all prognostic values including histological type and grade, vascular invasion, perineural invasion, and tumor border features. There were investigated 149 cases of resection specimen with colorectal cancer, which were fixed in buffered neutral formalin and embedded in paraffin. Tissue sections (4(µm thick were cut and stained with H&E. Adenocarcinoma was the most frequent histological type found in 85,90% of cases, in 60,94% of males and 39,06% of females; squamous cell carcinoma in 7,38%, in 63,63% of males and 36,36% of females; mucinous carcinoma in 4,68%, in 57,15% of males and 42,85% of females; while adenosquamous carcinoma, undifferentiated carcinoma and carcinoma in situ in 0,71% of cases each. Dukes' classification was used in order to define the depth of invasion. Dukes B was found in 68,45% of cases, whereas in 31,54% of cases Dukes C was found. As far as histological grading is concerned, Cc was mostly with moderate differentiation (75,16% with neither vascular nor perineural invasion. Resection margins were in all cases free of tumor. Our data indicate that the pathologic features of the resection specimen constitute the most powerful predictors of postoperative outcome in Cc. Dukes' stage and degree of differentiation provide independent prognostic information in Cc. However, differentiation should be assessed by the worst pattern.

  12. Machinery prognostics and prognosis oriented maintenance management

    CERN Document Server

    Yan, Jihong

    2014-01-01

    This book gives a complete presentatin of the basic essentials of machinery prognostics and prognosis oriented maintenance management, and takes a look at the cutting-edge discipline of intelligent failure prognosis technologies for condition-based maintenance.  Latest research results and application methods are introduced for signal processing, reliability moelling, deterioration evaluation, residual life prediction and maintenance-optimization as well as applications of these methods.

  13. Prognostic factors for mortality due to pneumonia among adults from different age groups in Singapore and mortality predictions based on PSI and CURB-65.

    Science.gov (United States)

    Zhang, Zoe Xz; Yong, Yang; Tan, Wan C; Shen, Liang; Ng, Han Seong; Fong, Kok Yong

    2017-08-14

    Pneumonia is associated with considerable mortality. However, the information on age-specific prognostic factors for death from pneumonia is limited. Patients hospitalised with a diagnosis of pneumonia through the emergency department were stratified into three age groups: 18-64 years; 65-84 years; and ≥ 85 years. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were conducted to evaluate prognostic factors for mortality and the performance of pneumonia severity scoring tools for mortality prediction. There were 1,902 patients (18-64 years: 614 [32.3%]; 65-84 years: 944 [49.6%]; ≥ 85 years: 344 [18.1%]) enrolled. Mortality rates increased with age (18-64 years: 7.3%; 65-84 years: 16.1%; ≥ 85 years: 29.7%; p aged 18-64 years. Male gender, malignancy, congestive heart failure and eight other parameters reflecting acute disease severity were associated with mortality among patients aged 65-84 years. For patients aged ≥ 85 years, altered mental status, tachycardia, blood urea nitrogen, hypoxaemia, arterial pH and pleural effusion were significantly predictive of mortality. Pneumonia Severity Index (PSI) was more sensitive than CURB-65 (Confusion, Uraemia, Respiratory rate ≥ 30 per minute, low Blood pressure, age 65 years or older) for mortality prediction across all age groups. The predictive effect of prognostic factors for mortality varied among patients with pneumonia from the different age groups. PSI performed significantly better than CURB-65 for mortality prediction, but its discriminative power decreased with advancing age.

  14. Metabolic Tumor Volume as a Prognostic Imaging-Based Biomarker for Head-and-Neck Cancer: Pilot Results From Radiation Therapy Oncology Group Protocol 0522

    Energy Technology Data Exchange (ETDEWEB)

    Schwartz, David L., E-mail: david.schwartz@utsw.edu [Department of Radiation Oncology, University of Texas Southwestern School of Medicine, Dallas, Texas (United States); Harris, Jonathan [Radiation Therapy Oncology Group Statistical Center, Philadelphia, Pennsylvania (United States); Yao, Min [Department of Radiation Oncology, Case Western Reserve University School of Medicine, Cleveland, Ohio (United States); Rosenthal, David I. [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Opanowski, Adam; Levering, Anthony [American College of Radiology Imaging Network, Philadelphia, Pennsylvania (United States); Ang, K. Kian [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Trotti, Andy M. [Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida (United States); Garden, Adam S. [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Jones, Christopher U. [Sutter Medical Group, Sacramento, California (United States); Harari, Paul [Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (United States); Foote, Robert [Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (United States); Holland, John [Department of Radiation Medicine, Oregon Health & Science University, Portland, Oregon (United States); Zhang, Qiang [Radiation Therapy Oncology Group Statistical Center, Philadelphia, Pennsylvania (United States); Le, Quynh-Thu [Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California (United States)

    2015-03-15

    Purpose: To evaluate candidate fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) imaging biomarkers for head-and-neck chemoradiotherapy outcomes in the cooperative group trial setting. Methods and Materials: Radiation Therapy Oncology Group (RTOG) protocol 0522 patients consenting to a secondary FDG-PET/CT substudy were serially imaged at baseline and 8 weeks after radiation. Maximum standardized uptake value (SUVmax), SUV peak (mean SUV within a 1-cm sphere centered on SUVmax), and metabolic tumor volume (MTV) using 40% of SUVmax as threshold were obtained from primary tumor and involved nodes. Results: Of 940 patients entered onto RTOG 0522, 74 were analyzable for this substudy. Neither high baseline SUVmax nor SUVpeak from primary or nodal disease were associated with poor treatment outcomes. However, primary tumor MTV above the cohort median was associated with worse local-regional control (hazard ratio 4.01, 95% confidence interval 1.28-12.52, P=.02) and progression-free survival (hazard ratio 2.34, 95% confidence interval 1.02-5.37, P=.05). Although MTV and T stage seemed to correlate (mean MTV 6.4, 13.2, and 26.8 for T2, T3, and T4 tumors, respectively), MTV remained a strong independent prognostic factor for progression-free survival in bivariate analysis that included T stage. Primary MTV remained prognostic in p16-associated oropharyngeal cancer cases, although sample size was limited. Conclusion: High baseline primary tumor MTV was associated with worse treatment outcomes in this limited patient subset of RTOG 0522. Additional confirmatory work will be required to validate primary tumor MTV as a prognostic imaging biomarker for patient stratification in future trials.

  15. Risk estimation of distant metastasis in node-negative, estrogen receptor-positive breast cancer patients using an RT-PCR based prognostic expression signature

    International Nuclear Information System (INIS)

    Tutt, Andrew; Shu, Henry; Springall, Robert; Cane, Paul; McCallie, Blair; Kam-Morgan, Lauren; Anderson, Steve; Buerger, Horst; Gray, Joe; Bennington, James; Esserman, Laura; Wang, Alice; Hastie, Trevor; Broder, Samuel; Sninsky, John; Brandt, Burkhard; Waldman, Fred; Rowland, Charles; Gillett, Cheryl; Lau, Kit; Chew, Karen; Dai, Hongyue; Kwok, Shirley; Ryder, Kenneth

    2008-01-01

    Given the large number of genes purported to be prognostic for breast cancer, it would be optimal if the genes identified are not confounded by the continuously changing systemic therapies. The aim of this study was to discover and validate a breast cancer prognostic expression signature for distant metastasis in untreated, early stage, lymph node-negative (N-) estrogen receptor-positive (ER+) patients with extensive follow-up times. 197 genes previously associated with metastasis and ER status were profiled from 142 untreated breast cancer subjects. A 'metastasis score' (MS) representing fourteen differentially expressed genes was developed and evaluated for its association with distant-metastasis-free survival (DMFS). Categorical risk classification was established from the continuous MS and further evaluated on an independent set of 279 untreated subjects. A third set of 45 subjects was tested to determine the prognostic performance of the MS in tamoxifen-treated women. A 14-gene signature was found to be significantly associated (p < 0.05) with distant metastasis in a training set and subsequently in an independent validation set. In the validation set, the hazard ratios (HR) of the high risk compared to low risk groups were 4.02 (95% CI 1.91–8.44) for the endpoint of DMFS and 1.97 (95% CI 1.28 to 3.04) for overall survival after adjustment for age, tumor size and grade. The low and high MS risk groups had 10-year estimates (95% CI) of 96% (90–99%) and 72% (64–78%) respectively, for DMFS and 91% (84–95%) and 68% (61–75%), respectively for overall survival. Performance characteristics of the signature in the two sets were similar. Ki-67 labeling index (LI) was predictive for recurrent disease in the training set, but lost significance after adjustment for the expression signature. In a study of tamoxifen-treated patients, the HR for DMFS in high compared to low risk groups was 3.61 (95% CI 0.86–15.14). The 14-gene signature is significantly

  16. Issues in practical model-based diagnosis

    NARCIS (Netherlands)

    Bakker, R.R.; Bakker, R.R.; van den Bempt, P.C.A.; van den Bempt, P.C.A.; Mars, Nicolaas; Out, D.-J.; Out, D.J.; van Soest, D.C.; van Soes, D.C.

    1993-01-01

    The model-based diagnosis project at the University of Twente has been directed at improving the practical usefulness of model-based diagnosis. In cooperation with industrial partners, the research addressed the modeling problem and the efficiency problem in model-based reasoning. Main results of

  17. Prognostic value of proliferation in pleomorphic soft tissue sarcomas

    DEFF Research Database (Denmark)

    Seinen, Jojanneke M; Jönsson, Mats; Bendahl, Pär-Ola O

    2012-01-01

    = 1.6-12.1), Top2a (hazard ratio = 2.2, CI = 1.2-3.5) and high S-phase fraction (hazard ratio = 1.8, CI = 1.2-3.7) significantly correlated with risk for metastasis. When combined with currently used prognostic factors, Ki-67, S-phase fraction and Top2a fraction contributed to refined identification...... of prognostic risk groups. Proliferation, as assessed by expression of Ki-67 and Top2a and evaluation of S-phase fraction and applied to statistical decision-tree models, provides prognostic information in soft tissue sarcomas of the extremity and trunk wall. Though proliferation contributes independently...... to currently applied prognosticators, its role is particularly strong when few other factors are available, which suggests a role in preoperative decision-making related to identification of high-risk individuals who would benefit from neoadjuvant therapy....

  18. Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model.

    Science.gov (United States)

    Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

    2018-01-01

    The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC models were compared using: concordance index (CI), bias-corrected concordance index (BCCI), calibration plots, the Grønnesby and Borgan test, Bayesian Information Criterion (BIC), generalized R 2 , Integrated Discrimination Improvement (IDI), and continuous Net Reclassification Index (cNRI) for individual risk factors and the three risk groups. Three hundred and twenty-one patients were eligible for analyses. The modified-IMDC model with NLR value of 3.6 and PLR value of 157 was selected for comparison with the IMDC model. Both models were well calibrated. All other measures favoured the modified-IMDC model over the IMDC model (CI, 0.706 vs. 0.677; BCCI, 0.699 vs. 0.671; BIC, 2,176.2 vs. 2,190.7; generalized R 2 , 0.238 vs. 0.202; IDI, 0.044; cNRI, 0.279 for individual risk factors; and CI, 0.669 vs. 0.641; BCCI, 0.669 vs. 0.641; BIC, 2,183.2 vs. 2,198.1; generalized R 2 , 0.163 vs. 0.123; IDI, 0.045; cNRI, 0.165 for the three risk groups). Incorporation of NLR and PLR in place of neutrophil count and platelet count improved prognostic accuracy of the IMDC model. These findings require external validation before introducing into clinical practice.

  19. Prognostic Impact of Primary Tumor Location on Clinical Outcomes of Metastatic Colorectal Cancer Treated With Cetuximab Plus Oxaliplatin-Based Chemotherapy: A Subgroup Analysis of the JACCRO CC-05/06 Trials.

    Science.gov (United States)

    Sunakawa, Yu; Ichikawa, Wataru; Tsuji, Akihito; Denda, Tadamichi; Segawa, Yoshihiko; Negoro, Yuji; Shimada, Ken; Kochi, Mitsugu; Nakamura, Masato; Kotaka, Masahito; Tanioka, Hiroaki; Takagane, Akinori; Tani, Satoshi; Yamaguchi, Tatsuro; Watanabe, Takanori; Takeuchi, Masahiro; Fujii, Masashi; Nakajima, Toshifusa

    2017-09-01

    Primary tumor location is a critical prognostic factor in metastatic colorectal cancer (mCRC); however, it remains unclear whether tumor location is a predictor of the response to cetuximab treatment. It is also uncertain if BRAF mutation contributes to the impact of tumor location on survival. We assessed the prognostic impact of tumor location on clinical outcomes in mCRC patients treated with first-line cetuximab chemotherapy. The associations of tumor location with overall survival and progression-free survival were evaluated in mCRC patients with KRAS exon 2 wild-type tumors who were enrolled onto 2 clinical trials: JACCRO CC-05 of cetuximab plus FOLFOX (n = 57, UMIN000004197) and CC-06 of cetuximab plus SOX (n = 61, UMIN000007022). Tumors proximal or from splenic flexure to rectum were defined as right-sided or left-sided, respectively. In addition, exploratory RAS and BRAF mutation analyses were performed. A total of 110 patients were assessable for tumor location; 90 had left-sided tumors. Left-sided tumors were significantly associated with longer overall survival (36.2 vs. 12.6 months, hazard ratio = 0.28, P location was an independent prognostic factor irrespective of BRAF status in RAS wild-type patients. Primary tumor location might be a predictor of survival independent of BRAF status in mCRC patients who receive first-line cetuximab combined with oxaliplatin-based chemotherapy. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Dissecting the regulatory microenvironment of a large animal model of non-Hodgkin lymphoma: evidence of a negative prognostic impact of FOXP3+ T cells in canine B cell lymphoma.

    Directory of Open Access Journals (Sweden)

    Dammy Pinheiro

    Full Text Available The cancer microenvironment plays a pivotal role in oncogenesis, containing a number of regulatory cells that attenuate the anti-neoplastic immune response. While the negative prognostic impact of regulatory T cells (Tregs in the context of most solid tissue tumors is well established, their role in lymphoid malignancies remains unclear. T cells expressing FOXP3 and Helios were documented in the fine needle aspirates of affected lymph nodes of dogs with spontaneous multicentric B cell lymphoma (BCL, proposed to be a model for human non-Hodgkin lymphoma. Multivariable analysis revealed that the frequency of lymph node FOXP3(+ T cells was an independent negative prognostic factor, impacting both progression-free survival (hazard ratio 1.10; p = 0.01 and overall survival (hazard ratio 1.61; p = 0.01 when comparing dogs showing higher than the median FOXP3 expression with those showing the median value of FOXP3 expression or less. Taken together, these data suggest the existence of a population of Tregs operational in canine multicentric BCL that resembles thymic Tregs, which we speculate are co-opted by the tumor from the periphery. We suggest that canine multicentric BCL represents a robust large animal model of human diffuse large BCL, showing clinical, cytological and immunophenotypic similarities with the disease in man, allowing comparative studies of immunoregulatory mechanisms.

  1. Sensor-based interior modeling

    International Nuclear Information System (INIS)

    Herbert, M.; Hoffman, R.; Johnson, A.; Osborn, J.

    1995-01-01

    Robots and remote systems will play crucial roles in future decontamination and decommissioning (D ampersand D) of nuclear facilities. Many of these facilities, such as uranium enrichment plants, weapons assembly plants, research and production reactors, and fuel recycling facilities, are dormant; there is also an increasing number of commercial reactors whose useful lifetime is nearly over. To reduce worker exposure to radiation, occupational and other hazards associated with D ampersand D tasks, robots will execute much of the work agenda. Traditional teleoperated systems rely on human understanding (based on information gathered by remote viewing cameras) of the work environment to safely control the remote equipment. However, removing the operator from the work site substantially reduces his efficiency and effectiveness. To approach the productivity of a human worker, tasks will be performed telerobotically, in which many aspects of task execution are delegated to robot controllers and other software. This paper describes a system that semi-automatically builds a virtual world for remote D ampersand D operations by constructing 3-D models of a robot's work environment. Planar and quadric surface representations of objects typically found in nuclear facilities are generated from laser rangefinder data with a minimum of human interaction. The surface representations are then incorporated into a task space model that can be viewed and analyzed by the operator, accessed by motion planning and robot safeguarding algorithms, and ultimately used by the operator to instruct the robot at a level much higher than teleoperation

  2. Is there any correlation between model-based perfusion parameters and model-free parameters of time-signal intensity curve on dynamic contrast enhanced MRI in breast cancer patients?

    Energy Technology Data Exchange (ETDEWEB)

    Yi, Boram; Kang, Doo Kyoung; Kim, Tae Hee [Ajou University School of Medicine, Department of Radiology, Suwon, Gyeonggi-do (Korea, Republic of); Yoon, Dukyong [Ajou University School of Medicine, Department of Biomedical Informatics, Suwon (Korea, Republic of); Jung, Yong Sik; Kim, Ku Sang [Ajou University School of Medicine, Department of Surgery, Suwon (Korea, Republic of); Yim, Hyunee [Ajou University School of Medicine, Department of Pathology, Suwon (Korea, Republic of)

    2014-05-15

    To find out any correlation between dynamic contrast-enhanced (DCE) model-based parameters and model-free parameters, and evaluate correlations between perfusion parameters with histologic prognostic factors. Model-based parameters (Ktrans, Kep and Ve) of 102 invasive ductal carcinomas were obtained using DCE-MRI and post-processing software. Correlations between model-based and model-free parameters and between perfusion parameters and histologic prognostic factors were analysed. Mean Kep was significantly higher in cancers showing initial rapid enhancement (P = 0.002) and a delayed washout pattern (P = 0.001). Ve was significantly lower in cancers showing a delayed washout pattern (P = 0.015). Kep significantly correlated with time to peak enhancement (TTP) (ρ = -0.33, P < 0.001) and washout slope (ρ = 0.39, P = 0.002). Ve was significantly correlated with TTP (ρ = 0.33, P = 0.002). Mean Kep was higher in tumours with high nuclear grade (P = 0.017). Mean Ve was lower in tumours with high histologic grade (P = 0.005) and in tumours with negative oestrogen receptor status (P = 0.047). TTP was shorter in tumours with negative oestrogen receptor status (P = 0.037). We could acquire general information about the tumour vascular physiology, interstitial space volume and pathologic prognostic factors by analyzing time-signal intensity curve without a complicated acquisition process for the model-based parameters. (orig.)

  3. [Comparison of the prognostic value of mortality Child Pugh Score and forecasting models of chronic liver disease in patients with decompensated cirrhosis of the Hospital Nacional Cayetano Heredia, Lima-Peru].

    Science.gov (United States)

    Valenzuela Granados, Vanessa; Salazar-Quiñones, Maria; Cheng-Zárate, Lester; Malpica-Castillo, Alexander; Huerta Mercado, Jorge; Ticse, Ray

    2015-01-01

    The assessment of prognosis is an essential part of the evaluation of all patients with liver cirrhosis. Currently continues to develop new models to optimize forecast accuracy mortality score is calculated by the Child-Turcotte-Pugh (CTP) and the model for end-stage liver disease (MELD). Compare the prognostic accuracy of hospital mortality and short-term mortality CTP, MELD and other models in patients with decompensated liver cirrhosis. Prospective descriptive study, comparison type of diagnostic test that included 84 patients. The score CTP, MELD and other models were calculated on the first day of hospitalization. The prognostic accuracy of mortality was assessed by the area under the ROC curve (AUROCs) of score CTP, MELD and other models. Hospital mortality and mortality in the short-term monitoring was 20 (23.8%) and 44 (52.4%), respectively. The AUROCs CTP, MELD, MELD Na, MESO, iMELD, RefitMELD and RefitMELD Na to predict hospital mortality was 0.4488, 0.5645, 0.5426, 0.5578, 0.5719, 0.5598 and 0.5754; and to predict short-term mortality was 0.5386, 0.5747, 0.5770, 0.5781, 0.5631, 0.5881 and 0.5693, respectively. By comparing each AUROCs of the CTP score, MELD and other models proved to be no better than the other (p>0.05). This study has not shown the predictive utility of the CTP score, MELD and other models (MELD Na, MESO, iMELD, Refit Refit MELD and MELD Na) to evaluate hospital mortality or short-term mortality in a sample of patients with decompensated cirrhosis of the Hospital Cayetano Heredia.

  4. DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

    Directory of Open Access Journals (Sweden)

    Amandine Etcheverry

    Full Text Available Consistently reported prognostic factors for glioblastoma (GBM are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors that responded poorly to the standard regimen. We further evaluated the potential prognostic value of DGKI methylation status.399 patients with newly diagnosed GBM and treated with a standard regimen were retrospectively included in this study. Survival modelling was performed on two patient populations: intention-to-treat population of all included patients (population 1 and MGMT-methylated patients (population 2. Cox proportional hazard models were fitted to identify the main prognostic factors. A nomogram was developed for population 1. The prognostic value of DGKI promoter methylation status was evaluated on population 1 and population 2.The nomogram-based stratification of the cohort identified two risk groups (high/low with significantly different median survival. We validated the prognostic value of DGKI methylation status for MGMT-methylated patients. We also demonstrated that the DGKI methylation status identified 22% of poorly responding patients in the low-risk group defined by the nomogram.Our results improve the conventional MGMT stratification of GBM patients receiving standard treatment. These results could help the interpretation of published or ongoing clinical trial outcomes and refine patient recruitment in the future.

  5. DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

    Science.gov (United States)

    Etcheverry, Amandine; Aubry, Marc; Idbaih, Ahmed; Vauleon, Elodie; Marie, Yannick; Menei, Philippe; Boniface, Rachel; Figarella-Branger, Dominique; Karayan-Tapon, Lucie; Quillien, Veronique; Sanson, Marc; de Tayrac, Marie; Delattre, Jean-Yves; Mosser, Jean

    2014-01-01

    Consistently reported prognostic factors for glioblastoma (GBM) are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors that responded poorly to the standard regimen. We further evaluated the potential prognostic value of DGKI methylation status. 399 patients with newly diagnosed GBM and treated with a standard regimen were retrospectively included in this study. Survival modelling was performed on two patient populations: intention-to-treat population of all included patients (population 1) and MGMT-methylated patients (population 2). Cox proportional hazard models were fitted to identify the main prognostic factors. A nomogram was developed for population 1. The prognostic value of DGKI promoter methylation status was evaluated on population 1 and population 2. The nomogram-based stratification of the cohort identified two risk groups (high/low) with significantly different median survival. We validated the prognostic value of DGKI methylation status for MGMT-methylated patients. We also demonstrated that the DGKI methylation status identified 22% of poorly responding patients in the low-risk group defined by the nomogram. Our results improve the conventional MGMT stratification of GBM patients receiving standard treatment. These results could help the interpretation of published or ongoing clinical trial outcomes and refine patient recruitment in the future.

  6. Prognostic accuracy of electroencephalograms in preterm infants

    DEFF Research Database (Denmark)

    Fogtmann, Emilie Pi; Plomgaard, Anne Mette; Greisen, Gorm

    2017-01-01

    CONTEXT: Brain injury is common in preterm infants, and predictors of neurodevelopmental outcome are relevant. OBJECTIVE: To assess the prognostic test accuracy of the background activity of the EEG recorded as amplitude-integrated EEG (aEEG) or conventional EEG early in life in preterm infants...... for predicting neurodevelopmental outcome. DATA SOURCES: The Cochrane Library, PubMed, Embase, and the Cumulative Index to Nursing and Allied Health Literature. STUDY SELECTION: We included observational studies that had obtained an aEEG or EEG within 7 days of life in preterm infants and reported...... neurodevelopmental outcomes 1 to 10 years later. DATA EXTRACTION: Two reviewers independently performed data extraction with regard to participants, prognostic testing, and outcomes. RESULTS: Thirteen observational studies with a total of 1181 infants were included. A metaanalysis was performed based on 3 studies...

  7. Towards Prognostics for Electronics Components

    Data.gov (United States)

    National Aeronautics and Space Administration — Electronics components have an increasingly critical role in avionics systems and in the development of future aircraft systems. Prognostics of such components is...

  8. Differential Geometry Based Multiscale Models

    Science.gov (United States)

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atom-istic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier–Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson–Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson–Nernst–Planck equations that

  9. Differential geometry based multiscale models.

    Science.gov (United States)

    Wei, Guo-Wei

    2010-08-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are

  10. Lifecycle Prognostics Architecture for Selected High-Cost Active Components

    Energy Technology Data Exchange (ETDEWEB)

    N. Lybeck; B. Pham; M. Tawfik; J. B. Coble; R. M. Meyer; P. Ramuhalli; L. J. Bond

    2011-08-01

    There are an extensive body of knowledge and some commercial products available for calculating prognostics, remaining useful life, and damage index parameters. The application of these technologies within the nuclear power community is still in its infancy. Online monitoring and condition-based maintenance is seeing increasing acceptance and deployment, and these activities provide the technological bases for expanding to add predictive/prognostics capabilities. In looking to deploy prognostics there are three key aspects of systems that are presented and discussed: (1) component/system/structure selection, (2) prognostic algorithms, and (3) prognostics architectures. Criteria are presented for component selection: feasibility, failure probability, consequences of failure, and benefits of the prognostics and health management (PHM) system. The basis and methods commonly used for prognostics algorithms are reviewed and summarized. Criteria for evaluating PHM architectures are presented: open, modular architecture; platform independence; graphical user interface for system development and/or results viewing; web enabled tools; scalability; and standards compatibility. Thirteen software products were identified and discussed in the context of being potentially useful for deployment in a PHM program applied to systems in a nuclear power plant (NPP). These products were evaluated by using information available from company websites, product brochures, fact sheets, scholarly publications, and direct communication with vendors. The thirteen products were classified into four groups of software: (1) research tools, (2) PHM system development tools, (3) deployable architectures, and (4) peripheral tools. Eight software tools fell into the deployable architectures category. Of those eight, only two employ all six modules of a full PHM system. Five systems did not offer prognostic estimates, and one system employed the full health monitoring suite but lacked operations and

  11. Lifecycle Prognostics Architecture for Selected High-Cost Active Components

    International Nuclear Information System (INIS)

    Lybeck, N.; Pham, B.; Tawfik, M.; Coble, J.B.; Meyer, R.M.; Ramuhalli, P.; Bond, L.J.

    2011-01-01

    There are an extensive body of knowledge and some commercial products available for calculating prognostics, remaining useful life, and damage index parameters. The application of these technologies within the nuclear power community is still in its infancy. Online monitoring and condition-based maintenance is seeing increasing acceptance and deployment, and these activities provide the technological bases for expanding to add predictive/prognostics capabilities. In looking to deploy prognostics there are three key aspects of systems that are presented and discussed: (1) component/system/structure selection, (2) prognostic algorithms, and (3) prognostics architectures. Criteria are presented for component selection: feasibility, failure probability, consequences of failure, and benefits of the prognostics and health management (PHM) system. The basis and methods commonly used for prognostics algorithms are reviewed and summarized. Criteria for evaluating PHM architectures are presented: open, modular architecture; platform independence; graphical user interface for system development and/or results viewing; web enabled tools; scalability; and standards compatibility. Thirteen software products were identified and discussed in the context of being potentially useful for deployment in a PHM program applied to systems in a nuclear power plant (NPP). These products were evaluated by using information available from company websites, product brochures, fact sheets, scholarly publications, and direct communication with vendors. The thirteen products were classified into four groups of software: (1) research tools, (2) PHM system development tools, (3) deployable architectures, and (4) peripheral tools. Eight software tools fell into the deployable architectures category. Of those eight, only two employ all six modules of a full PHM system. Five systems did not offer prognostic estimates, and one system employed the full health monitoring suite but lacked operations and

  12. Observation-Based Modeling for Model-Based Testing

    NARCIS (Netherlands)

    Kanstrén, T.; Piel, E.; Gross, H.G.

    2009-01-01

    One of the single most important reasons that modeling and modelbased testing are not yet common practice in industry is the perceived difficulty of making the models up to the level of detail and quality required for their automated processing. Models unleash their full potential only through

  13. Prognostic biomarkers in osteoarthritis

    Science.gov (United States)

    Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

    2013-01-01

    Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

  14. Fear of knowledge: Clinical hypotheses in diagnostic and prognostic reasoning.

    Science.gov (United States)

    Chiffi, Daniele; Zanotti, Renzo

    2017-10-01

    Patients are interested in receiving accurate diagnostic and prognostic information. Models and reasoning about diagnoses have been extensively investigated from a foundational perspective; however, for all its importance, prognosis has yet to receive a comparable degree of philosophical and methodological attention, and this may be due to the difficulties inherent in accurate prognostics. In the light of these considerations, we discuss a considerable body of critical thinking on the topic of prognostication and its strict relations with diagnostic reasoning, pointing out the distinction between nosographic and pathophysiological types of diagnosis and prognosis, underlying the importance of the explication and explanation processes. We then distinguish between various forms of hypothetical reasoning applied to reach diagnostic and prognostic judgments, comparing them with specific forms of abductive reasoning. The main thesis is that creative abduction regarding clinical hypotheses in diagnostic process is very unlikely to occur, whereas this seems to be often the case for prognostic judgments. The reasons behind this distinction are due to the different types of uncertainty involved in diagnostic and prognostic judgments. © 2016 John Wiley & Sons, Ltd.

  15. Guide to APA-Based Models

    Science.gov (United States)

    Robins, Robert E.; Delisi, Donald P.

    2008-01-01

    In Robins and Delisi (2008), a linear decay model, a new IGE model by Sarpkaya (2006), and a series of APA-Based models were scored using data from three airports. This report is a guide to the APA-based models.

  16. Nutritional prognostic scores in patients with hilar cholangiocarcinoma treated by percutaneous transhepatic biliary stenting combined with 125I seed intracavitary irradiation: A retrospective observational study.

    Science.gov (United States)

    Cui, Peiyuan; Pang, Qing; Wang, Yong; Qian, Zhen; Hu, Xiaosi; Wang, Wei; Li, Zongkuang; Zhou, Lei; Man, Zhongran; Yang, Song; Jin, Hao; Liu, Huichun

    2018-06-01

    We mainly aimed to preliminarily explore the prognostic values of nutrition-based prognostic scores in patients with advanced hilar cholangiocarcinoma (HCCA).We retrospectively analyzed 73 cases of HCCA, who underwent percutaneous transhepatic biliary stenting (PTBS) combined with I seed intracavitary irradiation from November 2012 to April 2017 in our department. The postoperative changes of total bilirubin (TBIL), direct bilirubin (DBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and albumin (ALB) were observed. The preoperative clinical data were collected to calculate the nutrition-based scores, including controlling nutritional status (CONUT), C-reactive protein/albumin ratio (CAR), and prognostic nutritional index (PNI). Kaplan-Meier curve and Cox regression model were used for overall survival (OS) analyses.The serum levels of TBIL, DBIL, ALT, AST, and ALP significantly reduced, and ALB significantly increased at 1 month and 3 months postoperatively. The median survival time of the cohort was 12 months and the 1-year survival rate was 53.1%. Univariate analysis revealed that the statistically significant factors related to OS were CA19-9, TBIL, ALB, CONUT, and PNI. Multivariate analysis further identified CA19-9, CONUT, and PNI as independent prognostic factors.Nutrition-based prognostic scores, CONUT and PNI in particular, can be used as predictors of survival in unresectable HCCA.

  17. Prognostic Assessment in Patients with Indolent B-Cell Lymphomas

    Directory of Open Access Journals (Sweden)

    Luca Arcaini

    2012-01-01

    Full Text Available Follicular lymphoma (FL is an indolent lymphoma with long median survival. Many studies have been performed to build up prognostic scores potentially useful to identify patients with poorer outcome. In 2004, an international consortium coordinated by the International Follicular Lymphoma Prognostic Factor project was established and a new prognostic study was launched (FLIPI2 using progression-free survival (PFS as main endpoint and integrating all the modern parameters prospectively collected. Low-grade non-Hodgkin lymphomas were once considered as a heterogenous group of lymphomas characterized by an indolent clinical course. Each entity is characterized by unique clinicobiologic features. Some studies have been focused on prognostic factors in single lymphoma subtypes, with the development of specific-entity scores based on retrospective series, for instance splenic marginal zone lymphoma (SMZL. A widely accepted prognostic tool for clinical usage for indolent non-follicular B-cell lymphomas is largely awaited. In this paper we summarized the current evidence regarding prognostic assessment of indolent follicular and non-follicular lymphomas.

  18. Prognostic Value of Plasma Epstein-Barr Virus DNA for Local and Regionally Advanced Nasopharyngeal Carcinoma Treated With Cisplatin-Based Concurrent Chemoradiotherapy in Intensity-Modulated Radiotherapy Era.

    Science.gov (United States)

    Chen, Wen-Hui; Tang, Lin-Quan; Guo, Shan-Shan; Chen, Qiu-Yan; Zhang, Lu; Liu, Li-Ting; Qian, Chao-Nan; Guo, Xiang; Xie, Dan; Zeng, Mu-Sheng; Mai, Hai-Qiang

    2016-02-01

    This study aimed to evaluate the prognostic value of plasma Epstein-Barr Virus DNA (EBV DNA) for local and regionally advanced nasopharyngeal carcinoma (NPC) patients treated with concurrent chemoradiotherapy in intensity-modulated radiotherapy (IMRT) era.In this observational study, 404 nonmetastatic local and regionally advanced NPC patients treated with IMRT and cisplatin-based concurrent chemotherapy were recruited. Blood samples were collected before treatment for examination of plasma EBV DNA levels. We evaluated the association of pretreatment plasma EBV DNA levels with progression-free survival rate (PFS), distant metastasis-free survival rate (DMFS), and overall survival rate (OS).Compared to patients with an EBV DNA level advanced NPC patients treated with IMRT and cisplatin-based concurrent chemotherapy. Future ramdomized clinical trials are needed to further evaluate whether plasma EBV DNA levels could be applied to guide concurrent chemotherapy regimen for local and regionally advanced NPC patients.

  19. Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

    Directory of Open Access Journals (Sweden)

    Sarah R. Haile

    2017-12-01

    Full Text Available Abstract Background Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Methods Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. Results We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. Conclusions We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties

  20. Prognostic factors of male patients with acute coronary syndrome after percutaneous coronary intervention therapy

    International Nuclear Information System (INIS)

    Xu Peng; Zhang Gaofeng; Wu Xusheng; Qiao Qi; Yu Liqun

    2005-01-01

    Objective: To study the prognostic risk factors of male patients with coronary heart disease in stent placement era. Methods: One hundred and four patients were enrolled in this study (aged 64.9 ± 9.6 years) including 61 diagnosed as acute myocardial infarction, and 43 as unstable angina with followed up 11.9 ± 8.7 months. All factors including demographic factors, non-interventional work-up, associated clinical complications and results of coronary artery angiography reached a model of Logistic regression analysis. Results: Based on MACE (major adverse cardiac events), as quantitative factors, diseased proximal middle left anterior descending artery was a significant independent variable (P<0.05), and its coefficient was 22.00. Conclusions: Diseased proximal middle left anterior descending coronary artery is the prognostic factor of MACE in male patients with acute coronary syndrome. (authors)

  1. Rule-based decision making model

    International Nuclear Information System (INIS)

    Sirola, Miki

    1998-01-01

    A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

  2. A Prognostic Indicator for Patients Hospitalized with Heart Failure.

    Science.gov (United States)

    Snow, Richard; Vogel, Karen; Vanderhoff, Bruce; Kelch, Benjamin P; Ferris, Frank D

    2016-12-01

    Current methods for identifying patients at risk of dying within six months suffer from clinician biases resulting in underestimation of this risk. As a result, patients who are potentially eligible for hospice and palliative care services frequently do not benefit from these services until they are very close to the end of their lives. To develop a prospective prognostic indicator based on actual survival within Centers for Medicare and Medicaid Services (CMS) claims data that identifies patients with congestive heart failure (CHF) who are at risk of six-month mortality. CMS claims data from January 1, 2008 to June 30, 2009 were reviewed to find the first hospitalization for CHF patients with episode of care diagnosis-related groups (DRGs) 291, 292, and 293. Univariate and multivariable analyses were used to determine the associations between demographic and clinical factors and six-month mortality. The resulting model was evaluated for discrimination and calibration. The resulting prospective prognostic model demonstrated fair discrimination with an ROC of 0.71 and good calibration with a Hosmer-Lemshow statistic of 0.98. Across all DRGs, 5% of discharged patients had a six-month mortality risk of greater than 50%. This prospective approach appears to provide a method to identify patients with CHF who would potentially benefit from a clinical evaluation for referral to hospice care or for a palliative care consult due to high predicted risk of dying within 180 days after discharge from a hospital. This approach can provide a model to match at-risk patients with evidenced-based care in a more consistent manner. This method of identifying patients at risk needs further prospective evaluation to see if it has value for clinicians, increases referrals to hospice and palliative care services, and benefits patients and families.

  3. The use of prognostic factors in metastatic renal cell carcinoma.

    Science.gov (United States)

    Li, Haoran; Samawi, Haider; Heng, Daniel Y C

    2015-12-01

    Over the last decade, the treatment landscape of metastatic renal cell carcinoma (mRCC) has evolved tremendously. The outcome of patients with mRCC has been improved since the advent of targeted therapy. In this review, we address the use of prognostic schema in the era of targeted treatment. This article summarizes the current available prognostic models and the evidence to support their use in clinical settings. Prognostic models can help guide clinicians in their decision making, as they have been validated in the first- and second-line targeted therapy settings as well as in non-clear cell mRCC. Prognostic factors are important in patient counseling, clinical trial stratification, and therapy planning. Very selected favorable-risk patients with minimal bulk and slow-growing disease could potentially be observed before needing treatment. Patients with poor-risk disease may be eligible for treatment with temsirolimus. Patients with a very poor prognosis may not be suitable candidates for cytoreductive nephrectomy. New biomarkers are on the horizon, though their roles need to be validated and their additive contribution to improve existing prognostic models examined. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Patterns of Primary Tumor Invasion and Regional Lymph Node Spread Based on Magnetic Resonance Imaging in Early-Stage Nasal NK/T-cell Lymphoma: Implications for Clinical Target Volume Definition and Prognostic Significance

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Run-Ye [Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing (China); Liu, Kang [Department of Imaging Diagnosis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing (China); Wang, Wei-Hu; Jin, Jing; Song, Yong-Wen; Wang, Shu-Lian; Liu, Yue-Ping; Ren, Hua; Fang, Hui; Liu, Qing-Feng; Yang, Yong; Chen, Bo; Qi, Shu-Nan; Lu, Ning-Ning; Tang, Yu; Tang, Yuan; Li, Ning [Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing (China); Ouyang, Han [Department of Imaging Diagnosis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing (China); Li, Ye-Xiong, E-mail: yexiong12@163.com [Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing (China)

    2017-01-01

    Purpose: This study aimed to determine the pathways of primary tumor invasion (PTI) and regional lymph node (LN) spread based on magnetic resonance imaging (MRI) in early-stage nasal NK/T-cell lymphoma (NKTCL), to improve clinical target volume (CTV) delineation and evaluate the prognostic value of locoregional extension patterns. Methods and Materials: A total of 105 patients with newly diagnosed early-stage nasal NKTCL who underwent pretreatment MRI were retrospectively reviewed. All patients received radiation therapy with or without chemotherapy. Results: The incidences of PTI and regional LN involvement were 64.7% and 25.7%, respectively. Based on the incidence of PTI, involved sites surrounding the nasal cavity were classified into 3 risk subgroups: high-risk (>20%), intermediate-risk (5%-20%), and low-risk (<5%). The most frequently involved site was the nasopharynx (35.2%), followed by the maxillary (21.9%) and ethmoid (21.9%) sinuses. Local disease and regional LN spread followed an orderly pattern without LN skipping. The retropharyngeal nodes (RPNs) were most frequently involved (19.0%), followed by level II (11.4%). The 5-year overall survival (OS), progression-free survival (PFS), and locoregional control (LRC) rates for all patients were 72.8%, 65.2%, and 90.0%, respectively. The presence of PTI and regional LN involvement based on MRI significantly and negatively affected PFS and OS. Conclusions: Early-stage nasal NKTCL presents with a high incidence of PTI but a relatively low incidence of regional LN spread. Locoregional spread followed an orderly pattern, and PTI and regional LN spread are powerful prognostic factors for poorer survival outcomes. CTV reduction may be feasible for selected patients.

  5. Model-based DSL frameworks

    NARCIS (Netherlands)

    Ivanov, Ivan; Bézivin, J.; Jouault, F.; Valduriez, P.

    2006-01-01

    More than five years ago, the OMG proposed the Model Driven Architecture (MDA™) approach to deal with the separation of platform dependent and independent aspects in information systems. Since then, the initial idea of MDA evolved and Model Driven Engineering (MDE) is being increasingly promoted to

  6. Model based design introduction: modeling game controllers to microprocessor architectures

    Science.gov (United States)

    Jungwirth, Patrick; Badawy, Abdel-Hameed

    2017-04-01

    We present an introduction to model based design. Model based design is a visual representation, generally a block diagram, to model and incrementally develop a complex system. Model based design is a commonly used design methodology for digital signal processing, control systems, and embedded systems. Model based design's philosophy is: to solve a problem - a step at a time. The approach can be compared to a series of steps to converge to a solution. A block diagram simulation tool allows a design to be simulated with real world measurement data. For example, if an analog control system is being upgraded to a digital control system, the analog sensor input signals can be recorded. The digital control algorithm can be simulated with the real world sensor data. The output from the simulated digital control system can then be compared to the old analog based control system. Model based design can compared to Agile software develop. The Agile software development goal is to develop working software in incremental steps. Progress is measured in completed and tested code units. Progress is measured in model based design by completed and tested blocks. We present a concept for a video game controller and then use model based design to iterate the design towards a working system. We will also describe a model based design effort to develop an OS Friendly Microprocessor Architecture based on the RISC-V.

  7. EPR-based material modelling of soils

    Science.gov (United States)

    Faramarzi, Asaad; Alani, Amir M.

    2013-04-01

    In the past few decades, as a result of the rapid developments in computational software and hardware, alternative computer aided pattern recognition approaches have been introduced to modelling many engineering problems, including constitutive modelling of materials. The main idea behind pattern recognition systems is that they learn adaptively from experience and extract various discriminants, each appropriate for its purpose. In this work an approach is presented for developing material models for soils based on evolutionary polynomial regression (EPR). EPR is a recently developed hybrid data mining technique that searches for structured mathematical equations (representing the behaviour of a system) using genetic algorithm and the least squares method. Stress-strain data from triaxial tests are used to train and develop EPR-based material models for soil. The developed models are compared with some of the well-known conventional material models and it is shown that EPR-based models can provide a better prediction for the behaviour of soils. The main benefits of using EPR-based material models are that it provides a unified approach to constitutive modelling of all materials (i.e., all aspects of material behaviour can be implemented within a unified environment of an EPR model); it does not require any arbitrary choice of constitutive (mathematical) models. In EPR-based material models there are no material parameters to be identified. As the model is trained directly from experimental data therefore, EPR-based material models are the shortest route from experimental research (data) to numerical modelling. Another advantage of EPR-based constitutive model is that as more experimental data become available, the quality of the EPR prediction can be improved by learning from the additional data, and therefore, the EPR model can become more effective and robust. The developed EPR-based material models can be incorporated in finite element (FE) analysis.

  8. Integration of Simulink Models with Component-based Software Models

    DEFF Research Database (Denmark)

    Marian, Nicolae

    2008-01-01

    Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics...... of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical...... constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems) is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI), University of Southern Denmark. Once specified, the software model has...

  9. Improving Agent Based Modeling of Critical Incidents

    Directory of Open Access Journals (Sweden)

    Robert Till

    2010-04-01

    Full Text Available Agent Based Modeling (ABM is a powerful method that has been used to simulate potential critical incidents in the infrastructure and built environments. This paper will discuss the modeling of some critical incidents currently simulated using ABM and how they may be expanded and improved by using better physiological modeling, psychological modeling, modeling the actions of interveners, introducing Geographic Information Systems (GIS and open source models.

  10. Models for Rational Number Bases

    Science.gov (United States)

    Pedersen, Jean J.; Armbruster, Frank O.

    1975-01-01

    This article extends number bases to negative integers, then to positive rationals and finally to negative rationals. Methods and rules for operations in positive and negative rational bases greater than one or less than negative one are summarized in tables. Sample problems are explained and illustrated. (KM)

  11. A Prognostic Model to Predict Mortality among Non-Small-Cell Lung Cancer Patients in the U.S. Military Health System.

    Science.gov (United States)

    Lin, Jie; Carter, Corey A; McGlynn, Katherine A; Zahm, Shelia H; Nations, Joel A; Anderson, William F; Shriver, Craig D; Zhu, Kangmin

    2015-12-01

    Accurate prognosis assessment after non-small-cell lung cancer (NSCLC) diagnosis is an essential step for making effective clinical decisions. This study is aimed to develop a prediction model with routinely available variables to assess prognosis in patients with NSCLC in the U.S. Military Health System. We used the linked database from the Department of Defense's Central Cancer Registry and the Military Health System Data Repository. The data set was randomly and equally split into a training set to guide model development and a testing set to validate the model prediction. Stepwise Cox regression was used to identify predictors of survival. Model performance was assessed by calculating area under the receiver operating curves and construction of calibration plots. A simple risk scoring system was developed to aid quick risk score calculation and risk estimation for NSCLC clinical management. The study subjects were 5054 patients diagnosed with NSCLC between 1998 and 2007. Age, sex, tobacco use, tumor stage, histology, surgery, chemotherapy, peripheral vascular disease, cerebrovascular disease, and diabetes mellitus were identified as significant predictors of survival. Calibration showed high agreement between predicted and observed event rates. The area under the receiver operating curves reached 0.841, 0.849, 0.848, and 0.838 during 1, 2, 3, and 5 years, respectively. This is the first NSCLC prognosis model for quick risk assessment within the Military Health System. After external validation, the model can be translated into clinical use both as a web-based tool and through mobile applications easily accessible to physicians, patients, and researchers.

  12. A decision tree-based combination of ezrin-interacting proteins to estimate the prognostic risk of patients with esophageal squamous cell carcinoma.

    Science.gov (United States)

    He, Jian-Zhong; Wu, Zhi-Yong; Wang, Shao-Hong; Ji, Xia; Yang, Cui-Xia; Xu, Xiu-E; Liao, Lian-Di; Wu, Jian-Yi; Li, En-Min; Zhang, Kai; Xu, Li-Yan

    2017-08-01

    Our previous studies have highlighted the importance of ezrin in esophageal squamous cell carcinoma (ESCC). Here our objective was to explore the clinical significance of ezrin-interacting proteins, which would provide a theoretical basis for understanding the function of ezrin and potential therapeutic targets for ESCC. We used affinity purification and mass spectrometry to identify PDIA3, CNPY2, and STMN1 as potential ezrin-interacting proteins. Confocal microscopy and coimmunoprecipitation analysis further confirmed the colocalization and interaction of ezrin with PDIA3, CNPY2, and STMN1. Tissue microarray data of ESCC samples (n=263) showed that the 5-year overall survival (OS) and disease-free survival (DFS) were significantly lower for the CNPY2 (OS, P=.003; DFS, P=.011) and STMN1 (OS, P=.010; DFS, P=.002) high-expression groups compared with the low-expression groups. By contrast, overexpression of PDIA3 was significantly correlated with favorable survival (OS, P<.001; DFS, P=.001). Cox regression demonstrated the prognostic value of PDIA3, CNPY2, and STMN1 in ESCC. Furthermore, decision tree analysis revealed that the resulting classifier of both ezrin and its interacting proteins could be used to better predict OS and DFS of patients with ESCC. In conclusion, a signature of ezrin-interacting proteins accurately predicts ESCC patient survival or tumor recurrence. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Bone Marrow Stromal Antigen 2 Is a Novel Plasma Biomarker and Prognosticator for Colorectal Carcinoma: A Secretome-Based Verification Study

    Directory of Open Access Journals (Sweden)

    Sum-Fu Chiang

    2015-01-01

    Full Text Available Background. The cancer cell secretome has been recognized as a valuable reservoir for identifying novel serum/plasma biomarkers for different cancers, including colorectal cancer (CRC. This study aimed to verify four CRC cell-secreted proteins (tumor-associated calcium signal transducer 2/trophoblast cell surface antigen 2 (TACSTD2/TROP2, tetraspanin-6 (TSPAN6, bone marrow stromal antigen 2 (BST2, and tumor necrosis factor receptor superfamily member 16 (NGFR as potential plasma CRC biomarkers. Methods. The study population comprises 152 CRC patients and 152 controls. Target protein levels in plasma and tissue samples were assessed by ELISA and immunohistochemistry, respectively. Results. Among the four candidate proteins examined by ELISA in a small sample set, only BST2 showed significantly elevated plasma levels in CRC patients versus controls. Immunohistochemical analysis revealed the overexpression of BST2 in CRC tissues, and higher BST2 expression levels correlated with poorer 5-year survival (46.47% versus 65.57%; p=0.044. Further verification confirmed the elevated plasma BST2 levels in CRC patients (2.35 ± 0.13 ng/mL versus controls (1.04 ± 0.03 ng/mL (p<0.01, with an area under the ROC curve (AUC being 0.858 comparable to that of CEA (0.867. Conclusion. BST2, a membrane protein selectively detected in CRC cell secretome, may be a novel plasma biomarker and prognosticator for CRC.

  14. Prognostic value and clinicopathological significance of serum- and tissue-based cytokeratin 18 express level in breast cancer: a meta-analysis.

    Science.gov (United States)

    Yang, Jiangling; Gao, Sicheng; Xu, Jian; Zhu, Junfeng

    2018-04-27

    Cytokeratin 18 (CK18), a type I cytokeratin of the intermediate filament family, has been associated with the prognosis of cancer patients for decades. However, its exact role in predicting the clinical outcome of breast cancer remains controversial. To comprehensively investigated the prognostic value of CK18 in breast cancer, a systematically meta-analysis was conducted to explore the association between CK18 expression and overall survival. Literature collection was conducted by retrieving electronic databases Pubmed, Cochrane Library, Web of Science, EMBASE, and OVID completely (up to January 1, 2017). Nine relevant studies with 4857 cases assessing the relationship between CK18 high expression and the outcome of breast cancer patients were enrolled in our analysis. The results indicated that the high level of CK18 expression was significantly associated with overall survival of breast cancer patients via a specimen-depended manner. Reports which used serum to detect the expression of CK18 predicted a poor outcome of breast cancer (HR = 1.24, 95%CI: 1.11-1.38, P present study demonstrated that CK18 might be served as a novel biomarker to predict clinicopathological features and the outcome of breast cancer. © 2018 The Author(s).

  15. PV panel model based on datasheet values

    DEFF Research Database (Denmark)

    Sera, Dezso; Teodorescu, Remus; Rodriguez, Pedro

    2007-01-01

    This work presents the construction of a model for a PV panel using the single-diode five-parameters model, based exclusively on data-sheet parameters. The model takes into account the series and parallel (shunt) resistance of the panel. The equivalent circuit and the basic equations of the PV cell....... Based on these equations, a PV panel model, which is able to predict the panel behavior in different temperature and irradiance conditions, is built and tested....

  16. Statistical methods for the assessment of prognostic biomarkers(part II): calibration and re-classification

    NARCIS (Netherlands)

    Tripepi, Giovanni; Jager, Kitty J.; Dekker, Friedo W.; Zoccali, Carmine

    2010-01-01

    Calibration is the ability of a prognostic model to correctly estimate the probability of a given event across the whole range of prognostic estimates (for example, 30% probability of death, 40% probability of myocardial infarction, etc.). The key difference between calibration and discrimination is

  17. Traceability in Model-Based Testing

    Directory of Open Access Journals (Sweden)

    Mathew George

    2012-11-01

    Full Text Available The growing complexities of software and the demand for shorter time to market are two important challenges that face today’s IT industry. These challenges demand the increase of both productivity and quality of software. Model-based testing is a promising technique for meeting these challenges. Traceability modeling is a key issue and challenge in model-based testing. Relationships between the different models will help to navigate from one model to another, and trace back to the respective requirements and the design model when the test fails. In this paper, we present an approach for bridging the gaps between the different models in model-based testing. We propose relation definition markup language (RDML for defining the relationships between models.

  18. Firm Based Trade Models and Turkish Economy

    Directory of Open Access Journals (Sweden)

    Nilüfer ARGIN

    2015-12-01

    Full Text Available Among all international trade models, only The Firm Based Trade Models explains firm’s action and behavior in the world trade. The Firm Based Trade Models focuses on the trade behavior of individual firms that actually make intra industry trade. Firm Based Trade Models can explain globalization process truly. These approaches include multinational cooperation, supply chain and outsourcing also. Our paper aims to explain and analyze Turkish export with Firm Based Trade Models’ context. We use UNCTAD data on exports by SITC Rev 3 categorization to explain total export and 255 products and calculate intensive-extensive margins of Turkish firms.

  19. Lévy-based growth models

    DEFF Research Database (Denmark)

    Jónsdóttir, Kristjana Ýr; Schmiegel, Jürgen; Jensen, Eva Bjørn Vedel

    2008-01-01

    In the present paper, we give a condensed review, for the nonspecialist reader, of a new modelling framework for spatio-temporal processes, based on Lévy theory. We show the potential of the approach in stochastic geometry and spatial statistics by studying Lévy-based growth modelling of planar o...... objects. The growth models considered are spatio-temporal stochastic processes on the circle. As a by product, flexible new models for space–time covariance functions on the circle are provided. An application of the Lévy-based growth models to tumour growth is discussed....

  20. Improving breast cancer survival analysis through competition-based multidimensional modeling.

    Directory of Open Access Journals (Sweden)

    Erhan Bilal

    Full Text Available Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.