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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. Model-Based Prognostics of Hybrid Systems

    Science.gov (United States)

    Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

    2015-01-01

    Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

  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. 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...

  5. 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...

  6. 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...

  7. Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics approaches capture system knowl- edge in the form of physics-based models of components that include how they fail. These methods consist of...

  8. Multiple Damage Progression Paths in Model-based Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics approaches employ do- main knowledge about a system, its components, and how they fail through the use of physics-based models. Compo- nent...

  9. 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...

  10. 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...

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

    Directory of Open Access Journals (Sweden)

    Matthew J. Daigle

    2011-01-01

    Full Text Available Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.

  12. 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.

  13. A Comparison of Filter-based Approaches for Model-based Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is...

  14. 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.

  15. 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

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

    Data.gov (United States)

    National Aeronautics and Space Administration — This article discusses several aspects of uncertainty represen- tation and management for model-based prognostics method- ologies based on our experience with Kalman...

  17. Stage Separation Failure: Model Based Diagnostics and Prognostics

    Science.gov (United States)

    Luchinsky, Dmitry; Hafiychuk, Vasyl; Kulikov, Igor; Smelyanskiy, Vadim; Patterson-Hine, Ann; Hanson, John; Hill, Ashley

    2010-01-01

    Safety of the next-generation space flight vehicles requires development of an in-flight Failure Detection and Prognostic (FD&P) system. Development of such system is challenging task that involves analysis of many hard hitting engineering problems across the board. In this paper we report progress in the development of FD&P for the re-contact fault between upper stage nozzle and the inter-stage caused by the first stage and upper stage separation failure. A high-fidelity models and analytical estimations are applied to analyze the following sequence of events: (i) structural dynamics of the nozzle extension during the impact; (ii) structural stability of the deformed nozzle in the presence of the pressure and temperature loads induced by the hot gas flow during engine start up; and (iii) the fault induced thrust changes in the steady burning regime. The diagnostic is based on the measurements of the impact torque. The prognostic is based on the analysis of the correlation between the actuator signal and fault-induced changes in the nozzle structural stability and thrust.

  18. 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...

  19. 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...

  20. 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.

  1. 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.

  2. Improving Computational Efficiency of Prediction in Model-based Prognostics Using the Unscented Transform

    Data.gov (United States)

    National Aeronautics and Space Administration — 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...

  3. A Framework for Model-Based Diagnostics and Prognostics of Switched-Mode Power Supplies

    Science.gov (United States)

    2014-10-02

    consumption, MOSFET voltage, diode reverse voltage, and 47K resistance consumption. ANNUAL CONFERENCE OF THE PROGNOSTICS AND HEALTH MANAGEMENT...methodology based on an equivalent circuit system simulation model developed from a commercially available switch-mode power supply, and empirical...of an integrated simulation model combining two empirical models in the application of SMPS: a circuit -based SMPS simulation model and the

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

    DEFF Research Database (Denmark)

    Asgarpour, Masoud

    2017-01-01

    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 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...

  5. 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.

  6. 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.

  7. Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

    Science.gov (United States)

    Daigle, Matthew J.; Sankararaman, Shankar

    2013-01-01

    Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

  8. 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

  9. 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.

  10. Prognostic models based on patient snapshots and time windows: Predicting disease progression to assisted ventilation in Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Carreiro, André V; Amaral, Pedro M T; Pinto, Susana; Tomás, Pedro; de Carvalho, Mamede; Madeira, Sara C

    2015-12-01

    Amyotrophic Lateral Sclerosis (ALS) is a devastating disease and the most common neurodegenerative disorder of young adults. ALS patients present a rapidly progressive motor weakness. This usually leads to death in a few years by respiratory failure. The correct prediction of respiratory insufficiency is thus key for patient management. In this context, we propose an innovative approach for prognostic prediction based on patient snapshots and time windows. We first cluster temporally-related tests to obtain snapshots of the patient's condition at a given time (patient snapshots). Then we use the snapshots to predict the probability of an ALS patient to require assisted ventilation after k days from the time of clinical evaluation (time window). This probability is based on the patient's current condition, evaluated using clinical features, including functional impairment assessments and a complete set of respiratory tests. The prognostic models include three temporal windows allowing to perform short, medium and long term prognosis regarding progression to assisted ventilation. Experimental results show an area under the receiver operating characteristics curve (AUC) in the test set of approximately 79% for time windows of 90, 180 and 365 days. Creating patient snapshots using hierarchical clustering with constraints outperforms the state of the art, and the proposed prognostic model becomes the first non population-based approach for prognostic prediction in ALS. The results are promising and should enhance the current clinical practice, largely supported by non-standardized tests and clinicians' experience. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. 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.

  12. 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.

  13. Prognostic factors for survival in adult patients with recurrent glioblastoma: a decision-tree-based model.

    Science.gov (United States)

    Audureau, Etienne; Chivet, Anaïs; Ursu, Renata; Corns, Robert; Metellus, Philippe; Noel, Georges; Zouaoui, Sonia; Guyotat, Jacques; Le Reste, Pierre-Jean; Faillot, Thierry; Litre, Fabien; Desse, Nicolas; Petit, Antoine; Emery, Evelyne; Lechapt-Zalcman, Emmanuelle; Peltier, Johann; Duntze, Julien; Dezamis, Edouard; Voirin, Jimmy; Menei, Philippe; Caire, François; Dam Hieu, Phong; Barat, Jean-Luc; Langlois, Olivier; Vignes, Jean-Rodolphe; Fabbro-Peray, Pascale; Riondel, Adeline; Sorbets, Elodie; Zanello, Marc; Roux, Alexandre; Carpentier, Antoine; Bauchet, Luc; Pallud, Johan

    2017-11-20

    We assessed prognostic factors in relation to OS from progression in recurrent glioblastomas. Retrospective multicentric study enrolling 407 (training set) and 370 (external validation set) adult patients with a recurrent supratentorial glioblastoma treated by surgical resection and standard combined chemoradiotherapy as first-line treatment. Four complementary multivariate prognostic models were evaluated: Cox proportional hazards regression modeling, single-tree recursive partitioning, random survival forest, conditional random forest. Median overall survival from progression was 7.6 months (mean, 10.1; range, 0-86) and 8.0 months (mean, 8.5; range, 0-56) in the training and validation sets, respectively (p = 0.900). Using the Cox model in the training set, independent predictors of poorer overall survival from progression included increasing age at histopathological diagnosis (aHR, 1.47; 95% CI [1.03-2.08]; p = 0.032), RTOG-RPA V-VI classes (aHR, 1.38; 95% CI [1.11-1.73]; p = 0.004), decreasing KPS at progression (aHR, 3.46; 95% CI [2.10-5.72]; p < 0.001), while independent predictors of longer overall survival from progression included surgical resection (aHR, 0.57; 95% CI [0.44-0.73]; p < 0.001) and chemotherapy (aHR, 0.41; 95% CI [0.31-0.55]; p < 0.001). Single-tree recursive partitioning identified KPS at progression, surgical resection at progression, chemotherapy at progression, and RTOG-RPA class at histopathological diagnosis, as main survival predictors in the training set, yielding four risk categories highly predictive of overall survival from progression both in training (p < 0.0001) and validation (p < 0.0001) sets. Both random forest approaches identified KPS at progression as the most important survival predictor. Age, KPS at progression, RTOG-RPA classes, surgical resection at progression and chemotherapy at progression are prognostic for survival in recurrent glioblastomas and should inform the treatment decisions.

  14. Physicians' perceptions of the value of prognostic models: the benefits and risks of prognostic confidence.

    Science.gov (United States)

    Hallen, Sarah A M; Hootsmans, Norbert A M; Blaisdell, Laura; Gutheil, Caitlin M; Han, Paul K J

    2015-12-01

    The communication of prognosis in end-of-life (EOL) care is a challenging task that is limited by prognostic uncertainty and physicians' lack of confidence in their prognostic estimates. Clinical prediction models (CPMs) are increasingly common evidence-based tools that may mitigate these problems and facilitate the communication and use of prognostic information in EOL care; however, little is known about physicians' perceptions of the value of these tools. To explore physicians' perceptions of the value of CPMs in EOL care. Qualitative study using semi-structured individual interviews which were analysed using a constant comparative method. Convenience sample of 17 attending physicians representing five different medical specialties at a single large tertiary care medical centre. Physicians perceived CPMs as having three main benefits in EOL care: (i) enhancing their prognostic confidence; (ii) increasing their prognostic authority; and (iii) enabling patient persuasion in circumstances of low prognostic and therapeutic uncertainty. However, physicians also perceived CPMs as having potential risks, which include producing emotional distress in patients and promoting prognostic overconfidence in EOL care. Physicians perceive CPMs as a potentially valuable means of increasing their prognostic confidence, communication and explicit use of prognostic information in EOL care. However, physicians' perceptions of CPMs also indicate a need to establish broad and consistent implementation processes to engage patients in shared decision making in EOL care, to effectively communicate uncertainty in prognostic information and to help both patients and physicians manage uncertainty in EOL care decisions. © 2014 John Wiley & Sons Ltd.

  15. 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...

  16. 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...

  17. 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...

  18. Electrohydraulic Servomechanisms Affected by Multiple Failures: A Model-Based Prognostic Method Using Genetic Algorithms

    OpenAIRE

    Dalla Vedova, Matteo Davide Lorenzo; Maggiore, Paolo

    2016-01-01

    In order to detect incipient failures due to a progressive wear of a primary flight command electro hydraulic actuator (EHA), prognostics could employ several approaches; the choice of the best ones is driven by the efficacy shown in failure detection, since not all the algorithms might be useful for the proposed purpose. In other words, some of them could be suitable only for certain applications while they could not give useful results for others. Developing a fault detection algorithm able...

  19. 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...... of the working model. We further illustrate the methods by computing the concordance probability for a prognostic model of coronary heart disease (CHD) events in the presence of the competing risk of non-CHD death.......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...

  20. A prognostic model to predict the success of artificial insemination in dairy cows based on readily available data

    NARCIS (Netherlands)

    Rutten, C.J.; Steeneveld, W.; Vernooij, J.C.M.; Huijps, K.; Nielen, M.; Hogeveen, H.

    2016-01-01

    A prognosis of the likelihood of insemination success is valuable information for the decision to start inseminating a cow. This decision is important for the reproduction management of dairy farms. The aim of this study was to develop a prognostic model for the likelihood of successful first

  1. A prognostic model to predict the success of artificial insemination in dairy cows based on readily available data

    NARCIS (Netherlands)

    Rutten, C J|info:eu-repo/dai/nl/353551031; Steeneveld, W|info:eu-repo/dai/nl/304833169; Vernooij, J C M|info:eu-repo/dai/nl/340304596; Huijps, K|info:eu-repo/dai/nl/304837881; Nielen, M|info:eu-repo/dai/nl/123535298; Hogeveen, H|info:eu-repo/dai/nl/126322864

    2016-01-01

    A prognosis of the likelihood of insemination success is valuable information for the decision to start inseminating a cow. This decision is important for the reproduction management of dairy farms. The aim of this study was to develop a prognostic model for the likelihood of successful first

  2. 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.

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

    Data.gov (United States)

    National Aeronautics and Space Administration — 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...

  4. 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

  5. Prognostic modeling in pediatric acute liver failure.

    Science.gov (United States)

    Jain, Vandana; Dhawan, Anil

    2016-10-01

    Liver transplantation (LT) is the only proven treatment for pediatric acute liver failure (PALF). However, over a period of time, spontaneous native liver survival is increasingly reported, making us wonder if we are overtransplanting children with acute liver failure (ALF). An effective prognostic model for PALF would help direct appropriate organ allocation. Only patients who would die would undergo LT, and those who would spontaneously recover would avoid unnecessary LT. Deriving and validating such a model for PALF, however, encompasses numerous challenges. In particular, the heterogeneity of age and etiology in PALF, as well as a lack of understanding of the natural history of the disease, contributed by the availability of LT has led to difficulties in prognostic model development. Several prognostic laboratory variables have been identified, and the incorporation of these variables into scoring systems has been attempted. A reliable targeted prognostic model for ALF in Wilson's disease has been established and externally validated. The roles of physiological, immunological, and metabolomic parameters in prognosis are being investigated. This review discusses the challenges with prognostic modeling in PALF and describes predictive methods that are currently available and in development for the future. Liver Transplantation 22 1418-1430 2016 AASLD. © 2016 by the American Association for the Study of Liver Diseases.

  6. Aircraft Anomaly Prognostics Project

    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...

  7. 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...

  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. Multidisciplinary Rehabilitation Treatment of Patients With Chronic Low Back Pain: A Prognostic Model for Its Outcome

    NARCIS (Netherlands)

    van der Hulst, Marije; Vollenbroek-Hutten, Miriam Marie Rosé; Groothuis-Oudshoorn, Catharina Gerarda Maria; Hermens, Hermanus J.

    Objectives: (1) To determine if treatment outcome in chronic low back pain can be predicted by a predefined multivariate prognostic model based on consistent predictors from the literature and (2) to explore the value of potentially prognostic factors further. Methods: Data were derived from a

  10. 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...

  11. Physiology-based prognostic modeling of the influence of changes in precipitation on a keystone dryland plant species.

    Science.gov (United States)

    Coe, Kirsten K; Sparks, Jed P

    2014-12-01

    Fluctuations in mean annual precipitation (MAP) will strongly influence the ecology of dryland ecosystems in the future, yet, because individual precipitation events drive growth and resource availability for many dryland organisms, changes in intra-annual precipitation may disproportionately influence future dryland processes. This work examines the hypothesis that intra-annual precipitation changes will drive dryland productivity to a greater extent than changes to MAP. To test this hypothesis, we created a physiology-based model to predict the effects of precipitation change on a widespread biocrust moss that regulates soil structure, water retention, and nutrient cycling in drylands. First, we used the model to examine moss productivity over the next 100 years driven by alterations in MAP by ± 10, 20 and 30%, and changes in intra-annual precipitation (event size and frequency). Productivity increased as a function of MAP, but differed among simulations where intra-annual precipitation was manipulated under constant MAP. Supporting our hypothesis, this demonstrates that, even if MAP does not change, changes in the features of individual precipitation events can strongly influence long-term performance. Second, we used the model to examine 100-year productivity based on projected dryland precipitation from published global and regional models. These simulations predicted 25-63% reductions in productivity and increased moss mortality rates, declines that will likely alter water and nutrient cycling in dryland ecosystems. Intra-annual precipitation in model-based simulations was a stronger predictor of productivity compared to MAP, further supporting our hypothesis, and illustrating that intra-annual precipitation patterns may dominate dryland responses to altered precipitation in a future climate.

  12. 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.

  13. The Practicability of a Novel Prognostic Index (PI) Model and Comparison with Nottingham Prognostic Index (NPI) in Stage I-III Breast Cancer Patients Undergoing Surgical Treatment.

    Science.gov (United States)

    Wen, Jiahuai; Ye, Feng; Li, Shuaijie; Huang, Xiaojia; Yang, Lu; Xiao, Xiangsheng; Xie, Xiaoming

    2015-01-01

    Previous studies have indicated the prognostic value of various laboratory parameters in cancer patients. This study was to establish a prognostic index (PI) model for breast cancer patients based on the potential prognostic factors. A retrospective study of 1661 breast cancer patients who underwent surgical treatment between January 2002 and December 2008 at Sun Yat-sen University Cancer Center was conducted. Multivariate analysis (Cox regression model) was performed to determine the independent prognostic factors and a prognostic index (PI) model was devised based on these factors. Survival analyses were used to estimate the prognostic value of PI, and the discriminatory ability of PI was compared with Nottingham Prognostic Index (NPI) by evaluating the area under the receiver operating characteristics curves (AUC). The mean survival time of all participants was 123.6 months. The preoperative globulin >30.0g/L, triglyceride >1.10mmol/L and fibrinogen >2.83g/L were identified as risk factors for shorter cancer-specific survival. The novel prognostic index model was established and enrolled patients were classified as low- (1168 patients, 70.3%), moderate- (410 patients, 24.7%) and high-risk groups (83 patients, 5.0%), respectively. Compared with the low-risk group, higher risks of poor clinical outcome were indicated in the moderate-risk group [Hazard ratio (HR): 1.513, 95% confidence interval (CI): 1.169-1.959, p = 0.002] and high-risk group (HR: 2.481, 95%CI: 1.653-3.724, p< 0.001). The prognostic index based on three laboratory parameters was a novel and practicable prognostic tool. It may serve as complement to help predict postoperative survival in breast cancer patients.

  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. Prognostic survival model for people diagnosed with invasive cutaneous melanoma.

    Science.gov (United States)

    Baade, Peter D; Royston, Patrick; Youl, Philipa H; Weinstock, Martin A; Geller, Alan; Aitken, Joanne F

    2015-01-31

    The ability of medical practitioners to communicate risk estimates effectively to patients diagnosed with melanoma relies on accurate information about prognostic factors and their impact on survival. This study reports the development of one of the few melanoma prognostic models, called the Melanoma Severity Index (MSI), based on population-based cancer registry data. Data from the Queensland Cancer Registry for people (20-89 years) diagnosed with a single invasive melanoma between 1995 and 2008 (n = 28,654; 1,700 melanoma deaths). Additional clinical information about metastasis, ulceration and positive lymph nodes was manually extracted from pathology forms. Flexible parametric survival models were combined with multivariable fractional polynomial for selecting variables and transformations of continuous variables. Multiple imputation was used for missing covariate values. The MSI contained the variables thickness (transformed, explained 40.6% of variation in survival), body site (additional 1.9% in variation), metastasis (1.8%), positive nodes (0.7%), ulceration (1.3%), age (1.1%). Royston and Sauerbrei's D statistic (measure of discrimination) was 1.50 (95% CI = 1.44, 1.56) and the corresponding RD2 (measure of explained variation) was 0.47 (0.45, 0.49), demonstrating strong explanatory performance. The Harrell-C statistic was 0.88 (0.88, 0.89). Lacking an external validation dataset, we applied internal-external cross validation to demonstrate the consistency of the prognostic information across geographically-defined subsets of the cohort. The MSI provides good ability to predict survival for melanoma patients. Beyond the immediate clinical use, the MSI may have important public health and research applications for evaluations of public health interventions aimed at reducing deaths from melanoma.

  16. 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...

  17. 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.

  18. Predicting intracranial hemorrhage after traumatic brain injury in low and middle-income countries: A prognostic model based on a large, multi-center, international cohort

    Directory of Open Access Journals (Sweden)

    Subaiya Saleena

    2012-11-01

    Full Text Available Abstract Background Traumatic brain injury (TBI affects approximately 10 million people annually, of which intracranial hemorrhage is a devastating sequelae, occurring in one-third to half of cases. Patients in low and middle-income countries (LMIC are twice as likely to die following TBI as compared to those in high-income countries. Diagnostic capabilities and treatment options for intracranial hemorrhage are limited in LMIC as there are fewer computed tomography (CT scanners and neurosurgeons per patient as in high-income countries. Methods The Medical Research Council CRASH-1 trial was utilized to build this model. The study cohort included all patients from LMIC who received a CT scan of the brain (n = 5669. Prognostic variables investigated included age, sex, time from injury to randomization, pupil reactivity, cause of injury, seizure and the presence of major extracranial injury. Results There were five predictors that were included in the final model; age, Glasgow Coma Scale, pupil reactivity, the presence of a major extracranial injury and time from injury to presentation. The model demonstrated good discrimination and excellent calibration (c-statistic 0.71. A simplified risk score was created for clinical settings to estimate the percentage risk of intracranial hemorrhage among TBI patients. Conclusion Simple prognostic models can be used in LMIC to estimate the risk of intracranial hemorrhage among TBI patients. Combined with clinical judgment this may facilitate risk stratification, rapid transfer to higher levels of care and treatment in resource-poor settings.

  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....... 82% for low risk group (P new drug trials....

  20. [Prognostic factors of postoperative delayed gastric emptying after pancreaticoduodenectomy: a predictive model].

    Science.gov (United States)

    Tan, H T; Zong, Y; Zhao, Z Q; Wu, L F; Liu, J; Sun, B; Jiang, H C

    2017-05-01

    Objective: To study the prognostic factors of delayed gastric emptying(DGE) after pancreaticoduodenectomy(PD) and construct a prognostic predictive model for clinical application. Methods: Clinic data of 401 consecutive patients who underwent PD between January 2012 and July 2016 in the First Affiliated Hospital of Harbin Medical University were retrospectively collected and analyzed. The patients were randomly selected to modeling group(n=299) and validation group(n=102) at a ratio of 3∶1. The data of modeling group were subjected to univariate and multivariate analysis for prognostic factors and to construct a prognostic predictive model of DGE after PD. The data of validation group were applied to test the prognostic predictive model. Results: DGE after PD occurred in 35 of 299 patients(11.7%) in the modeling group. The multivariate analysis of the modeling group showed that upper abdominal operation history(χ(2)=6.533, P=0.011), diabetes mellitus(χ(2)=17.872, P=0.000), preoperative hemoglobin predictive model of DGE after PD was constructed based on these factors and successfully tested. The area under the receiver operating characteristic(ROC) curve was 0.761(95%CI: 0.666-0.856) of the modeling group and 0.750(95% CI: 0.577-0.923) of the validation group. Conclusions: Upper abdominal operation history, diabetes mellitus, preoperative hemoglobinmodel is a valid tool to take precautions against DGE after PD.

  1. A prognostic model for lung adenocarcinoma patient survival with a focus on four miRNAs.

    Science.gov (United States)

    Li, Xianqiu; An, Zhaoling; Li, Peihui; Liu, Haihua

    2017-09-01

    There is currently no effective biomarker for determining the survival of patients with lung adenocarcinoma. The purpose of the present study was to construct a prognostic survival model using microRNA (miRNA) expression data from patients with lung adenocarcinoma. miRNA data were obtained from The Cancer Genome Atlas, and patients with lung adenocarcinoma were divided into either the training or validation set based on the random allocation principle. The prognostic model focusing on miRNA was constructed, and patients were divided into high-risk or low-risk groups as per the scores, to assess their survival time. The 5-year survival rate from the subgroups within the high- and low-risk groups was assessed. P-values of the prognostic model in the total population, the training set and validation set were 0.0017, 0.01986 and 0.02773, respectively, indicating that the survival time of the lung adenocarcinoma high-risk group was less than that of the low-risk group. Thus, the model had a good assessment effectiveness for the untreated group (P=0.00088) and the Caucasian patient group (P=0.00043). In addition, the model had the best prediction effect for the 5-year survival rate of the Caucasian patient group (AUC=0.629). In conclusion, the prognostic model developed in the present study can be used as an independent prognostic model for patients with lung adenocarcinoma.

  2. Remaining useful life prognostics for aeroengine based on superstatistics and information fusion

    Directory of Open Access Journals (Sweden)

    Liu Junqiang

    2014-10-01

    Full Text Available Remaining useful life (RUL prognostics is a fundamental premise to perform condition-based maintenance (CBM for a system subject to performance degradation. Over the past decades, research has been conducted in RUL prognostics for aeroengine. However, most of the prognostics technologies and methods simply base on single parameter, making it hard to demonstrate the specific characteristics of its degradation. To solve such problems, this paper proposes a novel approach to predict RUL by means of superstatistics and information fusion. The performance degradation evolution of the engine is modeled by fusing multiple monitoring parameters, which manifest non-stationary characteristics while degrading. With the obtained degradation curve, prognostics model can be established by state-space method, and then RUL can be estimated when the time-varying parameters of the model are predicted and updated through Kalman filtering algorithm. By this method, the non-stationary degradation of each parameter is represented, and multiple monitoring parameters are incorporated, both contributing to the final prognostics. A case study shows that this approach enables satisfactory prediction evolution and achieves a markedly better prognosis of RUL.

  3. 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

  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. Particle filter-based prognostic approach for railway track geometry

    Science.gov (United States)

    Mishra, Madhav; Odelius, Johan; Thaduri, Adithya; Nissen, Arne; Rantatalo, Matti

    2017-11-01

    Track degradation of ballasted railway track systems has to be measured on a regular basis, and these tracks must be maintained by tamping. Tamping aims to restore the geometry to its original shape to ensure an efficient, comfortable and safe transportation system. To minimize the disturbance introduced by tamping, this action has to be planned in advance. Track degradation forecasts derived from regression methods are used to predict when the standard deviation of a specific track section will exceed a predefined maintenance or safety limit. This paper proposes a particle filter-based prognostic approach for railway track degradation; this approach is demonstrated by examining different railway switches. The standard deviation of the longitudinal track degradation is studied, and forecasts of the maintenance limit intersection are derived. The particle filter-based prognostic results are compared with the standard regression method results for four railway switches, and the particle filter method shows similar or better result for the four cases. For longer prediction times, the error of the proposed method is equal to or smaller than that of the regression method. The main advantage of the particle filter-based prognostic approach is its ability to generate a probabilistic result based on input parameters with uncertainties. The distributions of the input parameters propagate through the filter, and the remaining useful life is presented using a particle distribution.

  7. Stroma Based Prognosticators Incorporating Differences between African and European Americans

    Science.gov (United States)

    2017-10-01

    We also proposed to study DNA methylation differences in Formalin-fixed paraffin-embedded (FFPE) samples (the material utilized in Pathology ). FFPE... Construct prognosticators for recurrence in AA and EA separately, and in AA+EA combined, with and without clinical parameters. Training set. 12-15 50...Microenvironment: Prospects for Diagnosis and Prognosis of Prostate Cancer Based on Changes in Tumor-Adjacent Stroma. Precision Molecular Pathology of

  8. Prognostics of Proton Exchange Membrane Fuel Cells stack using an ensemble of constraints based connectionist networks

    Science.gov (United States)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine; Hissel, Daniel

    2016-08-01

    Proton Exchange Membrane Fuel Cell (PEMFC) is considered the most versatile among available fuel cell technologies, which qualify for diverse applications. However, the large-scale industrial deployment of PEMFCs is limited due to their short life span and high exploitation costs. Therefore, ensuring fuel cell service for a long duration is of vital importance, which has led to Prognostics and Health Management of fuel cells. More precisely, prognostics of PEMFC is major area of focus nowadays, which aims at identifying degradation of PEMFC stack at early stages and estimating its Remaining Useful Life (RUL) for life cycle management. This paper presents a data-driven approach for prognostics of PEMFC stack using an ensemble of constraint based Summation Wavelet- Extreme Learning Machine (SW-ELM) models. This development aim at improving the robustness and applicability of prognostics of PEMFC for an online application, with limited learning data. The proposed approach is applied to real data from two different PEMFC stacks and compared with ensembles of well known connectionist algorithms. The results comparison on long-term prognostics of both PEMFC stacks validates our proposition.

  9. 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

    We aimed to create a prognostic model in metastatic melanoma based on independent prognostic factors in 321 patients receiving interleukin-2 (IL-2)-based immunotherapy with a median follow-up time for patients currently alive of 52 months (range 15-189 months). The patients were treated as part...... factors in univariate analyses. Subsequently, a multivariate Cox's regression analysis identified elevated LDH (P

  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. Melanoma prognostic model using tissue microarrays and genetic algorithms.

    Science.gov (United States)

    Gould Rothberg, Bonnie E; Berger, Aaron J; Molinaro, Annette M; Subtil, Antonio; Krauthammer, Michael O; Camp, Robert L; Bradley, William R; Ariyan, Stephan; Kluger, Harriet M; Rimm, David L

    2009-12-01

    As a result of the questionable risk-to-benefit ratio of adjuvant therapies, stage II melanoma is currently managed by observation because available clinicopathologic parameters cannot identify the 20% to 60% of such patients likely to develop metastatic disease. Here, we propose a multimarker molecular prognostic assay that can help triage patients at increased risk of recurrence. Protein expression for 38 candidates relevant to melanoma oncogenesis was evaluated using the automated quantitative analysis (AQUA) method for immunofluorescence-based immunohistochemistry in formalin-fixed, paraffin-embedded specimens from a cohort of 192 primary melanomas collected during 1959 to 1994. The prognostic assay was built using a genetic algorithm and validated on an independent cohort of 246 serial primary melanomas collected from 1997 to 2004. Multiple iterations of the genetic algorithm yielded a consistent five-marker solution. A favorable prognosis was predicted by ATF2 ln(non-nuclear/nuclear AQUA score ratio) of more than -0.052, p21(WAF1) nuclear compartment AQUA score of more than 12.98, p16(INK4A) ln(non-nuclear/nuclear AQUA score ratio) of < or = -0.083, beta-catenin total AQUA score of more than 38.68, and fibronectin total AQUA score of < or = 57.93. Primary tumors that met at least four of these five conditions were considered a low-risk group, and those that met three or fewer conditions formed a high-risk group (log-rank P < .0001). Multivariable proportional hazards analysis adjusting for clinicopathologic parameters shows that the high-risk group has significantly reduced survival on both the discovery (hazard ratio = 2.84; 95% CI, 1.46 to 5.49; P = .002) and validation (hazard ratio = 2.72; 95% CI, 1.12 to 6.58; P = .027) cohorts. This multimarker prognostic assay, an independent determinant of melanoma survival, might be beneficial in improving the selection of stage II patients for adjuvant therapy.

  12. Remote sensing data assimilation for a prognostic phenology model

    Energy Technology Data Exchange (ETDEWEB)

    Thornton, Peter E [ORNL; Stockli, Reto [Colorado State University, Fort Collins

    2008-01-01

    Predicting the global carbon and water cycle requires a realistic representation of vegetation phenology in climate models. However most prognostic phenology models are not yet suited for global applications, and diagnostic satellite data can be uncertain and lack predictive power. We present a framework for data assimilation of Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) and Leaf Area Index (LAI) from the MODerate Resolution Imaging Spectroradiometer (MODIS) to constrain empirical temperature, light, moisture and structural vegetation parameters of a prognostic phenology model. We find that data assimilation better constrains structural vegetation parameters than climate control parameters. Improvements are largest for drought-deciduous ecosystems where correlation of predicted versus satellite-observed FPAR and LAI increases from negative to 0.7-0.8. Data assimilation effectively overcomes the cloud- and aerosol-related deficiencies of satellite data sets in tropical areas. Validation with a 49-year-long phenology data set reveals that the temperature-driven start of season (SOS) is light limited in warm years. The model has substantial skill (R = 0.73) to reproduce SOS inter-annual and decadal variability. Predicted SOS shows a higher inter-annual variability with a negative bias of 5-20 days compared to species-level SOS. It is however accurate to within 1-2 days compared to SOS derived from net ecosystem exchange (NEE) measurements at a FLUXNET tower. The model only has weak skill to predict end of season (EOS). Use of remote sensing data assimilation for phenology model development is encouraged but validation should be extended with phenology data sets covering mediterranean, tropical and arctic ecosystems.

  13. 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

  14. 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

    2017-10-28

    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.

  15. Electromechanical actuators affected by multiple failures: Prognostic method based on spectral analysis techniques

    Science.gov (United States)

    Belmonte, D.; Vedova, M. D. L. Dalla; Ferro, C.; Maggiore, P.

    2017-06-01

    The proposal of prognostic algorithms able to identify precursors of incipient failures of primary flight command electromechanical actuators (EMA) is beneficial for the anticipation of the incoming failure: an early and correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. An innovative prognostic model-based approach, able to recognize the EMA progressive degradations before his anomalous behaviors become critical, is proposed: the Fault Detection and Identification (FDI) of the considered incipient failures is performed analyzing proper system operational parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. Subsequently, these operational parameters will be correlated with the actual EMA health condition by means of failure maps created by a reference monitoring model-based algorithm. In this work, the proposed method has been tested in case of EMA affected by combined progressive failures: in particular, partial stator single phase turn to turn short-circuit and rotor static eccentricity are considered. In order to evaluate the prognostic method, a numerical test-bench has been conceived. Results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual malfunctioning, minimizing the risk of fake alarms or unannounced failures.

  16. 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.

  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. Prognostic and Remaining Life Prediction of Electronic Device under Vibration Condition Based on CPSD of MPI

    Directory of Open Access Journals (Sweden)

    Ying Chen

    2016-01-01

    Full Text Available Prognostic of electronic device under vibration condition can help to get information to assist in condition-based maintenance and reduce life-cycle cost. A prognostic and remaining life prediction method for electronic devices under random vibration condition is proposed. Vibration response is measured and monitored with acceleration sensor and OMA parameters, including vibration resonance frequency, especially first-order resonance frequency, and damping ratio is calculated with cross-power spectrum density (CPSD method and modal parameter identification (MPI algorithm. Steinberg vibration fatigue model which considers transmissibility factor is used to predict the remaining life of electronic component. Case study with a test board is carried out and remaining life is predicted. Results show that with this method the vibration response characteristic can be monitored and predicted.

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

    Science.gov (United States)

    Wozniak, Matthew C.; Steiner, Allison L.

    2017-11-01

    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 model for the

  20. 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

  1. 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

  2. Systematic review of multivariable prognostic models for mild traumatic brain injury.

    Science.gov (United States)

    Silverberg, Noah D; Gardner, Andrew J; Brubacher, Jeffrey R; Panenka, William J; Li, Jun Jian; Iverson, Grant L

    2015-04-15

    Prognostic models can guide clinical management and increase statistical power in clinical trials. The availability and adequacy of prognostic models for mild traumatic brain injury (MTBI) is uncertain. The present study aimed to (1) identify and evaluate multivariable prognostic models for MTBI, and (2) determine which pre-, peri-, and early post-injury variables have independent prognostic value in the context of multivariable models. An electronic search of MEDLINE, PsycINFO, PubMed, EMBASE, and CINAHL databases for English-language MTBI cohort studies from 1970-2013 was supplemented by Web of Science citation and hand searching. This search strategy identified 7789 articles after removing duplicates. Of 182 full-text articles reviewed, 26 met eligibility criteria including (1) prospective inception cohort design, (2) prognostic information collected within 1 month post-injury, and (3) 2+variables combined to predict clinical outcome (e.g., post-concussion syndrome) at least 1 month later. Independent reviewers extracted sample characteristics, study design features, clinical outcome variables, predictor selection methods, and prognostic model discrimination, calibration, and cross-validation. These data elements were synthesized qualitatively. The present review found no multivariable prognostic model that adequately predicts individual patient outcomes from MTBI. Suboptimal methodology limits their reproducibility and clinical usefulness. The most robust prognostic factors in the context of multivariable models were pre-injury mental health and early post-injury neuropsychological functioning. Women and adults with early post-injury anxiety also have worse prognoses. Relative to these factors, the severity of MTBI had little long-term prognostic value. Future prognostic studies should consider a broad range of biopsychosocial predictors in large inception cohorts.

  3. GPU Accelerated Prognostics

    Science.gov (United States)

    Gorospe, George E., Jr.; Daigle, Matthew J.; Sankararaman, Shankar; Kulkarni, Chetan S.; Ng, Eley

    2017-01-01

    Prognostic methods enable operators and maintainers to predict the future performance for critical systems. However, these methods can be computationally expensive and may need to be performed each time new information about the system becomes available. In light of these computational requirements, we have investigated the application of graphics processing units (GPUs) as a computational platform for real-time prognostics. Recent advances in GPU technology have reduced cost and increased the computational capability of these highly parallel processing units, making them more attractive for the deployment of prognostic software. We present a survey of model-based prognostic algorithms with considerations for leveraging the parallel architecture of the GPU and a case study of GPU-accelerated battery prognostics with computational performance results.

  4. Prognostic transcriptional association networks: a new supervised approach based on regression trees

    Science.gov (United States)

    Nepomuceno-Chamorro, Isabel; Azuaje, Francisco; Devaux, Yvan; Nazarov, Petr V.; Muller, Arnaud; Aguilar-Ruiz, Jesús S.; Wagner, Daniel R.

    2011-01-01

    Motivation: The application of information encoded in molecular networks for prognostic purposes is a crucial objective of systems biomedicine. This approach has not been widely investigated in the cardiovascular research area. Within this area, the prediction of clinical outcomes after suffering a heart attack would represent a significant step forward. We developed a new quantitative prediction-based method for this prognostic problem based on the discovery of clinically relevant transcriptional association networks. This method integrates regression trees and clinical class-specific networks, and can be applied to other clinical domains. Results: Before analyzing our cardiovascular disease dataset, we tested the usefulness of our approach on a benchmark dataset with control and disease patients. We also compared it to several algorithms to infer transcriptional association networks and classification models. Comparative results provided evidence of the prediction power of our approach. Next, we discovered new models for predicting good and bad outcomes after myocardial infarction. Using blood-derived gene expression data, our models reported areas under the receiver operating characteristic curve above 0.70. Our model could also outperform different techniques based on co-expressed gene modules. We also predicted processes that may represent novel therapeutic targets for heart disease, such as the synthesis of leucine and isoleucine. Availability: The SATuRNo software is freely available at http://www.lsi.us.es/isanepo/toolsSaturno/. Contact: inepomuceno@us.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21098433

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Zachary Welz

    2017-08-01

    Full Text Available 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.

  7. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Vivek [Idaho National Lab. (INL), Idaho Falls, ID (United States); Lybeck, Nancy J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pham, Binh [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rusaw, Richard [Electric Power Research Inst. (EPRI), Palo Alto, CA (United States); Bickford, Randall [Expert Microsystems, Orangevale, CA (United States)

    2015-02-01

    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.

  9. 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

    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......R-21), quantified by in situ hybridisation, in a unique, large population-based cohort. PATIENTS AND METHODS: The study included 764 patients diagnosed with stage II colon cancer in Denmark in the year 2003. One section from a representative paraffin-embedded tumour tissue specimen from each patient...

  10. 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.

  11. A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering.

    Science.gov (United States)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine

    2015-12-01

    Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading machinery to optimize its service delivery potential. However, machinery operates in a dynamic environment and the acquired condition monitoring data are usually noisy and subject to a high level of uncertainty/unpredictability, which complicates prognostics. The complexity further increases, when there is absence of prior knowledge about ground truth (or failure definition). For such issues, data-driven prognostics can be a valuable solution without deep understanding of system physics. This paper contributes a new data-driven prognostics approach namely, an "enhanced multivariate degradation modeling," which enables modeling degrading states of machinery without assuming a homogeneous pattern. In brief, a predictability scheme is introduced to reduce the dimensionality of the data. Following that, the proposed prognostics model is achieved by integrating two new algorithms namely, the summation wavelet-extreme learning machine and subtractive-maximum entropy fuzzy clustering to show evolution of machine degradation by simultaneous predictions and discrete state estimation. The prognostics model is equipped with a dynamic failure threshold assignment procedure to estimate RUL in a realistic manner. To validate the proposition, a case study is performed on turbofan engines data from PHM challenge 2008 (NASA), and results are compared with recent publications.

  12. Survival probabilities of Pugh-child-PBC classified patients in the Euricterus primary biliary cirrhosis population, based on the Mayo clinic prognostic model

    NARCIS (Netherlands)

    Reisman, Y; vanDam, GM; Gips, CH; Lavelle, SM; CuervasMons, [No Value; deDombal, FT; Gauthier, A; MalchowMoller, A; Molino, G; Theodossi, A; Tsiftsis, DD; Dawids, S; Larsson, L

    1997-01-01

    Background/Aims: Estimation of prognosis becomes increasingly important in primary biliary cirrhosis (PBC) with advancing disease and also with regard to patient management. The ubiquitous used Pugh scoring for severity of disease is simple while the Mayo model which has been validated for survival

  13. 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.

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

    Science.gov (United States)

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

    2017-10-17

    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 different disease profiles, resource availability, and heterogeneity of the population may limit the transferability of such scores. A major shortcoming in using such models in LMICs is the unavailability of required measurements. This study proposes a simplified critical care prognostic model for use at the time of ICU admission. This was a prospective study of 3855 patients admitted to 21 ICUs from Bangladesh, India, Nepal, and Sri Lanka who were aged 16 years and over and followed to ICU discharge. Variables captured included patient age, admission characteristics, clinical assessments, laboratory investigations, and treatment measures. Multivariate logistic regression was used to develop three models for ICU mortality prediction: model 1 with clinical, laboratory, and treatment variables; model 2 with clinical and laboratory variables; and model 3, a purely clinical model. Internal validation based on bootstrapping (1000 samples) was used to calculate discrimination (area under the receiver operating characteristic curve (AUC)) and calibration (Hosmer-Lemeshow C-Statistic; higher values indicate poorer calibration). Comparison was made with the Acute Physiology and Chronic Health Evaluation (APACHE) II and Simplified Acute Physiology Score (SAPS) II models. Model 1 recorded the respiratory rate, systolic blood pressure, Glasgow Coma Scale (GCS), blood urea, haemoglobin, mechanical ventilation, and vasopressor use on ICU admission. Model 2, named TropICS (Tropical Intensive Care Score), included emergency surgery, respiratory rate, systolic blood pressure, GCS, blood urea, and haemoglobin. Model 3 included respiratory rate, emergency surgery, and GCS. AUC was 0.818 (95% confidence

  15. Prognostic models in acute pulmonary embolism: a systematic review and meta-analysis

    Science.gov (United States)

    Elias, Antoine; Mallett, Susan; Daoud-Elias, Marie; Poggi, Jean-Noël; Clarke, Mike

    2016-01-01

    Objective To review the evidence for existing prognostic models in acute pulmonary embolism (PE) and determine how valid and useful they are for predicting patient outcomes. Design Systematic review and meta-analysis. Data sources OVID MEDLINE and EMBASE, and The Cochrane Library from inception to July 2014, and sources of grey literature. Eligibility criteria Studies aiming at constructing, validating, updating or studying the impact of prognostic models to predict all-cause death, PE-related death or venous thromboembolic events up to a 3-month follow-up in patients with an acute symptomatic PE. Data extraction Study characteristics and study quality using prognostic criteria. Studies were selected and data extracted by 2 reviewers. Data analysis Summary estimates (95% CI) for proportion of risk groups and event rates within risk groups, and accuracy. Results We included 71 studies (44 298 patients). Among them, 17 were model construction studies specific to PE prognosis. The most validated models were the PE Severity Index (PESI) and its simplified version (sPESI). The overall 30-day mortality rate was 2.3% (1.7% to 2.9%) in the low-risk group and 11.4% (9.9% to 13.1%) in the high-risk group for PESI (9 studies), and 1.5% (0.9% to 2.5%) in the low-risk group and 10.7% (8.8% to12.9%) in the high-risk group for sPESI (11 studies). PESI has proved clinically useful in an impact study. Shifting the cut-off or using novel and updated models specifically developed for normotensive PE improves the ability for identifying patients at lower risk for early death or adverse outcome (0.5–1%) and those at higher risk (up to 20–29% of event rate). Conclusions We provide evidence-based information about the validity and utility of the existing prognostic models in acute PE that may be helpful for identifying patients at low risk. Novel models seem attractive for the high-risk normotensive PE but need to be externally validated then be assessed in impact studies. PMID

  16. A Hidden Semi-Markov Model with Duration-Dependent State Transition Probabilities for Prognostics

    Directory of Open Access Journals (Sweden)

    Ning Wang

    2014-01-01

    Full Text Available Realistic prognostic tools are essential for effective condition-based maintenance systems. In this paper, a Duration-Dependent Hidden Semi-Markov Model (DD-HSMM is proposed, which overcomes the shortcomings of traditional Hidden Markov Models (HMM, including the Hidden Semi-Markov Model (HSMM: (1 it allows explicit modeling of state transition probabilities between the states; (2 it relaxes observations’ independence assumption by accommodating a connection between consecutive observations; and (3 it does not follow the unrealistic Markov chain’s memoryless assumption and therefore it provides a more powerful modeling and analysis capability for real world problems. To facilitate the computation of the proposed DD-HSMM methodology, new forward-backward algorithm is developed. The demonstration and evaluation of the proposed methodology is carried out through a case study. The experimental results show that the DD-HSMM methodology is effective for equipment health monitoring and management.

  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. 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

    2017-01-01

    intracranial tumor volume (CITV) into the ds-GPA model for melanoma augmented its prognostic value. OBJECTIVE: To determine whether or not CITV augments the ds-GPA prognostic scale for melanoma. METHODS: We analyzed the survival pattern of 344 melanoma patients with BM treated with stereotactic radiosurgery...... (SRS) at separate institutions and validated our findings in an independent cohort of 201 patients. The prognostic value of ds-GPA for melanoma was quantitatively compared with and without the addition of CITV using the net reclassification index (NRI > 0) and integrated discrimination improvement (IDI...... validated these findings that CITV improves the prognostic utility of melanoma ds-GPA in an independent cohort of 201 melanoma cohort. CONCLUSION: The prognostic value of the ds-GPA scale for melanoma BM is enhanced by the incorporation of CITV....

  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. Geoinformational prognostic model of mudflows hazard and mudflows risk for the territory of Ukrainian Carpathians

    Science.gov (United States)

    Chepurna, Tetiana B.; Kuzmenko, Eduard D.; Chepurnyj, Igor V.

    2017-06-01

    The article is devoted to the geological issue of the space-time regional prognostication of mudflow hazard. The methodology of space-time prediction of mudflows hazard by creating GIS predictive model has been developed. Using GIS technologies the relevant and representative complex of significant influence of spatial and temporal factors, adjusted to use in the regional prediction of mudflows hazard, were selected. Geological, geomorphological, technological, climatic, and landscape factors have been selected as spatial mudflow factors. Spatial analysis is based on detection of a regular connection of spatial factor characteristics with spatial distribution of the mudflow sites. The function of a standard complex spatial index (SCSI) of the probability of the mudflow sites distribution has been calculated. The temporal, long-term prediction of the mudflows activity was based on the hypothesis of the regular reiteration of natural processes. Heliophysical, seismic, meteorological, and hydrogeological factors have been selected as time mudflow factors. The function of a complex index of long standing mudflow activity (CIMA) has been calculated. The prognostic geoinformational model of mudflow hazard up to 2020 year, a year of the next peak of the mudflows activity, has been created. Mudflow risks have been counted and carogram of mudflow risk assessment within the limits of administrative-territorial units has been built for 2020 year.

  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. Prognostic immune-related gene models for breast cancer: a pooled analysis.

    Science.gov (United States)

    Zhao, Jianli; Wang, Ying; Lao, Zengding; Liang, Siting; Hou, Jingyi; Yu, Yunfang; Yao, Herui; You, Na; Chen, Kai

    2017-01-01

    Breast cancer, the most common cancer among women, is a clinically and biologically heterogeneous disease. Numerous prognostic tools have been proposed, including gene signatures. Unlike proliferation-related prognostic gene signatures, many immune-related gene signatures have emerged as principal biology-driven predictors of breast cancer. Diverse statistical methods and data sets were used for building these immune-related prognostic models, making it difficult to compare or use them in clinically meaningful ways. This study evaluated successfully published immune-related prognostic gene signatures through systematic validations of publicly available data sets. Eight prognostic models that were built upon immune-related gene signatures were evaluated. The performances of these models were compared and ranked in ten publicly available data sets, comprising a total of 2,449 breast cancer cases. Predictive accuracies were measured as concordance indices (C-indices). All tests of statistical significance were two-sided. Immune-related gene models performed better in estrogen receptor-negative (ER-) and lymph node-positive (LN+) breast cancer subtypes. The three top-ranked ER- breast cancer models achieved overall C-indices of 0.62-0.63. Two models predicted better than chance for ER+ breast cancer, with C-indices of 0.53 and 0.59, respectively. For LN+ breast cancer, four models showed predictive advantage, with C-indices between 0.56 and 0.61. Predicted prognostic values were positively correlated with ER status when evaluated using univariate analyses in most of the models under investigation. Multivariate analyses indicated that prognostic values of the three models were independent of known clinical prognostic factors. Collectively, these analyses provided a comprehensive evaluation of immune-related prognostic gene signatures. By synthesizing C-indices in multiple independent data sets, immune-related gene signatures were ranked for ER+, ER-, LN+, and LN- breast

  3. Validation, revision and extension of the Mantle Cell Lymphoma International Prognostic Index in a population-based setting.

    Science.gov (United States)

    van de Schans, Saskia A M; Janssen-Heijnen, Maryska L G; Nijziel, Marten R; Steyerberg, Ewout W; van Spronsen, Dick Johan

    2010-09-01

    The aim of this study was to validate the Mantle Cell Lymphoma International Prognostic Index in a population-based cohort and to study the relevance of its revisions. We analyzed data from 178 unselected patients with stage III or IV mantle cell lymphoma, registered between 1994 and 2006 in the Eindhoven Cancer Registry. Follow-up was completed up to January 1(st), 2008. Multiple imputations for missing covariates were used. Validity was assessed by comparing observed survival in our cohort with predicted survival according to the original Mantle cell lymphoma International Prognostic Index. A revised model was constructed with Cox regression analysis. Discrimination was assessed by a concordance statistic ('c'). The original Mantle cell lymphoma International Prognostic Index could stratify our cohort into three distinct risk groups based on Eastern Cooperative Group performance status, white blood cell count, lactate dehydrogenase level, and age, with the discrimination being nearly as good as in the original cohort (c 0.65 versus 0.63). A modified model including performance status in five categories (0/1/2/3/4) instead of two (0-1/2-4), the presence of B-symptoms (yes/no) and sex (male/female) in addition to the original variables resulted in a better prognostic index (c 0.75). The Mantle cell lymphoma International Prognostic Index is a valid tool for risk stratification, comparison of prognosis, and treatment decisions in an unselected Dutch population-based setting. Although the index can be significantly improved, external validation on an independent data set is warranted before broad application of the modified instrument could be recommended.

  4. Model Updating and Uncertainty Management for Aircraft Prognostic Systems Project

    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...

  5. Baseline elevated leukocyte count in peripheral blood is associated with poor survival in patients with advanced non-small cell lung cancer: a prognostic model.

    Science.gov (United States)

    Tibaldi, C; Vasile, E; Bernardini, I; Orlandini, C; Andreuccetti, M; Falcone, A

    2008-10-01

    We aimed to investigate the prognostic significance of several baseline variables in stage IIIB-IV non-small cell lung cancer to create a model based on independent prognostic factors. A total of 320 patients were treated with last generation chemotherapy regimens. The majority of patients received treatment with cisplatin + gemcitabine or gemcitabine alone if older than 70 years or with an ECOG performance status (PS) = 2. Performance status of 2, squamous histology, number of metastatic sites >2, presence of bone, brain, liver and contralateral lung metastases and elevated leukocyte count in peripheral blood were all statistically significant prognostic factors in univariate analyses whereas the other tested variables (sex, stage, age, presence of adrenal gland and skin metastases) were not. Subsequently, a multivariate Cox's regression analysis identified PS 2 (P leukocyte count (P Leukocyte count resulted the stronger factor after performance status. If prospectly validated, the proposed prognostic model could be useful to stratify performance status 2 patients in specific future trials.

  6. A Prognostic Model for One-year Mortality in Patients Requiring Prolonged Mechanical Ventilation

    Science.gov (United States)

    Carson, Shannon S.; Garrett, Joanne; Hanson, Laura C.; Lanier, Joyce; Govert, Joe; Brake, Mary C.; Landucci, Dante L.; Cox, Christopher E.; Carey, Timothy S.

    2009-01-01

    Objective A measure that identifies patients who are at high risk of mortality after prolonged ventilation will help physicians communicate prognosis to patients or surrogate decision-makers. Our objective was to develop and validate a prognostic model for 1-year mortality in patients ventilated for 21 days or more. Design Prospective cohort study. Setting University-based tertiary care hospital Patients 300 consecutive medical, surgical, and trauma patients requiring mechanical ventilation for at least 21 days were prospectively enrolled. Measurements and Main Results Predictive variables were measured on day 21 of ventilation for the first 200 patients and entered into logistic regression models with 1-year and 3-month mortality as outcomes. Final models were validated using data from 100 subsequent patients. One-year mortality was 51% in the development set and 58% in the validation set. Independent predictors of mortality included requirement for vasopressors, hemodialysis, platelet count ≤150 ×109/L, and age ≥50. Areas under the ROC curve for the development model and validation model were 0.82 (se 0.03) and 0.82 (se 0.05) respectively. The model had sensitivity of 0.42 (se 0.12) and specificity of 0.99 (se 0.01) for identifying patients who had ≥90% risk of death at 1 year. Observed mortality was highly consistent with both 3- and 12-month predicted mortality. These four predictive variables can be used in a simple prognostic score that clearly identifies low risk patients (no risk factors, 15% mortality) and high risk patients (3 or 4 risk factors, 97% mortality). Conclusions Simple clinical variables measured on day 21 of mechanical ventilation can identify patients at highest and lowest risk of death from prolonged ventilation. PMID:18552692

  7. Prognostic Gleason grade grouping: data based on the modified Gleason scoring system

    Science.gov (United States)

    Pierorazio, Phillip M.; Walsh, Patrick C.; Partin, Alan W.; Epstein, Jonathan I.

    2014-01-01

    Objective • To investigate pathological and short-term outcomes since the most recent Gleason system modifications by the International Society of Urological Pathology (ISUP) in an attempt to divide the current Gleason grading system into prognostically accurate Gleason grade groups. Patients and Methods • We queried the Johns Hopkins Radical Prostatectomy Database (1982–2011), approved by the institutional review board, for men undergoing radical prostatectomy (RP) without a tertiary pattern since 2004 and identified 7869 men. • Multivariable models were created using preoperative and postoperative variables; prognostic grade group (Gleason grade ≤6; 3 + 4; 4 + 3; 8; 9–10) was among the strongest predictors of biochemical recurrence-free (BFS) survival. Results • Significant differences were noted among the Gleason grade groups at biopsy; differences were noted in the race, PSA level, clinical stage, number of positive cores at biopsy and the maximum percentage of positive cores among the Gleason grade groups at RP. • With a median (range) follow-up of 2 (1–7) years, 5-year BFS rates for men with Gleason grade ≤6, 3 + 4, 4 + 3, 8 and 9–10 tumours at biopsy were 94.6, 82.7, 65.1, 63.1 and 34.5%, respectively (P Gleason grading system for prostate carcinoma accurately categorize patients by pathological findings and short-term biochemical outcomes but, while retaining the essence of the Gleason system, there is a need for a change in its reporting to more closely reflect tumour behaviour. • We propose reporting Gleason grades, including prognostic grade groups which accurately reflect prognosis as follows: Gleason score ≤6 (prognostic grade group I); Gleason score 3+4=7 (prognostic grade group II); Gleason score 4+3=7 (prognostic grade group III); Gleason score 4+4=8 (prognostic grade group (IV); and Gleason score 9–10 (prognostic grade group (V). PMID:23464824

  8. 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

    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...... dehydrogenase (LDH), stage and albumin level, and (2) a separate age-adjusted DLBCL-PI for patients 1 extranodal lesion, however excluding stage....

  9. The search for stable prognostic models in multiple imputed data sets

    NARCIS (Netherlands)

    Vergouw, D.; Heijmans, M.W.; Peat, G.M.; Kuijpers, T.; Croft, P.R.; de Vet, H.C.W.; van der Horst, H.E.; van der Windt, D.A.W.M.

    2010-01-01

    Background: In prognostic studies model instability and missing data can be troubling factors. Proposed methods for handling these situations are bootstrapping (B) and Multiple imputation (MI). The authors examined the influence of these methods on model composition. Methods: Models were constructed

  10. Developing a CD-CBM Anticipatory Approach for Cavitation - Defining a Model-Based Descriptor Consistent Across Processes, Phase 1 Final Report Context-Dependent Prognostics and Health Assessment: A New Paradigm for Condition-based Maintenance SBIR Topic No. N98-114

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-06-01

    The objective of this research, and subsequent testing, was to identify specific features of cavitation that could be used as a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor is based on the physics of the phenomena, capturing the salient features of the process dynamics. The test methodology and approach were developed to make the cavitation features the dominant effect in the process and collected signatures. This would allow the accurate characterization of the salient cavitation features at different operational states. By developing such an abstraction, these attributes can be used as a general diagnostic for a system or any of its components. In this study, the particular focus will be pumps. As many as 90% of pump failures are catastrophic. They seem to be operating normally and fail abruptly without warning. This is true whether the failure is sudden hardware damage requiring repair, such as a gasket failure, or a transition into an undesired operating mode, such as cavitation. This means that conventional diagnostic methods fail to predict 90% of incipient failures and that in addressing this problem, model-based methods can add value where it is actually needed.

  11. Clinical prediction of 5-year survival in systemic sclerosis: validation of a simple prognostic model in EUSTAR centres

    NARCIS (Netherlands)

    Fransen, J.; Popa-Diaconu, D.A.; Hesselstrand, R.; Carreira, P.; Valentini, G.; Beretta, L.; Airo, P.; Inanc, M.; Ullman, S.; Balbir-Gurman, A.; Sierakowski, S.; Allanore, Y.; Czirjak, L.; Riccieri, V.; Giacomelli, R.; Gabrielli, A.; Riemekasten, G.; Matucci-Cerinic, M.; Farge, D.; Hunzelmann, N.; Hoogen, F.H. Van den; Vonk, M.C.

    2011-01-01

    OBJECTIVE: Systemic sclerosis (SSc) is associated with a significant reduction in life expectancy. A simple prognostic model to predict 5-year survival in SSc was developed in 1999 in 280 patients, but it has not been validated in other patients. The predictions of a prognostic model are usually

  12. Prognostic models for physical capacity at discharge and 1 year postdischarge from rehabilitation in persons with spinal cord injury

    NARCIS (Netherlands)

    Haisma, J.A.; van der Woude, L.H.V.; Stam, H.J.; Bergen, M.P.; Sluis, T.A.; de Groot, S.; Dallmeijer, A.J.; Bussmann, J.B.J.

    2007-01-01

    Haisma JA, van der Woude LH, Stam HJ, Bergen MP, Sluis TA, de Groot S, Dallmeijer AJ, Bussmann JB. Prognostic models for physical capacity at discharge and 1 year postdischarge from rehabilitation in persons with spinal cord injury. Objective: To develop prognostic models for physical capacity at

  13. 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, 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

    2016-01-01

    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

  14. 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

  15. Prognostic factors for metachronous contralateral breast cancer: a comparison of the linear Cox regression model and its artificial neural network extension.

    Science.gov (United States)

    Mariani, L; Coradini, D; Biganzoli, E; Boracchi, P; Marubini, E; Pilotti, S; Salvadori, B; Silvestrini, R; Veronesi, U; Zucali, R; Rilke, F

    1997-06-01

    The purpose of the present study was to assess prognostic factor for metachronous contralateral recurrence of breast cancer (CBC). Two factors were of particular interest, namely estrogen (ER) and progesterone (PgR) receptors assayed with the biochemical method in primary tumor tissue. Information was obtained from a prospective clinical database for 1763 axillary node-negative women who had received curative surgery, mostly of the conservative type, and followed-up for a median of 82 months. The analysis was performed based on both a standard (linear) Cox model and an artificial neural network (ANN) extension of this model proposed by Faraggi and Simon. Furthermore, to assess the prognostic importance of the factors considered, model predictive ability was computed. In agreement with already published studies, the results of our analysis confirmed the prognostic role of age at surgery, histology, and primary tumor site, in that young patients (extensive intraductal component, and a lower hazard in infiltrating lobular carcinoma or other histotypes. In spite of the above findings, the predictive value of both the standard and ANN Cox models was relatively low, thus suggesting an intrinsic limitation of the prognostic variables considered, rather than their suboptimal modeling. Research for better prognostic variables should therefore continue.

  16. Prognostic Model for Survival in Patients With Early Stage Cervical Cancer

    NARCIS (Netherlands)

    Biewenga, Petra; van der Velden, Jacobus; Mol, Ben Willem J.; Stalpers, Lukas J. A.; Schilthuis, Marten S.; van der Steeg, Jan Willem; Burger, Matthé P. M.; Buist, Marrije R.

    2011-01-01

    BACKGROUND: In the management of early stage cervical cancer, knowledge about the prognosis is critical. Although many factors have an impact on survival, their relative importance remains controversial. This study aims to develop a prognostic model for survival in early stage cervical cancer

  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.|info:eu-repo/dai/nl/157009939; 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. Prognostic model for survival in patients with early stage cervical cancer.

    Science.gov (United States)

    Biewenga, Petra; van der Velden, Jacobus; Mol, Ben Willem J; Stalpers, Lukas J A; Schilthuis, Marten S; van der Steeg, Jan Willem; Burger, Matthé P M; Buist, Marrije R

    2011-02-15

    In the management of early stage cervical cancer, knowledge about the prognosis is critical. Although many factors have an impact on survival, their relative importance remains controversial. This study aims to develop a prognostic model for survival in early stage cervical cancer patients and to reconsider grounds for adjuvant treatment. A multivariate Cox regression model was used to identify the prognostic weight of clinical and histological factors for disease-specific survival (DSS) in 710 consecutive patients who had surgery for early stage cervical cancer (FIGO [International Federation of Gynecology and Obstetrics] stage IA2-IIA). Prognostic scores were derived by converting the regression coefficients for each prognostic marker and used in a score chart. The discriminative capacity was expressed as the area under the curve (AUC) of the receiver operating characteristic. The 5-year DSS was 92%. Tumor diameter, histological type, lymph node metastasis, depth of stromal invasion, lymph vascular space invasion, and parametrial extension were independently associated with DSS and were included in a Cox regression model. This prognostic model, corrected for the 9% overfit shown by internal validation, showed a fair discriminative capacity (AUC, 0.73). The derived score chart predicting 5-year DSS showed a good discriminative capacity (AUC, 0.85). In patients with early stage cervical cancer, DSS can be predicted with a statistical model. Models, such as that presented here, should be used in clinical trials on the effects of adjuvant treatments in high-risk early cervical cancer patients, both to stratify and to include patients. Copyright © 2010 American Cancer Society.

  20. The search for stable prognostic models in multiple imputed data sets

    Directory of Open Access Journals (Sweden)

    de Vet Henrica CW

    2010-09-01

    Full Text Available Abstract Background In prognostic studies model instability and missing data can be troubling factors. Proposed methods for handling these situations are bootstrapping (B and Multiple imputation (MI. The authors examined the influence of these methods on model composition. Methods Models were constructed using a cohort of 587 patients consulting between January 2001 and January 2003 with a shoulder problem in general practice in the Netherlands (the Dutch Shoulder Study. Outcome measures were persistent shoulder disability and persistent shoulder pain. Potential predictors included socio-demographic variables, characteristics of the pain problem, physical activity and psychosocial factors. Model composition and performance (calibration and discrimination were assessed for models using a complete case analysis, MI, bootstrapping or both MI and bootstrapping. Results Results showed that model composition varied between models as a result of how missing data was handled and that bootstrapping provided additional information on the stability of the selected prognostic model. Conclusion In prognostic modeling missing data needs to be handled by MI and bootstrap model selection is advised in order to provide information on model stability.

  1. Population-based study of breast cancer in older women: prognostic factors of relative survival and predictors of treatment

    Directory of Open Access Journals (Sweden)

    Dialla Pegdwende

    2012-10-01

    Full Text Available Abstract Background A large proportion of women with breast cancer (BC are elderly. However, there is a lack of information regarding BC prognostic factors and care in this population. The aims of this study were to assess the prognostic factors of relative survival (RS among women with BC aged ≥ 75 years old and to identify the predictive factors of treatments administered to this population. Methods A population-based study was performed using data from the Cote d’Or breast and gynaecological cancer registry. Women aged 75 years and older with primary invasive BC and resident in Cote d’Or at the time of diagnosis made between January 1998 and December 2008 were retrospectively selected. Prognostic factors of RS were estimated in a generalized linear model with a Poisson error structure. RS rate for the whole population was given at 5 years. Logistic regression models were used to identify the predictors of the treatments administered. Results Six hundred and eighty-one women were included. Median age at diagnosis was 80. Comorbidities (p=0.02, pT stage (p=0.04, metastases (p= Conclusions Comorbid conditions adversely affect survival in older women with breast cancer. Moreover the results of this study showed that there are numerous predictors of the type of treatment administered, and that the most important were age and comorbidities.

  2. 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

  3. Prognostic value of a systemic inflammatory response index in metastatic renal cell carcinoma and construction of a predictive model

    Science.gov (United States)

    Li, Hongzhao; Chen, Luyao; Li, Xintao; Zhang, Yu; Xie, Yongpeng; Zhang, Xu

    2017-01-01

    Inflammation act as a crucial role in carcinogenesis and tumor progression. In this study, we aim to investigate the prognostic significance of systemic inflammatory biomarkers in metastatic renal cell carcinoma (mRCC) and develop a survival predictive model. One hundred and sixty-one mRCC patients who had undergone cytoreductive nephrectomy were enrolled from January 2006 to December 2013. We created a systemic inflammation response index (SIRI) basing on pretreatment hemoglobin and lymphocyte to monocyte ratio (LMR), and evaluated its associations with overall survival (OS) and clinicopathological features. Pretreatment hemoglobin and LMR both remained as independent factors adjusted for other markers of systemic inflammation responses and conventional clinicopathological parameters. A high SIRI seems to be an independent prognosis predictor of worse OS and was significantly correlated with aggressive tumor behaviors. Inclusion of the SIRI into a prognostic model including Fuhrman grade, histology, tumor necrosis and targeted therapy established a nomogram, which accurately predicted 1-year survival for mRCC patients. The SIRI seems to be a prognostic biomarker in mRCC patients. The proposed nomogram can be applied to predict OS of patients with mRCC after nephrectomy. PMID:28881716

  4. Fuzzy logic-based prognostic score for outcome prediction in esophageal cancer.

    Science.gov (United States)

    Wang, Chang-Yu; Lee, Tsair-Fwu; Fang, Chun-Hsiung; Chou, Jyh-Horng

    2012-11-01

    Given the poor prognosis of esophageal cancer and the invasiveness of combined modality treatment, improved prognostic scoring systems are needed. We developed a fuzzy logic-based system to improve the predictive performance of a risk score based on the serum concentrations of C-reactive protein (CRP) and albumin in a cohort of 271 patients with esophageal cancer before radiotherapy. Univariate and multivariate survival analyses were employed to validate the independent prognostic value of the fuzzy risk score. To further compare the predictive performance of the fuzzy risk score with other prognostic scoring systems, time-dependent receiver operating characteristic curve (ROC) analysis was used. Application of fuzzy logic to the serum values of CRP and albumin increased predictive performance for 1-year overall survival (AUC=0.773) compared with that of a single marker (AUC=0.743 and 0.700 for CRP and albumin, respectively), where the AUC denotes the area under curve. This fuzzy logic-based approach also performed consistently better than the Glasgow Prognostic Score (GPS) (AUC=0.745). Thus, application of fuzzy logic to the analysis of serum markers can more accurately predict the outcome for patients with esophageal cancer.

  5. A note on prognostic accuracy evaluation of regression models applied to longitudinal autocorrelated binary data

    Directory of Open Access Journals (Sweden)

    Giulia Barbati

    2014-11-01

    Full Text Available Background: Focus of this work was on evaluating the prognostic accuracy of two approaches for modelling binary longitudinal outcomes, a Generalized Estimating Equation (GEE and a likelihood based method, Marginalized Transition Model (MTM, in which a transition model is combined with a marginal generalized linear model describing the average response as a function of measured predictors.Methods: A retrospective study on cardiovascular patients and a prospective study on sciatic pain were used to evaluate discrimination by computing the Area Under the Receiver-Operating-Characteristics curve, (AUC, the Integrated Discrimination Improvement (IDI and the Net Reclassification Improvement (NRI at different time occasions. Calibration was also evaluated. A simulation study was run in order to compare model’s performance in a context of a perfect knowledge of the data generating mechanism. Results: Similar regression coefficients estimates and comparable calibration were obtained; an higher discrimination level for MTM was observed. No significant differences in calibration and MSE (Mean Square Error emerged in the simulation study, that instead confirmed the MTM higher discrimination level. Conclusions: The choice of the regression approach should depend on the scientific question being addressed, i.e. if the overall population-average and calibration or the subject-specific patterns and discrimination are the objectives of interest, and some recently proposed discrimination indices are useful in evaluating predictive accuracy also in a context of longitudinal studies.

  6. Incorporating a prognostic representation of marine nitrogen fixers into the global ocean biogeochemical model HAMOCC

    Science.gov (United States)

    Paulsen, Hanna; Ilyina, Tatiana; Six, Katharina D.; Stemmler, Irene

    2017-03-01

    Nitrogen (N2) fixation is a major source of bioavailable nitrogen to the euphotic zone, thereby exerting an important control on ocean biogeochemical cycling. This paper presents the incorporation of prognostic N2 fixers into the HAMburg Ocean Carbon Cycle model (HAMOCC), a component of the Max Planck Institute Earth System Model (MPI-ESM). Growth dynamics of N2 fixers in the model are based on physiological characteristics of the cyanobacterium Trichodesmium. The applied temperature dependency confines diazotrophic growth and N2 fixation to the tropical and subtropical ocean roughly between 40°S and 40°N. Simulated large-scale spatial patterns compare well with observations, and the global N2 fixation rate of 135.6 Tg N yr-1 is within the range of current estimates. The vertical distribution of N2 fixation also matches well the observations, with a major fraction of about 85% occurring in the upper 20 m. The observed seasonal variability at the stations BATS and ALOHA is reasonably reproduced, with highest fixation rates in northern summer/fall. Iron limitation was found to be an important factor in controlling the simulated distribution of N2 fixation, especially in the Pacific Ocean. The new model component considerably improves the representation of present-day N2 fixation in HAMOCC. It provides the basis for further studies on the role of diazotrophs in global biogeochemical cycles, as well as on the response of N2 fixation to changing environmental conditions.

  7. 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

    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...

  8. 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.

  9. Impact of the degree of anemia on the outcome of patients with myelodysplastic syndrome and its integration into the WHO classification-based Prognostic Scoring System (WPSS).

    Science.gov (United States)

    Malcovati, Luca; Della Porta, Matteo G; Strupp, Corinna; Ambaglio, Ilaria; Kuendgen, Andrea; Nachtkamp, Kathrin; Travaglino, Erica; Invernizzi, Rosangela; Pascutto, Cristiana; Lazzarino, Mario; Germing, Ulrich; Cazzola, Mario

    2011-10-01

    Anemia is an established negative prognostic factor in myelodysplastic syndromes but the relationship between its degree and clinical outcome is poorly defined. We, therefore, studied the relationship between severity of anemia and outcome in myelodysplastic syndrome patients. We studied 840 consecutive patients diagnosed with myelodysplastic syndromes at the Fondazione IRCCS Policlinico San Matteo, Pavia, Italy, and 504 patients seen at the Heinrich-Heine-University Hospital, Düsseldorf, Germany. Hemoglobin levels were monitored longitudinally and analyzed by means of time-dependent Cox's proportional hazards regression models. Hemoglobin levels lower than 9 g/dL in males (HR 5.56, P=0.018) and 8 g/dL in females (HR=5.35, P=0.026) were independently related to reduced overall survival, higher risk of non-leukemic death and cardiac death (Panemia, defined as hemoglobin below these thresholds, was found to be as effective as transfusion-dependency in the prognostic assessment. After integrating this definition of severe anemia into the WHO classification-based Prognostic Scoring System, time-dependent regression and landmark analyses showed that the refined model was able to identify risk groups with different survivals at any time during follow up. Accounting for severity of anemia through the WHO classification-based Prognostic Scoring System provides an objective criterion for prognostic assessment and implementation of risk-adapted treatment strategies in myelodysplastic syndrome patients.

  10. 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.

  11. A simple and effective prognostic staging system based on clinicopathologic features of intrahepatic cholangiocarcinoma.

    Science.gov (United States)

    Zhou, Huabang; Jiang, Xiaolan; Li, Qiaomei; Hu, Jingyi; Zhong, Zhengrong; Wang, Hao; Wang, Hui; Yang, Bing; Hu, Heping

    2015-01-01

    Incidence and mortality of intrahepatic cholangiocarcinoma (ICC) are increasing. However, its prognostic predictive system associated with outcome after surgery remains poorly defined. In this study, we conducted retrospective survival analyses in a primary cohort of 370 patients who underwent partial hepatectomy for ICC (2005 and 2009). We found that seven variables were significantly independent predictors for overall survival (OS): serum prealbumin (hazard ratio [HR]: 1.447; p = 0.015), carbohydrate antigen 19-9 (HR: 1.438; p = 0.009), carcinoembryonic antigen (HR: 1.732; p = 0.002), tumor number (HR: 1.781; p system for predicting survival of ICC patients after resection. The validity of the prognostic staging system was prospectively assessed in 115 patients who underwent partial hepatectomy between January 2010 and December 2010 at the same institution. The prognostic power was quantified using likelihood ratio test and Akaike information criteria. Compared with the 6(th) and 7(th) AJCC staging systems, the new staging system in the primary cohort had a higher predictive accuracy for OS in terms of homogeneity and discriminatory ability. In the validation cohort, the homogeneity and discrimination of the new staging system were also superior to the two other staging systems. The new staging system based on clinicopathologic features may provide relatively higher accuracy in prognostic prediction for ICC patients after tumor resection.

  12. Reduced nonlinear prognostic model construction from high-dimensional data

    Science.gov (United States)

    Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

    2017-04-01

    Construction of a data-driven model of evolution operator using universal approximating functions can only be statistically justified when the dimension of its phase space is small enough, especially in the case of short time series. At the same time in many applications real-measured data is high-dimensional, e.g. it is space-distributed and multivariate in climate science. Therefore it is necessary to use efficient dimensionality reduction methods which are also able to capture key dynamical properties of the system from observed data. To address this problem we present a Bayesian approach to an evolution operator construction which incorporates two key reduction steps. First, the data is decomposed into a set of certain empirical modes, such as standard empirical orthogonal functions or recently suggested nonlinear dynamical modes (NDMs) [1], and the reduced space of corresponding principal components (PCs) is obtained. Then, the model of evolution operator for PCs is constructed which maps a number of states in the past to the current state. The second step is to reduce this time-extended space in the past using appropriate decomposition methods. Such a reduction allows us to capture only the most significant spatio-temporal couplings. The functional form of the evolution operator includes separately linear, nonlinear (based on artificial neural networks) and stochastic terms. Explicit separation of the linear term from the nonlinear one allows us to more easily interpret degree of nonlinearity as well as to deal better with smooth PCs which can naturally occur in the decompositions like NDM, as they provide a time scale separation. Results of application of the proposed method to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical

  13. Physical Modeling for Anomaly Diagnostics and Prognostics Project

    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...

  14. 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.

  15. 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

  16. 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

  17. Introduction of prognostic rain in ECHAM5: design and Single Column Model simulations

    OpenAIRE

    Posselt, R.; Lohmann, U.

    2007-01-01

    International audience; Prognostic equations for the rain mass mixing ratio and the rain drop number concentration are introduced into the large-scale cloud microphysics parameterization of the ECHAM5 general circulation model (ECHAM5-PROG). To this end, a rain flux from one level to the next with the appropriate fall speed is introduced. This maintains rain water in the atmosphere to be available for the next time step. Rain formation in ECHAM5-PROG is, therefore, less dependent on the autoc...

  18. 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

  19. Prognostic factors for urachal cancer: a bayesian model-averaging approach.

    Science.gov (United States)

    Kim, In Kyong; Lee, Joo Yong; Kwon, Jong Kyou; Park, Jae Joon; Cho, Kang Su; Ham, Won Sik; Hong, Sung Joon; Yang, Seung Choul; Choi, Young Deuk

    2014-09-01

    This study was conducted to evaluate prognostic factors and cancer-specific survival (CSS) in a cohort of 41 patients with urachal carcinoma by use of a Bayesian model-averaging approach. Our cohort included 41 patients with urachal carcinoma who underwent extended partial cystectomy, total cystectomy, transurethral resection, chemotherapy, or radiotherapy at a single institute. All patients were classified by both the Sheldon and the Mayo staging systems according to histopathologic reports and preoperative radiologic findings. Kaplan-Meier survival curves and Cox proportional-hazards regression models were carried out to investigate prognostic factors, and a Bayesian model-averaging approach was performed to confirm the significance of each variable by using posterior probabilities. The mean age of the patients was 49.88 ± 13.80 years and the male-to-female ratio was 24:17. The median follow-up was 5.42 years (interquartile range, 2.8-8.4 years). Five- and 10-year CSS rates were 55.9% and 43.4%, respectively. Lower Sheldon (p=0.004) and Mayo (pcancer-specific mortality in urachal carcinoma. The Mayo staging system might be more effective than the Sheldon staging system. In addition, the multivariate analyses suggested that tumor size may be a prognostic factor for urachal carcinoma.

  20. [Molecular biological evaluation of prognostic parameters in GIST. Development of an integrative model of tumor progression].

    Science.gov (United States)

    Haller, F

    2010-10-01

    Prognosis evaluation in gastrointestinal stromal tumors (GIST) is currently based on tumor diameter, mitotic counts and anatomic localisation. There are two risk classifications as well as the first ever TNM classification for GISTs, whereby the risk classification according to the Armed Forces Institute of Pathology (AFIP) has the best correlation with clinical follow-up according to own experiences. "Very low/low risk" GISTs are almost benign, while the majority of "high risk" GISTs metastasize and benefit from adjuvant therapy. Careful evaluation of mitotic counts in 50 high-power fields is of particular relevance for correct risk classification. Apart from these classical prognostic factors, many molecular genetic parameters with correlation to follow-up have been evaluated and may help to improve prognosis evaluation of GISTs in the future. Since most of the molecular genetic parameters are associated or even determined by the clinico-pathological parameters, an integrated model for tumor progression of GISTs is helpful to interpret the different factors in correlation to one another. In particular for "intermediate risk" GISTs, additional parameters are needed for improved prognosis evaluation.

  1. Prognostic factors in patients with metastatic germ cell tumors who experienced treatment failure with cisplatin-based first-line chemotherapy.

    Science.gov (United States)

    Lorch, Anja; Beyer, Jörg; Bascoul-Mollevi, Caroline; Kramar, Andrew; Einhorn, Lawrence H; Necchi, Andrea; Massard, Christophe; De Giorgi, Ugo; Fléchon, Aude; Margolin, Kim A; Lotz, Jean-Pierre; Germa Lluch, Jose Ramon; Powles, Thomas; Kollmannsberger, Christian K

    2010-11-20

    To develop a prognostic model in patients with germ cell tumors (GCT) who experience treatment failure with cisplatin-based first-line chemotherapy. Data from 1,984 patients with GCT who progressed after at least three cisplatin-based cycles and were treated with cisplatin-based conventional-dose or carboplatin-based high-dose salvage chemotherapy was retrospectively collected from 38 centers/groups worldwide. One thousand five hundred ninety-four (80%) of 1,984 eligible patients were randomly divided into a training set of 1,067 patients (67%) and a validation set of 527 patients (33%). Seminomas were set aside for posthoc analyses. Primary end point was the 2-year progression-free survival after salvage treatment. Overall, 990 patients (62%) relapsed and 604 patients (38%) remained relapse free. Histology, primary tumor location, response, and progression-free interval after first-line treatment, as well as levels of alpha fetoprotein, human chorionic gonadotrophin, and the presence of liver, bone, or brain metastases at salvage were identified as independent prognostic variables and used to build a prognostic model in the training set. Survival rates in the training and validation set were very similar. The estimated 2-year progression-free survival rates in patients not included in the training set was 75% in very low risk, 51% in low risk, 40% in intermediate risk, 26% in high risk, and only 6% in very high-risk patients. Due to missing values in individual variables, 69 patients could not reliably be classified into one of these categories. Prognostic variables are important in patients with GCT who experienced treatment failure with cisplatin-based first-line chemotherapy and can be used to construct a prognostic model to guide salvage strategies.

  2. Prognostic Modeling of Valve Degradation within Power Stations

    Science.gov (United States)

    2014-10-02

    approach can be generated easily. The use of simulation can also satisfy the requirements stated by Wang et al. (2008) for a successful implementation...Simulation and Visualisation Based Training, Marine Electrical and Control Systems Safety Conference, (MECSS 2013), October 2-3, Amsterdam Heng, A

  3. 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.

  4. Introduction of prognostic rain in ECHAM5: design and single column model simulations

    Directory of Open Access Journals (Sweden)

    R. Posselt

    2008-06-01

    Full Text Available Prognostic equations for the rain mass mixing ratio and the rain drop number concentration are introduced into the large-scale cloud microphysics parameterization of the ECHAM5 general circulation model (ECHAM5-PROG. To this end, a rain flux from one level to the next with the appropriate fall speed is introduced. This maintains rain water in the atmosphere to be available for the next time step. Rain formation in ECHAM5-PROG is, therefore, less dependent on the autoconversion rate than the standard ECHAM5 but shifts the emphasis towards the accretion rates in accordance with observations. ECHAM5-PROG is tested and evaluated with Single Column Model (SCM simulations for two cases: the marine stratocumulus study EPIC (October 2001 and the continental mid-latitude ARM Cloud IOP (shallow frontal cloud case – March 2000. In case of heavy precipitation events, the prognostic equations for rain hardly affect the amount and timing of precipitation at the surface in different SCM simulations because heavy rain depends mainly on the large-scale forcing. In case of thin, drizzling clouds (i.e., stratocumulus, surface precipitation is sensitive to the number of sub-time steps used in the prognostic rain scheme. Cloud microphysical quantities, such as cloud liquid and rain water within the atmosphere, are sensitive to the number of sub-time steps in both considered cases. This results from the decreasing autoconversion rate and increasing accretion rate.

  5. Climate feedbacks in a general circulation model incorporating prognostic clouds

    Energy Technology Data Exchange (ETDEWEB)

    Colman, R.; Fraser, J. [Bureau of Meteorology Research Centre, Melbourne, Vic. (Australia); Rotstayn, L. [CSIRO Atmospheric Research, Aspendale (Australia)

    2001-11-01

    This study performs a comprehensive feedback analysis on the Bureau of Meteorology Research Centre General Circulation Model, quantifying all important feedbacks operating under an increase in atmospheric CO{sub 2}. The individual feedbacks are analysed in detail, using an offline radiation perturbation method, looking at long- and shortwave components, latitudinal distributions, cloud impacts, non-linearities under 2xCO{sub 2} and 4xCO{sub 2} warmings and at interannual variability. The water vapour feedback is divided into terms due to moisture height and amount changes. The net cloud feedback is separated into terms due to cloud amount, height, water content, water phase, physical thickness and convective cloud fraction. Globally the most important feedbacks were found to be (from strongest positive to strongest negative) those due to water vapour, clouds, surface albedo, lapse rate and surface temperature. For the longwave (LW) response the most important term of the cloud 'optical property' feedbacks is due to the water content. In the shortwave (SW), both water content and water phase changes are important. Cloud amount and height terms are also important for both LW and SW. Feedbacks due to physical cloud thickness and convective cloud fraction are found to be relatively small. All cloud component feedbacks (other than height) produce conflicting LW/SW feedbacks in the model. Furthermore, the optical property and cloud fraction feedbacks are also of opposite sign. The result is that the net cloud feedback is the (relatively small) product of conflicting physical processes. Non-linearities in the feedbacks are found to be relatively small for all but the surface albedo response and some cloud component contributions. The cloud impact on non-cloud feedbacks is also discussed: greatest impact is on the surface albedo, but impact on water vapour feedback is also significant. The analysis method here proves to be a powerful tool for detailing the

  6. A simplified prognostic model to predict mortality in patients with acute variceal bleeding.

    Science.gov (United States)

    Lee, Han Hee; Park, Jae Myung; Han, Seunghoon; Park, Sung Min; Kim, Hee Yeon; Oh, Jung Hwan; Kim, Chang Wook; Yoon, Seung Kew; Choi, Myung-Gyu

    2017-11-24

    Acute variceal bleeding (AVB) is a major cause of death in patients with liver cirrhosis. The aim of this study was to investigate mortality predictors and develop a new simple prognostic model using easily verified factors at admission in AVB patients. Between January 2009 and May 2015, 333 consecutive patients with AVB were included. A simplified prognostic model was developed using multiple logistic regression after identifying significant predictors of 6-week mortality. Mortality prediction accuracy was assessed with area under the receiver operating characteristic (AUROC) curve. We compared the new model to existing models of model for end-stage liver disease (MELD) and Child-Pugh scores. The 6-week overall mortality rate was 12.9%. Multivariate analysis showed that C-reactive protein (CRP), total bilirubin, and the international normalized ratio were independent predictors of mortality. A new logistic model using these variables was developed. This model's AUROC was 0.834, which was significantly higher than that of MELD (0.764) or Child-Pugh scores (0.699). Two external validation studies showed that the AUROC of our model was consistently higher than 0.8. Our new simplified model accurately and consistently predicted 6-week mortality in patients with AVB using objective variables measured at admission. Our system can be used to identify high risk AVB patients. Copyright © 2017 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

  7. 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

  8. 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 index in gastric cancer.

  9. Prognostic factors in skull base chordoma: a systematic literature review and meta-analysis.

    Science.gov (United States)

    Zou, Ming-Xiang; Lv, Guo-Hua; Zhang, Qian-Shi; Wang, Shao-Fu; Li, Jing; Wang, Xiao-Bin

    2017-10-15

    Currently, there are still lack of reviews assessing the complete range of prognostic factors in skull base chordoma (SBC). This study aimed to systematically review the published literature on prognostic factors in SBC and to establish pooled hazard ratios (HRs) of such factors. MEDLINE and EMBASE search (inception to April 04, 2017). Two reviewers independently selected papers involving SBC prognostic factors, and studied them for methodological quality and valuable factors. Pooled HRs and 95% confidence intervals (CIs) were calculated. The main endpoints determined were progression-free survival (PFS) and overall survival (OS). 22 studies with 1754 subjects were included in this systematic review. However, only 18 of them provided sufficient data for quantitative synthesis. Preoperative visual deficit (pooled HR = 2.77, 95% CI: 1.57-4.89 for PFS), older patient age (pooled HR = 1.03, 95% CI: 1.1-1.05 for PFS; pooled HR = 1.03, 95% CI: 1.2-1.04 for OS) and nontotal or intralesional tumor resection (pooled HR = 2.01, 95% CI: 1.54-2.62 for PFS; pooled HR = 5.16, 95% CI: 2.27-11.70 for OS) were negative predictors of survival outcomes. However, adjunctive radiotherapy (pooled HR = 0.30, 95% CI: 0.16-0.56) and chondroid chordoma type (pooled HR = 0.5, 95% CI: 0.36-0.69) portended a favorable PFS. In addition, several prognostic biomarkers were promising. This study demonstrated that several clinicopathological or molecular parameters are associated with survival up to tumor progression or mortality in SBC patients. However, further methodologically high-quality reports are still required to clarify the effects of these factors. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Development of prognostic model for predicting survival after retrograde placement of ureteral stent in advanced gastrointestinal cancer patients and its evaluation by decision curve analysis.

    Science.gov (United States)

    Kawano, Shingo; Komai, Yoshinobu; Ishioka, Junichiro; Sakai, Yasuyuki; Fuse, Nozomu; Ito, Masaaki; Kihara, Kazunori; Saito, Norio

    2016-10-01

    The aim of this study was to determine risk factors for survival after retrograde placement of ureteral stents and develop a prognostic model for advanced gastrointestinal tract (GIT: esophagus, stomach, colon and rectum) cancer patients. We examined the clinical records of 122 patients who underwent retrograde placement of a ureteral stent against malignant extrinsic ureteral obstruction. A prediction model for survival after stenting was developed. We compared its clinical usefulness with our previous model based on the results from nephrostomy cases by decision curve analysis. Median follow-up period was 201 days (8-1490) and 97 deaths occurred. The 1-year survival rate in this cohort was 29%. Based on multivariate analysis, primary site of colon origin, absence of retroperitoneal lymph node metastasis and serum albumin >3g/dL were significantly associated with a prolonged survival time. To develop a prognostic model, we divided the patients into 3 risk groups of favorable: 0-1 factors (N.=53), intermediate: 2 risk factors (N.=54), and poor: 3 risk factors (N.=15). There were significant differences in the survival profiles of these 3 risk groups (P<0.0001). Decision curve analyses revealed that the current model has a superior net benefit than our previous model for most of the examined probabilities. We have developed a novel prognostic model for GIT cancer patients who were treated with retrograde placement of a ureteral stent. The current model should help urologists and medical oncologists to predict survival in cases of malignant extrinsic ureteral obstruction.

  11. 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.)

  12. There’s Risk, and Then There’s RISK: The Latest Clinical Prognostic Risk Stratification Models in Myelodysplastic Syndromes

    OpenAIRE

    Zeidan, Amer M.; Komrokji, Rami S.

    2013-01-01

    Myelodysplastic syndromes (MDS) include a diverse group of clonal hematopoietic disorders characterized by progressive cytopenias and propensity for leukemic progression. The biologic heterogeneity that underlies MDS translates clinically in wide variations of clinical outcomes. Several prognostic schemes were developed to predict the natural course of MDS, counsel patients, and allow evidence-based, risk-adaptive implementation of therapeutic strategies. The prognostic schemes divide patient...

  13. Prognostic Factors and Treatment Results After Bleomycin, Etoposide, and Cisplatin in Germ Cell Cancer: A Population-based Study

    DEFF Research Database (Denmark)

    Kier, Maria G; Lauritsen, Jakob; Mortensen, Mette S

    2017-01-01

    BACKGROUND: First-line treatment for patients with disseminated germ cell cancer (GCC) is bleomycin, etoposide, and cisplatin (BEP). A prognostic classification of patients receiving chemotherapy was published by the International Germ Cell Cancer Collaborative Group (IGCCCG) in 1997, but only...... a small proportion of the patients received BEP. OBJECTIVE: To estimate survival probabilities after BEP, evaluate the IGCCCG prognostic classification, and propose new prognostic factors for outcome. DESIGN, SETTING, AND PARTICIPANTS: Of a Danish population-based cohort of GCC patients (1984-2007), 1889...... received first-line BEP, with median follow-up of 15 yr. Covariates evaluated as prognostic factors were age, year of treatment, primary site, non-pulmonary visceral metastases, pulmonary metastases, and tumor markers. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Outcomes measured were 5-yr progression...

  14. Prognostic value of the seventh AJCC/UICC TNM classification of intestinal-type ethmoid adenocarcinoma: Systematic review and risk prediction model.

    Science.gov (United States)

    Fiaux-Camous, Domitille; Chevret, Sylvie; Oker, Natalie; Turri-Zanoni, Mario; Lombardi, Davide; Choussy, Olivier; Duprez, Frederic; Jorissen, Marc; de Gabory, Ludovic; Malard, Olivier; Herman, Philippe; Nicolai, Piero; Castelnuovo, Paolo; Verillaud, Benjamin

    2017-04-01

    The purpose of this study was to propose a prognostic classification of intestinal-type adenocarcinoma (ITAC) based on literature search and prognostic modeling of cohort data. We first conducted a literature search to assess the homogeneity of the reported estimates of 5-year survival and to identify the influence of T classification. We then pooled prospective data from 3 large French and Italian series to predict time to all-cause mortality. The sample was randomly split to derive and then to validate the proposed prognostic model. Literature analysis confirmed the heterogeneity in 5-year survival rates, partly explained in subsets of homogeneous T-values. The sample included 223 patients, randomly separated into a derivation (n = 141) and a validation set (n = 82). Invasion of the sphenoid lateral and/or posterior walls and dura/cerebral invasion were systematically associated with a poor survival. The incorporation of the invasion of the sphenoid lateral or posterior walls should be considered for ITAC management and prognostication. © 2017 Wiley Periodicals, Inc. Head Neck 39: 668-678, 2017. © 2017 Wiley Periodicals, Inc.

  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. A laboratory prognostic index model for patients with advanced non-small cell lung cancer.

    Directory of Open Access Journals (Sweden)

    Arife Ulas

    Full Text Available We aimed to establish a laboratory prognostic index (LPI in advanced non-small cell lung cancer (NSCLC patients based on hematologic and biochemical parameters and to analyze the predictive value of LPI on NSCLC survival.The study retrospectively reviewed 462 patients with advanced NSCLC diagnosed between 2000 and 2010 in a single institution. We developed an LPI that included serum levels of white blood cells (WBC, lactate dehydrogenase (LDH, albumin, calcium, and alkaline phosphatase (ALP, based on the results of a Cox regression analysis. The patients were classified into 3 LPI groups as follows: LPI 0: normal; LPI 1: one abnormal laboratory finding; and LPI 2: at least 2 abnormal laboratory findings.The median follow up period was 44 months; the median overall survival (OS and median progression-free survival (PFS were 11 and 6 months, respectively. A multivariate analysis revealed that the following could be used as independent prognostic factors: an Eastern Cooperative Oncology Group performance status score (ECOG PS ≥2, a high LDH level, serum albumin 10.5 g/dL, number of metastases>2, presence of liver metastases, malignant pleural effusion, or receiving chemotherapy ≥4 cycles. The 1-year OS rates according to LPI 0, LPI 1, and LPI 2 were 54%, 34%, and 17% (p<0.001, respectively and 6-month PFS rates were 44%, 27%, and 15% (p<0.001, respectively. The LPI was a significant predictor for OS (Hazard Ratio (HR: 1.41; 1.05-1.88, p<0.001 and PFS (HR: 1.48; 1.14-1.93, p<0.001.An LPI is an inexpensive, easily accessible and independent prognostic index for advanced NSCLC and may be helpful in making individualized treatment plans and predicting survival rates when combined with clinical parameters.

  17. 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.

  18. 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

  19. Prognostic model for survival in patients with metastatic renal cell carcinoma: results from the international kidney cancer working group.

    Science.gov (United States)

    Manola, Judith; Royston, Patrick; Elson, Paul; McCormack, Jennifer Bacik; Mazumdar, Madhu; Négrier, Sylvie; Escudier, Bernard; Eisen, Tim; Dutcher, Janice; Atkins, Michael; Heng, Daniel Y C; Choueiri, Toni K; Motzer, Robert; Bukowski, Ronald

    2011-08-15

    To develop a single validated model for survival in metastatic renal cell carcinoma (mRCC) using a comprehensive international database. A comprehensive database of 3,748 patients including previously reported clinical prognostic factors was established by pooling patient-level data from clinical trials. Following quality control and standardization, descriptive statistics were generated. Univariate analyses were conducted using proportional hazards models. Multivariable analysis using a log-logistic model stratified by center and multivariable fractional polynomials was conducted to identify independent predictors of survival. Missing data were handled using multiple imputation methods. Three risk groups were formed using the 25th and 75th percentiles of the resulting prognostic index. The model was validated using an independent data set of 645 patients treated with tyrosine kinase inhibitor (TKI) therapy. Median survival in the favorable, intermediate and poor risk groups was 26.9 months, 11.5 months, and 4.2 months, respectively. Factors contributing to the prognostic index included treatment, performance status, number of metastatic sites, time from diagnosis to treatment, and pretreatment hemoglobin, white blood count, lactate dehydrogenase, alkaline phosphatase, and serum calcium. The model showed good concordance when tested among patients treated with TKI therapy (C statistic = 0.741, 95% CI: 0.714-0.768). Nine clinical factors can be used to model survival in mRCC and form distinct prognostic groups. The model shows utility among patients treated in the TKI era. ©2011 AACR.

  20. 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

  1. A prognostic model of therapy-related myelodysplastic syndrome for predicting survival and transformation to acute myeloid leukemia.

    Science.gov (United States)

    Quintás-Cardama, Alfonso; Daver, Naval; Kim, Hawk; Dinardo, Courtney; Jabbour, Elias; Kadia, Tapan; Borthakur, Gautam; Pierce, Sherry; Shan, Jianqin; Cardenas-Turanzas, Marylou; Cortes, Jorge; Ravandi, Farhad; Wierda, William; Estrov, Zeev; Faderl, Stefan; Wei, Yue; Kantarjian, Hagop; Garcia-Manero, Guillermo

    2014-10-01

    We evaluated the characteristics of a cohort of patients with myelodysplastic syndrome (MDS) related to therapy (t-MDS) to create a prognostic model. We identified 281 patients with MDS who had received previous chemotherapy and/or radiotherapy for previous malignancy. Potential prognostic factors were determined using univariate and multivariate analyses. Multivariate Cox regression analysis identified 7 factors that independently predicted short survival in t-MDS: age ≥ 65 years (hazard ratio [HR], 1.63), Eastern Cooperative Oncology Group performance status 2-4 (HR, 1.86), poor cytogenetics (-7 and/or complex; HR, 2.47), World Health Organization MDS subtype (RARs or RAEB-1/2; HR, 1.92), hemoglobin (HR, 2.24), platelets (HR, 2.01), and transfusion dependency (HR, 1.59). These risk factors were used to create a prognostic model that segregated patients into 3 groups with distinct median overall survival: good (0-2 risk factors; 34 months), intermediate (3-4 risk factors; 12 months), and poor (5-7 risk factors; 5 months) (P < .001) and 1-year leukemia-free survival (96%, 84%, and 72%, respectively, P = .003). This model also identified distinct survival groups according to t-MDS therapy. In summary, we devised a prognostic model specifically for patients with t-MDS that predicted overall survival and leukemia-free survival. This model might facilitate the development of risk-adapted therapeutic strategies. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Prognostic factors in gastric cancer evaluated by using Cox regression model.

    Science.gov (United States)

    Ghiandoni, G; Rocchi, M B; Signoretti, P; Belbusti, F

    1998-06-01

    To identify the most relevant short-term predictor variables in gastric cancer removal. A retrospective survival analysis executed by using the Cox regression model; the follow-up period is included between 18 and 90 months. A district general hospital surgery unit: "Divisione di Chirurgia Generale, Ospedale Civile di Urbino" (Marche, Italy). One hundred and twenty nine consecutive patients operated for gastric cancer. Surgery (total or subtotal gastrectomy). Survival times. Lymph node involvement (N) (p extension (T) (p < 0.001) and the age of the patients (p < 0.05) have been recognized as significant prognostic factors. Results show that the short-term prognosis largely depends on both the earliness of the diagnosis and the age of the patients.

  3. Urbanization Effects on air Quality and Climate in the Acapulco Area Using a Prognostic Meteorological and air Quality Model

    Science.gov (United States)

    Ortinez, A. A.; Garcia, A. R.; Jazcilevich, A. D.; Caetano, E.; Moya, M. N.; Delgado, J. C.

    2007-05-01

    The effects of urbanization growth on the Acapulco coastal metropolitan area were estimated by using a prognostic meteorological and air quality model. To this end three urbanization scenarios are proposed: The current Acapulco urban area that we call "Control Scenario" and two possible urban growths that we call "Scenario 1" and "Scenario 2". We estimated the urban growth of scenarios 1 and 2, using economic factors, population distribution and historical data. The urban distribution in the "Control Scenario" was taken from the aerial photographs of Acapulco and processed by a Geographic Information System (GIS).The variables devised for the scenarios comparison was a Comfort Index based on humidity and temperature and the Potential Exposure Index for Ozone. The model used was the Penn State/NCAR MM5 mesoscale meteorological model and the Multiscale Climate and Chemistry Model (MCCM). Since there is no local information, the emissions were estimated by using data of similar socio- economic urban areas where emission data is available. The meteorology and air quality models were calibrated using data of a measuring campaign performed in December 2005. This is a preliminary effort to propose a planned urban expansion for Acapulco from the point of view of air quality and urban climate.

  4. Validation, revision and extension of the mantle cell lymphoma international prognostic index in a population-based setting

    NARCIS (Netherlands)

    S.A.M. van de Schans (Saskia); M.L.G. Janssen-Heijnen (Maryska); M.R. Nijzie (Marten); E.W. Steyerberg (Ewout); D.J. van Spronsen (Dick Johan)

    2010-01-01

    textabstractBackground The aim of this study was to validate the Mantle Cell Lymphoma International Prognostic Index in a population-based cohort and to study the relevance of its revisions. Design and Methods We analyzed data from 178 unselected patients with stage III or IV mantle cell lymphoma,

  5. The prognostic effect of ethnicity for gastric and esophageal cancer: the population-based experience in British Columbia, Canada

    Directory of Open Access Journals (Sweden)

    Shah Amil M

    2011-05-01

    Full Text Available Abstract Background Gastric and esophageal cancers are among the most lethal human malignancies. Their epidemiology is geographically diverse. This study compares the survival of gastric and esophageal cancer patients among several ethnic groups including Chinese, South Asians, Iranians and Others in British Columbia (BC, Canada. Methods Data were obtained from the population-based BC Cancer Registry for patients diagnosed with invasive esophageal and gastric cancer between 1984 and 2006. The ethnicity of patients was estimated according to their names and categorized as Chinese, South Asian, Iranian or Other. Cox proportional hazards regression analysis was used to estimate the effect of ethnicity adjusted for patient sex and age, disease histology, tumor location, disease stage and treatment. Results The survival of gastric cancer patients was significantly different among ethnic groups. Chinese patients showed better survival compared to others in univariate and multivariate analysis. The survival of esophageal cancer patients was significantly different among ethnic groups when the data was analyzed by a univariate test (p = 0.029, but not in the Cox multivariate model adjusted for other patient and prognostic factors. Conclusions Ethnicity may represent underlying genetic factors. Such factors could influence host-tumor interactions by altering the tumor's etiology and therefore its chance of spreading. Alternatively, genetic factors may determine response to treatments. Finally, ethnicity may represent non-genetic factors that affect survival. Differences in survival by ethnicity support the importance of ethnicity as a prognostic factor, and may provide clues for the future identification of genetic or lifestyle factors that underlie these observations.

  6. The sequential organ failure assessment (SOFA) score is prognostically superior to the model for end-stage liver disease (MELD) and MELD variants following paracetamol (acetaminophen) overdose.

    Science.gov (United States)

    Craig, D G N; Reid, T W D J; Wright, E C; Martin, K G; Davidson, J S; Hayes, P C; Simpson, K J

    2012-03-01

    The prognostic value of the model for end-stage liver disease (MELD) and sodium-based MELD variants in predicting survival following paracetamol overdose remains unclear. To examine the prognostic accuracy of sodium-based MELD variants in paracetamol-induced acute liver injury compared with the sequential organ failure assessment (SOFA) score. Retrospective analysis of 138 single time point paracetamol overdoses admitted to a tertiary liver centre. Individual laboratory samples were correlated with the corresponding clinical parameters in relation to time post-overdose, and the daily MELD, MELD-Na, MELDNa, MESO, iMELD, UKELD, updated MELD and SOFA scores were calculated. Sixty-six (47.8%) patients developed hepatic encephalopathy, of whom 7 were transplanted and 21 died without liver transplantation. SOFA had a significantly greater area under the receiver operator characteristic for the prediction of spontaneous survival compared with MELD at both 72 (P = 0.024) and 96 (P = 0.017) h post-overdose. None of the sodium-based MELD variants improved the prognostic accuracy of MELD. A SOFA score >6 by 72 h or >7 by 96 h, post-overdose predicted death/transplantation with a negative predictive value of 96.9 (95% CI 90.2-99.4) and 98.8 (95% CI 93.6-99.9) respectively. SOFA and MELD had similar accuracy for predicting the development of hepatic encephalopathy (P = 0.493). The SOFA score is superior to MELD in predicting spontaneous survival following paracetamol-induced acute liver injury. Modification of the MELD score to include serum sodium does not improve prognostic accuracy in this setting. SOFA may have potential as a quantitative triage marker following paracetamol overdose. © 2012 Blackwell Publishing Ltd.

  7. 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.

  8. 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.

  9. Noncutaneous malignant melanoma: a prognostic model from a retrospective multicenter study

    Directory of Open Access Journals (Sweden)

    Kim Jung Han

    2010-04-01

    Full Text Available Abstract Background We performed multicenter study to define clinical characteristics of noncutaneous melanomas and to establish prognostic factors patients who received curative resection. Methods Of the 141 patients who were diagnosed of non-cutaneous melanoma at 4 institutions in Korea between June 1992 and May 2005, 129 (91.5% satisfied the selection criteria. Results Of the 129 noncutaneous melanoma patients, 14 patients had ocular melanoma and 115 patients had mucosal melanoma. For mucosal melanoma, anorectum was the most common anatomic site (n = 39, 30.2% which was followed by nasal cavity (n = 30, 23.3%, genitourinary (n = 21, 16.3%, oral cavity (n = 14, 10.9%, upper gastrointestinal tract (n = 6, 4.7% and maxillary sinus (n = 5, 3.9% in the order of frequency. With the median 64.5 (range 4.3-213.0 months follow-up, the median overall survival were 24.4 months (95% CI 13.2-35.5 for all patients, and 34.6 (95% CI 24.5-44.7 months for curatively resected mucosal melanoma patients. Adverse prognostic factors of survival for 87 curatively resected mucosal melanoma patients were complete resection (R1 resection margin, and age > 50 years. For 14 ocular melanoma, Survival outcome was much better than mucosal melanoma with 73.3% of 2 year OS and 51.2 months of median OS (P = .04. Conclusion Prognosis differed according to primary sites of noncutaneous melanoma. Based on our study, noncutaneous melanoma patients should be treated differently to improve survival outcome.

  10. A simple prognostic model for overall survival in metastatic renal cell carcinoma

    Science.gov (United States)

    Assi, Hazem I.; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

    2016-01-01

    Introduction: The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. Methods: We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. Results: There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. Conclusions: In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis. PMID:27217858

  11. A flexible alternative to the Cox proportional hazards model for assessing the prognostic accuracy of hospice patient survival.

    Directory of Open Access Journals (Sweden)

    Branko Miladinovic

    Full Text Available Prognostic models are often used to estimate the length of patient survival. The Cox proportional hazards model has traditionally been applied to assess the accuracy of prognostic models. However, it may be suboptimal due to the inflexibility to model the baseline survival function and when the proportional hazards assumption is violated. The aim of this study was to use internal validation to compare the predictive power of a flexible Royston-Parmar family of survival functions with the Cox proportional hazards model. We applied the Palliative Performance Scale on a dataset of 590 hospice patients at the time of hospice admission. The retrospective data were obtained from the Lifepath Hospice and Palliative Care center in Hillsborough County, Florida, USA. The criteria used to evaluate and compare the models' predictive performance were the explained variation statistic R(2, scaled Brier score, and the discrimination slope. The explained variation statistic demonstrated that overall the Royston-Parmar family of survival functions provided a better fit (R(2 =0.298; 95% CI: 0.236-0.358 than the Cox model (R(2 =0.156; 95% CI: 0.111-0.203. The scaled Brier scores and discrimination slopes were consistently higher under the Royston-Parmar model. Researchers involved in prognosticating patient survival are encouraged to consider the Royston-Parmar model as an alternative to Cox.

  12. 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.

  13. γ-H2AX: A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer

    Directory of Open Access Journals (Sweden)

    E. Chatzimichail

    2014-01-01

    Full Text Available Cancer is a leading cause of death worldwide and the prognostic evaluation of cancer patients is of great importance in medical care. The use of artificial neural networks in prediction problems is well established in human medical literature. The aim of the current study was to assess the prognostic value of a series of clinical and molecular variables with the addition of γ-H2AX—a new DNA damage response marker—for the prediction of prognosis in patients with early operable non-small cell lung cancer by comparing the γ-H2AX-based artificial network prediction model with the corresponding LR one. Two prognostic models of 96 patients with 27 input variables were constructed by using the parameter-increasing method in order to compare the predictive accuracy of neural network and logistic regression models. The quality of the models was evaluated by an independent validation data set of 11 patients. Neural networks outperformed logistic regression in predicting the patient’s outcome according to the experimental results. To assess the importance of the two factors p53 and γ-H2AX, models without these two variables were also constructed. JR and accuracy of these models were lower than those of the models using all input variables, suggesting that these biological markers are very important for optimal performance of the models. This study indicates that neural networks may represent a potentially more useful decision support tool than conventional statistical methods for predicting the outcome of patients with non-small cell lung cancer and that some molecular markers, such as γ-H2AX, enhance their predictive ability.

  14. Prognostic value of graph theory-based tissue architecture analysis in carcinomas of the tongue.

    Science.gov (United States)

    Sudbø, J; Bankfalvi, A; Bryne, M; Marcelpoil, R; Boysen, M; Piffko, J; Hemmer, J; Kraft, K; Reith, A

    2000-12-01

    Several studies on oral squamous cell carcinomas (OSCC) suggest that the clinical value of traditional histologic grading is limited both by poor reproducibility and by low prognostic impact. However, the prognostic potential of a strictly quantitative and highly reproducible assessment of the tissue architecture in OSCC has not been evaluated. Using image analysis, in 193 cases of T1-2 (Stage I-II) OSCC we retrospectively investigated the prognostic impact of two graph theory-derived structural features: the average Delaunay Edge Length (DEL_av) and the average homogeneity of the Ulam Tree (ELH_av). Both structural features were derived from subgraphs of the Voronoi Diagram. The geometric centers of the cell nuclei were computed, generating a two-dimensional swarm of point-like seeds from which graphs could be constructed. The impact on survival of the computed values of ELH_av and DEL_av was estimated by the method of Kaplan and Meier, with relapse-free survival and overall survival as end-points. The prognostic values of DEL_av and ELH_av as computed for the invasive front, the superficial part of the carcinoma, the total carcinoma, and the normal-appearing oral mucosa were compared. For DEL_av, significant prognostic information was found in the invasive front (p < 0.001). No significant prognostic information was found in superficial part of the carcinoma (p = 0.34), in the carcinoma as a whole (p = 0.35), or in the normal-appearing mucosa (p = 0.27). For ELH_av, significant prognostic information was found in the invasive front (p = 0.01) and, surprisingly, in putatively normal mucosa (p = 0.03). No significant prognostic information was found in superficial parts of the carcinoma (p = 0.34) or in the total carcinoma (p = 0.11). In conclusion, strictly quantitative assessment of tissue architecture in the invasive front of OSCC yields highly prognostic information.

  15. System Interdependency Modeling in the Design of Prognostic and Health Management Systems in Smart Manufacturing.

    Science.gov (United States)

    Malinowski, M L; Beling, P A; Haimes, Y Y; LaViers, A; Marvel, J A; Weiss, B A

    2015-01-01

    The fields of risk analysis and prognostics and health management (PHM) have developed in a largely independent fashion. However, both fields share a common core goal. They aspire to manage future adverse consequences associated with prospective dysfunctions of the systems under consideration due to internal or external forces. This paper describes how two prominent risk analysis theories and methodologies - Hierarchical Holographic Modeling (HHM) and Risk Filtering, Ranking, and Management (RFRM) - can be adapted to support the design of PHM systems in the context of smart manufacturing processes. Specifically, the proposed methodologies will be used to identify targets - components, subsystems, or systems - that would most benefit from a PHM system in regards to achieving the following objectives: minimizing cost, minimizing production/maintenance time, maximizing system remaining usable life (RUL), maximizing product quality, and maximizing product output. HHM is a comprehensive modeling theory and methodology that is grounded on the premise that no system can be modeled effectively from a single perspective. It can also be used as an inductive method for scenario structuring to identify emergent forced changes (EFCs) in a system. EFCs connote trends in external or internal sources of risk to a system that may adversely affect specific states of the system. An important aspect of proactive risk management includes bolstering the resilience of the system for specific EFCs by appropriately controlling the states. Risk scenarios for specific EFCs can be the basis for the design of prognostic and diagnostic systems that provide real-time predictions and recognition of scenario changes. The HHM methodology includes visual modeling techniques that can enhance stakeholders' understanding of shared states, resources, objectives and constraints among the interdependent and interconnected subsystems of smart manufacturing systems. In risk analysis, HHM is often paired

  16. Chronic lymphocytic leukemia: A prognostic model comprising only two biomarkers (IGHV mutational status and FISH cytogenetics) separates patients with different outcome and simplifies the CLL-IPI.

    Science.gov (United States)

    Delgado, Julio; Doubek, Michael; Baumann, Tycho; Kotaskova, Jana; Molica, Stefano; Mozas, Pablo; Rivas-Delgado, Alfredo; Morabito, Fortunato; Pospisilova, Sarka; Montserrat, Emili

    2017-04-01

    Rai and Binet staging systems are important to predict the outcome of patients with chronic lymphocytic leukemia (CLL) but do not reflect the biologic diversity of the disease nor predict response to therapy, which ultimately shape patients' outcome. We devised a biomarkers-only CLL prognostic system based on the two most important prognostic parameters in CLL (i.e., IGHV mutational status and fluorescence in situ hybridization [FISH] cytogenetics), separating three different risk groups: (1) low-risk (mutated IGHV + no adverse FISH cytogenetics [del(17p), del(11q)]); (2) intermediate-risk (either unmutated IGHV or adverse FISH cytogenetics) and (3) high-risk (unmutated IGHV + adverse FISH cytogenetics). In 524 unselected subjects with CLL, the 10-year overall survival was 82% (95% CI 76%-88%), 52% (45%-62%), and 27% (17%-42%) for the low-, intermediate-, and high-risk groups, respectively. Patients with low-risk comprised around 50% of the series and had a life expectancy comparable to the general population. The prognostic model was fully validated in two independent cohorts, including 417 patients representative of general CLL population and 337 patients with Binet stage A CLL. The model had a similar discriminatory value as the CLL-IPI. Moreover, it applied to all patients with CLL independently of age, and separated patients with different risk within Rai or Binet clinical stages. The biomarkers-only CLL prognostic system presented here simplifies the CLL-IPI and could be useful in daily practice and to stratify patients in clinical trials. © 2017 Wiley Periodicals, Inc.

  17. Prognostic modeling of oral cancer by gene profiles and clinicopathological co-variables.

    Science.gov (United States)

    Mes, Steven W; Te Beest, Dennis; Poli, Tito; Rossi, Silvia; Scheckenbach, Kathrin; van Wieringen, Wessel N; Brink, Arjen; Bertani, Nicoletta; Lanfranco, Davide; Silini, Enrico M; van Diest, Paul J; Bloemena, Elisabeth; Leemans, C René; van de Wiel, Mark A; Brakenhoff, Ruud H

    2017-08-29

    Accurate staging and outcome prediction is a major problem in clinical management of oral cancer patients, hampering high precision treatment and adjuvant therapy planning. Here, we have built and validated multivariable models that integrate gene signatures with clinical and pathological variables to improve staging and survival prediction of patients with oral squamous cell carcinoma (OSCC). Gene expression profiles from 249 human papillomavirus (HPV)-negative OSCCs were explored to identify a 22-gene lymph node metastasis signature (LNMsig) and a 40-gene overall survival signature (OSsig). To facilitate future clinical implementation and increase performance, these signatures were transferred to quantitative polymerase chain reaction (qPCR) assays and validated in an independent cohort of 125 HPV-negative tumors. When applied in the clinically relevant subgroup of early-stage (cT1-2N0) OSCC, the LNMsig could prevent overtreatment in two-third of the patients. Additionally, the integration of RT-qPCR gene signatures with clinical and pathological variables provided accurate prognostic models for oral cancer, strongly outperforming TNM. Finally, the OSsig gene signature identified a subpopulation of patients, currently considered at low-risk for disease-related survival, who showed an unexpected poor prognosis. These well-validated models will assist in personalizing primary treatment with respect to neck dissection and adjuvant therapies.

  18. Establishment and evaluation of a prognostic model for surgical outcomes of patients with atlanto-axial dislocations.

    Science.gov (United States)

    Guo, Shuai; Chen, Jie; Yang, Baohui; Li, Haopeng

    2016-12-01

    Objective Atlanto-axial dislocations (AADs) are potentially fatal disturbances with high spinal cord compression syndrome. As surgeons are still uncertain who is likely to benefit the most from surgery, a prediction tool is needed to provide decision-making support. Methods The model was established based on 108 patients with AADs using multiple binary logistic regression analysis and evaluated by calibration plot and the area under the receiver operating curve (AUC). Bootstrapping was used for internal validation. Results The prognostic model can be expressed as: logit(P) = -2.2428 + 0.3168SCOPE - 2.0375SIGNAL, in which two covariates were accepted (SCORE represents the preoperative modified Japanese Orthopedic Association (mJOA) score and SIGNAL represents the intramedullary hyperintense T2-weighted imaging (T2WI) with AUC = 0.8081). Conclusions The model was internally valid, and the preoperative mJOA score and hyperintense T2WI were important predictors of outcomes. The threshold was defined as logit(P) = -0.7282 according to the receiver operating curve (ROC).

  19. Population-based study of ovarian cancer in Côte d'Or: prognostic factors and trends in relative survival rates over the last 20 years

    Directory of Open Access Journals (Sweden)

    Altwegg Thierry

    2010-11-01

    Full Text Available Abstract Background The aim of this population-based study was to assess independent prognostic factors in ovarian cancer using relative survival (RS and to investigate changes in RS rates from 1982 to 2005. Methods Data on 748 patients with ovarian cancer were provided by the Côte d'Or gynaecologic cancer registry. The RS was estimated using a generalized linear model with a Poisson error structure. Relative survival and its 95% confidence interval (CI were described at the following specific time points 1, 3 and 5 years. The effect of prognostic factors on survival was assessed with multivariate analyses of RS. Results The median follow-up was 12 years. The RS rates at 1, 3 and 5 years were 81%, 55% and 44%, respectively. As compared with the period 1982-1989, an improvement in survival was found for the period 1998-2005: HR = 0.52[0.40-0.67]. Women who lived in urban areas had better RS: HR = 0.82[0.67-0.99]. Patients with epithelial types of ovarian cancer other than mucinous or endometrioid cancer had worse RS than those with serous histology. Age ≥ 70 years was associated with lower survival. Conclusions Period of diagnosis, stage at diagnosis, histology, place of residence and age were independent prognostic factors for survival in ovarian cancer. An improvement in the survival rate was observed after 1998 but a significant improvement was limited to advanced stage cancers.

  20. 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.

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

    Science.gov (United States)

    Louie, Alexander V; Haasbeek, Cornelis J A; Mokhles, Sahar; Rodrigues, George B; Stephans, Kevin L; Lagerwaard, Frank J; Palma, David A; Videtic, Gregory M M; Warner, Andrew; Takkenberg, Johanna J M; Reddy, Chandana A; Maat, Alex P W M; Woody, Neil M; Slotman, Ben J; Senan, Suresh

    2015-09-01

    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). 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. 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(2) = 0.97) and external SABR (r(2) = 0.79) and surgical cohorts (r(2) = 0.91). 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. An Energy-Based Prognostic Framework to Predict Fatigue Damage Evolution in Composites

    Data.gov (United States)

    National Aeronautics and Space Administration — In this work, a prognostics framework to predict the evolution of damage in fiber-reinforced composites materials under fatigue loads is proposed. The assessment of...

  3. 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.

    2014-01-01

    Purpose 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. Patients and Methods 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. Results 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. Conclusion 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. PMID

  4. Prognostic scoring systems for mortality in intensive care units--the APACHE model.

    Science.gov (United States)

    Niewiński, Grzegorz; Starczewska, Małgorzata; Kański, Andrzej

    2014-01-01

    The APACHE (Acute Physiology and Chronic Health Evaluation) scoring system is time consuming. The mean time for introducing a patient's data to APACHE IV is 37.3 min. Nevertheless, statisticians have known for years that the higher the number of variables the mathematical model describes, the more accurate the model. Because of the necessity of gathering data over a 24-hour period and of determining one cause for ICU admission, the system is troublesome and prone to mistakes. The evolution of the APACHE scoring system is an example of unfulfilled hopes for accurately estimating the risk of death for patients admitted to the ICU; satisfactory prognostic effects resulting from the use of APACHE II and III have been recently studied in patients undergoing liver transplantations. Because no increase in the predictive properties of successive versions has been observed, the search for other solutions continues. The APACHE IV scoring system is helpful; however, its use without prepared spreadsheets is almost impractical. Therefore, although many years have passed since its original publication, APACHE II or its extension APACHE III is currently used in clinical practice.

  5. Nuclear grade based on transbronchial cytology is an independent prognostic factor in patients with advanced, unresectable non-small cell lung cancer.

    Science.gov (United States)

    Kadota, Kyuichi; Miyai, Yumi; Katsuki, Naomi; Kushida, Yoshio; Matsunaga, Toru; Okuda, Masaya; Yokomise, Hiroyasu; Kanaji, Nobuhiro; Bandoh, Shuji; Haba, Reiji

    2016-09-01

    In patients with resected non-small cell lung cancer (NSCLC), the prognostic value of nuclear grade has been demonstrated. However, among patients with advanced, unresectable NSCLC, the prognostic usefulness of cytological nuclear grade to the authors' knowledge remains unknown. In the current study, the authors used transbronchial cytology to investigate whether nuclear morphometry correlated with clinical outcomes in patients with advanced NSCLC. The authors reviewed patients with advanced, unresectable NSCLC who were diagnosed on transbronchial cytology and were treated at the study institution from 2007 through 2015 (97 patients). Nuclear morphometry (including major diameter) was assessed by an image analysis system and small lymphocytes were used as a reference. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method, and multivariate analyses were performed using the Cox proportional hazards regression model. In the multivariate analysis, according to the nuclear major diameter as assessed by an image analysis system, a nuclear major diameter >15 μm was an independent prognostic factor of worse OS (hazard ratio [HR], 1.05; P = .003) and PFS (HR, 1.04; P = 0.011). According to the nuclear major diameter as assessed by small lymphocytes, a major diameter of >5 small lymphocytes was an independent prognostic factor of worse OS (HR, 1.32; P<.001) and PFS (HR, 1.20; P = 0.001). A moderately significant correlation between nuclear diameter measurements by an image analysis system and small lymphocytes was observed (P<.001; correlation coefficient, 0.662). Nuclear grade based on nuclear diameter was found to be independently associated with prognosis in patients with advanced, unresectable NSCLC. Cancer Cytopathol 2016;124:630-40. © 2016 American Cancer Society. © 2016 American Cancer Society.

  6. 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...

  7. Clinical Risk Factors and Prognostic Model for Primary Graft Dysfunction after Lung Transplantation in Patients with Pulmonary Hypertension.

    Science.gov (United States)

    Porteous, Mary K; Lee, James C; Lederer, David J; Palmer, Scott M; Cantu, Edward; Shah, Rupal J; Bellamy, Scarlett L; Lama, Vibha N; Bhorade, Sangeeta M; Crespo, Maria M; McDyer, John F; Wille, Keith M; Localio, A Russell; Orens, Jonathan B; Shah, Pali D; Weinacker, Ann B; Arcasoy, Selim; Wilkes, David S; Ware, Lorraine B; Christie, Jason D; Kawut, Steven M; Diamond, Joshua M

    2017-10-01

    Pulmonary hypertension from pulmonary arterial hypertension or parenchymal lung disease is associated with an increased risk for primary graft dysfunction after lung transplantation. We evaluated the clinical determinants of severe primary graft dysfunction in pulmonary hypertension and developed and validated a prognostic model. We conducted a retrospective cohort study of patients in the multicenter Lung Transplant Outcomes Group with pulmonary hypertension at transplant listing. Severe primary graft dysfunction was defined as PaO2/FiO2 ≤200 with allograft infiltrates at 48 or 72 hours after transplantation. Donor, recipient, and operative characteristics were evaluated in a multivariable explanatory model. A prognostic model derived using donor and recipient characteristics was then validated in a separate cohort. In the explanatory model of 826 patients with pulmonary hypertension, donor tobacco smoke exposure, higher recipient body mass index, female sex, listing mean pulmonary artery pressure, right atrial pressure and creatinine at transplant, cardiopulmonary bypass use, transfusion volume, and reperfusion fraction of inspired oxygen were associated with primary graft dysfunction. Donor obesity was associated with a lower risk for primary graft dysfunction. Using a 20% threshold for elevated risk, the prognostic model had good negative predictive value in both derivation and validation cohorts (89.1% [95% confidence interval, 85.3-92.8] and 83.3% [95% confidence interval, 78.5-88.2], respectively), but low positive predictive value. Several recipient, donor, and operative characteristics were associated with severe primary graft dysfunction in patients with pulmonary hypertension, including several risk factors not identified in the overall transplant population. A prognostic model with donor and recipient clinical risk factors alone had low positive predictive value, but high negative predictive value, to rule out high risk for primary graft dysfunction.

  8. An inflammation-based prognostic index predicts survival advantage after transarterial chemoembolization in hepatocellular carcinoma.

    Science.gov (United States)

    Pinato, David J; Sharma, Rohini

    2012-08-01

    Transarterial chemoembolization (TACE) is the preferred treatment for unresectable, intermediate-stage hepatocellular carcinoma (HCC). However, survival after TACE can be highly variable, suggesting the need for more accurate patient selection to improve therapeutic outcome. We have explored the prognostic ability of the blood neutrophil-to-lymphocyte ratio (NLR), a biomarker of systemic inflammation, as a predictor of survival after TACE. Fifty-four patients with a diagnosis of HCC eligible for TACE were selected. Clinicopathologic variables were collected, including demographics, tumor staging, liver functional reserve, and laboratory variables. Dynamic changes in the NLR before and after TACE were studied as predictors of survival using both a univariate and multivariate Cox regression model. Patients in whom the NLR remained stable or normalized after TACE showed a significant improvement in overall survival of 26 months compared with patients showing a persistently abnormal index (P = 0.006). Other predictors of survival on univariate analysis were Cancer of the Liver Italian Program score (P = 0.05), intrahepatic spread (P = 0.01), tumor diameter > 5 cm (P = 0.02), > 1 TACE (P = 0.01), alpha-fetoprotein ≥ 400 (P = 0.002), and radiologic response to TACE (P analysis. Changes in alpha-fetoprotein after treatment did not predict survival. Patients with a persistently increased NLR have a worse outcome after TACE. NLR is a simple and universally available stratifying biomarker that can help identify patients with a significant survival advantage after TACE. Copyright © 2012 Mosby, Inc. All rights reserved.

  9. Pattern and prognostic factor of ocular injuries in southwest Ethiopia: a hospital based prospective study

    Directory of Open Access Journals (Sweden)

    Sisay Bekele

    2016-05-01

    Full Text Available AIM: To determine the pattern, severity, and prognostic factors of ocular injuries in the southwest Ethiopia.METHODS:A prospective hospital based study was done on all patients presented with ocular injury to Jimma University Specialized Hospital from Apr. to Sep. 2009. Each patient underwent a detailed interview and a standard comprehensive ocular examination. Data were analyzed using SPSS version 13 and PRESULTS:The overall prevalence of ocular injury was 3.03%. Nearly 99% of ocular injuries were mechanical. The majority of the ocular injuries(53.2%were work-related and none of these patients had eye protection at the time of injury. Out of 170 globe injuries, 57.6% were closed globe injury and 42.4% were open globe injuries. Closed globe injuries were less severe and had significantly better visual outcome than open globe injuries(PPCONCLUSION: Most ocular injuries occurred in the workplace,and a significantly larger proportion of patients with ocular injury developed monocular blindness. For the prevention of serious injuries, eye health education and safety strategies should be applied both at home and work place.

  10. 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

  11. Fine Needle Aspiration Biopsies for Gene Expression Ratio-based Diagnostic and Prognostic Tests in Malignant Pleural Mesothelioma

    Science.gov (United States)

    De Rienzo, Assunta; Dong, Lingsheng; Yeap, Beow Y.; Jensen, Roderick V.; Richards, William G.; Gordon, Gavin J.; Sugarbaker, David J.; Bueno, Raphael

    2010-01-01

    Purpose Malignant pleural mesothelioma (MPM) is an aggressive disease associated with median survival between 9 and 12 months. The correct diagnosis of MPM is sometimes challenging and usually requires solid tissue biopsies rather than fine needle aspiration biopsies (FNA). We postulated that the accuracy of FNA-based diagnosis might be improved by the addition of molecular tests using a gene expression ratio-based algorithm and that prognostic tests could be similarly performed. Experimental Design Two MPM and two lung cancer cell lines were used to establish the minimal RNA amount required for ratio tests. Based on these results, 276 ex-vivo FNA biopsies from 63 MPM patients, and 250 ex-vivo FNA samples from 92 lung cancer patients were analyzed using previously described diagnostic and prognostic tests based on gene expression ratios. Results We found that the sensitivity of the diagnostic test for MPM was 100% (95% CI: 95–100%), and the specificity in primary lung adenocarcinoma was 90% (95% CI: 81–95%). The FNA-based prognostic classification was concordant among 76% (95% CI: 65–87%) of patients with the risk assignment in a subset of the matched surgical specimens previously analyzed by the prognostic test. Conclusions Sufficient RNA can be extracted from most FNA biopsies to perform gene expression molecular tests. In particular, we show that the gene expression ratio algorithms performed well when applied to diagnosis and prognosis in MPM. This study provides support for the development of additional RNA molecular tests that may enhance the utility of FNA in the management of other solid cancers. PMID:21088255

  12. 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.

  13. 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, Ppathologic variables was associated with an increased risk of death...

  14. Stage Separation Failure: Model Based Diagnostics and Prognostics

    Science.gov (United States)

    2010-10-01

    flow side thrust mass flow density [ j = uρ] heat transfer coefficient heat flow from the gas to a hole wall melting temperature point...Publishing Company, Inc. New York. F.P. Incropera and D. P. DeWitt (2002), Introduction to Heat Transfer , John Wiley & Sons, NY, D.G. Luchinsky, V.V...estimate the characteristic time of the heating of the nozzle wall analytically we use Bartz’ approximation (Bartz, 1965; Incropera and DeWitt, 2002

  15. 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...

  16. A Survey of Attitudes towards the Clinical Application of Systemic Inflammation Based Prognostic Scores in Cancer

    Directory of Open Access Journals (Sweden)

    David G. Watt

    2015-01-01

    Full Text Available Introduction. The systemic inflammatory response (SIR plays a key role in determining nutritional status and survival of patients with cancer. A number of objective scoring systems have been shown to have prognostic value; however, their application in routine clinical practice is not clear. The aim of the present survey was to examine the range of opinions internationally on the routine use of these scoring systems. Methods. An online survey was distributed to a target group consisting of individuals worldwide who have reported an interest in systemic inflammation in patients with cancer. Results. Of those invited by the survey (n=238, 65% routinely measured the SIR, mainly for research and prognostication purposes and clinically for allocation of adjuvant therapy or palliative chemotherapy. 40% reported that they currently used the Glasgow Prognostic Score/modified Glasgow Prognostic Score (GPS/mGPS and 81% reported that a measure of systemic inflammation should be incorporated into clinical guidelines, such as the definition of cachexia. Conclusions. The majority of respondents routinely measured the SIR in patients with cancer, mainly using the GPS/mGPS for research and prognostication purposes. The majority reported that a measure of the SIR should be adopted into clinical guidelines.

  17. Prognostic Utility of a Self-Reported Depression Questionnaire versus Clinician-Based Assessment on Renal Outcomes.

    Science.gov (United States)

    Jain, Nishank; Carmody, Thomas; Minhajuddin, Abu T; Toups, Marisa; Trivedi, Madhukar H; Rush, Augustus John; Hedayati, S Susan

    2016-01-01

    The prognostic utility of self-administered depression scales in chronic kidney disease (CKD) independent of a clinician-based major depressive disorder (MDD) diagnosis is neither clearly established nor are the optimal cutoff scores for predicting outcomes. The overlap between symptoms of depression and chronic disease raises the question of whether a cutoff score on a depression scale can be substituted for a time-consuming diagnostic interview to prognosticate risk. The 16-item Quick Inventory of Depression Symptomatology-Self Report scale (QIDS-SR16) was administered to 266 consecutive outpatients with non-dialysis CKD, followed prospectively for 12 months for an apriori composite outcome of death or dialysis or hospitalization. Association of QIDS-SR16 best cutoff score, determined by receiver/responder operating characteristics curves, with outcomes was investigated using survival analysis. The effect modification of an interview-based clinician MDD diagnosis on this association was ascertained. There were 126 composite events. A QIDS-SR16 cutoff ≥8 had the best prognostic accuracy, hazards ratio (HR) = 1.77, 95% CI 1.24-2.53, p = 0.002. This cutoff remained significantly associated with outcomes even after controlling for comorbidities, estimated glomerular filtration rate, hemoglobin and serum albumin, adjusted HR (aHR) = 1.80, 95% CI 1.23-2.62, p = 0.002, and performed similarly to a clinician-based MDD diagnosis (aHR = 1.72, 95% CI 1.14-2.68). Adjustment for MDD conferred the association of QIDS-SR16 with outcomes no longer significant. QIDS-SR16 cutoff ≥8 adds to the prognostic information available to practicing nephrologists during routine clinic visits from comorbidities and laboratory data. This cutoff score performs similar to a clinician diagnosis of MDD and provides a feasible and time-saving alternative to an interview-based MDD diagnosis for determining prognosis in CKD patients. © 2016 S. Karger AG, Basel.

  18. Measuring frailty in population-based healthcare databases: multi-dimensional prognostic indices for the improvement of geriatric care

    Directory of Open Access Journals (Sweden)

    Janet Sultana

    2016-04-01

    Full Text Available The prognostic evaluation of geriatric patients is critical in helping clinicians to weigh the risks versus the benefits of available therapeutic options. Frailty contributes significantly to the risk of mortality in older patients and is already known to have implications on the outcome of treatment in a clinical context. The multi-dimensional prognostic index (MPI is a prognostic tool based on a comprehensive geriatric assessment and includes detailed information on patient cognition, functionality, disease and drug burden. The value of the MPI in predicting mortality has already been shown in hospital and community settings but never in a population- based healthcare database setting. One of the aims of the ongoing EU-funded MPI_Age project is to improve our understanding of how geriatric frailty data can be identified in healthcare databases and whether this can be used to predict serious adverse events associated with pharmacotherapy. Our findings suggest that data on functionality in elderly patients is poorly registered in The Health Improvement Network (THIN, a UK nationwide general practice database, and only few of the functionality domains could be used in a population-based analysis. The most commonly registered functionality information was related to mobility, dressing, accommodation and cognition. Our results suggest that some of these functionality domains are predictive of short- and long-term mortality in community-dwelling patients. This may have implications in observational research where frailty is an unmeasured confounder.

  19. 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

    OpenAIRE

    Guinney, Justin; Tao WANG; 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

    2017-01-01

    Background: 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 ...

  20. A dynamic prognostic model to predict survival in primary myelofibrosis: a study by the IWG-MRT (International Working Group for Myeloproliferative Neoplasms Research and Treatment).

    Science.gov (United States)

    Passamonti, Francesco; Cervantes, Francisco; Vannucchi, Alessandro Maria; Morra, Enrica; Rumi, Elisa; Pereira, Arturo; Guglielmelli, Paola; Pungolino, Ester; Caramella, Marianna; Maffioli, Margherita; Pascutto, Cristiana; Lazzarino, Mario; Cazzola, Mario; Tefferi, Ayalew

    2010-03-04

    Age older than 65 years, hemoglobin level lower than 100 g/L (10 g/dL), white blood cell count greater than 25 x 10(9)/L, peripheral blood blasts 1% or higher, and constitutional symptoms have been shown to predict poor survival in primary myelofibrosis (PMF) at diagnosis. To investigate whether the acquisition of these factors during follow-up predicts survival, we studied 525 PMF patients regularly followed. All 5 variables had a significant impact on survival when analyzed as time-dependent covariates in a multivariate Cox proportional hazard model and were included in 2 separate models, 1 for all patients (Dynamic International Prognostic Scoring System [DIPSS]) and 1 for patients younger than 65 years (age-adjusted DIPSS). Risk factors were assigned score values based on hazard ratios (HRs). Risk categories were low, intermediate-1, intermediate-2, and high in both models. Survival was estimated by the HR. When shifting to the next risk category, the HR was 4.13 for low risk, 4.61 for intermediate-1, and 2.54 for intermediate-2 according to DIPSS; 3.97 for low risk, 2.84 for intermediate-1, and 1.81 for intermediate-2 according to the age-adjusted DIPSS. The novelty of these models is the prognostic assessment of patients with PMF anytime during their clinical course, which may be useful for treatment decision-making.

  1. The diagnostic and prognostic role of liquid-based cytology: are we ready to monitor therapy and resistance?

    Science.gov (United States)

    Rossi, Esther Diana; Bizzarro, Tommaso; Longatto-Filho, Adhemar; Gerhard, Rene; Schmitt, Fernando

    2015-01-01

    Here, we evaluate the diagnostic and prognostic role of liquid-based cytology (LBC) in different body lesions, including thyroid, lung, effusions and malignant breast lesions. LBC has gained consensus after being applied to both non-gynecologic and fine-needle aspiration cytology. Although some remain sceptical regarding the diagnostic efficacy of LBC, mainly when used alone, in recent years, good results have been obtained as long as it showed a high diagnostic accuracy. Here, we discuss the additional possibility of storing material for the application of ancillary techniques (immunocytochemistry-molecular analysis) with several diagnostic and prognostic advantages, which may pave the way for the challenging evaluation of both monitoring responses to treatment and resistance to targeted therapies in thyroid, lung, breast carcinoma or malignant effusions. Furthermore, it provides the use of several molecular spots as specific targets for personalized therapy.

  2. Real-Time Adaptive Algorithms for Flight Control Diagnostics and Prognostics Project

    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...

  3. 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.

  4. 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.

  5. 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.

  6. Significance analysis of prognostic signatures.

    Directory of Open Access Journals (Sweden)

    Andrew H Beck

    Full Text Available A major goal in translational cancer research is to identify biological signatures driving cancer progression and metastasis. A common technique applied in genomics research is to cluster patients using gene expression data from a candidate prognostic gene set, and if the resulting clusters show statistically significant outcome stratification, to associate the gene set with prognosis, suggesting its biological and clinical importance. Recent work has questioned the validity of this approach by showing in several breast cancer data sets that "random" gene sets tend to cluster patients into prognostically variable subgroups. This work suggests that new rigorous statistical methods are needed to identify biologically informative prognostic gene sets. To address this problem, we developed Significance Analysis of Prognostic Signatures (SAPS which integrates standard prognostic tests with a new prognostic significance test based on stratifying patients into prognostic subtypes with random gene sets. SAPS ensures that a significant gene set is not only able to stratify patients into prognostically variable groups, but is also enriched for genes showing strong univariate associations with patient prognosis, and performs significantly better than random gene sets. We use SAPS to perform a large meta-analysis (the largest completed to date of prognostic pathways in breast and ovarian cancer and their molecular subtypes. Our analyses show that only a small subset of the gene sets found statistically significant using standard measures achieve significance by SAPS. We identify new prognostic signatures in breast and ovarian cancer and their corresponding molecular subtypes, and we show that prognostic signatures in ER negative breast cancer are more similar to prognostic signatures in ovarian cancer than to prognostic signatures in ER positive breast cancer. SAPS is a powerful new method for deriving robust prognostic biological signatures from clinically

  7. CT-based volumetric tumor growth velocity: A novel imaging prognostic indicator in oropharyngeal cancer patients receiving radiotherapy.

    Science.gov (United States)

    Perni, Subha; Mohamed, Abdallah S R; Scott, Jacob; Enderling, Heiko; Garden, Adam S; Gunn, G Brandon; Rosenthal, David I; Fuller, Clifton D

    2016-12-01

    Volumetric tumor growth velocity (TGV) reflects in vitro tumor aggressiveness, but its prognostic value has not been investigated in vivo. We examined the prognostic impact of TGV on oncologic outcomes in patients with oropharyngeal squamous cell cancer (OSCC). 101 OSCC patients with two pretreatment CTs with time gap of 2 or more weeks treated at a single institution between 2004 and 2008 were identified. Primary tumor and nodal targets were segmented in scans. Linear growth rates were calculated. Recursive partitioning analysis (RPA) identified cut point associated with outcomes. Median follow-up was 59months (range 7-118). Median primary TGV was 0.65% increase per day (range 0-9.37%). RPA identified TGV cut point associated with local control (LC) of 1% per day. Patients with higher TGV had decreased 5-year LC (73% vs. 98%, p=0.0004), distant control (DC, 62% vs. 91%, p=0.0007), and overall survival (OS, 38% versus 93%, pTGV⩾1% per day independently predicted worsened LC (p = 0.02), DC (p = 0.003), and OS (p TGV cutoff was not significantly predictive of LC, DC, or OS for a subset of presumed HPV-positive patients. OSCC TGV⩾1% per day is a substantive negative prognostic indicator for disease control and overall survival, particularly in HPV non-associated tumors. This novel CT-based volumetric assessment of TGV suggests a simple methodology for risk stratification of patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Hurley, P.J. [CSIRO Atmospheric Research, Aspendale, Vic (Australia); Blockley, A.; Rayner, K. [Department of Environmental Protection, Perth, WA (Australia)

    2001-04-01

    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 95{mu}gm{sup -3}, TAPM predicted 94{mu}gm{sup -3}, DISPMOD-O predicted 111{mu}gm{sup -3} and DISPMOD-T predicted 125{mu}gm{sup -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

  10. Prognostic model for advanced breast carcinoma with luminal subtype and impact of hormonal maintenance: Implications for post-progression and conditional survival.

    Science.gov (United States)

    Carbognin, Luisa; Sperduti, Isabella; Ciccarese, Mariangela; Fabi, Alessandra; Petrucelli, Luciana; Vari, Sabrina; Forcignanò, Rosa Chiara; Nortilli, Rolando; Vicentini, Cecilia; Pilotto, Sara; Merler, Sara; Zampiva, Ilaria; Brunelli, Matteo; Manfrin, Erminia; Giannarelli, Diana; Tortora, Giampaolo; Bria, Emilio

    2016-10-01

    The aim of this analysis was to develop and validate a prognostic model for advanced breast cancer (ABC) with luminal subtype based on the combination of clinical, pathological and therapeutic predictors to provide a practical tool to evaluate patients' prognosis. Clinical and pathological data were retrospectively correlated to progression-free and overall survival (PFS/OS) using a Cox model. Significant treatment variables were adjusted with the propensity score analysis. A continuous score to identify risk classes was derived according to model ratios. The performance of the risk-class model was tested for post-progression survival (PPS) and conditional survival (CS) as well. Data from 335 patients (3 institutions) were gathered (median follow-up 58 months). At multivariate analysis Ki67, Performance Status (PS) and number of metastatic sites were significant predictors for PFS, whereas Ki67, PS, brain metastases, PFS after 1st-line therapy, number of chemotherapy lines, hormonal therapy and maintenance were significant predictors for OS. The hormonal maintenance resulted to be prognostic after adjustment with propensity score analysis. A two-class model significantly differentiated low-risk and high-risk patients for 2-year PFS (31.5% and 11.0%, p model separated low risk, intermediate-risk, and high-risk patients for 2-year PFS (40.8%, 24.4%, and 11.0%, p models equally discriminate the luminal ABC prognosis in terms of PPS and CS. A risk stratification model including 'easy-to-obtain' clinical, pathological and therapeutic parameters accurately separates luminal ABC patients into different risk classes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Prognostic Classifier Based on Genome-Wide DNA Methylation Profiling in Well-Differentiated Thyroid Tumors

    DEFF Research Database (Denmark)

    Bisarro Dos Reis, Mariana; Barros-Filho, Mateus Camargo; Marchi, Fábio Albuquerque

    2017-01-01

    . Objective: To identify a prognostic epigenetic signature in thyroid cancer. Design: Genome-wide DNA methylation assays (450k platform, Illumina) were performed in a cohort of 50 nonneoplastic thyroid tissues (NTs), 17 benign thyroid lesions (BTLs), and 74 thyroid carcinomas (60 papillary, 8 follicular, 2......Context: Even though the majority of well-differentiated thyroid carcinoma (WDTC) is indolent, a number of cases display an aggressive behavior. Cumulative evidence suggests that the deregulation of DNA methylation has the potential to point out molecular markers associated with worse prognosis...... Hürthle cell, 1 poorly differentiated, and 3 anaplastic). A prognostic classifier for WDTC was developed via diagonal linear discriminant analysis. The results were compared with The Cancer Genome Atlas (TCGA) database. Results: A specific epigenetic profile was detected according to each histological...

  12. Diagnostic and prognostic simulations with a full Stokes model accounting for superimposed ice of Midtre Lovénbreen, Svalbard

    Directory of Open Access Journals (Sweden)

    T. Zwinger

    2009-11-01

    Full Text Available We present steady state (diagnostic and transient (prognostic simulations of Midtre Lovénbreen, Svalbard performed with the thermo-mechanically coupled full-Stokes code Elmer. This glacier has an extensive data set of geophysical measurements available spanning several decades, that allow for constraints on model descriptions. Consistent with this data set, we included a simple model accounting for the formation of superimposed ice. Diagnostic results indicated that a dynamic adaptation of the free surface is necessary, to prevent non-physically high velocities in a region of under determined bedrock depths. Observations from ground penetrating radar of the basal thermal state agree very well with model predictions, while the dip angles of isochrones in radar data also match reasonably well with modelled isochrones, despite the numerical deficiencies of estimating ages with a steady state model.

    Prognostic runs for 53 years, using a constant accumulation/ablation pattern starting from the steady state solution obtained from the configuration of the 1977 DEM show that: 1 the unrealistic velocities in the under determined parts of the DEM quickly damp out; 2 the free surface evolution matches well measured elevation changes; 3 the retreat of the glacier under this scenario continues with the glacier tongue in a projection to 2030 being situated ≈500 m behind the position in 1977.

  13. Stroma-Based Prognosticators Incorporating Differences between African and European Americans

    Science.gov (United States)

    2016-10-01

    both RNA and DNA from 40 AA and 70 EA samples. We can profile the higher quality and higher yield RNA and DNA samples by array card RT-PCR, and...prognosticators from training set. months Status Subtask 1: Regulatory review and approval processes, including local Institutional Review...African American (AA) and 60 clinically matched European American (EA) samples with recurrence status and at least five years of follow- up. Training

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

    Science.gov (United States)

    Luo, Li; Orlow, Irene; Kanetsky, Peter A; Thomas, Nancy E; Fang, Shenying; Lee, Jeffrey E; Berwick, Marianne; Lee, Ji-Hyun

    2017-01-01

    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.

  15. 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.

  16. 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

  17. Prognostic value of self-reported work ability and performance-based lifting tests for sustainable return to work among construction workers.

    Science.gov (United States)

    Kuijer, P Paul F M; Gouttebarge, Vincent; Wind, Haije; van Duivenbooden, Cor; Sluiter, Judith K; Frings-Dresen, Monique H W

    2012-11-01

    This study aims to evaluate whether performance-based tests have additional prognostic value over self-reported work ability for sustainable return to work (RTW) in physically demanding work. A one-year prospective cohort study was performed among 72 construction workers on sick leave for six weeks due to musculoskeletal disorders. The Work Ability Index (WAI) question regarding "current work ability" was used. Three dynamic lifting tests were used from a Functional Capacity Evaluation (FCE). Sustainable RTW was the number of days on sick leave until the first day of returning fully to work for a period of ≥4 weeks. Regression models were built to calculate the prognostic values. Self-reported work ability alone predicted sustainable RTW (R=0.31, R (2)=0.09, P=0.009). In combination with one lifting test, the explained variance (R (2)) increased to 0.16 (P=0.001). Combining self-reported work ability and a lifting test nearly doubled the explained variance for sustainable RTW in physically demanding work, although the strength remained modest.

  18. Prognostic factors of patients with newly diagnosed acute promyelocytic leukemia treated with arsenic trioxide-based frontline therapy.

    Science.gov (United States)

    Lou, Yinjun; Ma, Yafang; Suo, Shanshan; Ni, Wanmao; Wang, Yungui; Pan, Hanzhang; Tong, Hongyan; Qian, Wenbin; Meng, Haitao; Mai, Wenyuan; Huang, Jian; Yu, Wenjuan; Wei, Juyin; Mao, Liping; Jin, Jie

    2015-09-01

    Prognostic factors for patients with acute promyelocytic leukemia (APL) treated in the context of arsenic trioxide (ATO)-based frontline regimes have not been established clearly. We retrospectively analyzed the clinical features, immunophenotypes, Fms-like tyrosine kinase-3 internal tandem duplication (FLT3-ITD), and outcomes of 184 consecutive newly diagnosed APL patients treated by intravenous ATO-based therapy. The median age was 40 years (14-77 years). The early death rate was 4.9% (9/184 patients). With a median follow-up time of 36 months (9-74 months), the 3-year relapse-free survival (RFS) and overall survival (OS) were 93.3% and 92.2%, respectively. Interestingly, there was no meaningful association between 3-year RFS and initial white blood cell count, FLT3-ITD status, or type of PML-RARA isoforms. In multivariable analysis, the CD56 expression was the only independent risk factor in terms of RFS (hazard ratio, 4.70; P=0.005). These results suggested that ATO-based therapy may ameliorate the unfavorable influence of previously known high-risk features; moreover, CD56 expression remains to be a potentially unfavorable prognostic factor in APL patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. 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

  20. S100A16, a promising candidate as a prognostic marker for platinum-based adjuvant chemotherapy in resected lung adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Katono K

    2017-11-01

    Full Text Available Ken Katono,1 Yuichi Sato,2 Makoto Kobayashi,3 Ryo Nagashio,2 Shinichiro Ryuge,1 Satoshi Igawa,1 Masaaki Ichinoe,4 Yoshiki Murakumo,4 Makoto Saegusa,4 Noriyuki Masuda1 1Department of Respiratory Medicine, School of Medicine, 2Department of Molecular Diagnostics, School of Allied Health Sciences, 3Department of Applied Tumor Pathology, Graduate School of Medical Sciences, 4Department of Pathology, School of Medicine, Kitasato University, Minami-ku, Sagamihara, Kanagawa, Japan Purpose: Although cisplatin-based adjuvant chemotherapy improves the survival of patients with resected non-small-cell lung cancer, not all patients show a survival benefit, and some patients experience severe toxicity. Therefore, identifying biomarkers is important for selecting subgroups of patients who may show improved survival with platinum-based adjuvant chemotherapy. S100A16 is thought to play key roles during different steps of tumor progression. The aim of this study was to evaluate the use of S100A16 expression as a prognostic marker in patients with completely resected lung adenocarcinoma receiving platinum-based adjuvant chemotherapy. Methods: S100A16 expression was immunohistochemically studied in 65 consecutive lung adenocarcinoma patients who underwent complete resection and received platinum-based adjuvant chemotherapy. Kaplan–Meier survival analysis and Cox proportional hazards models were used to estimate the effect of S100A16 expression on disease-free survival (DFS and overall survival (OS.Results: S100A16 expression was detected in 26 of the 65 (40.0% lung adenocarcinoma patients. Although S100A16 expression was not correlated with DFS (P=0.062, it was significantly correlated with OS (P=0.009. In addition, multivariable analysis revealed that S100A16 expression independently predicted a poorer survival (HR =4.79; 95% CI =1.87–12.23; P=0.001. Conclusion: The present study revealed that S100A16 is a promising candidate as a prognostic marker for

  1. The clinical characteristics and prognostic analysis of Chinese advanced NSCLC patients based on circulating tumor DNA sequencing

    Directory of Open Access Journals (Sweden)

    Rao C

    2018-01-01

    Full Text Available Chuangzhou Rao,1 Liangqin Nie,1 Xiaobo Miao,1 Yunbao Xu,1 Bing Li,2 Tengfei Zhang2 1Radiotherapy & Chemotherapy Dept 2, Ningbo No. 2 Hospital, Zhejiang, 2Burning Rock Biotech, Guangzhou, People’s Republic of China Purpose: Circulating tumor DNA (ctDNA is a noninvasive and real-time marker for tumor diagnosis, prognosis, and prediction. However, further investigations about ctDNA prognostic and predictive value are still needed, and conclusions from several studies were inconsistent.Experimental design: We performed capture-based targeted ultradeep sequencing on liquid biopsies from a cohort of 34 advanced Chinese non-small-cell lung cancer (NSCLC patients and analyzed the clinical use of ctDNA in this study.Results: On the basis of clinical characteristics of the 34 NSCLC patients, we found that brain metastasis correlated with shorter progression-free survival (PFS and is more prone to happen in younger patients. After ctDNA sequencing, we analyzed the prognostic value of baseline ctDNA. In osimertinib-treated group, high max allelic fraction (maxAF correlated with shorter PFS. But for the cohort of 34 patients, no correlation can be observed between maxAF and PFS. We also presented two cases to demonstrate the value of disease progression prediction by ctDNA, which can be detected earlier than clinical response.Conclusion: In this study, we demonstrated that ctDNA is a prognostic marker for evaluating treatment response and predicting recurrence in advanced NSCLC. Further investigations with larger cohort and uniformed patient background are still needed to validate our findings. Keywords: circulating tumor DNA, non-small-cell lung cancer, prognosis 

  2. 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.

  3. Significance of stromal-1 and stromal-2 signatures and biologic prognostic model in diffuse large B-cell lymphoma

    Science.gov (United States)

    Abdou, Asmaa Gaber; Asaad, Nancy; Kandil, Mona; Shabaan, Mohammed; Shams, Asmaa

    2017-01-01

    Objective : Diffuse Large B Cell Lymphoma (DLBCL) is a heterogeneous group of tumors with different biological and clinical characteristics that have diverse clinical outcomes and response to therapy. Stromal-1 signature of tumor microenvironment of DLBCL represents extracellular matrix deposition and histiocytic infiltrate, whereas stromal-2 represents angiogenesis that could affect tumor progression. Methods : The aim of the present study is to assess the significance of stromal-1 signature using SPARC-1 and stromal-2 signature using CD31 expression and then finally to construct biologic prognostic model (BPM) in 60 cases of DLBCL via immunohistochemistry. Results : Microvessel density (PBPM showed that 42 cases (70%) were of low biologic score (0–1) and 18 cases (30%) were of high biologic score (2–3). Low BPM cases showed less probability for splenic involvement (P=0.04) and a higher rate of complete response to therapy compared with high score cases (P=0.08). Conclusions : The DLBCL microenvironment could modulate tumor progression behavior since angiogenesis and SPARC positive stromal cells promote dissemination by association with spleen involvement and capsular invasion. Biologic prognostic models, including modified BPM, which considered cell origin of DLBCL and stromal signature pathways, could determine DLBCL progression and response to therapy. PMID:28607806

  4. Composite prognostic models across the non-alcoholic fatty liver disease spectrum: Clinical application in developing countries

    Science.gov (United States)

    Lückhoff, Hilmar K; Kruger, Frederik C; Kotze, Maritha J

    2015-01-01

    Heterogeneity in clinical presentation, histological severity, prognosis and therapeutic outcomes characteristic of non-alcoholic fatty liver disease (NAFLD) necessitates the development of scientifically sound classification schemes to assist clinicians in stratifying patients into meaningful prognostic subgroups. The need for replacement of invasive liver biopsies as the standard method whereby NAFLD is diagnosed, graded and staged with biomarkers of histological severity injury led to the development of composite prognostic models as potentially viable surrogate alternatives. In the present article, we review existing scoring systems used to (1) confirm the presence of undiagnosed hepatosteatosis; (2) distinguish between simple steatosis and NASH; and (3) predict advanced hepatic fibrosis, with particular emphasis on the role of NAFLD as an independent cardio-metabolic risk factor. In addition, the incorporation of functional genomic markers and application of emerging imaging technologies are discussed as a means to improve the diagnostic accuracy and predictive performance of promising composite models found to be most appropriate for widespread clinical adoption. PMID:26019735

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

    Science.gov (United States)

    Bhooshan, Neha; Giger, Maryellen; Edwards, Darrin; Yuan, Yading; Jansen, Sanaz; Li, Hui; Lan, Li; Sattar, Husain; Newstead, Gillian

    2011-09-01

    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.

  6. External validation of a prognostic model for predicting survival of cirrhotic patients with refractory ascites.

    Science.gov (United States)

    Guardiola, Jordi; Baliellas, Carme; Xiol, Xavier; Fernandez Esparrach, Glòria; Ginès, Pere; Ventura, Pere; Vazquez, Santiago

    2002-09-01

    Cirrhotic patients with refractory ascites (RA) have a poor prognosis, although individual survival varies greatly. A model that could predict survival for patients with RA would be helpful in planning treatment. Moreover, in cases of potential liver transplantation, a model of these characteristics would provide the bases for establishing priorities of organ allocation and the selection of patients for a living donor graft. Recently, we developed a model to predict survival of patients with RA. The aim of this study was to establish its generalizability for predicting the survival of patients with RA. The model was validated by assessing its performance in an external cohort of patients with RA included in a multicenter, randomized, controlled trial that compared large-volume paracentesis and peritoneovenous shunt. The values for actual and model-predicted survival of three risk groups of patients, established according to the model, were compared graphically and by means of the one-sample log-rank test. The model provided a very good fit to the survival data of the three risk groups in the validation cohort. We also found good agreement between the survival predicted from the model and the observed survival when patients treated with peritoneovenous shunt and with paracentesis were considered separately. Our survival model can be used to predict the survival of patients with RA and may be a useful tool in clinical decision making, especially in deciding priority for liver transplantation.

  7. 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

  8. 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...

  9. 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

  10. 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.

  11. A mathematical model describes the malignant transformation of low grade gliomas: Prognostic implications.

    Directory of Open Access Journals (Sweden)

    Magdalena U Bogdańska

    Full Text Available Gliomas are the most frequent type of primary brain tumours. Low grade gliomas (LGGs, WHO grade II gliomas may grow very slowly for the long periods of time, however they inevitably cause death due to the phenomenon known as the malignant transformation. This refers to the transition of LGGs to more aggressive forms of high grade gliomas (HGGs, WHO grade III and IV gliomas. In this paper we propose a mathematical model describing the spatio-temporal transition of LGGs into HGGs. Our modelling approach is based on two cellular populations with transitions between them being driven by the tumour microenvironment transformation occurring when the tumour cell density grows beyond a critical level. We show that the proposed model describes real patient data well. We discuss the relationship between patient prognosis and model parameters. We approximate tumour radius and velocity before malignant transformation as well as estimate the onset of this process.

  12. 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.

  13. Emerging gene-based prognostic tools in early breast cancer: First steps to personalised medicine.

    Science.gov (United States)

    Wazir, Umar; Mokbel, Kefah

    2014-12-10

    Breast cancer remains a major cause of neoplastic disease in much of the developed world. The majority of cases are diagnosed with oestrogen receptor (ER)-positive and human epidermal growth factor receptor-2 negative invasive ductal carcinoma and are treated predominantly by surgery which includes sentinel node biopsy and adjuvant endocrine therapy ± adjuvant radiotherapy. It is believed that an indeterminate subset of the patient population is needlessly incurring chemotherapy related morbidity without attaining any increase in survival due to therapy. Furthermore in the era of extended adjuvant endocrine therapy it is important to identify those patients who can be safely treated with 5 years rather than 10 years of endocrine therapy thus optimising the benefit-risk balance. This perception has propelled the development of more personalised prognostic tools for newly diagnosed cases of ER-positive breast cancer. In this article, we shall review the evidence regarding the currently available gene assays for human breast cancer.

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

    Energy Technology Data Exchange (ETDEWEB)

    Hatt, Mathieu; Visvikis, Dimitris; Tixier, Florent [CHU Morvan, INSERM, U650 LaTIM, Brest (France); Albarghach, Nidal M.; Pradier, Olivier [CHU Morvan, INSERM, U650 LaTIM, Brest (France); CHU Morvan, Department of Radiotherapy, Brest (France); Cheze-le Rest, Catherine [CHU Morvan, INSERM, U650 LaTIM, Brest (France); CHU Morvan, Academic Department of Nuclear Medicine, Brest (France)

    2011-07-15

    {sup 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 {sup 18}F-FDG scans using adaptive threshold and automatic (fuzzy locally adaptive Bayesian, FLAB) methodologies. The maximum standardized uptake value (SUV{sub max}), SUV{sub peak}, SUV{sub 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.)

  15. A Generic Software Architecture For Prognostics

    Science.gov (United States)

    Teubert, Christopher; Daigle, Matthew J.; Sankararaman, Shankar; Goebel, Kai; Watkins, Jason

    2017-01-01

    Prognostics is a systems engineering discipline focused on predicting end-of-life of components and systems. As a relatively new and emerging technology, there are few fielded implementations of prognostics, due in part to practitioners perceiving a large hurdle in developing the models, algorithms, architecture, and integration pieces. As a result, no open software frameworks for applying prognostics currently exist. This paper introduces the Generic Software Architecture for Prognostics (GSAP), an open-source, cross-platform, object-oriented software framework and support library for creating prognostics applications. GSAP was designed to make prognostics more accessible and enable faster adoption and implementation by industry, by reducing the effort and investment required to develop, test, and deploy prognostics. This paper describes the requirements, design, and testing of GSAP. Additionally, a detailed case study involving battery prognostics demonstrates its use.

  16. A Cochlear Implant Performance Prognostic Test Based on Electrical Field Interactions Evaluated by eABR (Electrical Auditory Brainstem Responses.

    Directory of Open Access Journals (Sweden)

    Nicolas Guevara

    Full Text Available Cochlear implants (CIs are neural prostheses that have been used routinely in the clinic over the past 25 years. They allow children who were born profoundly deaf, as well as adults affected by hearing loss for whom conventional hearing aids are insufficient, to attain a functional level of hearing. The "modern" CI (i.e., a multi-electrode implant using sequential coding strategies has yielded good speech comprehension outcomes (recognition level for monosyllabic words about 50% to 60%, and sentence comprehension close to 90%. These good average results however hide a very important interindividual variability as scores in a given patients' population often vary from 5 to 95% in comparable testing conditions. Our aim was to develop a prognostic model for patients with unilateral CI. A novel method of objectively measuring electrical and neuronal interactions using electrical auditory brainstem responses (eABRs is proposed.The method consists of two measurements: 1 eABR measurements with stimulation by a single electrode at 70% of the dynamic range (four electrodes distributed within the cochlea were tested, followed by a summation of these four eABRs; 2 Measurement of a single eABR with stimulation from all four electrodes at 70% of the dynamic range. A comparison of the eABRs obtained by these two measurements, defined as the monaural interaction component (MIC, indicated electrical and neural interactions between the stimulation channels. Speech recognition performance without lip reading was measured for each patient using a logatome test (64 "vowel-consonant-vowel"; VCV; by forced choice of 1 out of 16. eABRs were measured in 16 CI patients (CIs with 20 electrodes, Digisonic SP; Oticon Medical ®, Vallauris, France. Significant correlations were found between speech recognition performance and the ratio of the amplitude of the V wave of the eABRs obtained with the two measurements (Pearson's linear regression model, parametric correlation: r

  17. Assessing calibration of prognostic risk scores.

    Science.gov (United States)

    Crowson, Cynthia S; Atkinson, Elizabeth J; Therneau, Terry M

    2016-08-01

    Current methods used to assess calibration are limited, particularly in the assessment of prognostic models. Methods for testing and visualizing calibration (e.g. the Hosmer-Lemeshow test and calibration slope) have been well thought out in the binary regression setting. However, extension of these methods to Cox models is less well known and could be improved. We describe a model-based framework for the assessment of calibration in the binary setting that provides natural extensions to the survival data setting. We show that Poisson regression models can be used to easily assess calibration in prognostic models. In addition, we show that a calibration test suggested for use in survival data has poor performance. Finally, we apply these methods to the problem of external validation of a risk score developed for the general population when assessed in a special patient population (i.e. patients with particular comorbidities, such as rheumatoid arthritis). © The Author(s) 2013.

  18. Predicting outcome after traumatic brain injury: development of prognostic scores based on the IMPACT and the APACHE II.

    Science.gov (United States)

    Raj, Rahul; Siironen, Jari; Kivisaari, Riku; Hernesniemi, Juha; Skrifvars, Markus B

    2014-10-15

    Prediction models are important tools for heterogeneity adjustment in clinical trials and for the evaluation of quality of delivered care to patients with traumatic brain injury (TBI). We sought to improve the predictive performance of the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials) prognostic model by combining it with the APACHE II (Acute Physiology and Chronic Health Evaluation II) for 6-month outcome prediction in patients with TBI treated in the intensive care unit. A total of 890 patients with TBI admitted to a large urban level 1 trauma center in 2009-2012 comprised the study population. The IMPACT and the APACHE II scores were combined using binary logistic regression. A randomized, split-sample technique with secondary bootstrapping was used for model development and internal validation. Model performance was assessed by discrimination (by area under the curve [AUC]), calibration, precision, and net reclassification improvement (NRI). Overall 6-month mortality was 22% and unfavorable neurological outcome 47%. The predictive power of the new combined IMPACT-APACHE II models was significantly superior, compared to the original IMPACT models (AUC, 0.81-0.82 vs. 0.84-0.85; p0.05). However, NRI showed a significant improvement in risk stratification of patients with unfavorable outcome by the IMPACT-APACHE II models, compared to the original models (NRI, 5.4-23.2%; pAPACHE II with the IMPACT, improved 6-month outcome predictive performance is achieved. This may be applicable for heterogeneity adjustment in forthcoming TBI studies.

  19. A radiobiological model of radiotherapy response and its correlation with prognostic imaging variables

    Science.gov (United States)

    Crispin-Ortuzar, Mireia; Jeong, Jeho; Fontanella, Andrew N.; Deasy, Joseph O.

    2017-04-01

    Radiobiological models of tumour control probability (TCP) can be personalized using imaging data. We propose an extension to a voxel-level radiobiological TCP model in order to describe patient-specific differences and intra-tumour heterogeneity. In the proposed model, tumour shrinkage is described by means of a novel kinetic Monte Carlo method for inter-voxel cell migration and tumour deformation. The model captures the spatiotemporal evolution of the tumour at the voxel level, and is designed to take imaging data as input. To test the performance of the model, three image-derived variables found to be predictive of outcome in the literature have been identified and calculated using the model’s own parameters. Simulating multiple tumours with different initial conditions makes it possible to perform an in silico study of the correlation of these variables with the dose for 50% tumour control (\\text{TC}{{\\text{D}}50} ) calculated by the model. We find that the three simulated variables correlate with the calculated \\text{TC}{{\\text{D}}50} . In addition, we find that different variables have different levels of sensitivity to the spatial distribution of hypoxia within the tumour, as well as to the dynamics of the migration mechanism. Finally, based on our results, we observe that an adequate combination of the variables may potentially result in higher predictive power.

  20. On the Use of Particle Flow to Enhance the Computational Performance of Particle-Filtering-based Prognostics

    Science.gov (United States)

    2014-10-02

    Institute of Control Theory and Systems Engineering, Technische Universität Dortmund, Germany javier.oliva@tu-dortmund.de torsten.bertram@tu...AND HEALTH MANAGEMENT SOCIETY 2014 309 ANNUAL CONFERENCE OF THE PROGNOSTICS AND HEALTH MANAGEMENT SOCIETY 2014 The remainder of this paper is...3) 2 ANNUAL CONFERENCE OF THE PROGNOSTICS AND HEALTH MANAGEMENT SOCIETY 2014 310 ANNUAL CONFERENCE OF THE PROGNOSTICS AND HEALTH MANAGEMENT SOCIETY

  1. Assessing the cost effectiveness of using prognostic biomarkers with decision models: case study in prioritising patients waiting for coronary artery surgery.

    Science.gov (United States)

    Henriksson, Martin; Palmer, Stephen; Chen, Ruoling; Damant, Jacqueline; Fitzpatrick, Natalie K; Abrams, Keith; Hingorani, Aroon D; Stenestrand, Ulf; Janzon, Magnus; Feder, Gene; Keogh, Bruce; Shipley, Martin J; Kaski, Juan-Carlos; Timmis, Adam; Sculpher, Mark; Hemingway, Harry

    2010-01-19

    To determine the effectiveness and cost effectiveness of using information from circulating biomarkers to inform the prioritisation process of patients with stable angina awaiting coronary artery bypass graft surgery. Decision analytical model comparing four prioritisation strategies without biomarkers (no formal prioritisation, two urgency scores, and a risk score) and three strategies based on a risk score using biomarkers: a routinely assessed biomarker (estimated glomerular filtration rate), a novel biomarker (C reactive protein), or both. The order in which to perform coronary artery bypass grafting in a cohort of patients was determined by each prioritisation strategy, and mean lifetime costs and quality adjusted life years (QALYs) were compared. Swedish Coronary Angiography and Angioplasty Registry (9935 patients with stable angina awaiting coronary artery bypass grafting and then followed up for cardiovascular events after the procedure for 3.8 years), and meta-analyses of prognostic effects (relative risks) of biomarkers. The observed risk of cardiovascular events while on the waiting list for coronary artery bypass grafting was 3 per 10,000 patients per day within the first 90 days (184 events in 9935 patients). Using a cost effectiveness threshold of pound20,000- pound30,000 (euro22,000-euro33,000; $32,000-$48,000) per additional QALY, a prioritisation strategy using a risk score with estimated glomerular filtration rate was the most cost effective strategy (cost per additional QALY was < pound410 compared with the Ontario urgency score). The impact on population health of implementing this strategy was 800 QALYs per 100,000 patients at an additional cost of pound 245,000 to the National Health Service. The prioritisation strategy using a risk score with C reactive protein was associated with lower QALYs and higher costs compared with a risk score using estimated glomerular filtration rate. Evaluating the cost effectiveness of prognostic biomarkers is

  2. Population-specific prognostic models are needed to stratify outcomes for African-Americans with diffuse large B-cell lymphoma.

    Science.gov (United States)

    Chen, Qiushi; Ayer, Turgay; Nastoupil, Loretta J; Koff, Jean L; Staton, Ashley D; Chhatwal, Jagpreet; Flowers, Christopher R

    2016-01-01

    Diffuse large B-cell lymphoma (DLBCL) demonstrates significant racial differences in age of onset, stage, and survival. To examine whether population-specific models improve prediction of outcomes for African-American (AA) patients with DLBCL, we utilized Surveillance, Epidemiology, and End Results data and compared stratification by the international prognostic index (IPI) in general and AA populations. We also constructed and compared prognostic models for general and AA populations using multivariable logistic regression (LR) and artificial neural network approaches. While the IPI adequately stratified outcomes for the general population, it failed to separate AA DLBCL patients into distinct risk groups. Our AA LR model identified age ≥ 55 (odds ratio 0.45, [95% CI: 0.36, 0.56], male sex (0.75, [0.60, 0.93]), and stage III/IV disease (0.43, [0.34, 0.54]) as adverse predictors of 5-year survival for AA patients. In addition, general-population prognostic models were poorly calibrated for AAs with DLBCL, indicating a need for validated AA-specific prognostic models.

  3. A clinical prognostic model for the identification of low-risk patients with acute symptomatic pulmonary embolism and active cancer.

    Science.gov (United States)

    den Exter, Paul L; Gómez, Vicente; Jiménez, David; Trujillo-Santos, Javier; Muriel, Alfonso; Huisman, Menno V; Monreal, Manuel

    2013-01-01

    Physicians need a specific risk-stratification tool to facilitate safe and cost-effective approaches to the management of patients with cancer and acute pulmonary embolism (PE). The objective of this study was to develop a simple risk score for predicting 30-day mortality in patients with PE and cancer by using measures readily obtained at the time of PE diagnosis. Investigators randomly allocated 1,556 consecutive patients with cancer and acute PE from the international multicenter Registro Informatizado de la Enfermedad TromboEmbólica to derivation (67%) and internal validation (33%) samples. The external validation cohort for this study consisted of 261 patients with cancer and acute PE. Investigators compared 30-day all-cause mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. In the derivation sample, multivariable analyses produced the risk score, which contained six variables: age > 80 years, heart rate ≥ 110/min, systolic BP < 100 mm Hg, body weight < 60 kg, recent immobility, and presence of metastases. In the internal validation cohort (n = 508), the 22.2% of patients (113 of 508) classified as low risk by the prognostic model had a 30-day mortality of 4.4% (95% CI, 0.6%-8.2%) compared with 29.9% (95% CI, 25.4%-34.4%) in the high-risk group. In the external validation cohort, the 18% of patients (47 of 261) classified as low risk by the prognostic model had a 30-day mortality of 0%, compared with 19.6% (95% CI, 14.3%-25.0%) in the high-risk group. The developed clinical prediction rule accurately identifies low-risk patients with cancer and acute PE.

  4. [Assessment of Cachexia in Head and Neck Cancer Patients Based on a Modified Glasgow Prognostic Score].

    Science.gov (United States)

    Matsuzuka, Takashi; Suzuki, Masahiro; Saijoh, Satoshi; Ikeda, Masakazu; Imaizumi, Mitsumasa; Nomoto, Yukio; Matsui, Takamichi; Tada, Yasuhiro; Omori, Koichi

    2016-02-01

    We retrospectively analyzed 54 patients who died of head and neck squamous cell caricinoma regarding the process and duration of cachexia using the modified Glasgow Prognostic Score (mGPS). The patients were classified as having cachexia when the serum albumin level was less than 3.5 mg/dL and the C-reactive protein (CRP) level was more than 0.5 mg/dL. The number of patients with cachexia was eight (8%) at the first visit and 50 (93%) at the time of death. In the 50 patients, the median and average time of having cachexia was 59 and 95 days, respectively. Thirty-two of the 50 patients (64%) died within three months after the presence of cachexia was confirmed. In this study, the time of having cachexia was so short, then the policy of care should be converted from aggressive into supportive in patients classified as having cachexia. mGPS would be an accurate assessment tool for cachexia and ascertain the end stage of head and neck cancer patients.

  5. The added value that increasing levels of diagnostic information provide in prognostic models to estimate hospital mortality for adult intensive care patients

    NARCIS (Netherlands)

    de Keizer, N. F.; Bonsel, G. J.; Goldfad, C.; Rowan, K. M.

    2000-01-01

    To investigate in a systematic, reproducible way the potential of adding increasing levels of diagnostic information to prognostic models for estimating hospital mortality. Prospective cohort study. Thirty UK intensive care units (ICUs) participating in the ICNARC Case Mix Programme. Eight thousand

  6. Genomics-based Approach and Prognostic Stratification Significance of Gene Mutations in Intermediate-risk Acute Myeloid Leukemia

    Directory of Open Access Journals (Sweden)

    Bian-Hong Wang

    2015-01-01

    Conclusions: NGS represents a pioneering and helpful approach to prognostic risk stratification of IR-AML patients. Further large-scale studies for comprehensive molecular analysis are needed to provide guidance and a theoretical basis for IR-AML prognostic stratification and clinical management.

  7. Prognostic Model for Resected Squamous-Cell Lung Cancer: External Multicenter Validation and Propensity Score Analysis exploring the Impact of Adjuvant and Neoadjuvant Treatment.

    Science.gov (United States)

    Pilotto, Sara; Sperduti, Isabella; Leuzzi, Giovanni; Chiappetta, Marco; Mucilli, Felice; Ratto, Giovanni Battista; Lococo, Filippo; Filosso, Pierluigi; Spaggiari, Lorenzo; Novello, Silvia; Milella, Michele; Santo, Antonio; Scarpa, Aldo; Infante, Maurizio; Tortora, Giampaolo; Facciolo, Francesco; Bria, Emilio

    2017-12-18

    We developed one of the first clinicopathological prognostic nomograms for resected squamous cell lung cancer (SQLC). Herein, we validate the model in a larger multicenter cohort and we explore the impact of adjuvant/neoadjuvant treatment (ANT). Resected SQLC patients from January 2002 to December 2012 in six institutions were eligible. To each patient was assigned a prognostic score based on those clinicopathological factors included in the model (age, T-descriptor according to TNM 7th edition, lymph nodes, grading). Kaplan-Meier analysis for disease-free/cancer-specific/overall survival (DFS/CSS/OS) was performed according to three-class risk model. Harrell's C-statistics were adopted for model validation. The effect of ANT was adjusted with propensity score (PS). Data from 1,375 patients was gathered (median age: 68 years; male: 86.8%; T-descriptor 1-2/3-4: 71.7%/24.9%; nodes negative/positive: 53.4%/46.6%; grading 1-2/3: 35.0%/41.1%). Data for survival analysis was available for 1,097 patients. With a median follow-up of 55 months, patients at low risk had a significantly longer DFS versus intermediate (HR 1.67, 95% CI 1.40-2.01) and high risk (HR 2.46, 95% CI 1.90-3.19), as well as for CSS (HR 2.46, 95% CI 1.80-3.36; HR 4.30, 95% CI 2.92-6.33) and OS (HR 1.79, 95% CI 1.48-2.17; HR 2.33, 95% CI 1.76-3.07). A trend in favor of ANT was observed for intermediate/high risk patients, particularly for CSS (p=0.06; 5-year CSS 72.7% versus 60.8%). A model based on a combination of easily available clinicopathological factors effectively stratifies resected SQLC patients in three-risk classes. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  8. A Relevance Vector Machine-Based Approach with Application to Oil Sand Pump Prognostics

    Directory of Open Access Journals (Sweden)

    Peter W. Tse

    2013-09-01

    Full Text Available Oil sand pumps are widely used in the mining industry for the delivery of mixtures of abrasive solids and liquids. Because they operate under highly adverse conditions, these pumps usually experience significant wear. Consequently, equipment owners are quite often forced to invest substantially in system maintenance to avoid unscheduled downtime. In this study, an approach combining relevance vector machines (RVMs with a sum of two exponential functions was developed to predict the remaining useful life (RUL of field pump impellers. To handle field vibration data, a novel feature extracting process was proposed to arrive at a feature varying with the development of damage in the pump impellers. A case study involving two field datasets demonstrated the effectiveness of the developed method. Compared with standalone exponential fitting, the proposed RVM-based model was much better able to predict the remaining useful life of pump impellers.

  9. A relevance vector machine-based approach with application to oil sand pump prognostics.

    Science.gov (United States)

    Hu, Jinfei; Tse, Peter W

    2013-09-18

    Oil sand pumps are widely used in the mining industry for the delivery of mixtures of abrasive solids and liquids. Because they operate under highly adverse conditions, these pumps usually experience significant wear. Consequently, equipment owners are quite often forced to invest substantially in system maintenance to avoid unscheduled downtime. In this study, an approach combining relevance vector machines (RVMs) with a sum of two exponential functions was developed to predict the remaining useful life (RUL) of field pump impellers. To handle field vibration data, a novel feature extracting process was proposed to arrive at a feature varying with the development of damage in the pump impellers. A case study involving two field datasets demonstrated the effectiveness of the developed method. Compared with standalone exponential fitting, the proposed RVM-based model was much better able to predict the remaining useful life of pump impellers.

  10. A prognostic model for platinum-doublet as second-line chemotherapy in advanced non-small-cell lung cancer patients.

    Science.gov (United States)

    Mo, Hongnan; Hao, Xuezhi; Liu, Yutao; Wang, Lin; Hu, Xingsheng; Xu, Jianping; Yang, Sheng; Xing, Puyuan; Shi, Youwu; Jia, Bo; Wang, Yan; Li, Junling; Wang, Hongyu; Wang, Ziping; Sun, Yan; Shi, Yuankai

    2016-06-01

    Poor prognosis of advanced non-small-cell lung cancer (NSCLC) patients and the promising therapeutic effect of platinum urge the oncologists to evaluate the role of platinum doublet as second-line chemotherapy and establish the definition of platinum sensitivity in NSCLC. We retrospectively analyzed 364 advanced NSCLC patients who received platinum-doublet regimens as second-line chemotherapy after platinum-based first-line treatment. Patients were divided into four groups by their time-to-progression (TTP) after first-line chemotherapy: 0-3, 4-6, 7-12, and >12-month group, respectively. Treatment efficacy of patients' overall survival (OS), progression-free survival (PFS), and response rate (RR), as well as treatment-related toxicity, were compared among the four groups. A prognosis score system and a nomogram were established by Cox proportional hazard model, and validated by concordance index (c-index). Median OS was 14.0, 16.0, 20.0, 25.0 months for patients in the 0-3, 4-6, 7-12, >12-month group, respectively. Age ≤60 years (P = 0.002), female (P = 0.019), and TTP>12 months (P = 0.003) were independent prognostic factors. Prognostic score was calculated by adding 1 point each for any of the above three indicators, with a c-index of 0.590 (95% confidential interval [CI], 0.552-0.627). Median OS were equal to 25.0, 16.0, and 11.0 months for best (2-3 points), intermediate (1 point) and worst (0 point) category, respectively (P chemotherapy in advanced NSCLCpatients. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  11. 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

  12. 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 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 the likelihood of long-term survival.

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

    Energy Technology Data Exchange (ETDEWEB)

    Noel, G.; Jauffret, E.; Mammar, H.; Ferrand, R. [Centre de Protontherapie d' Orsay, Orsay (France); Habrand, J.L.; Crevoisier, R. de; Haie-Meder, C.; Beaudre, A. [Inst. Gustave Roussy, Villejuif (France); Dederke, S.; Hasboun, D.; Boisserie, G. [Groupe Pitie Salpetriere, AP-HP, Paris (France); Pontvert, D.; Gaboriaud, G. [Inst. Curie, Paris (France); Guedea, F.; Petriz, L. [Catalan Inst. of Oncology, Barcelona (Spain); Mazeron, J.J. [Centre de Protontherapie d' Orsay, Orsay (France); Groupe Pitie Salpetriere, AP-HP, Paris (France)

    2003-04-01

    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

  14. Prognostic implication of HSPA (HSP70) in breast cancer patients treated with neoadjuvant anthracycline-based chemotherapy.

    Science.gov (United States)

    Nadin, Silvina B; Sottile, Mayra L; Montt-Guevara, Maria M; Gauna, Gisel V; Daguerre, Pedro; Leuzzi, Marcela; Gago, Francisco E; Ibarra, Jorge; Cuello-Carrión, F Darío; Ciocca, Daniel R; Vargas-Roig, Laura M

    2014-07-01

    Neoadjuvant chemotherapy is used in patients with locally advanced breast cancer to reduce tumor size before surgery. Unfortunately, resistance to chemotherapy may arise from a variety of mechanisms. Heat shock proteins (HSPs), which are highly expressed in mammary tumor cells, have been implicated in anticancer drug resistance. In spite of the widely described value of HSPs as molecular markers in cancer, their implications in breast tumors treated with anthracycline-based neoadjuvant chemotherapy has been poorly explored. In this study, we have evaluated, by immunohistochemistry, the expression of HSP27 (HSPB1) and HSP70 (HSPA) in serial biopsies from locally advanced breast cancer patients (n = 60) treated with doxorubicin (DOX)- or epirubicin (EPI)-based monochemotherapy. Serial biopsies were taken at days 1, 3, 7, and 21, and compared with prechemotherapy and surgical biopsies. After surgery, the patients received additional chemotherapy with cyclophosphamide, methotrexate, and 5-fluorouracil. High nuclear HSPB1 and HSPA expressions were found in invasive cells after DOX/EPI administration (P 31 % of the cells) and cytoplasmic HSPA expressions (>11 % of the tumor cells) were associated with better DFS (P = 0.0348 and P = 0.0118, respectively). We conclude that HSPA expression may be a useful prognostic marker in breast cancer patients treated with neoadjuvant DOX/EPI chemotherapy indicating the need to change the administered drugs after surgery for overcoming drug resistance.

  15. Microarray-based identification of CUB-domain containing protein 1 as a potential prognostic marker in conventional renal cell carcinoma.

    Science.gov (United States)

    Awakura, Yasuo; Nakamura, Eijiro; Takahashi, Takeshi; Kotani, Hirokazu; Mikami, Yoshiki; Kadowaki, Tadashi; Myoumoto, Akira; Akiyama, Hideo; Ito, Noriyuki; Kamoto, Toshiyuki; Manabe, Toshiaki; Nobumasa, Hitoshi; Tsujimoto, Gozoh; Ogawa, Osamu

    2008-12-01

    Renal cell carcinoma (RCC) is characterized by a variable and unpredictable clinical course. Thus, accurate prediction of the prognosis is important in clinical settings. We conducted microarray-based study to identify a novel prognostic marker in conventional RCC. The present study included the patients surgically treated at Kyoto University Hospital. Gene expression profiling of 39 samples was carried out to select candidate prognostic markers. Quantitative real-time PCR of 65 samples confirmed the microarray experiment results. Finally, we evaluated the significance of potential markers at their protein expression level by immunohistochemically analyzing 230 conventional RCC patients. Using expression profiling analysis, we identified 14 candidate genes whose expression levels predicted unfavorable disease-specific survival. Next, we examined the expression levels of nine candidate genes by quantitative real-time PCR and selected CUB-domain containing protein 1 (CDCP1) for further immunohistochemical analysis. Positive staining for CDCP1 inversely correlated with disease-specific and recurrence-free survivals. In multivariate analysis including clinical/pathological factors, CDCP1 staining was a significant predictor of disease-specific and recurrence-free survivals. We identified CDCP1 as a potential prognostic marker for conventional RCC. Further studies might be required to confirm the prognostic value of CDCP1 and to understand its function in RCC progression.

  16. 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 < 99. Simulating increasing score cut-off values not only enhanced specificity (correctly identified non-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.

  17. A Prognostic Model of Surgical Site Infection Using Daily Clinical Wound Assessment.

    Science.gov (United States)

    Sanger, Patrick C; van Ramshorst, Gabrielle H; Mercan, Ezgi; Huang, Shuai; Hartzler, Andrea L; Armstrong, Cheryl A L; Lordon, Ross J; Lober, William B; Evans, Heather L

    2016-08-01

    Surgical site infection (SSI) remains a common, costly, and morbid health care-associated infection. Early detection can improve outcomes, yet previous risk models consider only baseline risk factors (BF) not incorporating a proximate and timely data source-the wound itself. We hypothesize that incorporation of daily wound assessment improves the accuracy of SSI identification compared with traditional BF alone. A prospective cohort of 1,000 post open abdominal surgery patients at an academic teaching hospital were examined daily for serial features (SF), for example, wound characteristics and vital signs, in addition to standard BF, for example, wound class. Using supervised machine learning, we trained 3 Naïve Bayes classifiers (BF, SF, and BF+SF) using patient data from 1 to 5 days before diagnosis to classify SSI on the following day. For comparison, we also created a simplified SF model that used logistic regression. Control patients without SSI were matched on 5 similar consecutive postoperative days to avoid confounding by length of stay. Accuracy, sensitivity/specificity, and area under the receiver operating characteristic curve were calculated on a training and hold-out testing set. Of 851 patients, 19.4% had inpatient SSIs. Univariate analysis showed differences in C-reactive protein, surgery duration, and contamination, but no differences in American Society of Anesthesiologists scores, diabetes, or emergency surgery. The BF, SF, and BF+SF classifiers had area under the receiver operating characteristic curves of 0.67, 0.76, and 0.76, respectively. The best-performing classifier (SF) had optimal sensitivity of 0.80, specificity of 0.64, positive predictive value of 0.35, and negative predictive value of 0.93. Features most associated with subsequent SSI diagnosis were granulation degree, exudate amount, nasogastric tube presence, and heart rate. Serial features provided moderate positive predictive value and high negative predictive value for early

  18. Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy.

    Science.gov (United States)

    Darb-Esfahani, Silvia; Loibl, Sibylle; Müller, Berit M; Roller, Marc; Denkert, Carsten; Komor, Martina; Schlüns, Karsten; Blohmer, Jens Uwe; Budczies, Jan; Gerber, Bernd; Noske, Aurelia; du Bois, Andreas; Weichert, Wilko; Jackisch, Christian; Dietel, Manfred; Richter, Klaus; Kaufmann, Manfred; von Minckwitz, Gunter

    2009-01-01

    Reliable predictive and prognostic markers for routine diagnostic purposes are needed for breast cancer patients treated with neoadjuvant chemotherapy. We evaluated protein biomarkers in a cohort of 116 participants of the GeparDuo study on anthracycline/taxane-based neoadjuvant chemotherapy for operable breast cancer to test for associations with pathological complete response (pCR) and disease-free survival (DFS). Particularly, we evaluated if interactions between hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression might lead to a different clinical behavior of HR+/HER2+ co-expressing and HR+/HER2- tumors and whether subgroups of triple negative tumors might be identified by the help of Ki67 labeling index, cytokeratin 5/6 (CK5/6), as well as cyclooxygenase-2 (COX-2), and Y-box binding protein 1 (YB-1) expression. Expression analysis was performed using immunohistochemistry and silver-enhanced in situ hybridization on tissue microarrays (TMAs) of pretherapeutic core biopsies. pCR rates were significantly different between the biology-based tumor types (P = 0.044) with HR+/HER2+ and HR-/HER2- tumors having higher pCR rates than HR+/HER2- tumors. Ki67 labeling index, confirmed as significant predictor of pCR in the whole cohort (P = 0.001), identified HR-/HER- (triple negative) carcinomas with a higher chance for a pCR (P = 0.006). Biology-based tumor type (P = 0.046 for HR+/HER2+ vs. HR+/HER2-), Ki67 labeling index (P = 0.028), and treatment arm (P = 0.036) were independent predictors of pCR in a multivariate model. DFS was different in the biology-based tumor types (P Biology-based tumor type was an independent prognostic factor for DFS in multivariate analysis (P biology-based breast cancer classification using estrogen receptor (ER), progesterone receptor (PgR), and HER2 bears independent predictive and prognostic potential. The HR+/HER2+ co-expressing carcinomas emerged as a group of tumors with a good response rate to

  19. Two novel mixed effects models for prognostics of rolling element bearings

    Science.gov (United States)

    Wang, Dong; Tsui, Kwok-Leung

    2018-01-01

    Rolling element bearings are widely used in various machines to support rotating shafts. Due to harsh working environments, the health condition of a bearing degrades over time. A typical bearing degradation process includes two phases. In Phase I, the health condition of the bearing is in normal and it exhibits a stable trend. In Phase II, the health condition of the bearing degrades exponentially. To analytically model the bearing degradation process, two novel mixed effects models are proposed in this paper. Each of the two mixed effects models is able to simultaneously model Phases I and II of the bearing degradation process. The main difference between the two mixed effects models is that different error assumptions including multiplicative normal random error and multiplicative Brownian motion error are respectively considered in the two mixed effects models. Consequently, two different closed-form distributions of bearing remaining useful life are derived from the two mixed effects models via Bayes' theorem once real-time bearing condition monitoring data are available. 25 sets of bearing degradation data collected from an experimental machine are used to illustrate how the two mixed effects models work. Comparisons are conducted to show that the mixed effects model with multiplicative Brownian motion error results in lower prediction errors than the mixed effects model with multiplicative normal random error for bearing remaining useful life prediction.

  20. 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 association with tumor size was found to be strongest for BI-RADS categories 3 and 4 (P for heterogeneity associated with both unfavorable (high grade) and favorable (small size, hormone receptor positivity) prognostic factors. Detailed analysis of the biological features of

  1. Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models.

    Science.gov (United States)

    Thangaratinam, Shakila; Allotey, John; Marlin, Nadine; Dodds, Julie; Cheong-See, Fiona; von Dadelszen, Peter; Ganzevoort, Wessel; Akkermans, Joost; Kerry, Sally; Mol, Ben W; Moons, Karl G M; Riley, Richard D; Khan, Khalid S

    2017-03-30

    Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes. A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81-0.87; PREP-S) and 0.82 (0.80-0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets. PREP models can be used to obtain predictions of adverse maternal outcome risk, including

  2. 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

  3. 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 Cancer Genome Atlas were analysed. The data from The Cancer Genome Atlas and results from quantitative reverse transcription polymerase chain reaction also verified the anterior 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 breast cancer excluded) and grade 1 + 2 tissues compared with grade 3 tissues (p breast cancer and can be regarded as a putative biomarker for breast cancer prognosis.

  4. Comparison of the predictive qualities of three prognostic models of colorectal cancer

    Science.gov (United States)

    Anderson, Billie; Hardin, J. Michael; Alexander, Dominik D.; Meleth, Sreelatha; Grizzle, William E.; Manne, Upender

    2013-01-01

    Most discoveries of cancer biomarkers involve construction of a single model to determine predictions of survival. ‘Data-mining’ techniques, such as artificial neural networks (ANNs), perform better than traditional methods, such as logistic regression. In this study, the quality of multiple predictive models built on a molecular data set for colorectal cancer (CRC) was evaluated. Predictive models (logistic regressions, ANNs, and decision trees) were compared, and the effect of techniques for variable selection on the predictive quality of these models was investigated. The Kolmogorov-Smirnoff (KS) statistic was used to compare the models. Overall, the logistic regression and ANN methods outperformed use of a decision tree. In some instances (e.g., for a model that included ‘all variables without tumor stage’ and use of a decision tree for variable selection), the ANN marginally outperformed logistic regression, although the difference between the accuracy of the KS statistic was minimal (0.80 versus 0.82). Regardless of the variable(s) and the methods for variable selection, all three predictive models identified survivors and non-survivors with the same level of statistical accuracy. PMID:20515758

  5. Empirical Mode Decomposition Based Features for Diagnosis and Prognostics of Systems

    National Research Council Canada - National Science Library

    Khatri, Hiralal; Ranney, Kenneth; Tom, Kwok; del Rosario, Romeo

    2008-01-01

    We present a new procedure to generate additional features for system diagnosis. The procedure is based on empirical mode decomposition of measured signals obtained by monitoring the relevant state of a system...

  6. 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.)

  7. Prognostic impact of array-based genomic profiles in esophageal squamous cell cancer

    DEFF Research Database (Denmark)

    Carneiro, Ana; Isinger, Anna; Karlsson, Anna

    2008-01-01

    applied array-based comparative genomic hybridization (aCGH) to obtain a whole genome copy number profile relevant for identifying deranged pathways and clinically applicable markers. METHODS: A 32 k aCGH platform was used for high resolution mapping of copy number changes in 30 stage I-IV ESCC. Potential...

  8. 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

    2017-04-01

    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

  9. 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.

  10. Assessing the utility of a prognostication model to predict 1-year mortality in patients receiving radiation therapy for spinal metastases.

    Science.gov (United States)

    Shi, Diana D; Chen, Yu-Hui; Lam, Tai Chung; Leonard, Dana; Balboni, Tracy Anne; Schoenfeld, Andrew; Skamene, Sonia; Cagney, Daniel N; Chi, John H; Cho, Charles H; Harris, Mitchel; Ferrone, Marco L; Hertan, Lauren M

    2017-10-12

    Predicting survival outcomes after radiation therapy alone for metastatic disease of the spine is a challenging task that is important to guiding treatment decisions (e.g., determining dose fractionation and intensity). The New England Spinal Metastasis Score (NESMS) was recently introduced and validated in independent cohorts as a tool to predict 1-year survival following surgery for spinal metastases. This metric is composed of 3 factors: pre-operative albumin, ambulatory status, and modified Bauer score, with the total score ranging from 0 to 3. The purpose of this study is to assess the applicability of the NESMS model to predict 1-year survival among patients treated with radiation therapy alone for spinal metastases. This study is a retrospective analysis. This sample included 290 patients who underwent conventional radiation therapy alone for spinal metastases. Patients' NESMS scores (comprised of ambulatory status, pre-treatment serum albumin, and modified Bauer score) were assessed as well as their 1-year overall survival rates following radiation for metastatic disease of the spine. This study is a single-institution retrospective analysis of 290 patients treated with conventional radiation alone for spinal metastases from 2008 to 2013. The predictive value of the NESMS was assessed using multivariable logistic regression modeling, adjusted for potential confounding variables. This analysis indicated that patients with lower NESMS scores had higher rates of 1-year mortality. Multivariable analysis demonstrated a strong association between lower NESMS scores and lower rates of survival. The NESMS score is a simple prognostic scheme that requires clinical data that is often readily available and has been validated in independent cohorts of surgical patients. This study serves to validate the utility of the NESMS composite score to predict 1-year mortality in patients treated with radiation alone for spinal metastases. Copyright © 2017 Elsevier Inc. All

  11. 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

  12. Prognosticating fault development rate in wind turbine generator bearings using local trend models

    DEFF Research Database (Denmark)

    Skrimpas, Georgios Alexandros; Palou, Jonel; Sweeney, Christian Walsted

    2016-01-01

    Generator bearing defects, e.g. ball, inner and outer race defects, are ranked among the most frequent mechanical failures encountered in wind turbines. Diagnosis and prognosis of bearing faults can be successfully implemented using vibration based condition monitoring systems, where tracking...... of vibration trends from multi-megawatt wind turbine generators are presented, showing the effectiveness of the suggested approach on the calculation of the RUL and fault progression rate....

  13. Model-Based Testing

    NARCIS (Netherlands)

    Timmer, Mark; Brinksma, Hendrik; Stoelinga, Mariëlle Ida Antoinette; Broy, M.; Leuxner, C.; Hoare, C.A.R.

    This paper provides a comprehensive introduction to a framework for formal testing using labelled transition systems, based on an extension and reformulation of the ioco theory introduced by Tretmans. We introduce the underlying models needed to specify the requirements, and formalise the notion of

  14. Microarray-based analysis and clinical validation identify ubiquitin-conjugating enzyme E2E1 (UBE2E1 as a prognostic factor in acute myeloid leukemia

    Directory of Open Access Journals (Sweden)

    Hongmei Luo

    2016-11-01

    Full Text Available Abstract Background Previous research suggested that single gene expression might be correlated with acute myeloid leukemia (AML survival. Therefore, we conducted a systematical analysis for AML prognostic gene expressions. Methods We performed a microarray-based analysis for correlations between gene expression and adult AML overall survival (OS using datasets GSE12417 and GSE8970. Positive findings were validated in an independent cohort of 50 newly diagnosed, non-acute promyelocytic leukemia (APL AML patients by quantitative RT-PCR and survival analysis. Results Microarray-based analysis suggested that expression of eight genes was each associated with 1-year and 3-year AML OS in both GSE12417 and GSE8970 datasets (p < 0.05. Next, we validated our findings in an independent cohort of AML samples collected in our hospital. We found that ubiquitin-conjugating enzyme E2E1 (UBE2E1 expression was adversely correlated with AML survival (p = 0.04. Multivariable analysis showed that UBE2E1 high patients had a significant shorter OS and shorter progression-free survival after adjusting other known prognostic factors (p = 0.03. At last, we found that UBE2E1 expression was negatively correlated with patients’ response to induction chemotherapy (p < 0.05. Conclusions In summary, we demonstrated that UBE2E1 expression was a novel prognostic factor in adult, non-APL AML patients.

  15. Base excision repair imbalance in colorectal cancer has prognostic value and modulates response to chemotherapy

    Science.gov (United States)

    Leguisamo, Natalia M.; Gloria, Helena C.; Kalil, Antonio N.; Martins, Talita V.; Azambuja, Daniel B.

    2017-01-01

    Colorectal cancer (CRC) is prevalent worldwide, and treatment often involves surgery and genotoxic chemotherapy. DNA repair mechanisms, such as base excision repair (BER) and mismatch repair (MMR), may not only influence tumour characteristics and prognosis but also dictate chemotherapy response. Defective MMR contributes to chemoresistance in colorectal cancer. Moreover, BER affects cellular survival by repairing genotoxic base damage in a process that itself can disrupt metabolism. In this study, we characterized BER and MMR gene expression in colorectal tumours and the association between this repair profile with patients’ clinical and pathological features. In addition, we exploited the possible mechanisms underlying the association between altered DNA repair, metabolism and response to chemotherapy. Seventy pairs of sporadic colorectal tumour samples and adjacent non-tumour mucosal specimens were assessed for BER and MMR gene and protein expression and their association with pathological and clinical features. MMR-deficient colon cancer cells (HCT116) transiently overexpressing MPG or XRCC1 were treated with 5-FU or TMZ and evaluated for viability and metabolic intermediate levels. Increase in BER gene and protein expression is associated with more aggressive tumour features and poor pathological outcomes in CRC. However, tumours with reduced MMR gene expression also displayed low MPG, OGG1 and PARP1 expression. Imbalancing BER by overexpression of MPG, but not XRCC1, sensitises MMR-deficient colon cancer cells to 5-FU and TMZ and leads to ATP depletion and lactate accumulation. MPG overexpression alters DNA repair and metabolism and is a potential strategy to overcome 5-FU chemotherapeutic resistance in MMR-deficient CRC. PMID:28903334

  16. Modifying effect of gender on the prognostic value of clinicopathological factors and Ki67 expression in melanoma: a population-based cohort study

    Directory of Open Access Journals (Sweden)

    Fridberg Marie

    2012-07-01

    Full Text Available Abstract Background Malignant melanoma is the most deadly form of skin cancer. Female sex is known to have a protective effect on incidence, tumour characteristics, and mortality from melanoma. However, the potentially modifying effect of sex on the prognostic significance of clinicopathological and investigative factors is generally not taken into consideration in biomarker studies. In this study, we compared the sex-specific distribution and prognostic value of established tumour characteristics and Ki67 expression in 255 cases of incident primary melanoma in a prospective, population-based cohort study. Methods The study included 255 incident cases of melanoma, 132 females and 123 males, in the Malmö Diet and Cancer Study. Tumours from 226 (88.6% cases had been assembled in tissue microarrays. Clinicopathological factors and immunohistochemical Ki67 expression were assessed and correlated with disease-free survival (DFS and overall survival (OS using Kaplan-Meier analysis, log rank test and univariable and multivariable Cox regression analyses, stratified for gender. Effect of gender on melanoma-specific survival (MSS after first recurrence was also analysed. Results Women were significantly younger at diagnosis than men (p = 0.012. The most common tumour sites were the legs in women (37.5% and the dorsal trunk in men (37.8%. Kaplan-Meier analysis revealed that tumour location had no prognostic impact in women, but in men, location to the frontal trunk was significantly associated with a reduced DFS compared with all other locations combined and location to the dorsal trunk was significantly associated with a prolonged OS. High Ki67 expression was significantly associated with a reduced DFS and OS in men but not in women, also when adjusted for other factors. In men, but not in women, ulceration was an independent prognostic factor for both DFS and OS. MSS after first local, regional or distant recurrence was significantly shorter for

  17. Tumor Budding in Colorectal Carcinoma: Confirmation of Prognostic Significance and Histologic Cutoff in a Population-based Cohort.

    Science.gov (United States)

    Graham, Rondell P; Vierkant, Robert A; Tillmans, Lori S; Wang, Alice H; Laird, Peter W; Weisenberger, Daniel J; Lynch, Charles F; French, Amy J; Slager, Susan L; Raissian, Yassaman; Garcia, Joaquin J; Kerr, Sarah E; Lee, Hee Eun; Thibodeau, Stephen N; Cerhan, James R; Limburg, Paul J; Smyrk, Thomas C

    2015-10-01

    Tumor budding in colorectal carcinoma has been associated with poor outcome in multiple studies, but the absence of an established histologic cutoff for "high" tumor budding, heterogeneity in study populations, and varying methods for assessing tumor budding have hindered widespread incorporation of this parameter in clinical reports. We used an established scoring system in a population-based cohort to determine a histologic cutoff for "high" tumor budding and confirm its prognostic significance. We retrieved hematoxylin and eosin-stained sections from 553 incident colorectal carcinoma cases. Each case was previously characterized for select molecular alterations and survival data. Interobserver agreement was assessed between 2 gastrointestinal pathologists and a group of 4 general surgical pathologists. High budding (≥ 10 tumor buds in a ×20 objective field) was present in 32% of cases, low budding in 46%, and no budding in 22%. High tumor budding was associated with advanced pathologic stage (P 2 times risk of cancer-specific death (hazard ratio = 2.57 [1.27, 5.19]). After multivariate adjustment, by penalized smoothing splines, we found increasing tumor bud counts from 5 upward to be associated with an increasingly shortened cancer-specific survival. By this method, a tumor bud count of 10 corresponded to approximately 2.5 times risk of cancer-specific death. The interobserver agreement was good with weighted κ of 0.70 for 2 gastrointestinal pathologists over 121 random cases and 0.72 between all 6 pathologists for 20 random cases. Using an established method to assess budding on routine histologic stains, we have shown that a cutoff of 10 for high tumor budding is independently associated with a significantly worse prognosis. The reproducibility data provide support for the routine widespread implementation of tumor budding in clinical reports.

  18. A two-dimensional volatility basis set – Part 3: Prognostic modeling and NOx dependence

    Directory of Open Access Journals (Sweden)

    W. K. Chuang

    2016-01-01

    Full Text Available When NOx is introduced to organic emissions, aerosol production is sometimes, but not always, reduced. Under certain conditions, these interactions will instead increase aerosol concentrations. We expanded the two-dimensional volatility basis set (2D-VBS to include the effects of NOx on aerosol formation. This includes the formation of organonitrates, where the addition of a nitrate group contributes to a decrease of 2.5 orders of magnitude in volatility. With this refinement, we model outputs from experimental results, such as the atomic N : C ratio, organonitrate mass, and nitrate fragments in Aerosol Mass Spectrometer (AMS measurements. We also discuss the mathematical methods underlying the implementation of the 2D-VBS and provide the complete code in the Supplement. A developer version is available on Bitbucket, an online community repository.

  19. A two-dimensional volatility basis set - Part 3: Prognostic modeling and NOx dependence

    Science.gov (United States)

    Chuang, W. K.; Donahue, N. M.

    2016-01-01

    When NOx is introduced to organic emissions, aerosol production is sometimes, but not always, reduced. Under certain conditions, these interactions will instead increase aerosol concentrations. We expanded the two-dimensional volatility basis set (2D-VBS) to include the effects of NOx on aerosol formation. This includes the formation of organonitrates, where the addition of a nitrate group contributes to a decrease of 2.5 orders of magnitude in volatility. With this refinement, we model outputs from experimental results, such as the atomic N : C ratio, organonitrate mass, and nitrate fragments in Aerosol Mass Spectrometer (AMS) measurements. We also discuss the mathematical methods underlying the implementation of the 2D-VBS and provide the complete code in the Supplement. A developer version is available on Bitbucket, an online community repository.

  20. 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...

  1. HER2 amplification level is not a prognostic factor for HER2-positive breast cancer with trastuzumab-based adjuvant treatment: a systematic review and meta-analysis

    Science.gov (United States)

    Xu, Qian-Qian; Pan, Bo; Wang, Chang-Jun; Zhou, Yi-Dong; Mao, Feng; Lin, Yan; Guan, Jing-Hong; Shen, Song-Jie; Zhang, Xiao-Hui; Xu, Ya-Li; Zhong, Ying; Wang, Xue-Jing; Zhang, Yan-Na; Sun, Qiang

    2016-01-01

    Background Trastuzumab-based therapy is a standard, targeted treatment for HER2-positive breast cancer in the adjuvant setting. However, patients do not benefit equally from it and the association between HER2 amplification level and patients' survival remains controversial. A systematic review and meta-analysis was conducted by incorporating all available evidence to evaluate the association between disease free survival (DFS) and HER2 amplification level. Results Three cohort studies involving 1360 HER2-positive breast cancer patients stratified by HER2 amplification magnitude were eligible for meta-analysis. The combined HRs for DFS were 1.05 (95% CI: 0.80−1.36, p = 0.74) and 0.97 (95% CI: 0.73−1.29, p = 0.83) for HER2 gene copy number (GCN) and HER2/CEP 17 ratio. No evidence of heterogeneity or public bias was found. Methods Databases including PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL), were searched for eligible literature. HER2 amplification level was evaluated by fluorescence in situ hybridization (FISH) in terms of gene copy number (GCN) and HER2/CEP17 ratio. Hazard ratios (HRs) for DFS with 95% confidence interval (CI) according to the amplification level of HER2 were extracted. The outcomes were synthesized based on a fixed-effects model. Conclusions HER2 amplification level is not a prognostic factor for HER2-positive breast cancer with trastuzumab-based targeted therapy in the clinical adjuvant setting. PMID:27566580

  2. Basic critical care echocardiography by pulmonary fellows: learning trajectory and prognostic impact using a minimally resourced training model*.

    Science.gov (United States)

    See, Kay Choong; Ong, Venetia; Ng, Jeffrey; Tan, Rou An; Phua, Jason

    2014-10-01

    The spread of basic critical care echocardiography may be limited by training resources. Another barrier is the lack of information about the learning trajectory and prognostic impact of individual basic critical care echocardiography domains like acute cor pulmonale determination and left ventricular function estimation. We thus developed a minimally resourced training model and studied the latter outcomes. Prospective observational study. Twenty-bed medical ICU. Echocardiography-naive trainees enrolled in the first year of our Pulmonary Medicine Fellowship Program from September 2012 to September 2013. We described the learning trajectory in six basic critical care echocardiography domains (adequate views, pericardial effusion, acute cor pulmonale, left ventricular ejection fraction, mitral regurgitation, and inferior vena cava variability) and correlated abnormalities in selected basic critical care echocardiography domains with clinical outcomes (mortality and length of stay). Three-hundred forty-three basic critical care echocardiography scans were done for 318 patients by seven fellows (median of 40 scans per fellow; range, 34-105). Only one-third patients had normal basic critical care echocardiography studies. Accuracy in various basic critical care echocardiography domains was high (> 90%), especially beyond the first 30 examinations. Acute cor pulmonale was associated with ICU mortality when adjusted for Acute Physiology and Chronic Health Evaluation II score and presence of sepsis, whereas mitral regurgitation was associated with longer hospitalization only on univariate analysis. Basic critical care echocardiography training using minimal resources is feasible. New trainees can achieve reasonable competency in most basic critical care echocardiography domains after performing about 30 examinations within the first year. The relatively high prevalence of abnormalities and the significant association of acute cor pulmonale with ICU mortality support the

  3. Prognostic and symptomatic aspects of rapid eye movement sleep in a mouse model of posttraumatic stress disorder

    Directory of Open Access Journals (Sweden)

    Stephanie A. Polta

    2013-05-01

    Full Text Available Not every individual develops Posttraumatic Stress Disorder (PTSD after the exposure to a potentially traumatic event. Therefore, the identification of pre-existing risk factors and early diagnostic biomarkers is of high medical relevance. However, no objective biomarker has yet progressed into clinical practice. Sleep disturbances represent commonly reported complaints in PTSD patients. In particular, changes in rapid eye movement sleep (REMS properties are frequently observed in PTSD patients. Here, we examined in a mouse model of PTSD whether (1 mice developed REMS alterations after trauma and (2 whether REMS architecture before and/or shortly after trauma predicted the development of PTSD-like symptoms. We monitored sleep-wake behavior via combined EEG/EMG recordings immediately before (24 h pre, immediately after (0-48 h post and two months after exposure to an electric foot shock in male C57BL/6N mice (n=15. PTSD-like symptoms, including hyperarousal, contextual and generalized fear, were assessed one month post-trauma.Shocked mice showed early-onset and sustained elevation of REMS compared to non-shocked controls. In addition, REMS architecture before trauma was correlated with the intensity of acoustic startle responses, but not contextual fear, one month after trauma.Our data suggest REMS as prognostic (pre-trauma and symptomatic (post-trauma marker of PTSD-like symptoms in mice. Translated to the situation in humans, REMS may constitute a viable, objective and non-invasive biomarker in PTSD and other trauma-related psychiatric disorders, which could guide pharmacological interventions in humans at high risk.

  4. Realizing the Translational Potential of Telomere Length Variation as a Tissue Based Prognostic Marker for Prostate Cancer

    Science.gov (United States)

    2016-10-01

    pathologic prognostic factors are imperfect predictors of outcome in the men with clinically localized prostate cancer, the majority of men diagnosed...E, De Vivo I, Platz EA. Circulating leukocyte telomere length and risk of overall and aggressive prostate cancer. Br J Cancer. 2015 Feb 17;112(4

  5. Validation of prediction models based on lasso regression with multiply imputed data

    NARCIS (Netherlands)

    Musoro, Jammbe Z.; Zwinderman, Aeilko H.; Puhan, Milo A.; ter Riet, Gerben; Geskus, Ronald B.

    2014-01-01

    In prognostic studies, the lasso technique is attractive since it improves the quality of predictions by shrinking regression coefficients, compared to predictions based on a model fitted via unpenalized maximum likelihood. Since some coefficients are set to zero, parsimony is achieved as well. It

  6. 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.)

  7. Adverse prognostic impact of abnormal lesions detected by genome-wide single nucleotide polymorphism array-based karyotyping analysis in acute myeloid leukemia with normal karyotype.

    Science.gov (United States)

    Yi, Jun Ho; Huh, Jungwon; Kim, Hee-Jin; Kim, Sun-Hee; Kim, Hyeoung-Joon; Kim, Yeo-Kyeoung; Sohn, Sang Kyun; Moon, Joon Ho; Kim, Sung Hyun; Kim, Kyoung Ha; Won, Jong Ho; Mun, Yeung Chul; Kim, Hawk; Park, Jinny; Jung, Chul Won; Kim, Dong Hwan

    2011-12-10

    This study attempted to analyze the prognostic role of single nucleotide polymorphism array (SNP-A) -based karyotying in 133 patients with acute myeloid leukemia with normal karyotype (AML-NK), which presents with diverse clinical outcomes, thus requiring further stratification of patient subgroups according to their prognoses. A total of 133 patients with AML-NK confirmed by metaphase cytogenetics (MC) and fluorescent in situ hybridization analysis were included in this study. Analysis by Genome-Wide Human SNP 6.0 Array was performed by using DNAs derived from marrow samples at diagnosis. Forty-three patients (32.3%) had at least one abnormal SNP lesion that was not detected by MC. One hundred thirteen abnormal SNP lesions included 55 losses, 23 gains, and 35 copy-neutral losses of heterozygosity. Multivariate analyses showed that detection of abnormal SNP lesions by SNP-A karyotyping results in an unfavorable prognostic value for overall survival (hazard ratio [HR], 2.69; 95% CI, 1.50 to 4.82; P = .001); other significant prognostic factors included secondary AML (HR, 5.55; 95% CI, 1.80 to 17.14; P = .003), presence of the FLT3 mutation (HR, 3.17; 95% CI, 1.71 to 5.87; P abnormal SNP lesions detected by SNP-A karyotyping might indicate an adverse prognosis in patients with AML-NK, thus requiring a more sophisticated treatment strategy for improvement of treatment outcomes.

  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. Refining Prognosis in Lung Cancer: A Report on the Quality and Relevance of Clinical Prognostic Tools.

    Science.gov (United States)

    Mahar, Alyson L; Compton, Carolyn; McShane, Lisa M; Halabi, Susan; Asamura, Hisao; Rami-Porta, Ramon; Groome, Patti A

    2015-11-01

    Accurate, individualized prognostication for lung cancer patients requires the integration of standard patient and pathologic factors, biological, genetic, and other molecular characteristics of the tumor. Clinical prognostic tools aim to aggregate information on an individual patient to predict disease outcomes such as overall survival, but little is known about their clinical utility and accuracy in lung cancer. A systematic search of the scientific literature for clinical prognostic tools in lung cancer published from January 1, 1996 to January 27, 2015 was performed. In addition, web-based resources were searched. A priori criteria determined by the Molecular Modellers Working Group of the American Joint Committee on Cancer were used to investigate the quality and usefulness of tools. Criteria included clinical presentation, model development approaches, validation strategies, and performance metrics. Thirty-two prognostic tools were identified. Patients with metastases were the most frequently considered population in non-small-cell lung cancer. All tools for small-cell lung cancer covered that entire patient population. Included prognostic factors varied considerably across tools. Internal validity was not formally evaluated for most tools and only 11 were evaluated for external validity. Two key considerations were highlighted for tool development: identification of an explicit purpose related to a relevant clinical population and clear decision points and prioritized inclusion of established prognostic factors over emerging factors. Prognostic tools will contribute more meaningfully to the practice of personalized medicine if better study design and analysis approaches are used in their development and validation.

  10. 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.

  11. 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.

  12. Model Based Definition

    Science.gov (United States)

    Rowe, Sidney E.

    2010-01-01

    In September 2007, the Engineering Directorate at the Marshall Space Flight Center (MSFC) created the Design System Focus Team (DSFT). MSFC was responsible for the in-house design and development of the Ares 1 Upper Stage and the Engineering Directorate was preparing to deploy a new electronic Configuration Management and Data Management System with the Design Data Management System (DDMS) based upon a Commercial Off The Shelf (COTS) Product Data Management (PDM) System. The DSFT was to establish standardized CAD practices and a new data life cycle for design data. Of special interest here, the design teams were to implement Model Based Definition (MBD) in support of the Upper Stage manufacturing contract. It is noted that this MBD does use partially dimensioned drawings for auxiliary information to the model. The design data lifecycle implemented several new release states to be used prior to formal release that allowed the models to move through a flow of progressive maturity. The DSFT identified some 17 Lessons Learned as outcomes of the standards development, pathfinder deployments and initial application to the Upper Stage design completion. Some of the high value examples are reviewed.

  13. Predictive and prognostic value of CT based radiomics signature in locally advanced head and neck cancers patients treated with concurrent chemoradiotherapy or bioradiotherapy and its added value to Human Papillomavirus status.

    Science.gov (United States)

    Ou, Dan; Blanchard, Pierre; Rosellini, Silvia; Levy, Antonin; Nguyen, France; Leijenaar, Ralph T H; Garberis, Ingrid; Gorphe, Philippe; Bidault, François; Ferté, Charles; Robert, Charlotte; Casiraghi, Odile; Scoazec, Jean-Yves; Lambin, Philippe; Temam, Stephane; Deutsch, Eric; Tao, Yungan

    2017-08-01

    To explore prognostic and predictive value of radiomics in patients with locally advanced head and neck squamous cell carcinomas (LAHNSCC) treated with concurrent chemoradiotherapy (CRT) or bioradiotherapy (BRT). Data of 120 patients (CRT vs. BRT matched 2:1) were retrospectively analyzed. A total of 544 radiomics features of the primary tumor were extracted from radiotherapy planning computed tomography scans. Cox proportional hazards models were used to examine the association between survival and radiomics features with false discovery rate correction. The discriminatory performance was evaluated using receiver operating characteristic curve analysis. Multivariate analysis showed a 24-feature based signature significantly predicted for OS (HR=0.3, P=0.02) and progression-free survival (PFS) (HR=0.3, P=0.01). Combining the radiomics signature with p16 status showed a significant improvement of prognostic performance compared with p16 (AUC=0.78vs. AUC=0.64 at 5years, P=0.01) or radiomics signature (AUC=0.78vs. AUC=0.67, P=0.01) alone. When patients were stratified according to this combination, OS and PFS were significantly different according to the 4 sub-types (p16+ with low/high signature score; p16- with low/high signature score) (Padded value of radiomics features as prognostic and predictive biomarker in HNSCC treated with CRT/BRT. Moreover, the radiomics signature provided additional information to HPV/p16 status to further stratify patients. External validation of such findings is mandatory given the risk of overfitting. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. 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

  15. A multi-factorial genetic model for prognostic assessment of high risk melanoma patients receiving adjuvant interferon.

    Directory of Open Access Journals (Sweden)

    Ena Wang

    Full Text Available PURPOSE: IFNa was the first cytokine to demonstrate anti-tumor activity in advanced melanoma. Despite the ability of high-dose IFNa reducing relapse and mortality by up to 33%, large majority of patients experience side effects and toxicity which outweigh the benefits. The current study attempts to identify genetic markers likely to be associated with benefit from IFN-a2b treatment and predictive for survival. EXPERIMENTAL DESIGN: We tested the association of variants in FOXP3 microsatellites, CTLA4 SNPs and HLA genotype in 284 melanoma patients and their association with prognosis and survival of melanoma patients who received IFNa adjuvant therapy. RESULTS: Univariate survival analysis suggested that patients bearing either the DRB1*15 or HLA-Cw7 allele suffered worse OS while patients bearing either HLA-Cw6 or HLA-B44 enjoyed better OS. DRB1*15 positive patients suffered also worse RFS and conversely HLA-Cw6 positive patients had better RFS. Multivariate analysis revealed that a five-marker genotyping signature was prognostic of OS independent of disease stage. In the multivariate Cox regression model, HLA-B38 (p = 0.021, HLA-C15 (p = 0.025, HLA-C3 (p = 0.014, DRB1*15 (p = 0.005 and CT60*G/G (0.081 were significantly associated with OS with risk ratio of 0.097 (95% CI, 0.013-0.709, 0.387 (95% CI, 0.169-0.889, 0.449 (95% CI, 0.237-0.851, 1.948 (95% CI, 1.221-3.109 and 1.484 (95% IC, 0.953-2.312 respectively. CONCLUSION: These results suggest that gene polymorphisms relevant to a biological occurrence are more likely to be informative when studied in concert to address potential redundant or conflicting functions that may limit each gene individual contribution. The five markers identified here exemplify this concept though prospective validation in independent cohorts is needed.

  16. External validation of a proposed prognostic model for the prediction of 1-year postoperative eGFR after living donor nephrectomy.

    Science.gov (United States)

    Kulik, Ulf; Gwiasda, Jill; Oldhafer, Felix; Kaltenborn, Alexander; Arelin, Viktor; Gueler, Faikah; Richter, Nicolas; Klempnauer, Juergen; Schrem, Harald

    2017-11-01

    The goal of this study was to externally validate the recently proposed prognostic model for the prediction of estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m(2) 1 year after living donor nephrectomy. 130 living kidney donors (median age at donation 52.3 years, range 24.7-75.6 years) were investigated before and after donation between March 2000 and April 2016. Preoperative eGFR values varied between 61.7 and 148.4 ml/min (mean: 89, median: 88). Observed eGFR 1 year after transplantation (±45 days) ranged between 36.3 and 97.1 ml/min (mean: 55, median: 53). 70.8% of donors displayed eGFR values < 60 ml/min 1 year after donation. Predicted eGFR 1 year after donation was determined using the prognostic model proposed by Benoit et al. (Int Urol Nephrol 49(5):793-801. doi: 10.1007/s11255-017-1559-1 , 2017): postoperative eGFR ml/min/1.73 m(2) = 31.71 + (0.521 × eGFR in ml/min prior to donation -0.314 × Age in years at donation). Pearson correlation and receiver operating characteristics curve (ROC-curve) were used to assess external validity of the proposed prognostic model to predict postoperative eGFR in ml/min and eGFR < 60 ml/min. The correlation between predicted and observed eGFR 1 year after donation was significant (p < 0.001; R (2) = 0.594). The area under the ROC-curve (AUROC) demonstrated a high sensitivity and specificity for predicted eGFR values < 60 ml/min (AUROC = 0.866). The proposed prognostic model for the prediction of postoperative eGFR was successfully validated in our cohort. We therefore consider the model as generally applicable.

  17. Feasibility of transitioning from APACHE II to SAPS III as prognostic model in a Brazilian general intensive care unit. A retrospective study.

    Science.gov (United States)

    Serpa Neto, Ary; Assunção, Murillo Santucci Cesar de; Pardini, Andréia; Silva, Eliézer

    2015-01-01

    Prognostic models reflect the population characteristics of the countries from which they originate. Predictive models should be customized to fit the general population where they will be used. The aim here was to perform external validation on two predictive models and compare their performance in a mixed population of critically ill patients in Brazil. Retrospective study in a Brazilian general intensive care unit (ICU). This was a retrospective review of all patients admitted to a 41-bed mixed ICU from August 2011 to September 2012. Calibration (assessed using the Hosmer-Lemeshow goodness-of-fit test) and discrimination (assessed using area under the curve) of APACHE II and SAPS III were compared. The standardized mortality ratio (SMR) was calculated by dividing the number of observed deaths by the number of expected deaths. A total of 3,333 ICU patients were enrolled. The Hosmer-Lemeshow goodness-of-fit test showed good calibration for all models in relation to hospital mortality. For in-hospital mortality there was a worse fit for APACHE II in clinical patients. Discrimination was better for SAPS III for in-ICU and in-hospital mortality (P = 0.042). The SMRs for the whole population were 0.27 (confidence interval [CI]: 0.23 - 0.33) for APACHE II and 0.28 (CI: 0.22 - 0.36) for SAPS III. In this group of critically ill patients, SAPS III was a better prognostic score, with higher discrimination and calibration power.

  18. Development of a model to predict breast cancer survival using data from the National Cancer Data Base.

    Science.gov (United States)

    Asare, Elliot A; Liu, Lei; Hess, Kenneth R; Gordon, Elisa J; Paruch, Jennifer L; Palis, Bryan; Dahlke, Allison R; McCabe, Ryan; Cohen, Mark E; Winchester, David P; Bilimoria, Karl Y

    2016-02-01

    With the large amounts of data on patient, tumor, and treatment factors available to clinicians, it has become critically important to harness this information to guide clinicians in discussing a patient's prognosis. However, no widely accepted survival calculator is available that uses national data and includes multiple prognostic factors. Our objective was to develop a model for predicting survival among patients diagnosed with breast cancer using the National Cancer Data Base (NCDB) to serve as a prototype for the Commission on Cancer's "Cancer Survival Prognostic Calculator." A retrospective cohort of patients diagnosed with breast cancer (2003-2006) in the NCDB was included. A multivariable Cox proportional hazards regression model to predict overall survival was developed. Model discrimination by 10-fold internal cross-validation and calibration was assessed. There were 296,284 patients for model development and internal validation. The c-index for the 10-fold cross-validation ranged from 0.779 to 0.788 after inclusion of all available pertinent prognostic factors. A plot of the observed versus predicted 5 year overall survival showed minimal deviation from the reference line. This breast cancer survival prognostic model to be used as a prototype for building the Commission on Cancer's "Cancer Survival Prognostic Calculator" will offer patients and clinicians an objective opportunity to estimate personalized long-term survival based on patient demographic characteristics, tumor factors, and treatment delivered. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. 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

  20. Prognostic molecular markers in cancer - quo vadis?

    Science.gov (United States)

    Søland, Tine M; Brusevold, Ingvild J

    2013-09-01

    Despite the tremendous number of studies of prognostic molecular markers in cancer, only a few such markers have entered clinical practise. The lack of clinical prognostic markers clearly reflects limitations in or an inappropriate approach to prognostic studies. This situation should be of great concern for the research community, clinicians and patients. In the present review, we evaluate immunohistochemical prognostic marker studies in oral squamous cell carcinomas (OSCC) from 2006 to 2012. We comment upon general issues such as study design, assay methods and statistical methods, applicable to prognostic marker studies irrespective of cancer type. The three most frequently studied markers in OSCC are reviewed. Our analysis revealed that most new molecular markers are reported only once. To draw conclusions of clinical relevance based on the few markers that appeared in more than one study was problematic due to between-study heterogeneity. Currently, much valuable tissue material, time and money are wasted on irrelevant studies. © 2013 John Wiley & Sons Ltd.

  1. Prognostic factors of overall survival and cancer-specific survival in patients with resected early-stage rectal adenocarcinoma: a SEER-based study.

    Science.gov (United States)

    Lee, Ko-Chao; Chung, Kuan-Chih; Chen, Hong-Hwa; Liu, Chia-Cheng; Lu, Chien-Chang

    2017-12-01

    The benefits of radiotherapy for colorectal cancer are well documented, but the impact of adjuvant radiotherapy on early-stage rectal adenocarcinoma remains unclear. This study aimed to identify predictors of overall survival (OS) and cancer-specific survival (CSS) in patients with stage II rectal adenocarcinoma treated with preoperative or postoperative radiation therapy. Patients with early-stage rectal adenocarcinoma in the postoperative state were identified using the Surveillance, Epidemiology, and End Results database. The primary endpoints were OS and overall CSS. Stage IIA patients without radiotherapy had significantly lower OS and CSS compared with those who received radiation before or after surgery. Stage IIB patients with radiotherapy before surgery had significantly higher OS and CSS compared with patients in the postoperative or no radiotherapy groups. Patients with signet ring cell carcinoma had the poorest OS among all the groups. Multivariable analysis showed that ethnicity (HR, 0.388, p=0.006) and radiation before surgery (HR, 0.614, p=0.006) were favorable prognostic factors for OS, while age (HR, 1.064, pstage IIB (HR, 3.011, p=0.011), and more than one tumor deposit (TD) (HR, 2.300, p=0.001) were unfavorable prognostic factors for OS. Old age (HR, 1.047, pstage IIB (HR, 8.619, p=0.005), circumferential resection margin between 0.1 mm and 10 mm (HR, 1.529, p=0.039), and more than one TD (HR, 2.688, p=0.001) were unfavorable prognostic factors for CSS. This population-based study identified predictors of OS and CSS in patients with early-stage resected rectal adenocarcinoma, which may help to guide future management of this patient population. © American Federation for Medical Research (unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  2. K-Ras gene mutation status as a prognostic and predictive factor in patients with colorectal cancer undergoing irinotecan- or oxaliplatin-based chemotherapy.

    Science.gov (United States)

    Stec, Rafał; Bodnar, Lubomir; Charkiewicz, Radosław; Korniluk, Jan; Rokita, Marta; Smoter, Marta; Ciechowicz, Marzena; Chyczewski, Lech; Nikliński, Jacek; Kozłowski, Wojciech; Szczylik, Cezary

    2012-11-01

    CRC caused more than 600,000 estimated deaths in 2008. Dysregulated signaling through the RAS/RAF/mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) signaling pathway due to mutations in K-Ras and B-Raf are common events in CRC. Incidence of mutations in codons 12 and 13 of K-Ras and exons 11 and 15 of B-Raf were analyzed in amplified PCR products from primary tumors of 273 patients with CRC, and their prognostic and predictive significance was assessed. The prognostic role of clinical and pathological factors was also examined. K-Ras mutations were present in 89 patients (32.6%), of whom 76 (85.4%) had mutations in codon 12 and 10 (11.2%) had mutations in codon 13. B-Raf gene mutations were present in 17 patients (6.9%), of whom 6 (35.3%) had mutations in exon 15. Multivariate analysis revealed a predictive significance for K-Ras mutations with respect to time to progression in patients treated with irinotecan and oxaliplatin as first-line chemotherapy. There was no predictive significance for B-Raf gene mutation status in these patients. The following risk factors were found to affect overall survival (OS) rates: primary tumor location, lymph node involvement grade, carcinoembryonic antigen (CEA) level before treatment, and performance status according to WHO criteria. Based on the results of this study, K-Ras mutation status may be a suitable indicator of patient eligibility and a prognostic indicator for responsiveness to anti-EGFR therapy alone, or in combination with chemotherapy. Also, K-Ras mutation status may predict time to progression in patients treated with irinotecan and oxaliplatin.

  3. 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

    2017-11-10

    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

  4. Preoperative multivariable prognostic models for prediction of survival and major complications following surgical resection of renal cell carcinoma with suprahepatic caval tumor thrombus.

    Science.gov (United States)

    Haddad, Ahmed Q; Leibovich, Bradley C; Abel, Edwin Jason; Luo, Jun-Hang; Krabbe, Laura-Maria; Thompson, Robert Houston; Heckman, Jennifer E; Merrill, Megan M; Gayed, Bishoy A; Sagalowsky, Arthur I; Boorjian, Stephen A; Wood, Christopher G; Margulis, Vitaly

    2015-09-01

    Surgical resection for renal cell carcinoma (RCC) with suprahepatic inferior vena cava tumor thrombus is associated with significant morbidity, yet there are currently no tools for preoperative prognostic evaluation. Our goal was to develop a preoperative multivariable model for prediction of survival and risk of major complications in patients with suprahepatic thrombi. We identified patients who underwent surgery for RCC with suprahepatic tumor thrombus extension from 2000 to 2013 at 4 tertiary centers. A Cox proportional hazard model was used for analysis of overall survival (OS) and logistic regression was used for major complications within 90 days of surgery (Clavien ≥ 3A). Nomograms were internally calibrated by bootstrap resampling method. A total of 49 patients with level III thrombus and 83 patients with level IV thrombus were identified. During median follow-up of 24.5 months, 80 patients (60.6%) died and 46 patients (34.8%) experienced major complication. Independent prognostic factors for OS included distant metastases at presentation (hazard ratio = 2.52, P = 0.002) and Eastern Cooperative Oncology Group (ECOG) performance status (hazard ratio = 1.84, Pmodels for the prediction of survival and major complications in patients with RCC who have a suprahepatic inferior vena cava thrombus. If externally validated, these tools may aid in patient selection for surgical intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Anticipating the clinical use of prognostic gene expression-based tests for colon cancer stage II and III: is Godot finally arriving?

    Science.gov (United States)

    Sveen, Anita; Nesbakken, Arild; Ågesen, Trude H; Guren, Marianne G; Tveit, Kjell M; Skotheim, Rolf I; Lothe, Ragnhild A

    2013-12-15

    According to current recommendations for adjuvant treatment, patients with colon cancer stage II are not routinely offered chemotherapy, unless considered to have a high risk of relapse based on specific clinicopathological parameters. Following these criteria, it is challenging to identify the subgroup of patients that will benefit the most from adjuvant treatment. Contrarily, patients with colon cancer stage III are routinely offered chemotherapy, but due to expected adverse effects and frailty, elderly patients are often excluded from standard protocols. Colon cancer is a disease of the elderly and accordingly, there is a large subgroup of patients for which guidelines for adjuvant treatment remain less clear. In these two clinical settings, improved risk stratification has great potential impact on patient care, anticipating that high-risk patients will benefit from chemotherapy. However, microsatellite instability is the only molecular prognostic marker recommended for clinical use. In this perspective, we provide an updated view on the status and clinical potential of the many proposed prognostic gene expression-based tests for colon cancer stage II and III. The main limitation for clinical implementation is lack of prospective validation. For patients with stage II, highly promising tests have been identified and clinical trials are ongoing. For elderly patients with stage III, the value of such tests has received less focus, but promising early results have been shown. Although awaiting results from prospective trials, improved risk assessment for patients with stage II and III is likely to be achieved in the foreseeable future. ©2013 AACR.

  6. Congress of Neurological Surgeons Systematic Review and Evidence-Based Guidelines on Pathological Methods and Prognostic Factors in Vestibular Schwannomas.

    Science.gov (United States)

    Sughrue, Michael E; Fung, Kar-Ming; Van Gompel, Jamie J; Peterson, Jo Elle G; Olson, Jeffrey J

    2017-12-20

    Adults diagnosed with vestibular schwannomas. What is the prognostic significance of Antoni A vs B histologic patterns in vestibular schwannomas? No recommendations can be made due to a lack of adequate data. What is the prognostic significance of mitotic figures seen in vestibular schwannoma specimens? No recommendations can be made due to a lack of adequate data. Are there other light microscopic features that predict clinical behavior of vestibular schwannomas? No recommendations can be made due to a lack of adequate data. Does the KI-67 labeling index predict clinical behavior of vestibular schwannomas? No recommendations can be made due to a lack of adequate data. Does the proliferating cell nuclear antigen labeling index predict clinical behavior of vestibular schwannomas? No recommendations can be made due to a lack of adequate data. Does degree of vascular endothelial growth factor expression predict clinical behavior of vestibular schwannomas? No recommendations can be made due to a lack of adequate data.  The full guideline can be found at: https://www.cns.org/guidelines/guidelines-management-patients-vestibular-schwannoma/chapter_6.

  7. 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...

  8. BRCA1 mRNA expression as a predictive and prognostic marker in advanced esophageal squamous cell carcinoma treated with cisplatin- or docetaxel-based chemotherapy/chemoradiotherapy.

    Directory of Open Access Journals (Sweden)

    Yong Gao

    Full Text Available BACKGROUND: The molecular backgrounds that determine therapeutic effectiveness in esophageal cancer remain largely unknown. Breast cancer susceptibility gene 1 (BRCA1 expression has been found to switch the response to cisplatin- or paclitaxel-based chemotherapy. It remains unclear how variations in BRCA1 expression influence clinical outcomes in esophageal cancer. PATIENTS AND METHODS: Quantitative real-time polymerase chain reaction (qPCR was performed to examine BRCA1 mRNA expressions in paraffin-embedded specimens from 144 patients with advanced or metastatic esophageal squamous cell carcinoma who received cisplatin- or docetaxel-based first-line treatments. RESULTS: Low BRCA1 mRNA expression correlated with increased response rate (RR; P = 0.025 and 0.017, respectively and median overall survival (mOS; P = 0.002 and P<0.001, respectively in cisplatin-based chemotherapy or chemoradiotherapy group and also correlated with decreased RR (P = 0.017 and 0.024, respectively and mOS (both P<0.001 in docetaxel-based chemotherapy or chemoradiotherapy group. Multivariate analysis revealed that low BRCA1 expression was an independent prognostic factor in cisplatin-based chemotherapy (HR 0.29; 95%CI 0.12-0.71; P = 0.007 or chemoradiotherapy (HR 0.12; 95%CI 0.04-0.37; P<0.001 group and higher risk for mortality in docetaxel-based chemotherapy (HR 5.02; 95%CI 2.05-12.28; P<0.001 or chemoradiotherapy (HR 7.02; 95%CI 2.37-27.77; P<0.001 group. CONCLUSIONS: BRCA1 mRNA expression could be used as a predictive and prognostic marker in esophageal cancer who underwent first-line cisplatin- or docetaxel-based treatments.

  9. 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...

  10. 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...

  11. Prognostic model to identify patients with myelofibrosis at the highest risk of transformation to acute myeloid leukemia.

    Science.gov (United States)

    Quintás-Cardama, Alfonso; Kantarjian, Hagop; Pierce, Sherry; Cortes, Jorge; Verstovsek, Srdan

    2013-06-01

    Some patients with myelofibrosis (MF) progress to acute myeloid leukemia (AML). Current prognostic tools were not devised to assess risk of AML transformation. Multivariate analysis in 649 patients followed for a median of 19 months (range, 1-180 months). We identified age > 60 (P = .004; hazard ratio [HR], 1.63), platelets HR, 1.62), bone marrow blast > 10% (P = .002; HR, 2.18), high-risk karyotype (P HR, 2.44), transfusion dependency (P HR, 2.64), performance status > 1 (P = .003; HR, 1.47), lactate dehydrogenase > 2000 U/L (P HR, 1.62), previous hydroxyurea (P HR, 1.69), and male sex (P = .005; HR, 1.41) as independent poor prognostic factors for survival. Using the same baseline variables we identified bone marrow blasts >10% and worst karyotype as independent risk factors for AML transformation. Patients with 1 or both of these risk factors (n = 80; 12%) had a median survival of 10 months and a 1-year AML transformation rate of 13% (2% if none of those factors, P = .001). We have identified risk factors that predict high risk of transformation from MF to AML. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. 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.

  13. Prognostic Factors and a New Prognostic Index Model for Children and Adolescents with Hodgkin’s Lymphoma Who Underwent Autologous Hematopoietic Stem Cell Transplantation: A Multicenter Study of the Turkish Pediatric Bone Marrow Transplantation Study

    Directory of Open Access Journals (Sweden)

    Vural Kesik

    2016-12-01

    Full Text Available Objective: The prognostic factors and a new childhood prognostic index after autologous hematopoietic stem cell transplantation (AHSCT in patients with relapsed/refractory Hodgkin’s lymphoma (HL were evaluated. Materials and Methods: The prognostic factors of 61 patients who underwent AHSCT between January 1990 and December 2014 were evaluated. In addition, the Age-Adjusted International Prognostic Index and the Childhood International Prognostic Index (CIPI were evaluated for their impact on prognosis. Results: The median age of the 61 patients was 14.8 years (minimummaximum: 5-20 years at the time of AHSCT. There were single relapses in 28 patients, ≥2 relapses in eight patients, and refractory disease in 25 patients. The chemosensitivity/chemorefractory ratio was 36/25. No pretransplant radiotherapy, no remission at the time of transplantation, posttransplant white blood cell count over 10x103/ μL, posttransplant positron emission tomography positivity at day 100, and serum albumin of <2.5 g/dL at diagnosis were correlated with progression-free survival. No remission at the time of transplantation, bone marrow positivity at diagnosis, and relapse after AHSCT were significant parameters for overall survival. Conclusion: The major factors affecting the progression-free and overall survival were clearly demonstrated. A CIPI that uses a lactate dehydrogenase level of 500 IU/L worked well for estimating the prognosis. We recommend AHSCT at first complete remission for relapsed cases, and it should also be taken into consideration for patients with high prognostic scores at diagnosis.

  14. 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.

  15. Magnetic resonance imaging (MRI) and prognostication in neonatal hypoxic-ischemic injury: a vignette-based study of Canadian specialty physicians.

    Science.gov (United States)

    Bell, Emily; Rasmussen, Lisa Anne; Mazer, Barbara; Shevell, Michael; Miller, Steven P; Synnes, Anne; Yager, Jerome Y; Majnemer, Annette; Muhajarine, Nazeem; Chouinard, Isabelle; Racine, Eric

    2015-02-01

    Magnetic resonance imaging (MRI) could improve prognostication in neonatal brain injury; however, factors beyond technical or scientific refinement may impact its use and interpretation. We surveyed Canadian neonatologists and pediatric neurologists using general and vignette-based questions about the use of MRI for prognostication in neonates with hypoxic-ischemic injury. There was inter- and intra-vignette variability in prognosis and in ratings about the usefulness of MRI. Severity of predicted outcome correlated with certainty about the outcome. A majority of physicians endorsed using MRI results in discussing prognosis with families, and most suggested that MRI results contribute to end-of-life decisions. Participating neonatologists, when compared to participating pediatric neurologists, had significantly less confidence in the interpretation of MRI by colleagues in neurology and radiology. Further investigation is needed to understand the complexity of MRI and of its application. Potential gaps relative to our understanding of the ethical importance of these findings should be addressed. © The Author(s) 2014.

  16. Model-based distance sampling

    OpenAIRE

    Buckland, Stephen Terrence; Oedekoven, Cornelia Sabrina; Borchers, David Louis

    2015-01-01

    CSO was part-funded by EPSRC/NERC Grant EP/1000917/1. Conventional distance sampling adopts a mixed approach, using model-based methods for the detection process, and design-based methods to estimate animal abundance in the study region, given estimated probabilities of detection. In recent years, there has been increasing interest in fully model-based methods. Model-based methods are less robust for estimating animal abundance than conventional methods, but offer several advantages: they ...

  17. Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy

    OpenAIRE

    Darb-Esfahani, Silvia; Loibl, Sibylle; Müller, Berit M; Roller, Marc; Denkert, Carsten; Komor, Martina; Schlüns, Karsten; Blohmer, Jens Uwe; Budczies, Jan; Gerber, Bernd; Noske, Aurelia; du Bois, Andreas; Weichert, Wilko; Jackisch, Christian; Dietel, Manfred

    2009-01-01

    Introduction: Reliable predictive and prognostic markers for routine diagnostic purposes are needed for breast cancer patients treated with neoadjuvant chemotherapy. We evaluated protein biomarkers in a cohort of 116 participants of the GeparDuo study on anthracycline/taxane-based neoadjuvant chemotherapy for operable breast cancer to test for associations with pathological complete response (pCR) and disease-free survival (DFS). Particularly, we evaluated if interactions between hormone rece...

  18. Method for gesture based modeling

    DEFF Research Database (Denmark)

    2006-01-01

    A computer program based method is described for creating models using gestures. On an input device, such as an electronic whiteboard, a user draws a gesture which is recognized by a computer program and interpreted relative to a predetermined meta-model. Based on the interpretation, an algorithm...... is assigned to the gesture drawn by the user. The executed algorithm may, for example, consist in creating a new model element, modifying an existing model element, or deleting an existing model element....

  19. A Novel Inflammation- and Nutrition-Based Prognostic System for Patients with Laryngeal Squamous Cell Carcinoma: Combination of Red Blood Cell Distribution Width and Body Mass Index (COR-BMI.

    Directory of Open Access Journals (Sweden)

    Yan Fu

    Full Text Available Laryngeal squamous cell carcinoma (LSCC is a head and neck cancer type. In this study, we introduced a novel inflammation- and nutrition-based prognostic system, referred to as COR-BMI (Combination of red blood cell distribution width and body mass index, for LSCC patients.A total of 807 LSCC patients (784 male and 23 female, 22-87 y of age who underwent surgery were enrolled in this retrospective cohort study. The patients were stratified by COR-BMI into three groups: COR-BMI (0 (RDW ≤ 13.1 and BMI ≥ 25; COR-BMI (1 (RDW ≤ 13.1 and BMI 13.1 and 18.5 ≤ BMI 13.1 and BMI < 18.5. Cox regression models were used to investigate the association between COR-BMI and cancer-specific survival (CSS rate among LSCC patients.The 5-y, 10-y, and 15-y CSS rates were 71.6%, 60.1%, and 55.4%, respectively. There were significant differences among the COR-BMI groups in age (< 60 versus ≥ 60 y; P = 0.005 and T stage (T1, T2, T3, or T4; P = 0.013. Based on the results, COR-BMI (1 versus 0: HR = 1.76; 95% CI = 0.98-3.15; 2 versus 0: HR = 2.91; 95% CI = 1.53-5.54, P = 0.001 was a significant independent predictor of CSS.COR-BMI is a novel inflammation- and nutrition-based prognostic system, which could predict long-term survival in LSCC patients who underwent surgery.

  20. 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…

  1. Comparison of Myelodysplastic Syndrome Prognostic Scoring Systems

    Science.gov (United States)

    Bektaş, Özlen; Üner, Ayşegül; Eliaçık, Eylem; Uz, Burak; Işık, Ayşe; Etgül, Sezgin; Bozkurt, Süreyya; Haznedaroğlu, İbrahim Celalettin; Göker, Hakan; Sayınalp, Nilgün; Aksu, Salih; Demiroğlu, Haluk; Özcebe, Osman İlhami; Büyükaşık, Yahya

    2016-01-01

    Objective: Myelodysplastic syndrome (MDS) is a clonal hematopoietic stem cell disease. Patients are at risk of developing cytopenias or progression to acute myeloid leukemia. Different classifications and prognostic scoring systems have been developed. The aim of this study was to compare the different prognostic scoring systems. Materials and Methods: One hundred and one patients who were diagnosed with primary MDS in 2003-2011 in a tertiary care university hospital’s hematology department were included in the study. Results: As the International Prognostic Scoring System (IPSS), World Health Organization Classification-Based Prognostic Scoring System (WPSS), MD Anderson Prognostic Scoring System (MPSS), and revised IPSS (IPSS-R) risk categories increased, leukemia-free survival and overall survival decreased (p<0.001). When the IPSS, WPSS, MPSS, and IPSS-R prognostic systems were compared by Cox regression analysis, the WPSS was the best in predicting leukemia-free survival (p<0.001), and the WPSS (p<0.001) and IPSS-R (p=0.037) were better in predicting overall survival. Conclusion: All 4 prognostic systems were successful in predicting overall survival and leukemia-free survival (p<0.001). The WPSS was found to be the best predictor for leukemia-free survival, while the WPSS and IPSS-R were found to be the best predictors for overall survival. PMID:26376664

  2. Comparison of Myelodysplastic Syndrome Prognostic Scoring Systems

    Directory of Open Access Journals (Sweden)

    Özlen Bektaş

    2016-05-01

    Full Text Available Objective: Myelodysplastic syndrome (MDS is a clonal hematopoietic stem cell disease. Patients are at risk of developing cytopenias or progression to acute myeloid leukemia. Different classifications and prognostic scoring systems have been developed. The aim of this study was to compare the different prognostic scoring systems. Materials and Methods: One hundred and one patients who were diagnosed with primary MDS in 2003-2011 in a tertiary care university hospital’s hematology department were included in the study. Results: As the International Prognostic Scoring System (IPSS, World Health Organization Classification-Based Prognostic Scoring System (WPSS, MD Anderson Prognostic Scoring System (MPSS, and revised IPSS (IPSS-R risk categories increased, leukemia-free survival and overall survival decreased (p<0.001. When the IPSS, WPSS, MPSS, and IPSS-R prognostic systems were compared by Cox regression analysis, the WPSS was the best in predicting leukemia-free survival (p<0.001, and the WPSS (p<0.001 and IPSS-R (p=0.037 were better in predicting overall survival. Conclusion: All 4 prognostic systems were successful in predicting overall survival and leukemia-free survival (p<0.001. The WPSS was found to be the best predictor for leukemia-free survival, while the WPSS and IPSS-R were found to be the best predictors for overall survival.

  3. The prognostic value of the plasma N-terminal pro-brain natriuretic peptide level on all-cause death and major cardiovascular events in a community-based population

    Directory of Open Access Journals (Sweden)

    Zhu Q

    2016-02-01

    Full Text Available Qiwei Zhu,1 Wenkai Xiao,1,* Yongyi Bai,1,* Ping Ye,1 Leiming Luo,1 Peng Gao,1 Hongmei Wu,1 Jie Bai2 1Department of Geriatric Cardiology, 2Department of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, People’s Republic of China *These authors contributed equally to this work Background: Despite growing evidence that N-terminal pro-brain natriuretic peptide (NT-proBNP has an important prognostic value for patients with cardiovascular disease, chronic kidney disease, etc, the prognostic significance of NT-proBNP levels in the general population has not been established. The aim of this study was to evaluate the clinical significance of NT-proBNP in a community population.Methods: This is a community-based prospective survey of residents from two communities in Beijing conducted for a routine health status checkup. Out of 1,860 individuals who were eligible for inclusion from 2007 to 2009, 1,499 completed a follow-up and were assessed for the prognostic value of NT-proBNP in 2013. A questionnaire was used for end point events. Anthropometry and blood pressure were measured. Plasma NT-proBNP, creatinine, lipids, and glucose were determined.Results: A total of 1,499 subjects with complete data were included in the analysis. Participants were divided into four groups according to baseline NT-proBNP levels (quartile 1, <19.8 pg/mL; quartile 2, 19.8–41.6 pg/mL; quartile 3, 41.7–81.8 pg/mL; quartile 4, ≥81.9 pg/mL. During a median 4.8-year follow-up period, the all-cause mortality rate rose from 0.8% in the lowest concentration NT-proBNP group (<19.8 pg/mL to 7.8% in the highest NT-proBNP group (≥81.9 pg/mL; P<0.001. The incidence of major adverse cardiovascular events (MACEs increased from 3.1% in the lowest NT-proBNP group to 18.9% in the highest group (P<0.001. Individuals in the highest NT-proBNP group (≥81.9 pg/mL were associated with higher risk of all-cause death and MACEs compared with the lowest NT-proBNP group

  4. 心力衰竭预后评估模型与评价%Different prognostic models of heart failure and their evaluation

    Institute of Scientific and Technical Information of China (English)

    黄樱硕; 孙颖

    2013-01-01

    Heart failure is the end-stage of various cardiomyopathy, and is of characteristics with difficult therapeutic options, poor prognosis and very high mortality. Many studies reported a wide variety of risk factors associated to heart failure. So, clinical physicians have to face some important decisions, such as, optimal therapeutic option, left ventricular assisted devices, and priority groups for heart transplantation, and prognosis and death risk. Though prognostic models of heart failure are helpful to assess prognosis, different models have their own characteristics, and are suitable for different population. This article introduced several prognostic models of heart failure.%心力衰竭是各种器质性心脏病的终末阶段,其治疗难度大、预后差、死亡率高。已有很多研究分析了心力衰竭的危险因素。选择正确的治疗措施,识别左室辅助装置及心脏移植的优先人群,正确判断预后及死亡风险,是临床医师面临的重要问题。心力衰竭的风险预后模型有助于评估预后,但现有模型各有特点,适用于不同人群。本文分别介绍心力衰竭的几种预后评估模型。

  5. 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...

  6. Diagnosis and prognostication of ductal adenocarcinomas of the pancreas based on genome-wide DNA methylation profiling by bacterial artificial chromosome array-based methylated CpG island amplification.

    Science.gov (United States)

    Gotoh, Masahiro; Arai, Eri; Wakai-Ushijima, Saori; Hiraoka, Nobuyoshi; Kosuge, Tomoo; Hosoda, Fumie; Shibata, Tatsuhiro; Kondo, Tadashi; Yokoi, Sana; Imoto, Issei; Inazawa, Johji; Kanai, Yae

    2011-01-01

    To establish diagnostic criteria for ductal adenocarcinomas of the pancreas (PCs), bacterial artificial chromosome (BAC) array-based methylated CpG island amplification was performed using 139 tissue samples. Twelve BAC clones, for which DNA methylation status was able to discriminate cancerous tissue (T) from noncancerous pancreatic tissue in the learning cohort with a specificity of 100%, were identified. Using criteria that combined the 12 BAC clones, T-samples were diagnosed as cancers with 100% sensitivity and specificity in both the learning and validation cohorts. DNA methylation status on 11 of the BAC clones, which was able to discriminate patients showing early relapse from those with no relapse in the learning cohort with 100% specificity, was correlated with the recurrence-free and overall survival rates in the validation cohort and was an independent prognostic factor by multivariate analysis. Genome-wide DNA methylation profiling may provide optimal diagnostic markers and prognostic indicators for patients with PCs.

  7. Diagnosis and Prognostication of Ductal Adenocarcinomas of the Pancreas Based on Genome-Wide DNA Methylation Profiling by Bacterial Artificial Chromosome Array-Based Methylated CpG Island Amplification

    Directory of Open Access Journals (Sweden)

    Masahiro Gotoh

    2011-01-01

    Full Text Available To establish diagnostic criteria for ductal adenocarcinomas of the pancreas (PCs, bacterial artificial chromosome (BAC array-based methylated CpG island amplification was performed using 139 tissue samples. Twelve BAC clones, for which DNA methylation status was able to discriminate cancerous tissue (T from noncancerous pancreatic tissue in the learning cohort with a specificity of 100%, were identified. Using criteria that combined the 12 BAC clones, T-samples were diagnosed as cancers with 100% sensitivity and specificity in both the learning and validation cohorts. DNA methylation status on 11 of the BAC clones, which was able to discriminate patients showing early relapse from those with no relapse in the learning cohort with 100% specificity, was correlated with the recurrence-free and overall survival rates in the validation cohort and was an independent prognostic factor by multivariate analysis. Genome-wide DNA methylation profiling may provide optimal diagnostic markers and prognostic indicators for patients with PCs.

  8. Critical Assessment of Clinical Prognostic Tools in Melanoma.

    Science.gov (United States)

    Mahar, Alyson L; Compton, Carolyn; Halabi, Susan; Hess, Kenneth R; Gershenwald, Jeffrey E; Scolyer, Richard A; Groome, Patti A

    2016-09-01

    The 7th edition American Joint Committee on Cancer (AJCC) melanoma staging system classifies patients according to prognosis. Significant within-stage heterogeneity remains and the inclusion of additional clinicopathologic and other host- and tumor-based prognostic factors have been proposed. Clinical prognostic tools have been developed for use in clinical practice to refine survival estimates. Little is known about the comparative features of tools in melanoma. We performed a systematic search of the scientific published literature for clinical prognostic tools in melanoma and web-based resources. A priori criteria were used to evaluate their quality and clinical relevance, and included intended clinical use, model development approaches, validation strategies, and performance metrics. We identified 17 clinical prognostic tools for primary cutaneous melanoma. Patients with stages I-III and T1 or thin melanoma were the most frequently considered populations. Seventy-five percent of tools were developed using data collected from patients diagnosed in 2006 or earlier, and the well-established factors of tumor thickness, ulceration, and age were included in 70 % of tools. Internal validity using cross-validation or bootstrapping techniques was performed for two tools only. Fewer than half were evaluated for external validity; however, when done, the appropriate statistical methodology was applied and results indicated good generalizability. Several clinical prognostic tools have the potential to refine survival estimates for individual melanoma patients; however, there is a great opportunity to improve these tools and to foster the development of new, validated tools by the inclusion of contemporary clinicopathological covariates and by using improved statistical and methodological approaches.

  9. 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.

  10. A new prognostic scale for the early prediction of ischemic stroke recovery mainly based on traditional Chinese medicine symptoms and NIHSS score: a retrospective cohort study.

    Science.gov (United States)

    Cao, Ke-Gang; Fu, Cai-Hong; Li, Huan-Qin; Xin, Xi-Yan; Gao, Ying

    2015-11-16

    Ischemic stroke (IS) is a common disease, often resulting in death or disability. Previous studies on prognosis of stroke mainly focused on the baseline condition or modern expensive tests. However, the change of clinical symptoms during acute stage is considerably neglected. In our study, we aim to develop a new prognostic scale to predict the 90-day outcome of IS patients. In this retrospective cohort study, a secondary data analysis was performed on 489 patients extracted from 1046 patients of 4 hospitals. A new prognostic scale was constructed to predict the recovery of IS mainly based on the National Institutes of Health Stroke Scale (NIHSS) score, traditional Chinese Medicine (TCM) symptoms & signs and the changes during the first 3 days of patients in the 3 TCM hospitals. Receiver Operating Characteristic (ROC) curve was used to determine the cutoff point for prediction. In the end, the scale was used to test the outcome of IS patients in Xuanwu hospital. The new prognostic scale was composed of 8 items including age degree (OR = 3.32; 95 % CI: 1.72-6.42), history of diabetes mellitus (DM) (OR = 2.20; 95 % CI: 1.19-4.08), NIHSS score (OR = 3.08; 95 % CI: 2.16-4.40), anxiety (OR = 3.17; 95 % CI: 1.90-5.29) and irritability (OR = 4.61; 95 % CI: 1.36-15.63) on the 1st day of illness onset, change in NIHSS score (OR = 2.49; 95 % CI: 1.31-4.73), and circumrotating (OR = 7.80; 95 % CI: 1.98-30.64) and tinnitus (OR = 13.25; 95 % CI: 1.55-113.34) during the first 3 days of stroke onset. The total score of the scale was 16.5 and the cutoff point was 9.5, which means patients would have poor outcome at 90 days of stroke onset if the score was higher than 9.5. The new scale was validated on the data of Xuanwu hospital, and the value of its sensitivity, specificity and overall accuracy were 69.6 %, 83.3 % and 75.0 % respectively. The 8-item scale, mainly based on TCM symptoms, NIHSS score and their changes during the first 3 days, can predict the 90-day outcome for IS

  11. gis-based hydrological model based hydrological model upstream

    African Journals Online (AJOL)

    eobe

    Hydrological. Hydrological modeling tools have been increasingl modeling tools have been increasingl watershed watershed level. The application of these tools hav. The application of these tools hav sensing and G sensing and Geographical Information System (GIS) eographical Information System (GIS) based models ...

  12. Prediction of outcome after moderate and severe traumatic brain injury: External validation of the International Mission on Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation after Significant Head injury (CRASH) prognostic models

    NARCIS (Netherlands)

    B. Roozenbeek (Bob); H.F. Lingsma (Hester); F.E. Lecky (Fiona); J. Lu (Juan); J. Weir (James); I. Butcher (Isabella); G.S. McHugh (Gillian); G.D. Murray (Gordon); P. Perel (Pablo); A.I.R. Maas (Andrew); E.W. Steyerberg (Ewout)

    2012-01-01

    textabstractObjective: The International Mission on Prognosis and Analysis of Clinical Trials and Corticoid Randomisation After Significant Head injury prognostic models predict outcome after traumatic brain injury but have not been compared in large datasets. The objective of this is study is to

  13. 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...

  14. Model based on γ-glutamyltransferase and alkaline phosphatase for hepatocellular carcinoma prognosis.

    Science.gov (United States)

    Xu, Xin-Sen; Wan, Yong; Song, Si-Dong; Chen, Wei; Miao, Run-Chen; Zhou, Yan-Yan; Zhang, Ling-Qiang; Qu, Kai; Liu, Si-Nan; Zhang, Yue-Lang; Dong, Ya-Feng; Liu, Chang

    2014-08-21

    To determine the prognostic value of alkaline phosphatase (ALP) and γ-glutamyltransferase (GGT) for hepatocellular carcinoma (HCC) . We analyzed the outcome of 172 HCC patients who underwent liver resection. Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off value of ALP and GGT. Then, preoperative risk factors for survival were evaluated by multivariate analysis. Based on the significant factors, a prognostic score model was established. By ROC curve analysis, ALP > 120 U/L and GGT > 115 U/L were considered elevated. Overall survival (OS) and tumor-free survival (TFS) for patients with elevated ALP and GGT were significantly worse than for patients with ALP and GGT within the normal range. Multivariate analysis showed that the elevated levels of ALP, GGT and tumor size were independent prognostic factors. Giving each positive factor as a score of 1, we established a preoperative prognostic score model. The 5-year OS for patients with a score of 0, 1, 2 and 3 were 84.0%, 45.9%, 44.1% and 0%, respectively, while the TFS was 80.6%, 40.0%, 38.8% and 0%, respectively. When combining patients with scores of 1 and 2 into the middle risk group, and patients with scores of 0 and 3 into the low-risk and high-risk groups, respectively, different outcomes would be significantly distinguished by the risk groups. Elevated ALP and GGT levels were risk predictors in HCC patients. Our prognostic model might vary the outcomes of patients from different risk groups.

  15. Hematological changes as prognostic indicators of survival: similarities between Gottingen minipigs, humans, and other large animal models.

    Directory of Open Access Journals (Sweden)

    Maria Moroni

    Full Text Available The animal efficacy rule addressing development of drugs for selected disease categories has pointed out the need to develop alternative large animal models. Based on this rule, the pathophysiology of the disease in the animal model must be well characterized and must reflect that in humans. So far, manifestations of the acute radiation syndrome (ARS have been extensively studied only in two large animal models, the non-human primate (NHP and the canine. We are evaluating the suitability of the minipig as an additional large animal model for development of radiation countermeasures. We have previously shown that the Gottingen minipig manifests hematopoietic ARS phases and symptoms similar to those observed in canines, NHPs, and humans.We establish here the LD50/30 dose (radiation dose at which 50% of the animals succumb within 30 days, and show that at this dose the time of nadir and the duration of cytopenia resemble those observed for NHP and canines, and mimic closely the kinetics of blood cell depletion and recovery in human patients with reversible hematopoietic damage (H3 category, METREPOL approach. No signs of GI damage in terms of diarrhea or shortening of villi were observed at doses up to 1.9 Gy. Platelet counts at days 10 and 14, number of days to reach critical platelet values, duration of thrombocytopenia, neutrophil stress response at 3 hours and count at 14 days, and CRP-to-platelet ratio were correlated with survival. The ratios between neutrophils, lymphocytes and platelets were significantly correlated with exposure to irradiation at different time intervals.As a non-rodent animal model, the minipig offers a useful alternative to NHP and canines, with attractive features including ARS resembling human ARS, cost, and regulatory acceptability. Use of the minipig may allow accelerated development of radiation countermeasures.

  16. 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.

  17. Validation and Extension of the Prolonged Mechanical Ventilation Prognostic Model (ProVent) Score for Predicting 1-Year Mortality after Prolonged Mechanical Ventilation.

    Science.gov (United States)

    Udeh, Chiedozie I; Hadder, Brent; Udeh, Belinda L

    2015-12-01

    Prognostic models can inform management decisions for patients requiring prolonged mechanical ventilation. The Prolonged Mechanical Ventilation Prognostic model (ProVent) score was developed to predict 1-year mortality in these patients. External evaluation of such models is needed before they are adopted for routine use. The goal was to perform an independent external validation of the modified ProVent score and assess for spectrum extension at 14 days of mechanical ventilation. This was a retrospective cohort analysis of patients who received prolonged mechanical ventilation at the University of Iowa Hospitals. Patients who received 14 or more days of mechanical ventilation were identified from a database. Manual review of their medical records was performed to abstract relevant data including the four model variables at Days 14 and 21 of mechanical ventilation. Vital status at 1 year was checked in the medical records or the social security death index. Logistic regressions examined the associations between the different variables and mortality. Model performance at 14 to 20 days and 21+ days was assessed for discrimination by calculating the area under the receiver operating characteristic curve, and calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. A total of 180 patients (21+ d) and 218 patients (14-20 d) were included. Overall, 75% were surgical patients. One-year mortality was 51% for 21+ days and 32% for 14 to 20 days of mechanical ventilation. Age greater than 65 years was the strongest predictor of mortality at 1 year in all cohorts. There was no significant difference between predicted and observed mortality rates for patients stratified by ProVent score. There was near-perfect specificity for mortality in the groups with higher ProVent scores. Areas under the curve were 0.69 and 0.75 for the 21+ days and the 14 to 20 days cohorts respectively. P values for the Hosmer-Lemeshow statistics were 0.24 for 21+ days and 0.22 for 14 to

  18. 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

    PROGNOSTICS AND HEALTH MANAGEMENT SOCIETY 2014 2 expected benefits in this case are substitutions of preventive inspection tasks and reductions of...goal is to derive maximum acceptable investment costs for PHM systems from the analysis results. Therefore, no additional fix costs for an airplane ...September 23-28, Brisbane, Australia . Keller, K., & Poblete, J. (2011). The Business Case for SHM, System Health Management: with aerospace

  19. Activity-based DEVS modeling

    DEFF Research Database (Denmark)

    Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

    2018-01-01

    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...... 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...... 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...

  20. Prognostic Utility of Morning Blood Pressure Surge for 20-Year All-Cause and Cardiovascular Mortalities: Results of a Community-Based Study.

    Science.gov (United States)

    Cheng, Hao-Min; Wu, Chung-Li; Sung, Shih-Hsien; Lee, Jia-Chun; Kario, Kazuomi; Chiang, Chern-En; Huang, Chi-Jung; Hsu, Pai-Feng; Chuang, Shao-Yuan; Lakatta, Edward G; Yin, Frank C P; Chou, Pesus; Chen, Chen-Huan

    2017-12-09

    Morning blood pressure (BP) surge (MS), defined by the MS amplitude, is an independent prognostic factor of cardiovascular outcomes in some, but not all, populations. We enrolled 2020 participants (1029 men; aged 30-79 years) with 24-hour ambulatory BP data. During a median 19.7-year follow-up, 607 deaths (182 by cardiovascular causes) were confirmed from the National Death Registry. The amplitude of sleep-trough MS (STMS) was derived from the difference between morning systolic BP (SBP) and lowest nighttime SBP. The rate of STMS was derived as the slope of linear regression of sequential SBP measures on time intervals within the STMS period. Thresholds for high STMS amplitude and rate were determined by the 95th percentiles (43.7 mm Hg and 11.3 mm Hg/h, respectively). Multivariable Cox models, adjusting for age, sex, body mass index, smoking, alcohol, low-density lipoprotein cholesterol, 24-hour SBP, night:day SBP ratio, and antihypertensive treatment, revealed that a high STMS rate (hazard ratio, 1.666; 95% confidence interval, 1.185-2.341), but not STMS amplitude (hazard ratio, 1.245; 95% confidence interval, 0.984-1.843), was significantly associated with a greater mortality risk. Similarly, STMS rate (hazard ratio, 2.608; 95% confidence interval, 1.554-4.375), but not STMS amplitude, was significantly associated with the risk of cardiovascular mortality (hazard ratio, 0.966; 95% confidence interval, 0.535-1.747). Moreover, the prognostic values of STMS rate were comparable in subjects with or without morning and nocturnal hypertension (P>0.05 for interaction for all). In simulation studies, STMS rate was less susceptible to measurement errors of the sleep-trough SBP than STMS amplitude. STMS rate could independently help identify subjects with an increased cardiovascular risk. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

  1. 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...... infrastructure for different symbolic positioning technologies, e.g., Bluetooth and RFID. More specifically, the paper proposes a model of indoor space that comprises a base graph and mappings that represent the topology of indoor space at different levels. The resulting model can be used for one or several...... indoor positioning technologies. Focusing on RFID-based positioning, an RFID specific reader deployment graph model is built from the base graph model. This model is then used in several algorithms for constructing and refining trajectories from raw RFID readings. Empirical studies with implementations...

  2. 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...

  3. Identification of high independent prognostic value of nanotechnology based circulating tumor cell enumeration in first-line chemotherapy for metastatic breast cancer patients.

    Science.gov (United States)

    Liu, Xiao-Ran; Shao, Bin; Peng, Jia-Xi; Li, Hui-Ping; Yang, Yan-Lian; Kong, Wei-Yao; Song, Guo-Hong; Jiang, Han-Fang; Liang, Xu; Yan, Ying

    2017-04-01

    Enumeration of circulating tumor cells (CTCs) is a promising tool in the management of metastatic breast cancer (MBC). This study investigated the capturing efficiency and prognostic value of our previously reported peptide-based nanomagnetic CTC isolation system (Pep@MNPs). We counted CTCs in blood samples taken at baseline (n = 102) and later at patients' first clinical evaluation after starting firstline chemotherapy (n = 72) in a cohort of women treated for MBC. Their median follow-up was 16.3 months (range: 9.0-31.0 months). The CTC detection rate was 69.6 % for the baseline samples. Patients with ≤2 CTC/2 ml at baseline had longer median progression-free survival (PFS) than did those with >2 CTC/2 ml (17.0 months vs. 8.0 months; P = 0.002). Patients with ≤2 CTC/2 ml both at baseline and first clinical evaluation had longest PFS (18.2 months) among all patient groups (P = 0.004). Particularly, among patients with stable disease (SD; per imaging evaluation) our assay could identify those with longer PFS (P 2 CTC/2 ml at baseline were also significantly more likely to suffer liver metastasis (P = 0.010). This study confirmed the prognostic value of Pep@MNPs assays for MBC patients who undergo firstline chemotherapy, and offered extra stratification regarding PFS for patients with SD, and a possible indicator for patients at risk for liver metastasis. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Can metabolic tumor parameters on primary staging18F-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.

  5. Palliative medicine review: prognostication.

    Science.gov (United States)

    Glare, Paul A; Sinclair, Christian T

    2008-01-01

    Prognostication, along with diagnosis and treatment, is a traditional core clinical skill of the physician. Many patients and families receiving palliative care want information about life expectancy to help plan realistically for their futures. Although underappreciated, prognosis is, or at least should be, part of every clinical decision. Despite this crucial role, expertise in the art and science of prognostication diminished during the twentieth century, due largely to the ascendancy of accurate diagnostic tests and effective therapies. Consequently, "Doctor, how long do I have?" is a question most physicians find unprepared to answer effectively. As we focus on palliative care in the twenty-first century, prognostication will need to be restored as a core clinical proficiency. The discipline of palliative medicine can provide leadership in this direction. This paper begins by discussing a framework for understanding prognosis and how its different domains might be applied to all patients with life limiting illness, although the main focus of the paper is predicting survival in patients with cancer. Examples of prognostic tools are provided, although the subjective assessment of prognosis remains important in the terminally ill. Other issues addressed include: the importance of prognostication in terms of clinical decision-making, discharge planning, and care planning; the impact of prognosis on hospice referrals and patient/family satisfaction; and physicians' willingness to prognosticate.

  6. Event-Based Activity Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2004-01-01

    We present and discuss a modeling approach that supports event-based modeling of information and activity in information systems. Interacting human actors and IT-actors may carry out such activity. We use events to create meaningful relations between information structures and the related...... activities inside and outside an IT-system. We use event-activity diagrams to model activity. Such diagrams support the modeling of activity flow, object flow, shared events, triggering events, and interrupting events....

  7. 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

  8. Integrative prognostic risk score in acute myeloid leukemia with normal karyotype

    National Research Council Canada - National Science Library

    Damm, Frederik; Heuser, Michael; Morgan, Helen; Wagner, Katharina; Görlich, Kerstin; Großhennig, Anika; Hamwi, Iyas; Thol, Felicitas; Surdziel, Ewa; Fiedler, Walter; Lübbert, Michael; Kanz, Lothar; Reuter, Christoph; Heil, Gerhard; Delwel, Ruud; Löwenberg, Bob; Valk, Peter; Krauter, J; Ganser, Arnold

    2011-01-01

    .... Integrative prognostic risk score (IPRS) was modeled in 181 patients based on age, white blood cell count, mutation status of NPM1, FLT3-ITD, CEBPA, single nucleotide polymorphism rs16754, and expression levels of BAALC, ERG, MN1, and WT1...

  9. Prognostication of traumatic brain injury outcomes in older trauma patients: A novel risk assessment tool based on initial cranial CT findings.

    Science.gov (United States)

    Stawicki, Stanislaw P; Wojda, Thomas R; Nuschke, John D; Mubang, Ronnie N; Cipolla, James; Hoff, William S; Hoey, Brian A; Thomas, Peter G; Sweeney, Joan; Ackerman, Daniel; Hosey, Jonathan; Falowski, Steven

    2017-01-01

    using matched NSI (n = 310) and non-NSI (n = 310) groups. All other analyses examined the combined patient sample (n = 620). Variables achieving a significance level of P functional outcome scores on discharge. Increasing CCTST was associated with greater mortality, morbidity, HLOS, SDLOS, ICULOS, and ventilator days. On multivariate analysis, factors independently associated with mortality included AISh (AOR 2.70, 95% CI 1.21-6.00), initial GCS (AOR 1.14, 1.07-1.22), and CCTST (AOR 1.31, 1.09-1.58). Variables independently associated with in-hospital morbidity included CCTST (AOR 1.16, 1.02-1.34), GCS (AOR 1.05, 1.01-1.09), and NSI (AOR 2.62, 1.69-4.06). Multivariate models incorporating factors independently associated with each respective outcome displayed good overall predictive characteristics for mortality (AUC 0.787) and in-hospital morbidity (AUC 0.651). Finally, modified CCTST demonstrated good overall predictive ability for NSI (AUC 0.755). This study found that the number of discrete findings on CCT is independently associated with major TBI outcome measures, including 30-day mortality, in-hospital morbidity, and NSI. Of note, multivariate models with best predictive characteristics incorporate both CCTST and GCS. CCTST is easy to calculate, and this preliminary investigation of its predictive utility in older patients with TBI warrants further validation, focusing on exploring prognostic synergies between CCTST, GCS, and AISh. If independently confirmed to be predictive of clinical outcomes and the need for NSI, the approach described herein could lead to a shift in both operative and nonoperative management of patients with TBI.

  10. Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report

    Science.gov (United States)

    Cornhill, Dennis; Bharadwaj, Raj; Mylaraswamy, Dinkar

    2013-01-01

    This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning.

  11. 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....

  12. 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.

  13. 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

  14. 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

  15. Computer-based image studies on tumor nests mathematical features of breast cancer and their clinical prognostic value.

    Directory of Open Access Journals (Sweden)

    Lin-Wei Wang

    Full Text Available BACKGROUND: The expending and invasive features of tumor nests could reflect the malignant biological behaviors of breast invasive ductal carcinoma. Useful information on cancer invasiveness hidden within tumor nests could be extracted and analyzed by computer image processing and big data analysis. METHODS: Tissue microarrays from invasive ductal carcinoma (n = 202 were first stained with cytokeratin by immunohistochemical method to clearly demarcate the tumor nests. Then an expert-aided computer analysis system was developed to study the mathematical and geometrical features of the tumor nests. Computer recognition system and imaging analysis software extracted tumor nests information, and mathematical features of tumor nests were calculated. The relationship between tumor nests mathematical parameters and patients' 5-year disease free survival was studied. RESULTS: There were 8 mathematical parameters extracted by expert-aided computer analysis system. Three mathematical parameters (number, circularity and total perimeter with area under curve >0.5 and 4 mathematical parameters (average area, average perimeter, total area/total perimeter, average (area/perimeter with area under curve <0.5 in ROC analysis were combined into integrated parameter 1 and integrated parameter 2, respectively. Multivariate analysis showed that integrated parameter 1 (P = 0.040 was independent prognostic factor of patients' 5-year disease free survival. The hazard risk ratio of integrated parameter 1 was 1.454 (HR 95% CI [1.017-2.078], higher than that of N stage (HR 1.396, 95% CI [1.125-1.733] and hormone receptor status (HR 0.575, 95% CI [0.353-0.936], but lower than that of histological grading (HR 3.370, 95% CI [1.125-5.364] and T stage (HR 1.610, 95% CI [1.026 -2.527]. CONCLUSIONS: This study indicated integrated parameter 1 of mathematical features (number, circularity and total perimeter of tumor nests could be a useful parameter to predict the

  16. 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 < 0.001) and worsened with advanced tumor stages (p < 0.001). Patients with the worst Naples prognostic score experienced more postoperative complications (all patients, p = 0.010; radically resected patients, p = 0.026). Compared with group 0, patients in groups 1 and 2 had worse overall (group 1, HR = 2.90; group 2, HR = 8.01; p < 0.001) and disease-free survival rates (group 1, HR = 2.57; group 2, HR = 6.95; p < 0.001). Only the Naples prognostic score was an independent significant predictor of overall (HR = 2.0; p = 0.03) and disease-free survival rates (HR = 2.6; p = 0.01). The receiver operating characteristic curve analysis showed that the Naples prognostic score had the best prognostic

  17. Base Flow Model Validation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The program focuses on turbulence modeling enhancements for predicting high-speed rocket base flows. A key component of the effort is the collection of high-fidelity...

  18. 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.

  19. 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...

  20. Implementing targeted expectant management in fertility care using prognostic modelling: a cluster randomized trial with a multifaceted strategy.

    Science.gov (United States)

    Kersten, F A M; Nelen, W L D M; van den Boogaard, N M; van Rumste, M M; Koks, C A; IntHout, J; Verhoeve, H R; Pelinck, M J; Boks, D E S; Gianotten, J; Broekmans, F J M; Goddijn, M; Braat, D D M; Mol, B W J; Hermens, R P G M

    2017-08-01

    What is the effectiveness of a multifaceted implementation strategy compared to usual care on improving the adherence to guideline recommendations on expectant management for couples with unexplained infertility? The multifaceted implementation strategy did not significantly increase adherence to guideline recommendations on expectant management compared to care as usual. Intrauterine insemination (IUI) with or without ovarian hyperstimulation has no beneficial effect compared to no treatment for 6 months after the fertility work-up for couples with unexplained infertility and a good prognosis of natural conception. Therefore, various professionals and policy makers have advocated the use of prognostic profiles and expectant management in guideline recommendations. A cluster randomized controlled trial in 25 clinics in the Netherlands was conducted between March 2013 and May 2014. Clinics were randomized between the implementation strategy (intervention, n = 13) and care as usual (control, n = 12). The effect of the implementation strategy was evaluated by comparing baseline and effect measurement data. Data collection was retrospective and obtained from medical record research and a patient questionnaire. A total of 544 couples were included at baseline and 485 at the effect measurement (247 intervention group/238 control group). Guideline adherence increased from 49 to 69% (OR 2.66; 95% CI 1.45-4.89) in the intervention group, and from 49 to 61% (OR 2.03; 95% CI 1.38-3.00) in the control group. Multilevel analysis with case-mix adjustment showed that the difference of 8% was not statistically significant (OR 1.31; 95% CI 0.67-2.59). The ongoing pregnancy rate within six months after fertility work-up did not significantly differ between intervention and control group (25% versus 27%: OR 0.72; 95% CI 0.40-1.27). There is a possible selection bias, couples included in the study had a higher socio-economic status than non-responders. How this affects guideline

  1. Validation of risk stratification models in acute myeloid leukemia using sequencing-based molecular profiling.

    Science.gov (United States)

    Wang, M; Lindberg, J; Klevebring, D; Nilsson, C; Mer, A S; Rantalainen, M; Lehmann, S; Grönberg, H

    2017-10-01

    Risk stratification of acute myeloid leukemia (AML) patients needs improvement. Several AML risk classification models based on somatic mutations or gene-expression profiling have been proposed. However, systematic and independent validation of these models is required for future clinical implementation. We performed whole-transcriptome RNA-sequencing and panel-based deep DNA sequencing of 23 genes in 274 intensively treated AML patients (Clinseq-AML). We also utilized the The Cancer Genome Atlas (TCGA)-AML study (N=142) as a second validation cohort. We evaluated six previously proposed molecular-based models for AML risk stratification and two revised risk classification systems combining molecular- and clinical data. Risk groups stratified by five out of six models showed different overall survival in cytogenetic normal-AML patients in the Clinseq-AML cohort (P-value0.5). Risk classification systems integrating mutational or gene-expression data were found to add prognostic value to the current European Leukemia Net (ELN) risk classification. The prognostic value varied between models and across cohorts, highlighting the importance of independent validation to establish evidence of efficacy and general applicability. All but one model replicated in the Clinseq-AML cohort, indicating the potential for molecular-based AML risk models. Risk classification based on a combination of molecular and clinical data holds promise for improved AML patient stratification in the future.

  2. 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:

  3. 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.

  4. 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...

  5. Validation of Model-Based Prognostics for Pneumatic Valves in a Demonstration Testbed

    Science.gov (United States)

    2014-10-02

    distribution, and reproduction in any medium, pro- vided the original author and source are credited. bile robots (Tang, Hettler , Zhang, & DeCastro, 2011; Bala...in- fotech@aerospace 2007 conference and exhibit. Tang, L., Hettler , E., Zhang, B., & DeCastro, J. (2011). A testbed for real-time autonomous vehicle

  6. 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...

  7. A Combined Model-Based and Data-Driven Prognostic Approach for Aircraft System Life Management

    Data.gov (United States)

    National Aeronautics and Space Administration — Failure prognosis - as a natural extension to the fault detection and isolation (FDI) problem - has become a key issue in a world where the economic impact of system...

  8. 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.

  9. Prognostic factors in papillary and follicular thyroid carcinomas

    DEFF Research Database (Denmark)

    Godballe, C; Asschenfeldt, P; Jørgensen, K E

    1998-01-01

    To identify clinical and histologic prognostic factors and to investigate whether immunohistochemical detection of p53 expression might contain prognostic information, a retrospective study of patient and tumor characteristics was performed in 225 cases of papillary and follicular thyroid carcino...... prognostic indicator, which might be of value in the treatment planning in patients with papillary or follicular thyroid carcinomas.......To identify clinical and histologic prognostic factors and to investigate whether immunohistochemical detection of p53 expression might contain prognostic information, a retrospective study of patient and tumor characteristics was performed in 225 cases of papillary and follicular thyroid...... carcinomas. The analyses were based on cause-specific and crude survival. In univariate analysis, age at diagnosis, tumor size, presence of distant metastases, histology (papillary contra follicular type), extrathyroidal invasion, necrosis in primary tumor, and p53 expression were significant prognostic...

  10. Prognostic value of blood-biomarkers related to hypoxia, inflammation, immune response and tumour load in non-small cell lung cancer - A survival model with external validation.

    Science.gov (United States)

    Carvalho, Sara; Troost, Esther G C; Bons, Judith; Menheere, Paul; Lambin, Philippe; Oberije, Cary

    2016-06-01

    Improve the prognostic prediction of clinical variables for non-small cell lung cancer (NSCLC), by selecting from blood-biomarkers, non-invasively describing hypoxia, inflammation and tumour load. Model development and validation included 182 and 181 inoperable stage I-IIIB NSCLC patients treated radically with radiotherapy (55.2%) or chemo-radiotherapy (44.8%). Least absolute shrinkage and selection operator (LASSO), selected from blood-biomarkers related to hypoxia [osteopontin (OPN) and carbonic anhydrase IX (CA-IX)], inflammation [interleukin-6 (IL-6), IL-8, and C-reactive protein (CRP)], and tumour load [carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1 (Cyfra 21-1)]. Sequent model extension selected from alpha-2-macroglobulin (α2M), serum interleukin-2 receptor (sIL2r), toll-like receptor 4 (TLR4), and vascular endothelial growth factor (VEGF). Discrimination was reported by concordance-index. OPN and Cyfra 21-1 (hazard ratios of 3.3 and 1.7) significantly improved a clinical model comprising gender, World Health Organization performance-status, forced expiratory volume in 1s, number of positive lymph node stations, and gross tumour volume, from a concordance-index of 0.66 to 0.70 (validation=0.62 and 0.66). Extension of the validated model yielded a concordance-index of 0.67, including α2M, sIL2r and VEGF (hazard ratios of 4.6, 3.1, and 1.4). Improvement of a clinical model including hypoxia and tumour load blood-biomarkers was validated. New immunological markers were associated with overall survival. Data and models can be found at www.cancerdata.org (http://dx.doi.org/10.17195/candat.2016.04.1) and www.predictcancer.org. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  11. Accelerated Aging Experiments for Capacitor Health Monitoring and Prognostics

    Science.gov (United States)

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

    2012-01-01

    This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions. Electrolytic capacitors have higher failure rates than other components in electronic systems like power drives, power converters etc. Our current work focuses on developing first-principles-based degradation models for electrolytic capacitors under varying electrical and thermal stress conditions. Prognostics and health management for electronic systems aims to predict the onset of faults, study causes for system degradation, and accurately compute remaining useful life. Accelerated life test methods are often used in prognostics research as a way to model multiple causes and assess the effects of the degradation process through time. It also allows for the identification and study of different failure mechanisms and their relationships under different operating conditions. Experiments are designed for aging of the capacitors such that the degradation pattern induced by the aging can be monitored and analyzed. Experimental setups and data collection methods are presented to demonstrate this approach.

  12. Clinical prognostic factors in adults with astrocytoma: Historic cohort.

    Science.gov (United States)

    Wegman-Ostrosky, Talia; Reynoso-Noverón, Nancy; Mejía-Pérez, Sonia I; Sánchez-Correa, Thalía E; Alvarez-Gómez, Rosa María; Vidal-Millán, Silvia; Cacho-Díaz, Bernardo; Sánchez-Corona, José; Herrera-Montalvo, Luis A; Corona-Vázquez, Teresa

    2016-07-01

    To explore the clinical prognostic factors for adults affected with astrocytoma. Using a historic cohort, we selected 155 clinical files from patients with astrocytoma using simple randomization. The main outcome variable was overall survival time. To identify clinical prognostic factors, we used bivariate analysis, Kaplan Meier, the log rank test and the Cox regression models. The number of lost years lived with disability (DALY) based on prevalence, was calculated. The mean age at diagnosis was 45.7 years. Analysis according to tumour stage, including grades II, III and IV, also showed a younger age of presentation. Kaplan-Meier survival estimates showed that tumour grade, Karnofsky status (KPS) ≥70, resection type, chemotherapy, radiotherapy, alcohol consumption, familial history of cancer and clinical presentation were significantly associated with survival time. Using a proportional hazard model, age, grade IV, resection, chemotherapy+radiotherapy and KPS were identified as prognostic factors.The amount of life lost due to premature death in this population was 28 years. In our study, astrocytoma was diagnosed in young adults. The overall survival was 15 months, 9% (n=14) of patients presented a survival of 2 years, and 3% of patients survived 3 years. On average the number of years lost due to premature death and disability was 28.53 years. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Integrated Diagnostics and Prognostics of Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Kam W. Ng

    1999-01-01

    Full Text Available This paper provides an overview of current research efforts in integrated diagnostics and prognostics of rotating machinery. Specifically, the following topics are discussed: sensing techniques and sensors; signal detection, identification and extraction; classification of faults; predictive failure models; data/model fusion; information management; and man–machine interface. Technical issues, recommendations, and future research directions are also addressed.

  14. Improvement of criteria for refractory cytopenia with multilineage dysplasia according to the WHO classification based on prognostic significance of morphological features in patients with refractory anemia according to the FAB classification.

    Science.gov (United States)

    Matsuda, A; Germing, U; Jinnai, I; Iwanaga, M; Misumi, M; Kuendgen, A; Strupp, C; Miyazaki, Y; Tsushima, H; Sakai, M; Bessho, M; Gattermann, N; Aul, C; Tomonaga, M

    2007-04-01

    In the criteria of refractory cytopenia with multilineage dysplasia (RCMD) according to the WHO (World Health Organization) classification, the frequency threshold concerning dysplasia of each lineage was defined as 10%. To predict overall survival (OS) and leukemia-free survival (LFS) for patients with refractory anemia (RA) according to the French-American-British (FAB) classification, we investigated prognostic factors based on the morphological features of 100 Japanese and 87 German FAB-RA patients, excluding 5q-syndrome. In the univariate analysis of all patients, pseudo-Pelger-Huet anomalies >or=10% (Pelger+), micromegakaryocytes >or=10% (mMgk+), dysgranulopoiesis (dys G) >or=10% and dysmegakaryopoiesis (dys Mgk) >or=40% were unfavorable prognostic factors for OS and LFS (OS; Por=10% was not correlated with OS and LFS. In the multivariate analysis, mMgk+ and dys Mgk>or=40% were adverse prognostic factors for OS for all patients, and dys G >or=10% and dys Mgk>or=40% were adverse prognostic factors for LFS for all patients. On the basis of the present analysis, we propose the following modified morphological criteria for RCMD. Modified RCMD should be defined as FAB-RA, excluding 5q-syndrome with dys G >or=10%, dys Mgk>or=40% or mMgk+.

  15. 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.

  16. Prognostic factors in patients with metastatic (stage D2) prostate cancer: experience from the Scandinavian Prostatic Cancer Group Study-2.

    Science.gov (United States)

    Jørgensen, T; Kanagasingam, Y; Kaalhus, O; Tveter, K J; Bryne, M; Skjørten, F; Berner, A; Danielsen, H E

    1997-07-01

    Nuclear texture reflects the overall structures of the chromatin organization. We recently reported the principles and prognostic importance of image analysis of nuclei from metastatic prostate cancer. Immunohistochemical up regulation of the adhesion molecule sialyl Lewis(x) is also reported to be a prognostic parameter. Presently we analyzed statistically the prognostic impact of these 2 new parameters compared to well-known clinical parameters in metastatic prostate cancer. Prognostic factors, such as sedimentation rate, alkaline and acid phosphatases, hemoglobin, testosterone, performance status, pain due to metastasis, T category, histological grade and patient age, were included in a multivariate Cox proportional hazards regression analysis based on 262 patients from the Scandinavian Prostatic Cancer Group Study-2. Extent of bone lesions, deoxyribonucleic acid ploidy, texture analysis and sialyl Lewis(x) molecules based on subsets of these 262 patients were also analyzed in the same multivariate model. This test identified chromatin texture as the most important factor (p < 0.001), followed by reaction of the oligosaccharide sialyl Lewis(x) (p < 0.01). Among the routine clinical and laboratory data, sedimentation rate, alkaline phosphatase and hemoglobin (p < 0.05) showed prognostic importance. Performance status, pain due to metastasis and extent of bone lesions showed prognostic value in the univariate analysis (p < 0.05). These data indicate that computerized nuclear texture analysis as well as up regulation of sialyl Lewis(x) molecules may be new important prognostic factors in metastatic prostate cancer. Furthermore the prognostic importance of sedimentation rate, alkaline phosphatase and hemoglobin was confirmed.

  17. 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...

  18. Prognostic Disclosures to Children: A Historical Perspective.

    Science.gov (United States)

    Sisk, Bryan A; Bluebond-Langner, Myra; Wiener, Lori; Mack, Jennifer; Wolfe, Joanne

    2016-09-01

    Prognostic disclosure to children has perpetually challenged clinicians and parents. In this article, we review the historical literature on prognostic disclosure to children in the United States using cancer as an illness model. Before 1948, there was virtually no literature focused on prognostic disclosure to children. As articles began to be published in the 1950s and 1960s, many clinicians and researchers initially recommended a "protective" approach to disclosure, where children were shielded from the harms of bad news. We identified 4 main arguments in the literature at this time supporting this "protective" approach. By the late 1960s, however, a growing number of clinicians and researchers were recommending a more "open" approach, where children were included in discussions of diagnosis, which at the time was often synonymous with a terminal prognosis. Four different arguments in the literature were used at this time supporting this "open" approach. Then, by the late 1980s, the recommended approach to prognostic disclosure in pediatrics shifted largely from "never tell" to "always tell." In recent years, however, there has been a growing appreciation for the complexity of prognostic disclosure in pediatrics. Current understanding of pediatric disclosure does not lead to simple "black-and-white" recommendations for disclosure practices. As with most difficult questions, we are left to balance competing factors on a case-by-case basis. We highlight 4 categories of current considerations related to prognostic disclosure in pediatrics, and we offer several approaches to prognostic disclosure for clinicians who care for these young patients and their families. Copyright © 2016 by the American Academy of Pediatrics.

  19. Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication in Terminally Ill Patients

    Science.gov (United States)

    2016-03-01

    Mbah, PhD2*, Ambuj Kumar, MD, MPH3, Kim Sehwan, PhD4*, Ronald Schonwetter, MD5* and Benjamin Djulbegovic, MD, PhD6 1Center for Evidence - Based Medicine , University...of South Florida, Tampa, FL 2USF, Tampa, FL 3University of South Florida, College of Medicine, Center for Evidence Based Medicine , Tampa...4HPC healthcare, Tampa, FL 5HPC Healthcare, Tampa, FL 6Center for Evidence - Based Medicine & Health Outcomes Research, University of South

  20. 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.

  1. Delta model for end-stage liver disease and delta clinical prognostic indicator as predictors of mortality in patients with viral acute liver failure.

    Science.gov (United States)

    Pannu, Ashok Kumar; Bhalla, Ashish; Rao, Chelapati; Singh, Charanpreet

    2017-01-01

    The objective of the study is to compare the model for end-stage liver disease (MELD) with clinical prognostic indicators (CPI) specifically the change in these parameters after 48 h of admission in predicting the mortality in patients with acute liver failure (ALF) due to acute viral hepatitis. An open label, investigator-initiated prospective study was conducted that included 41 patients with acute viral hepatitis with ALF. The cases were followed prospectively till death or discharge. The MELD and CPI were calculated at admission and 48 h of admission. Patients having no change or worsening in CPI score, i.e., delta CPI more negative had a higher mortality over the next 48 h compared to patients having an improvement in their respective CPI score. Delta CPI predicted adverse outcome better than the presence of any three CPI on admission (P = 0.019). Patients having no change or a worsening in MELD score, i.e., delta MELD more negative, had a higher mortality in the next 48 h compared to the patients having improvement in their respective MELD score. However, MELD >33 on admission was superior to delta MELD in predicting the adverse outcome (P = 0.019). Among the patients with ALF due to viral hepatitis, delta CPI was found to be superior to delta MELD in predicting the adverse outcome in patients with viral ALF (P < 0.0001).

  2. 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.

  3. 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 thei...... 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....

  4. A prognostic model for development of significant liver fibrosis in HIV-hepatitis C co-infection.

    Directory of Open Access Journals (Sweden)

    Nasheed Moqueet

    Full Text Available Liver fibrosis progresses rapidly in HIV-Hepatitis C virus (HCV co-infected individuals partially due to heightened inflammation. Immune markers targeting stages of fibrogenesis could aid in prognosis of fibrosis.A case-cohort study was nested in the prospective Canadian Co-infection Cohort (n = 1119. HCV RNA positive individuals without fibrosis, end-stage liver disease or chronic Hepatitis B at baseline (n = 679 were eligible. A random subcohort (n = 236 was selected from those eligible. Pro-fibrogenic markers and Interferon Lambda (IFNL rs8099917 genotype were measured from first available sample in all fibrosis cases (APRI ≥ 1.5 during follow-up and the subcohort. We used Cox proportional hazards and compared Model 1 (selected clinical predictors only to Model 2 (Model 1 plus selected markers for predicting 3-year risk of liver fibrosis using weighted Harrell's C and Net Reclassification Improvement indices.113 individuals developed significant liver fibrosis over 1300 person-years (8.63 per 100 person-years 95% CI: 7.08, 10.60. Model 1 (age, sex, current alcohol use, HIV RNA, baseline APRI, HCV genotype was nested in model 2, which also included IFNL genotype and IL-8, sICAM-1, RANTES, hsCRP, and sCD14. The C indexes (95% CI for model 1 vs. model 2 were 0.720 (0.649, 0.791 and 0.756 (0.688, 0.825, respectively. Model 2 classified risk more appropriately (overall net reclassification improvement, p<0.05.Including IFNL genotype and inflammatory markers IL-8, sICAM-1, RANTES, hs-CRP, and sCD14 enabled better prediction of the 3-year risk of significant liver fibrosis over clinical predictors alone. Whether this modest improvement in prediction justifies their additional cost requires further cost-benefit analyses.

  5. 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...

  6. Model-based equipment diagnosis

    Science.gov (United States)

    Collins, David J.; Strojwas, Andrzej J.; Mozumder, P. K.

    1994-09-01

    A versatile methodology is described in which equipment models have been incorporated into a single process diagnostic system for the PECVD of silicon nitride. The diagnosis system has been developed and tested with data collected using an Applied Materials Precision 5000 single wafer reactor. The parametric equipment diagnosis system provides the basis for optimal control of multiple process responses by the classification of potential sources of equipment faults without the assistance of in-situ sensor data. The basis for the diagnosis system is the use of tuned empirical equipment models which have been developed using a physically-based experimental design. Nine individual site-specific models were used to provide an effective method of modeling the spatially-dependent process variations across the wafer with better sensitivity than mean-based models. The diagnostic system has been tested using data that was produced by adjusting the actual equipment controls to artificially simulate a variety of possible subtle equipment drifts and shifts. Statistical algorithms have been implemented which detect equipment drift, shift and variance stability faults using the difference between the predicted process responses to the off-line measured process responses. Fault classification algorithms have been developed to classify the most likely causes for the process drifts and shifts using a pattern recognition system based upon flexible discriminant analysis.

  7. Combining Prognostic and Predictive Enrichment Strategies to Identify Children With Septic Shock Responsive to Corticosteroids.

    Science.gov (United States)

    Wong, Hector R; Atkinson, Sarah J; Cvijanovich, Natalie Z; Anas, Nick; Allen, Geoffrey L; Thomas, Neal J; Bigham, Michael T; Weiss, Scott L; Fitzgerald, Julie C; Checchia, Paul A; Meyer, Keith; Quasney, Michael; Hall, Mark; Gedeit, Rainer; Freishtat, Robert J; Nowak, Jeffrey; Raj, Shekhar S; Gertz, Shira; Lindsell, Christopher J

    2016-10-01

    Prognostic and predictive enrichment strategies are fundamental tools of precision medicine. Identifying children with septic shock who may benefit from corticosteroids remains a challenge. We combined prognostic and predictive strategies to identify a pediatric septic shock subgroup responsive to corticosteroids. We conducted a secondary analysis of 288 previously published pediatric subjects with septic shock. For prognostic enrichment, each study subject was assigned a baseline mortality probability using the pediatric sepsis biomarker risk model. For predictive enrichment, each study subject was allocated to one of two septic shock endotypes, based on a 100-gene signature reflecting adaptive immunity and glucocorticoid receptor signaling. The primary study endpoint was complicated course, defined as the persistence of two or more organ failures at day 7 of septic shock or 28-day mortality. We used logistic regression to test for an association between corticosteroids and complicated course within endotype. Among endotype B subjects at intermediate to high pediatric sepsis biomarker risk model-based risk of mortality, corticosteroids were independently associated with more than a 10-fold reduction in the risk of a complicated course (relative risk, 0.09; 95% CI, 0.01-0.54; p = 0.007). A combination of prognostic and predictive strategies based on serum protein and messenger RNA biomarkers can identify a subgroup of children with septic shock who may be more likely to benefit from corticosteroids. Prospective validation of these strategies and the existence of this subgroup are warranted.

  8. 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...

  9. Realizing the Translational Potential of Telomere Length Variation as a Tissue-Based Prognostic Marker for Prostate Cancer

    Science.gov (United States)

    2015-10-01

    488/Cy2, Alexa 568/Cy3, and Alexa 633/Cy5. The system contains an ultra -precise motorized stage for 8 slides for high throughput scanning. In addition...Kulac I, Graham MK , Joshu CE, De Marzo AM, Platz EA, Meeker AK. Tissue-based telomere length measurements as a biomarker for individualized prostate

  10. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes.

    Science.gov (United States)

    Pellagatti, Andrea; Benner, Axel; Mills, Ken I; Cazzola, Mario; Giagounidis, Aristoteles; Perry, Janet; Malcovati, Luca; Della Porta, Matteo G; Jädersten, Martin; Verma, Amit; McDonald, Emma-Jane; Killick, Sally; Hellström-Lindberg, Eva; Bullinger, Lars; Wainscoat, James S; Boultwood, Jacqueline

    2013-10-01

    The diagnosis of patients with myelodysplastic syndromes (MDS) is largely dependent on morphologic examination of bone marrow aspirates. Several criteria that form the basis of the classifications and scoring systems most commonly used in clinical practice are affected by operator-dependent variation. To identify standardized molecular markers that would allow prediction of prognosis, we have used gene expression profiling (GEP) data on CD34+ cells from patients with MDS to determine the relationship between gene expression levels and prognosis. GEP data on CD34+ cells from 125 patients with MDS with a minimum 12-month follow-up since date of bone marrow sample collection were included in this study. Supervised principal components and lasso penalized Cox proportional hazards regression (Coxnet) were used for the analysis. We identified several genes, the expression of which was significantly associated with survival of patients with MDS, including LEF1, CDH1, WT1, and MN1. The Coxnet predictor, based on expression data on 20 genes, outperformed other predictors, including one that additionally used clinical information. Our Coxnet gene signature based on CD34+ cells significantly identified a separation of patients with good or bad prognosis in an independent GEP data set based on unsorted bone marrow mononuclear cells, demonstrating that our signature is robust and may be applicable to bone marrow cells without the need to isolate CD34+ cells. We present a new, valuable GEP-based signature for assessing prognosis in MDS. GEP-based signatures correlating with clinical outcome may significantly contribute to a refined risk classification of MDS.

  11. Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example.

    Directory of Open Access Journals (Sweden)

    Klaus-Jürgen Winzer

    Full Text Available Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches.Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived.The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases.

  12. Utilizing patch and site level greenhouse-gas concentration measurements in tandem with the prognostic model, ecosys

    Science.gov (United States)

    Morin, T. H.; Rey Sanchez, C.; Bohrer, G.; Riley, W. J.; Angle, J.; Mekonnen, Z. A.; Stefanik, K. C.; Wrighton, K. C.

    2016-12-01

    Estimates of wetland greenhouse gas (GHG) budgets currently have large uncertainties. While wetlands are the largest source of natural methane (CH4) emissions worldwide, they are also important carbon dioxide (CO2) sinks. Determining the GHG budget of a wetland is challenging, particularly because wetlands have intrinsically temporally and spatially heterogeneous land cover patterns and complex dynamics of CH4 production and emissions. These issues pose challenges to both measuring and modeling GHG budgets from wetlands. To improve wetland GHG flux predictability, we utilized the ecosys model to predict CH4 fluxes from a natural temperate estuarine wetland in northern Ohio. Multiple patches of terrain (that included Typha spp. and Nelumbo lutea) were represented as separate grid cells in the model. Cells were initialized with measured values but were allowed to dynamically evolve in response to meteorological, hydrological, and thermodynamic conditions. Trace gas surface emissions were predicted as the end result of microbial activity, physical transport, and plant processes. Corresponding to each model gridcell, measurements of dissolved gas concentrations were conducted with pore-water dialysis samplers (peepers). The peeper measurements were taken via a series of tubes, providing an undisturbed observation of the pore water concentrations of in situ dissolved gases along a vertical gradient. Non-steady state chambers and a flux tower provided both patch level and integrated site-level fluxes of CO2 and CH4. New Typha chambers were also developed to enclose entire plants and segregate the plant fluxes from soil/water fluxes. We expect ecosys to predict the seasonal and diurnal fluxes of CH4 from within each land cover type and to resolve where CH4 is generated within the soil column and its transmission mechanisms. We demonstrate the need for detailed information at both the patch and site level when using models to predict whole wetland ecosystem-scale GHG

  13. Medicines Optimisation Assessment Tool (MOAT): a prognostic model to target hospital pharmacists' input to improve patient outcomes. Protocol for an observational study.

    Science.gov (United States)

    Geeson, Cathy; Wei, Li; Franklin, Bryony Dean

    2017-06-14

    Medicines optimisation is a key role for hospital pharmacists, but with ever-increasing demands on services there is a need to increase efficiency while maintaining patient safety. The aim of this study is to develop a prognostic model, the Medicines Optimisation Assessment Tool (MOAT), which can be used to target patients most in need of pharmacists' input while in hospital. The MOAT will be developed following recommendations of the Prognosis Research Strategy partnership. Using a cohort study we will prospectively include 1500 adult patients from the medical wards of two UK hospitals. Data on medication-related problems (MRPs) experienced by study patients will be collected by pharmacists at the study sites as part of their routine daily clinical assessment of patients. Data on potential risk factors such as polypharmacy, renal impairment and the use of 'high risk' medicines will be collected retrospectively from the information departments at the study sites, laboratory reporting systems and patient medical records. Multivariable logistic regression models will then be used to determine the relationship between potential risk factors and the study outcome of preventable MRPs that are at least moderate in severity. Bootstrapping will be used to adjust the MOAT for optimism, and predictive performance will be assessed using calibration and discrimination. A simplified scoring system will also be developed, which will be assessed for sensitivity and specificity. This study has been approved by the Proportionate Review Service Sub-Committee of the National Health Service Research Ethics Committee Wales REC 7 (16/WA/0016) and the Health Research Authority (project ID 197298). We plan to disseminate the results via presentations at relevant patient/public, professional, academic and scientific meetings and conferences, and will submit findings for publication in peer-reviewed journals. NCT02582463. © Article author(s) (or their employer(s) unless otherwise stated in

  14. 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.

  15. Survival rate variation with different histological subtypes of poor prognostic male anal squamous cell carcinoma: a population-based study

    Science.gov (United States)

    Rai, Kelash; Vikash, Sindhu; Chen, Liaobin; Li, Jingfeng

    2017-01-01

    Background and objective The prognosis of male anal squamous cell carcinoma (MASCC) and female anal squamous cell carcinoma (FASCC) is variable. The influence of tumor subtype on the survival rate and gender is poorly known. Our study is the largest population-based study and aims to outline the difference in survival between MASCC and FASCC patients. Methods A retrospective population-based study was performed to compare the disease-specific mortalities (DSMs) between genders related to the tumor subtypes. The Surveillance, Epidemiology, and End Results (SEER) program database was employed to obtain the data from January 1988 to December 2014. Results A total of 4,516, (3,249 males and 1,267 females), patients with anal squamous cell carcinomas (ASCC) were investigated. The 5-year DSMs were 24.18% and 18.08% for men and women, respectively. The univariate analysis of the male basaloid squamous cell carcinoma (BSCC) and cloacogenic carcinoma (CC) patients demonstrated higher DSMs (P <0.001). Moreover, in the multivariate analysis, BSCC and CC were associated with soaring DSMs in male patients (P < 0.05). Conclusions In the cohort of BSCC and CC patients, male patients demonstrated a considerable decrease in survival rate compared to females. A more precise classification of ASCC and individualized management for MASCC are warranted. PMID:29137429

  16. 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

    to 2012 including 92 patients with histologically verified high-grade BS (N = 37) or STS (N = 55). All patients underwent a pretreatment F-18 FDG PET/CT scan. Clinical data were registered. Measurements of the accuracy of metabolic tumor volume with a preset threshold of 40% of the maximum standardized...... 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...

  17. 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 OBJECTIVES: 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. STUDY DESIGN: 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. RESULTS: 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. CONCLUSIONS: 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.

  18. A novel classification of frontal bone fractures: The prognostic significance of vertical fracture trajectory and skull base extension.

    Science.gov (United States)

    Garg, Ravi K; Afifi, Ahmed M; Gassner, Jennifer; Hartman, Michael J; Leverson, Glen; King, Timothy W; Bentz, Michael L; Gentry, Lindell R

    2015-05-01

    The broad spectrum of frontal bone fractures, including those with orbital and skull base extension, is poorly understood. We propose a novel classification scheme for frontal bone fractures. Maxillofacial CT scans of trauma patients were reviewed over a five year period, and frontal bone fractures were classified: Type 1: Frontal sinus fracture without vertical extension. Type 2: Vertical fracture through the orbit without frontal sinus involvement. Type 3: Vertical fracture through the frontal sinus without orbit involvement. Type 4: Vertical fracture through the frontal sinus and ipsilateral orbit. Type 5: Vertical fracture through the frontal sinus and contralateral or bilateral orbits. We also identified the depth of skull base extension, and performed a chart review to identify associated complications. 149 frontal bone fractures, including 51 non-vertical frontal sinus (Type 1, 34.2%) and 98 vertical (Types 2-5, 65.8%) fractures were identified. Vertical fractures penetrated the middle or posterior cranial fossa significantly more often than non-vertical fractures (62.2 v. 15.7%, p = 0.0001) and had a significantly higher mortality rate (18.4 v. 0%, p fractures with frontal sinus and orbital extension, and fractures that penetrated the middle or posterior cranial fossa had the strongest association with intracranial injuries, optic neuropathy, disability, and death (p bone fractures carry a worse prognosis than frontal bone fractures without a vertical pattern. In addition, vertical fractures with extension into the frontal sinus and orbit, or with extension into the middle or posterior cranial fossa have the highest complication rate and mortality. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  19. Energy based hybrid turbulence modeling

    Science.gov (United States)

    Haering, Sigfried; Moser, Robert

    2015-11-01

    Traditional hybrid approaches exhibit deficiencies when used for fluctuating smooth-wall separation and reattachment necessitating ad-hoc delaying functions and model tuning making them no longer useful as a predictive tool. Additionally, complex geometries and flows often require high cell aspect-ratios and large grid gradients as a compromise between resolution and cost. Such transitions and inconsistencies in resolution detrimentally effect the fidelity of the simulation. We present the continued development of a new hybrid RANS/LES modeling approach specifically developed to address these challenges. In general, modeled turbulence is returned to resolved scales by reduced or negative model viscosity until a balance between theoretical and actual modeled turbulent kinetic energy is attained provided the available resolution. Anisotropy in the grid and resolved field are directly integrated into this balance. A viscosity-based correction is proposed to account for resolution inhomogeneities. Both the hybrid framework and resolution gradient corrections are energy conserving through an exchange of resolved and modeled turbulence.

  20. Model-based tomographic reconstruction

    Science.gov (United States)

    Chambers, David H; Lehman, Sean K; Goodman, Dennis M

    2012-06-26

    A model-based approach to estimating wall positions for a building is developed and tested using simulated data. It borrows two techniques from geophysical inversion problems, layer stripping and stacking, and combines them with a model-based estimation algorithm that minimizes the mean-square error between the predicted signal and the data. The technique is designed to process multiple looks from an ultra wideband radar array. The processed signal is time-gated and each section processed to detect the presence of a wall and estimate its position, thickness, and material parameters. The floor plan of a building is determined by moving the array around the outside of the building. In this paper we describe how the stacking and layer stripping algorithms are combined and show the results from a simple numerical example of three parallel walls.

  1. Prognostic value of microsatellite instability and p53 expression in metastatic colorectal cancer treated with oxaliplatin and fluoropyrimidine-based chemotherapy.

    Science.gov (United States)

    Nöpel-Dünnebacke, S; Schulmann, K; Reinacher-Schick, A; Porschen, R; Schmiegel, W; Tannapfel, A; Graeven, U

    2014-12-01

    The aim of this study was to evaluate the prognostic value of MSI-H and p53 overexpression in metastatic colorectal cancer (mCRC) treated with oxaliplatin and fluoropyrimidine-based first line chemotherapy. Tumour samples were retrospectively obtained from 229 patients from a prospective randomised phase III trial of the AIO colorectal study group, comparing CAPOX and FUFOX in mCRC. Immunohistochemistry of p53 and MMR proteins as well as microsatellite analysis were performed. The incidence of MSI-H and p53 overexpression was 7.9 % and 65.4 %, respectively. MSI-H status was not correlated with ORR, PFS and OS. We observed a trend to lower DCR for MSI-H tumours (65 % vs. 85 %, p = 0.055). p53 overexpression was not correlated with DCR, ORR and PFS. The median OS of patients with tumors with p53 overexpression was significantly longer compared to tumors withhout p53 overexpression (19.6 vs. 15.8 months; p = 0.05). The post-progression survival (PPS) of p53-positive patients undergoing 2nd and/or 3rd line chemotherapy with irinotecan and/or cetuximab was significantly longer compared to p53-negative patients. MSI-H tumours tend to have lower disease control rates when treated with an oxaliplatin/fluoropyrmidin combination. mCRC patients with p53 overexpression undergoing an irinotecan containing second- or third-line chemotherapy after oxaliplatin failure have a significantly longer post-progression survival compared to patients without p53 overexpression. To validate the clinical impact of p53 in patients with mCRC treated with irinotecan- and/or cetuximab further studies are needed. © Georg Thieme Verlag KG Stuttgart · New York.

  2. 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.

  3. 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.

  4. Multidimensional Geriatric Prognostic Index, Based on a Geriatric Assessment, for Long-Term Survival in Older Adults in Korea.

    Directory of Open Access Journals (Sweden)

    Hee-Won Jung

    Full Text Available The patient´s survival estimate is important for clinical decision-making, especially in frail patients with multimorbidities. We aimed to develop a multidimensional geriatric prognosis index (GPI for 3- and 5-year mortality in community-dwelling elderly and to validate the GPI in a separate hospital-based population. The GPI was constructed using data for 988 participants in the Korean Longitudinal Study on Health and Aging (KLoSHA and cross-validated with 1109 patients who underwent a geriatric assessment at the Seoul National University Bundang Hospital (SNUBH. The GPI, with a total possible score of 8, included age, gender, activities of daily living, instrumental activities of daily living, comorbidities, mood, cognitive function, and nutritional status. During the 5-year observation period, 179 KLoSHA participants (18.1% and 340 SNUBH patients (30.7% died. The c-indices for 3- and 5-year mortality were 0.78 and 0.80, respectively, in the KLoSHA group and 0.73 and 0.80, respectively, in the SNUBH group. Positive linear trends were observed for GPI scores and both 3- and 5-year mortality in both groups. In conclusions, using common components of a geriatric assessment, the GPI can stratify the risk of 3- and 5-year mortality in Korean elderly people both in the community and hospital.

  5. Comparison of the prognostic value of Chronic Liver Failure Consortium scores and traditional models for predicting mortality in patients with cirrhosis.

    Science.gov (United States)

    Antunes, Artur Gião; Teixeira, Cristina; Vaz, Ana Margarida; Martins, Cláudio; Queirós, Patrícia; Alves, Ana; Velasco, Francisco; Peixe, Bruno; Oliveira, Ana Paula; Guerreiro, Horácio

    2017-04-01

    Recently, the European Association for the Study of the Liver - Chronic Liver Failure (CLIF) Consortium defined two new prognostic scores, according to the presence or absence of acute-on-chronic liver failure (ACLF): the CLIF Consortium ACLF score (CLIF-C ACLFs) and the CLIF-C Acute Decompensation score (CLIF-C ADs). We sought to compare their accuracy in predicting 30- and 90-day mortality with some of the existing models: Child-Turcotte-Pugh (CTP), Model for End-Stage Liver Disease (MELD), MELD-Na, integrated MELD (iMELD), MELD to serum sodium ratio index (MESO), Refit MELD and Refit MELD-Na. Retrospective cohort study that evaluated all admissions due to decompensated cirrhosis in 2 centers between 2011 and 2014. At admission each score was assessed, and the discrimination ability was compared by measuring the area under the ROC curve (AUROC). A total of 779 hospitalizations were evaluated. Two hundred and twenty-two patients met criteria for ACLF (25.9%). The 30- and 90-day mortality were respectively 17.7 and 37.3%. CLIF-C ACLFs presented an AUROC for predicting 30- and 90-day mortality of 0.684 (95% CI: 0.599-0.770) and 0.666 (95% CI: 0.588-0.744) respectively. No statistically significant differences were found when compared to traditional models. For patients without ACLF, CLIF-C ADs had an AUROC for predicting 30- and 90-day mortality of 0.689 (95% CI: 0.614-0.763) and 0.672 (95% CI: 0.624-0.720) respectively. When compared to other scores, it was only statistically superior to MELD for predicting 30-day mortality (p=0.0296). The new CLIF-C scores were not statistically superior to the traditional models, with the exception of CLIF-C ADs for predicting 30-day mortality. Copyright © 2017 Elsevier España, S.L.U., AEEH y AEG. All rights reserved.

  6. [Development and validation of risk score model for acute myocardial infarction in China: prognostic value thereof for in hospital major adverse cardiac events and evaluation of revascularization].

    Science.gov (United States)

    Wu, Xiao-fan; Lü, Shu-zheng; Chen, Yun-dai; Pan, Wei-qi; Song, Xian-tao; Li, Jing; Liu, Xin; Wang, Xi-zhi; Zhang, Li-jie; Ren, Fang; Luo, Jing-guang

    2008-07-08

    To develop a simple risk score model of in-hospital major adverse cardiac events (MACE) including all-cause mortality, new or recurrent myocardial infarction (MI), and evaluate the efficacy about revascularization on patients with different risk. The basic characteristics, diagnosis, therapy, and in-hospital outcomes of 1512 ACS patients from Global Registry of Acute Coronary Events (GRACE) study of China were collected to develop a risk score model by multivariable stepwise logistic regression. The goodness-of-fit test and discriminative power of the final model were assessed respectively. The best cut-off value for the risk score was used to assess the impact of revascularization for ST-elevation MI (STEMI) and non-ST elevation acute coronary artery syndrome (NSTEACS) on in-hospital outcomes. (1) The following 6 independent risk factors accounted for about 92.5% of the prognostic information: age > or =80 years (4 points), SBP or =90 mm Hg (2 points), Killip II (3 points), Killip III or IV (9 points), cardiac arrest during presentation (4 points), ST-segment elevation (3 points) or depression (5 points) or combination of elevation and depression (4 points) on electrocardiogram at presentation. (2) CHIEF risk model was excellent with Hosmer-Lemeshow goodness-of-fit test of 0.673 and c statistics of 0.776. (3)1301 ACS patients previously enrolled in GRACE study were divided into 2 groups with the best cut-off value of 5.5 points. The impact of revascularization on the in-hospital MACE of the higher risk subsets was stronger than that of the lower risk subsets both in STEMI [OR (95% CI) = 0.32 (0.11, 0.94), chi2 = 5.39, P = 0.02] and NSTEACS [OR (95% CI) = 0.32 (0.06, 0.94), chi2 =4.17, P = 0.04] population. However, both STEMI (61.7% vs. 78.3%, P = 0.000) and NSTEACS (42.0% vs 62.3%, P = 0.000) patients with the risk scores more than 5.5 points had lower revascularization rates. The risk score provides excellent ability to predict in-hospital death or (re) MI

  7. Element-based prognostics of occupational pneumoconiosis using micro-proton-induced X-ray emission analysis.

    Science.gov (United States)

    He, Xiaodong; Shen, Hao; Chen, Zidan; Rong, Caicai; Ren, Minqin; Hou, Likun; Wu, Chunyan; Mao, Ling; Lu, Quan; Su, Bo

    2017-12-01

    Pneumoconiosis is an occupational disease accompanied by long-term lung impairment, for which prediction of prognosis is poorly understood because of the complexity of the inhaled particles. Micro-proton-induced X-ray emission (micro-PIXE) analysis, which is advantageous for high-sensitivity, two-dimensional element mapping of lung tissues, was used to investigate element-based predictive factors of prognosis in Chinese patients with welder's and coal miner's pneumoconiosis. Chest radiographs and lung function tests showed that most of the coal miners deteriorated, whereas symptoms in some welders were alleviated after 5 yr, as determined by comparing percent vital capacity (%VC) and forced expiratory volume in the 1st second over forced vital capacity (FEV1.0/FVC) to values taken at the initial diagnosis. Micro-PIXE analysis suggested that the most abundant particulates in welder's pneumoconiosis were Fe, Mn, and Ti (metallic oxide),which were accompanied by particulates containing Si, Al, and Ca (aluminum silicate) or only Si (SiO2); the most abundant particulates in coal miner's pneumoconiosis were composed of C, Si, Al, K, and Ti, which were accompanied by particulates containing Ca or Fe. Particulates containing Al, Si, S, K, Ca, and Ti (orthoclase and anorthite) were correlated with severity of fibrosis. Multivariable linear regression suggested that long-term FEV1.0/FVC decrease was independently associated with Si and smoking index, whereas %VC decrease was associated with Si and Ti. A risk index comprised of these factors was developed to predict the prognosis of pneumoconiosis. Micro-PIXE analysis is feasible for the evaluation of elemental composition and dust exposure, especially for patients whose exposure is mixed or uncertain. Copyright © 2017 the American Physiological Society.

  8. The impact of adjuvant therapy on contralateral breast cancer risk and the prognostic significance of contralateral breast cancer : a population based study in the Netherlands

    NARCIS (Netherlands)

    Schaapveld, Michael; Visser, Otto; Louwman, W. J.; Willemse, Pax H. B.; de Vries, Elisabeth G. E.; van der Graaf, Winette T. A.; Otter, Renee; Coebergh, Jan Willem W.; van Leeuwen, Flora E.

    Background The impact of age and adjuvant therapy on contralateral breast cancer (CBC) risk and prognostic significance of CBC were evaluated. Patients and Methods In 45,229 surgically treated stage I-IIIA patients diagnosed in the Netherlands between 1989 and 2002 CBC risk was quantified using

  9. The impact of adjuvant therapy on contralateral breast cancer risk and the prognostic significance of contralateral breast cancer: a population based study in the Netherlands.

    NARCIS (Netherlands)

    Schaapveld, M.; Visser, O.; Louwman, W.J.; Willemse, P.H.; Vries, EG de; Graaf, W.T.A. van der; Otter, R.; Coebergh, J.W.; Leeuwen, F.E. van

    2008-01-01

    BACKGROUND: The impact of age and adjuvant therapy on contralateral breast cancer (CBC) risk and prognostic significance of CBC were evaluated. PATIENTS AND METHODS: In 45,229 surgically treated stage I-IIIA patients diagnosed in the Netherlands between 1989 and 2002 CBC risk was quantified using

  10. The impact of adjuvant therapy on contralateral breast cancer risk and the prognostic significance of contralateral breast cancer: A population based study in the Netherlands

    NARCIS (Netherlands)

    M. Schaapveld (Michael); O.J. Visser (Otto); W.J. Louwman; P.H.B. Willemse (Pax); E.G.E. de Vries (Elisabeth); W.T.A. van der Graaf (Winette); R. Otter (Renée); J.W.W. Coebergh (Jan Willem); F.E. van Leeuwen (Flora)

    2008-01-01

    textabstractBackground: The impact of age and adjuvant therapy on contralateral breast cancer (CBC) risk and prognostic significance of CBC were evaluated. Patients and Methods: In 45,229 surgically treated stage I-IIIA patients diagnosed in the Netherlands between 1989 and 2002 CBC risk was

  11. Risk estimation of distant metastasis in node-negative, estrogen receptor-positive breast cancer patients using an RT-PCR based prognostic expression signature

    Directory of Open Access Journals (Sweden)

    Gray Joe

    2008-11-01

    Full Text Available Abstract Background 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. Methods 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. Results A 14-gene signature was found to be significantly associated (p Conclusion The 14-gene signature is significantly associated with risk of distant metastasis. The signature has a predominance of proliferation genes which have prognostic significance above that of Ki-67 LI and may aid in prioritizing future mechanistic studies and therapeutic interventions.

  12. 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.

  13. 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...

  14. Importance of excision repair cross-complementation group 1 and ribonucleotide reductase M1 as prognostic biomarkers in malignant pleural mesothelioma treated with platinum-based induction chemotherapy followed by surgery.

    Science.gov (United States)

    Frischknecht, Lukas; Meerang, Mayura; Soltermann, Alex; Stahel, Rolf; Moch, Holger; Seifert, Burkhardt; Weder, Walter; Opitz, Isabelle

    2015-06-01

    Survival and response to platinum-based induction chemotherapy are heterogeneous among patients with malignant pleural mesothelioma. The aim of the present study was to assess the prognostic role of DNA repair markers, such as excision repair cross-complementation group 1 and ribonucleotide reductase M1, in multimodally treated patients with malignant pleural mesothelioma. Tumor tissue of a malignant pleural mesothelioma cohort (n = 107) treated with platinum/gemcitabine (n = 46) or platinum/pemetrexed (n = 61) induction chemotherapy followed by extrapleural pneumonectomy was assembled on a tissue microarray. Immunohistochemical expression of excision repair cross-complementation group 1 (nuclear) and ribonucleotide reductase M1 (nuclear and cytoplasmic) was assessed for its prognostic impact (association with overall survival or freedom from recurrence). Patients with high nuclear ribonucleotide reductase M1 expression before chemotherapy showed significantly longer freedom from recurrence (P = .03). When specifically analyzed in the subgroup of patients receiving platinum/gemcitabine followed by extrapleural pneumonectomy, high nuclear ribonucleotide reductase M1 was associated with prolonged freedom from recurrence (P = .03) and overall survival (P = .02). Low excision repair cross-complementation group 1 expression in prechemotherapy tumor tissues was associated with significantly longer freedom from recurrence (P = .04). Nuclear ribonucleotide reductase M1 and excision repair cross-complementation group 1 were independent prognosticators of freedom from recurrence in addition to pT stage in multivariate analysis. In the present study, nuclear ribonucleotide reductase M1 and excision repair cross-complementation group 1 expression were identified as independent prognosticators for freedom from recurrence of malignant pleural mesothelioma in patients undergoing induction chemotherapy followed by extrapleural pneumonectomy. Copyright © 2015 The American

  15. 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.

  16. Prognostic factors and outcomes for osteosarcoma: an international collaboration

    NARCIS (Netherlands)

    Pakos, Emilios E.; Nearchou, Andreas D.; Grimer, Robert J.; Koumoullis, Haris D.; Abudu, Adesegun; Bramer, Jos A. M.; Jeys, Lee M.; Franchi, Alessandro; Scoccianti, Guido; Campanacci, Domenico; Capanna, Rodolfo; Aparicio, Jorge; Tabone, Marie-Dominique; Holzer, Gerold; Abdolvahab, Fashid; Funovics, Philipp; Dominkus, Martin; Ilhan, Inci; Berrak, Su G.; Patino-Garcia, Ana; Sierrasesumaga, Luis; San-Julian, Mikel; Garraus, Moira; Petrilli, Antonio Sergio; Filho, Reynaldo Jesus Garcia; Macedo, Carla Renata Pacheco Donato; Alves, Maria Teresa de Seixas; Seiwerth, Sven; Nagarajan, Rajaram; Cripe, Timothy P.; Ioannidis, John P. A.

    2009-01-01

    We aimed to evaluate the prognostic significance of traditional clinical predictors in osteosarcoma through an international collaboration of 10 teams of investigators (2680 patients) who participated. In multivariate models the mortality risk increased with older age, presence of metastatic disease

  17. 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.

  18. 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.

  19. Prognostics Approach For Power Mosfet Under Thermal-Stress Aging

    Data.gov (United States)

    National Aeronautics and Space Administration — 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...

  20. 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.

  1. Prognostic factors in oligodendrogliomas

    DEFF Research Database (Denmark)

    Westergaard, L; Gjerris, F; Klinken, L

    1997-01-01

    .5 years and for the group older than 60 years of 13 months. The group without neurological deficits had a 5-years survival of 43 per cent while the group with deficits had a 5-years survival of 5 per cent. The 5-years survival for oligodendroglioma of grade II was 46 per cent and for grade III 10 per cent......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...

  2. 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...

  3. 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.

  4. Research on BOM based composable modeling method

    NARCIS (Netherlands)

    Zhang, M.; He, Q.; Gong, J.

    2013-01-01

    Composable modeling method has been a research hotpot in the area of Modeling and Simulation for a long time. In order to increase the reuse and interoperability of BOM based model, this paper put forward a composable modeling method based on BOM, studied on the basic theory of composable modeling

  5. 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.

  6. 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....

  7. Requirements Specifications for Prognostics: An Overview

    Data.gov (United States)

    National Aeronautics and Space Administration — With recent advancements in prognostics methodologies there has been a significant interest in maturing Prognostics and Health Management (PHM) to increase its...

  8. On Applying the Prognostic Performance Metrics

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics performance evaluation has gained significant attention in the past few years. *As prognostics technology matures and more sophisticated methods for...

  9. Metrics for Offline Evaluation of Prognostic Performance

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostic performance evaluation has gained significant attention in the past few years.*Currently, prognostics concepts lack standard definitions and suffer from...

  10. Development of an On-board Failure Diagnostics and Prognostics System for Solid Rocket Booster

    Science.gov (United States)

    Smelyanskiy, Vadim N.; Luchinsky, Dmitry G.; Osipov, Vyatcheslav V.; Timucin, Dogan A.; Uckun, Serdar

    2009-01-01

    We develop a case breach model for the on-board fault diagnostics and prognostics system for subscale solid-rocket boosters (SRBs). The model development was motivated by recent ground firing tests, in which a deviation of measured time-traces from the predicted time-series was observed. A modified model takes into account the nozzle ablation, including the effect of roughness of the nozzle surface, the geometry of the fault, and erosion and burning of the walls of the hole in the metal case. The derived low-dimensional performance model (LDPM) of the fault can reproduce the observed time-series data very well. To verify the performance of the LDPM we build a FLUENT model of the case breach fault and demonstrate a good agreement between theoretical predictions based on the analytical solution of the model equations and the results of the FLUENT simulations. We then incorporate the derived LDPM into an inferential Bayesian framework and verify performance of the Bayesian algorithm for the diagnostics and prognostics of the case breach fault. It is shown that the obtained LDPM allows one to track parameters of the SRB during the flight in real time, to diagnose case breach fault, and to predict its values in the future. The application of the method to fault diagnostics and prognostics (FD&P) of other SRB faults modes is discussed.

  11. A Novel Inflammation- and Nutrition-Based Prognostic System for Patients with Laryngeal Squamous Cell Carcinoma: Combination of Red Blood Cell Distribution Width and Body Mass Index (COR-BMI)

    OpenAIRE

    Yan Fu; Yize Mao; Shiqi Chen; Ankui Yang; Quan Zhang

    2016-01-01

    Background Laryngeal squamous cell carcinoma (LSCC) is a head and neck cancer type. In this study, we introduced a novel inflammation- and nutrition-based prognostic system, referred to as COR-BMI (Combination of red blood cell distribution width and body mass index), for LSCC patients. Methods A total of 807 LSCC patients (784 male and 23 female, 22?87 y of age) who underwent surgery were enrolled in this retrospective cohort study. The patients were stratified by COR-BMI into three groups: ...

  12. Improved risk stratification by the integration of the revised international prognostic scoring system with the myelodysplastic syndromes comorbidity index.

    Science.gov (United States)

    van Spronsen, M F; Ossenkoppele, G J; Holman, R; van de Loosdrecht, A A

    2014-12-01

    Myelodysplastic syndromes (MDS) comprise bone marrow failure diseases with a diverse clinical outcome. For improved risk stratification, the International Prognostic Scoring System (IPSS) has recently been revised (IPSS-R). This single-centre study aimed to validate the IPSS-R and to evaluate prior prognostic scoring systems for MDS. We retrospectively analysed 363 patients diagnosed with MDS according to the FAB criteria between 2000 and 2012. The IPSS, MD Anderson Risk Model Score (MDAS), World Health Organisation (WHO)-classification based Prognostic Scoring System (WPSS), refined WPSS (WPSS-R), IPSS-R and MDS-Comorbidity Index (MDS-CI) were applied to 222 patients considered with primary MDS following the WHO criteria and their prognostic power was investigated. According to the IPSS-R, 18 (8%), 81 (37%), 50 (23%), 43 (19%) and 30 (13%) patients were classified as very low, low, intermediate, high and very high risk with, respectively, a median overall survival of 96 (95% Confidence interval (CI) not reached), 49 (95% CI 34-64), 22 (95% CI 0-49), 19 (95% CI 11-27) and 10 (95% CI 6-13) months (pMDS-CI refined the risk stratification of MDS patients stratified according to the IPSS-R. In conclusion, accounting for the disease status by means of the IPSS-R and comorbidity through the MDS-CI considerably improves the prognostic assessment in MDS patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Gene expression analysis of a Helicobacter pylori-infected and high-salt diet-treated mouse gastric tumor model: identification of CD177 as a novel prognostic factor in patients with gastric cancer.

    Science.gov (United States)

    Toyoda, Takeshi; Tsukamoto, Tetsuya; Yamamoto, Masami; Ban, Hisayo; Saito, Noriko; Takasu, Shinji; Shi, Liang; Saito, Ayumi; Ito, Seiji; Yamamura, Yoshitaka; Nishikawa, Akiyoshi; Ogawa, Kumiko; Tanaka, Takuji; Tatematsu, Masae

    2013-07-30

    Helicobacter pylori (H. pylori) infection and excessive salt intake are known as important risk factors for stomach cancer in humans. However, interactions of these two factors with gene expression profiles during gastric carcinogenesis remain unclear. In the present study, we investigated the global gene expression associated with stomach carcinogenesis and prognosis of human gastric cancer using a mouse model. To find candidate genes involved in stomach carcinogenesis, we firstly constructed a carcinogen-induced mouse gastric tumor model combined with H. pylori infection and high-salt diet. C57BL/6J mice were given N-methyl-N-nitrosourea in their drinking water and sacrificed after 40 weeks. Animals of a combination group were inoculated with H. pylori and fed a high-salt diet. Gene expression profiles in glandular stomach of the mice were investigated by oligonucleotide microarray. Second, we examined an availability of the candidate gene as prognostic factor for human patients. Immunohistochemical analysis of CD177, one of the up-regulated genes, was performed in human advanced gastric cancer specimens to evaluate the association with prognosis. The multiplicity of gastric tumor in carcinogen-treated mice was significantly increased by combination of H. pylori infection and high-salt diet. In the microarray analysis, 35 and 31 more than two-fold up-regulated and down-regulated genes, respectively, were detected in the H. pylori-infection and high-salt diet combined group compared with the other groups. Quantitative RT-PCR confirmed significant over-expression of two candidate genes including Cd177 and Reg3g. On immunohistochemical analysis of CD177 in human advanced gastric cancer specimens, over-expression was evident in 33 (60.0%) of 55 cases, significantly correlating with a favorable prognosis (P = 0.0294). Multivariate analysis including clinicopathological factors as covariates revealed high expression of CD177 to be an independent prognostic factor

  14. 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

  15. Product modelling for model-based maintenance

    NARCIS (Netherlands)

    van Houten, Frederikus J.A.M.; Tomiyama, T.; Salomons, O.W.

    1998-01-01

    The paper describes the fundamental concepts of maintenance and the role that information technology can play in the support of maintenance activities. Function-Behaviour-State modelling is used to describe faults and deterioration of mechanisms in terms of user perception and measurable quantities.

  16. 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.

  17. MGMT Gene Promoter Methylation as a Potent Prognostic Factor in Glioblastoma Treated With Temozolomide-Based Chemoradiotherapy: A Single-Institution Study

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Young Suk [Department of Radiation Oncology, Yonsei University College of Medicine, Yonsei University Health System, Seoul (Korea, Republic of); Kim, Se Hoon [Department of Pathology, Yonsei University College of Medicine, Yonsei University Health System, Seoul (Korea, Republic of); Cho, Jaeho; Kim, Jun Won [Department of Radiation Oncology, Yonsei University College of Medicine, Yonsei University Health System, Seoul (Korea, Republic of); Chang, Jong Hee; Kim, Dong Suk; Lee, Kyu Sung [Department of Neurosurgery, Yonsei University College of Medicine, Yonsei University Health System, Seoul (Korea, Republic of); Suh, Chang-Ok, E-mail: cosuh317@yuhs.ac [Department of Radiation Oncology, Yonsei University College of Medicine, Yonsei University Health System, Seoul (Korea, Republic of)

    2012-11-01

    Purpose: Recently, cells deficient in O{sup 6}-methylguanine-DNA methyltransferase (MGMT) were found to show increased sensitivity to temozolomide (TMZ). We evaluated whether hypermethylation of MGMT was associated with survival in patients with glioblastoma multiforme (GBM). Methods and Materials: We retrospectively analyzed 93 patients with histologically confirmed GBM who received involved-field radiotherapy with TMZ from 2001 to 2008. The median age was 58 years (range, 24-78 years). Surgical resection was total in 39 patients (42%), subtotal in 30 patients (32%), and partial in 17 patients (18%); only a biopsy was performed in 7 patients (8%). Postoperative radiotherapy began within 3 weeks of surgery in 87% of the patients. Radiotherapy doses ranged from 50 to 74 Gy (median, 70 Gy). MGMT gene methylation was determined in 78 patients; MGMT was unmethylated in 43 patients (55%) and methylated in 35 patients (45%). The median follow-up period was 22 months (range, 3-88 months) for all patients. Results: The median overall survival (OS) was 22 months, and progression-free survival (PFS) was 11 months. MGMT gene methylation was an independently significant prognostic factor for both OS (p = 0.002) and PFS (p = 0.008) in multivariate analysis. The median OS was 29 months for the methylated group and 20 months for the unmethylated group. In 35 patients with methylated MGMT genes, the 2-year and 5-year OS rates were 54% and 31%, respectively. Six patients with combined prognostic factors of methylated MGMT genes, age {<=}50 years, and total/subtotal resections are all alive 38 to 77 months after operation, whereas the median OS in 8 patients with unmethylated MGMT genes, age >50 years, and less than subtotal resection was 13.2 months. Conclusion: We confirmed that MGMT gene methylation is a potent prognostic factor in patients with GBM. Our results suggest that early postoperative radiotherapy and a high total/subtotal resection rate might further improve the

  18. 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.

  19. 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.

  20. 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...... on the intermediate shafts inside the gearbox. An angular velocity error function is defined and compared in the faulty and fault-free conditions in frequency domain. Faults can be detected from the change in the energy level of the frequency spectrum of an error function. The method is demonstrated by detecting...... 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...

  1. Does the modified Glasgow Prognostic Score (mGPS) have a prognostic role in esophageal cancer?

    Science.gov (United States)

    Walsh, Siun M; Casey, Sarah; Kennedy, Raymond; Ravi, Narayanasamy; Reynolds, John V

    2016-06-01

    The modified Glasgow Prognostic Score (mGPS), which combines indices of decreased plasma albumin and elevated CRP, has reported independent prognostic significance in colorectal cancer, but its value in upper gastrointestinal cancer is unclear. The aim of this study was to assess the prognostic significance of mGPS in patients with operable esophageal malignancy. Patients undergoing resection with curative intent between January 2008 and June 2013 were included. The mGPS was scored as 0, 1, or 2 based on CRP(>10 mg/L) and albumin(<35g/L). The mGPS score (0 vs. 1/2 combined) was correlated with patient and tumor characteristics, and operative and oncologic outcomes. Two hundred and twenty-three patients were included. Median (range) follow-up was 21(12-70) months. The mGPS was 0 in 174 patients(78%). mGPS was significantly associated with positive nodal status(P = 0.008) and stage ≥III (P = 0.017). There was a significant improvement in overall survival in patients with mGPS = 0 (47.8 vs. 37.5 months, P = 0.014) but in multivariate analysis, only TNM-stage and nodal status were found to be independent prognostic indicators. mGPS is associated with advanced stage but has no independent prognostic significance and does not impact on operative outcomes. Consequently, this data does not support its routine application in patient selection or prognostication. J. Surg. Oncol. 2016;113:732-737. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  2. Risk estimation of distant metastasis in node-negative, estrogen receptor-positive breast cancer patients using an RT-PCR based prognostic expression signature

    Science.gov (United States)

    Tutt, Andrew; Wang, Alice; Rowland, Charles; Gillett, Cheryl; Lau, Kit; Chew, Karen; Dai, Hongyue; Kwok, Shirley; Ryder, Kenneth; Shu, Henry; Springall, Robert; Cane, Paul; McCallie, Blair; Kam-Morgan, Lauren; Anderson, Steve; Buerger, Horst; Gray, Joe; Bennington, James; Esserman, Laura; Hastie, Trevor; Broder, Samuel; Sninsky, John; Brandt, Burkhard; Waldman, Fred

    2008-01-01

    Background 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. Methods 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. Results 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). Conclusion The 14

  3. 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.

  4. gis-based hydrological model based hydrological model upstream

    African Journals Online (AJOL)

    eobe

    er river catchments in Nigeria graphical data [2]. A spatial hydrology which simulates the water flow and pecified region of the earth using GIS. In view of this, the use of modeling with GIS provides the platform to processes tailored towards hydrologic dely applied hydrological models for in recent time is the Soil and Water.

  5. 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....

  6. A Novel Inflammation- and Nutrition-Based Prognostic System for Patients with Laryngeal Squamous Cell Carcinoma: Combination of Red Blood Cell Distribution Width and Body Mass Index (COR-BMI).

    Science.gov (United States)

    Fu, Yan; Mao, Yize; Chen, Shiqi; Yang, Ankui; Zhang, Quan

    Laryngeal squamous cell carcinoma (LSCC) is a head and neck cancer type. In this study, we introduced a novel inflammation- and nutrition-based prognostic system, referred to as COR-BMI (Combination of red blood cell distribution width and body mass index), for LSCC patients. A total of 807 LSCC patients (784 male and 23 female, 22-87 y of age) who underwent surgery were enrolled in this retrospective cohort study. The patients were stratified by COR-BMI into three groups: COR-BMI (0) (RDW ≤ 13.1 and BMI ≥ 25); COR-BMI (1) (RDW ≤ 13.1 and BMI 13.1 and 18.5 ≤ BMI 13.1 and BMI cancer-specific survival (CSS) rate among LSCC patients. The 5-y, 10-y, and 15-y CSS rates were 71.6%, 60.1%, and 55.4%, respectively. There were significant differences among the COR-BMI groups in age (nutrition-based prognostic system, which could predict long-term survival in LSCC patients who underwent surgery.

  7. Trace-Based Code Generation for Model-Based Testing

    NARCIS (Netherlands)

    Kanstrén, T.; Piel, E.; Gross, H.G.

    2009-01-01

    Paper Submitted for review at the Eighth International Conference on Generative Programming and Component Engineering. Model-based testing can be a powerful means to generate test cases for the system under test. However, creating a useful model for model-based testing requires expertise in the

  8. Data assimilation and prognostic whole ice sheet modelling with the variationally derived, higher order, open source, and fully parallel ice sheet model VarGlaS

    Directory of Open Access Journals (Sweden)

    D. J. Brinkerhoff

    2013-07-01

    Full Text Available We introduce a novel, higher order, finite element ice sheet model called VarGlaS (Variational Glacier Simulator, which is built on the finite element framework FEniCS. Contrary to standard procedure in ice sheet modelling, VarGlaS formulates ice sheet motion as the minimization of an energy functional, conferring advantages such as a consistent platform for making numerical approximations, a coherent relationship between motion and heat generation, and implicit boundary treatment. VarGlaS also solves the equations of enthalpy rather than temperature, avoiding the solution of a contact problem. Rather than include a lengthy model spin-up procedure, VarGlaS possesses an automated framework for model inversion. These capabilities are brought to bear on several benchmark problems in ice sheet modelling, as well as a 500 yr simulation of the Greenland ice sheet at high resolution. VarGlaS performs well in benchmarking experiments and, given a constant climate and a 100 yr relaxation period, predicts a mass evolution of the Greenland ice sheet that matches present-day observations of mass loss. VarGlaS predicts a thinning in the interior and thickening of the margins of the ice sheet.

  9. Survival after resection of perihilar cholangiocarcinoma-development and external validation of a prognostic nomogram.

    Science.gov (United States)

    Groot Koerkamp, B; Wiggers, J K; Gonen, M; Doussot, A; Allen, P J; Besselink, M G H; Blumgart, L H; Busch, O R C; D'Angelica, M I; DeMatteo, R P; Gouma, D J; Kingham, T P; van Gulik, T M; Jarnagin, W R

    2015-09-01

    The objective of this study was to derive and validate a prognostic nomogram to predict disease-specific survival (DSS) after a curative intent resection of perihilar cholangiocarcinoma (PHC). A nomogram was developed from 173 patients treated at Memorial Sloan Kettering Cancer Center (MSKCC), New York, USA. The nomogram was externally validated in 133 patients treated at the Academic Medical Center (AMC), Amsterdam, The Netherlands. Prognostic accuracy was assessed with concordance estimates and calibration, and compared with the American Joint Committee on Cancer (AJCC) staging system. The nomogram will be available as web-based calculator at mskcc.org/nomograms. For all 306 patients, the median overall survival (OS) was 40 months and the median DSS 41 months. Median follow-up for patients alive at last follow-up was 48 months. Lymph node involvement, resection margin status, and tumor differentiation were independent prognostic factors in the derivation cohort (MSKCC). A nomogram with these prognostic factors had a concordance index of 0.73 compared with 0.66 for the AJCC staging system. In the validation cohort (AMC), the concordance index was 0.72, compared with 0.60 for the AJCC staging system. Calibration was good in the derivation cohort; in the validation cohort patients had a better median DSS than predicted by the model. The proposed nomogram to predict DSS after curative intent resection of PHC had a better prognostic accuracy than the AJCC staging system. Calibration was suboptimal because DSS differed between the two institutions. The nomogram can inform patients and physicians, guide shared decision making for adjuvant therapy, and stratify patients in future randomized, controlled trials. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  10. Model-Based Testing of Probabilistic Systems

    NARCIS (Netherlands)

    Gerhold, Marcus; Stoelinga, Mariëlle Ida Antoinette; Stevens, Perdita; Wasowski, Andzej

    This paper presents a model-based testing framework for probabilistic systems. We provide algorithms to generate, execute and evaluate test cases from a probabilistic requirements model. In doing so, we connect ioco-theory for model-based testing and statistical hypothesis testing: our ioco-style

  11. Multidimensional Prognostic Index in Association with Future Mortality and Number of Hospital Days in a Population-Based Sample of Older Adults: Results of the EU Funded MPI_AGE Project.

    Science.gov (United States)

    Angleman, Sara B; Santoni, Giola; Pilotto, Alberto; Fratiglioni, Laura; Welmer, Anna-Karin

    2015-01-01

    The Multidimensional Prognostic Index (MPI) has been found to predict mortality in patients with a variety of clinical conditions. We aimed to assess the association of the MPI with future mortality and number of in-hospital days for the first time in a population-based cohort. The study population consisted of 2472 persons, aged 66-99 years, from the Swedish National Study on Aging and Care in Kungsholmen, Sweden, who underwent the baseline visit 2001-4, and were followed up >10 years for in-hospital days and >12 years for mortality. The MPI was a modified version of the original and aggregated seven domains (personal and instrumental activities of daily living, cognitive function, illness severity and comorbidity, number of medications, co-habitation status, and nutritional status). The MPI score was divided into risk groups: low, medium and high. Number of in-hospital days (within 1, 3 and 10 years) and mortality data were derived from official registries. All analyses were age-stratified (sexagenarians, septuagenarians, octogenarians, nonagenarians). During the follow-up 1331 persons (53.8%) died. Laplace regression models, suggested that median survival in medium risk groups varied by age from 2.2-3.6 years earlier than for those in the corresponding low risk groups (p = 0.002-p<0.001), and median survival in high risk groups varied by age from 3.8-9.0 years earlier than for corresponding low risk groups (p<0.001). For nonagenarians, the median age at death was 3.8 years earlier in the high risk group than for the low risk group (p<0.001). The mean number of in-hospital days increased significantly with higher MPI risk score within 1 and 3 years for people of each age group. For the first time, the effectiveness of MPI has been verified in a population-based cohort. Higher MPI risk scores associated with more days in hospital and with fewer years of survival, across a broad and stratified age range.

  12. Multidimensional Prognostic Index in Association with Future Mortality and Number of Hospital Days in a Population-Based Sample of Older Adults: Results of the EU Funded MPI_AGE Project.

    Directory of Open Access Journals (Sweden)

    Sara B Angleman

    Full Text Available The Multidimensional Prognostic Index (MPI has been found to predict mortality in patients with a variety of clinical conditions. We aimed to assess the association of the MPI with future mortality and number of in-hospital days for the first time in a population-based cohort.The study population consisted of 2472 persons, aged 66-99 years, from the Swedish National Study on Aging and Care in Kungsholmen, Sweden, who underwent the baseline visit 2001-4, and were followed up >10 years for in-hospital days and >12 years for mortality. The MPI was a modified version of the original and aggregated seven domains (personal and instrumental activities of daily living, cognitive function, illness severity and comorbidity, number of medications, co-habitation status, and nutritional status. The MPI score was divided into risk groups: low, medium and high. Number of in-hospital days (within 1, 3 and 10 years and mortality data were derived from official registries. All analyses were age-stratified (sexagenarians, septuagenarians, octogenarians, nonagenarians.During the follow-up 1331 persons (53.8% died. Laplace regression models, suggested that median survival in medium risk groups varied by age from 2.2-3.6 years earlier than for those in the corresponding low risk groups (p = 0.002-p<0.001, and median survival in high risk groups varied by age from 3.8-9.0 years earlier than for corresponding low risk groups (p<0.001. For nonagenarians, the median age at death was 3.8 years earlier in the high risk group than for the low risk group (p<0.001. The mean number of in-hospital days increased significantly with higher MPI risk score within 1 and 3 years for people of each age group.For the first time, the effectiveness of MPI has been verified in a population-based cohort. Higher MPI risk scores associated with more days in hospital and with fewer years of survival, across a broad and stratified age range.

  13. 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

  14. 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...

  15. Standardizing Research Methods for Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics and health management (PHM) is a maturing system engineering discipline. As with most maturing disciplines, PHM does not yet have a universally accepted...

  16. 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

  17. 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.

  18. Vehicle Integrated Prognostic Reasoner (VIPR) 2010 Annual Final Report

    Science.gov (United States)

    Hadden, George D.; Mylaraswamy, Dinkar; Schimmel, Craig; Biswas, Gautam; Koutsoukos, Xenofon; Mack, Daniel

    2011-01-01

    Honeywell's Central Maintenance Computer Function (CMCF) and Aircraft Condition Monitoring Function (ACMF) represent the state-of-the art in integrated vehicle health management (IVHM). Underlying these technologies is a fault propagation modeling system that provides nose-to-tail coverage and root cause diagnostics. The Vehicle Integrated Prognostic Reasoner (VIPR) extends this technology to interpret evidence generated by advanced diagnostic and prognostic monitors provided by component suppliers to detect, isolate, and predict adverse events that affect flight safety. This report describes year one work that included defining the architecture and communication protocols and establishing the user requirements for such a system. Based on these and a set of ConOps scenarios, we designed and implemented a demonstration of communication pathways and associated three-tiered health management architecture. A series of scripted scenarios showed how VIPR would detect adverse events before they escalate as safety incidents through a combination of advanced reasoning and additional aircraft data collected from an aircraft condition monitoring system. Demonstrating VIPR capability for cases recorded in the ASIAS database and cross linking them with historical aircraft data is planned for year two.

  19. Base Flow Model Validation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The innovation is the systematic "building-block" validation of CFD/turbulence models employing a GUI driven CFD code (RPFM) and existing as well as new data sets to...

  20. 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

  1. 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.

  2. 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....

  3. 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.

  4. Prognostic scoring system for peripheral nerve repair in the upper extremity.

    Science.gov (United States)

    Galanakos, Spyridon P; Zoubos, Aristides B; Mourouzis, Iordanis; Ignatiadis, Ioannis; Bot, Arjan G J; Soucacos, Panayotis N

    2013-02-01

    So far, predictive models with individualized estimates of prognosis for patients with peripheral nerve injuries are lacking. Our group has previously shown the prognostic value of a standardized scoring system by examining the functional outcome after acute, sharp complete laceration and repair of median and/or ulnar nerves at various levels in the forearm. In the present study, we further explore the potential mathematical model in order to devise an effective prognostic scoring system. We retrospectively collected medical record data of 73 cases with a peripheral nerve injury in the upper extremity in order to estimate which patients would return to work, and what time was necessary to return to the pre-injury work. Postoperative assessment followed the protocol described by Rosén and Lundborg. We found that return to pre-injury work can be predicted with high sensitivity (100%) and specificity (95%) using the total numerical score of the Rosén and Lundborg protocol at the third follow-up interval (TS3) as well as the difference between the TS3 and the total score at second follow-up interval (TS2). In addition, the factors age and type of injured nerve (median, ulnar, or combined) can determine the time of return to work based on a mathematical model. This prognostic protocol can be a useful tool to provide information about the functional and social prospects of the patients with these types of injuries. Copyright © 2012 Wiley Periodicals, Inc.

  5. 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.

  6. 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...... 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....

  7. Modelling of acid-base equilibria.

    Science.gov (United States)

    Jabor, A; Kazda, A

    1995-01-01

    A quantitative evaluation of metabolic acid-base component is described. The model is based on Stewart's analysis of acid-base chemistry. The metabolic component of acid-base disturbances is divided into four partial metabolic disorders; they can result from abnormal concentrations of chloride, albumin and phosphate disturbances, or from appearance of abnormal unidentified strong anions. The efficiency of the model is sufficient, quantitative partial results are given in the same units as base excess. In complex acid-base disturbances, such as are seen in critically ill patients, a detailed analysis of the specific components of the metabolic acid-base status allows one to plan specific therapeutic interventions.

  8. Prognostic impact of autophagy biomarkers for cutaneous melanoma.

    Directory of Open Access Journals (Sweden)

    Diana Yao Li Tang

    2016-11-01

    Full Text Available Prognosis and survival for malignant melanoma is highly dependent on early diagnosis and treatment. While the American Joint Committee on Cancer (AJCC criteria provides a means of staging melanomas and guiding treatment approaches, it is unable to identify the risk of disease progression of early stage tumours or provide reliable stratification for novel adjuvant therapies. The demand for credible prognostic/companion biomarkers able to identify high risk melanoma subgroups as well as guide more effective personalised/precision based therapy is therefore of paramount importance. Autophagy, the principle lysosomal-mediated process for the degradation/recycling of cellular debris, is a hot topic in cancer medicine and observations of its deregulation in melanoma have brought its potential as a prognostic biomarker to the forefront of current research. Key regulatory proteins, including Atg8/microtubule-associated light chain 3 (LC3 and BECN1 (Beclin 1 have been proposed as potential prognostic biomarkers. However, given the dynamic nature of autophagy, their expression in vitro does not translate to their use as a prognostic biomarker for melanoma in vivo. We have recently identified the expression levels of Sequestosome1/SQSTM1 (p62 and activating molecule in Beclin 1 regulated autophagy protein 1 (AMBRA1 as novel independent prognostic biomarkers for early stage melanomas. While increasing followed by subsequent decreasing levels of p62 expression reflects the paradoxical role of autophagy in melanoma, expression levels additionally define a novel prognostic biomarker for AJCC stage II tumours. Conversely, loss of AMBRA1 in the epidermis overlying primary melanomas defines a novel prognostic biomarker for AJCC stage I tumours. Collectively, the definition of AMBRA1 and p62 as prognostic biomarkers for early stage melanomas provides novel and accurate means through which to identify tumours at risk of disease progression, facilitating earlier

  9. Prognostic Impact of Autophagy Biomarkers for Cutaneous Melanoma.

    Science.gov (United States)

    Tang, Diana Y L; Ellis, Robert A; Lovat, Penny E

    2016-01-01

    Prognosis and survival for malignant melanoma is highly dependent on early diagnosis and treatment. While the American Joint Committee on Cancer (AJCC) criterion provides a means of staging melanomas and guiding treatment approaches, it is unable to identify the risk of disease progression of early stage tumors or provide reliable stratification for novel adjuvant therapies. The demand for credible prognostic/companion biomarkers able to identify high-risk melanoma subgroups as well as guide more effective personalized/precision-based therapy is therefore of paramount importance. Autophagy, the principle lysosomal-mediated process for the degradation/recycling of cellular debris, is a hot topic in cancer medicine, and observations of its deregulation in melanoma have brought its potential as a prognostic biomarker to the forefront of current research. Key regulatory proteins, including Atg8/microtubule-associated light chain 3 (LC3) and BECN1 (Beclin 1), have been proposed as potential prognostic biomarkers. However, given the dynamic nature of autophagy, their expression in vitro does not translate to their use as a prognostic biomarker for melanoma in vivo. We have recently identified the expression levels of Sequestosome1/SQSTM1 (p62) and activating molecule in Beclin 1-regulated autophagy protein 1 (AMBRA1) as novel independent prognostic biomarkers for early stage melanomas. While increasing followed by subsequent decreasing levels of p62 expression reflects the paradoxical role of autophagy in melanoma, expression levels additionally define a novel prognostic biomarker for AJCC stage II tumors. Conversely, loss of AMBRA1 in the epidermis overlying primary melanomas defines a novel prognostic biomarker for AJCC stage I tumors. Collectively, the definition of AMBRA1 and p62 as prognostic biomarkers for early stage melanomas provides novel and accurate means through which to identify tumors at risk of disease progression, facilitating earlier patient therapeutic

  10. Prognostic Analysis of the Tactical Quiet Generator

    Energy Technology Data Exchange (ETDEWEB)

    Hively, Lee M [ORNL

    2008-09-01

    The U.S. Army needs prognostic analysis of mission-critical equipment to enable condition-based maintenance before failure. ORNL has developed and patented prognostic technology that quantifies condition change from noisy, multi-channel, time-serial data. This report describes an initial application of ORNL's prognostic technology to the Army's Tactical Quiet Generator (TQG), which is designed to operate continuously at 10 kW. Less-than-full power operation causes unburned fuel to accumulate on internal components, thereby degrading operation and eventually leading to failure. The first objective of this work was identification of easily-acquired, process-indicative data. Two types of appropriate data were identified, namely output-electrical current and voltage, plus tri-axial acceleration (vibration). The second objective of this work was data quality analysis to avoid the garbage-in-garbage-out syndrome. Quality analysis identified more than 10% of the current data as having consecutive values that are constant, or that saturate at an extreme value. Consequently, the electrical data were not analyzed further. The third objective was condition-change analysis to indicate operational stress under non-ideal operation and machine degradation in proportion to the operational stress. Application of ORNL's novel phase-space dissimilarity measures to the vibration power quantified the rising operational stress in direct proportion to the less-than-full-load power. We conclude that ORNL's technology is an excellent candidate to meet the U.S. Army's need for equipment prognostication.

  11. Prognostic value of perinodal lymphovascular invasion following radical cystectomy for lymph node-positive urothelial carcinoma.

    Science.gov (United States)

    Fritsche, Hans-Martin; May, Matthias; Denzinger, Stefan; Otto, Wolfgang; Siegert, Sabine; Giedl, Christian; Giedl, Johannes; Eder, Fabian; Agaimy, Abbas; Novotny, Vladimir; Wirth, Manfred; Stief, Christian; Brookman-May, Sabine; Hofstädter, Ferdinand; Gierth, Michael; Aziz, Atiqullah; Kocot, Arkadius; Riedmiller, Hubertus; Bastian, Patrick J; Toma, Marieta; Wieland, Wolf F; Hartmann, Arndt; Burger, Maximilian

    2013-04-01

    Metastasis of urothelial carcinoma of the bladder (UCB) into regional lymph nodes (LNs) is a key prognosticator for cancer-specific survival (CSS) after radical cystectomy (RC). Perinodal lymphovascular invasion (pnLVI) has not yet been defined. To assess the prognostic value of histopathologic prognostic factors, especially pnLVI, on survival. A total of 598 patients were included in a prospective multicentre study after RC for UCB without distant metastasis and neoadjuvant and/or adjuvant chemotherapy. En bloc resection and histopathologic evaluation of regional LNs were performed based on a prospective protocol. The final study group comprised 158 patients with positive LNs (26.4%). Histopathologic analysis was performed based on prospectively defined morphologic criteria of LN metastases. Multivariable Cox proportional hazard regression models determined prognostic impact of clinical and histopathologic variables (age, gender, tumour stage, surgical margin status, pN, diameter of LN metastasis, LN density [LND], extranodal extension [ENE], pnLVI) on CSS. The median follow-up was 20 mo (interquartile range: 11-38). Thirty-one percent of patients were staged pN1, and 69% were staged pN2/3. ENE and pnLVI was present in 52% and 39%, respectively. CSS rates after 1 yr, 3 yr, and 5 yr were 77%, 44%, and 27%, respectively. Five-year CSS rates in patients with and without pnLVI were 16% and 34% (pCox model, the only parameters that were significant for CSS were pnLVI (hazard ratio: 2.47; p=0.003) and pT stage. However, pnLVI demonstrated only a minimal gain in predictive accuracy (0.1%; p=0.856), and the incremental accuracy of prediction is of uncertain clinical value. We present the first explorative study on the prognostic impact of pnLVI. In contrast to other parameters that show the extent of LN metastasis, pnLVI is an independent prognosticator for CSS. Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  12. Computer Based Modelling and Simulation

    Indian Academy of Sciences (India)

    Likewise, ships and buildings are built by naval and civil architects. While these are useful, they are, in most cases, static models. We are ..... The basic theory of transition from one state to another was developed by the Russian mathematician. Andrei Markov and hence the name Markov chains. Andrei Markov [1856-1922] ...

  13. Prognostic ability of EndoPredict compared to research-based versions of the PAM50 risk of recurrence (ROR) scores in node-positive, estrogen receptor-positive, and HER2-negative breast cancer. A GEICAM/9906 sub-study.

    Science.gov (United States)

    Martin, Miguel; Brase, Jan C; Ruiz, Amparo; Prat, Aleix; Kronenwett, Ralf; Calvo, Lourdes; Petry, Christoph; Bernard, Philip S; Ruiz-Borrego, Manuel; Weber, Karsten E; Rodriguez, César A; Alvarez, Isabel M; Segui, Miguel A; Perou, Charles M; Casas, Maribel; Carrasco, Eva; Caballero, Rosalía; Rodriguez-Lescure, Alvaro

    2016-02-01

    There are several prognostic multigene-based tests for managing breast cancer (BC), but limited data comparing them in the same cohort. We compared the prognostic performance of the EndoPredict (EP) test (standardized for pathology laboratory) with the research-based PAM50 non-standardized qRT-PCR assay in node-positive estrogen receptor-positive (ER+) and HER2-negative (HER2-) BC patients receiving adjuvant chemotherapy followed by endocrine therapy (ET) in the GEICAM/9906 trial. EP and PAM50 risk of recurrence (ROR) scores [based on subtype (ROR-S) and on subtype and proliferation (ROR-P)] were compared in 536 ER+/HER2- patients. Scores combined with clinical information were evaluated: ROR-T (ROR-S, tumor size), ROR-PT (ROR-P, tumor size), and EPclin (EP, tumor size, nodal status). Patients were assigned to risk-categories according to prespecified cutoffs. Distant metastasis-free survival (MFS) was analyzed by Kaplan-Meier. ROR-S, ROR-P, and EP scores identified a low-risk group with a relative better outcome (10-year MFS: ROR-S 87 %; ROR-P 89 %; EP 93 %). There was no significant difference between tests. Predictors including clinical information showed superior prognostic performance compared to molecular scores alone (10-year MFS, low-risk group: ROR-T 88 %; ROR-PT 92 %; EPclin 100 %). The EPclin-based risk stratification achieved a significantly improved prediction of MFS compared to ROR-T, but not ROR-PT. All signatures added prognostic information to common clinical parameters. EPclin provided independent prognostic information beyond ROR-T and ROR-PT. ROR and EP can reliably predict risk of distant metastasis in node-positive ER+/HER2- BC patients treated with chemotherapy and ET. Addition of clinical parameters into risk scores improves their prognostic ability.

  14. Residual-based model diagnosis methods for mixture cure models.

    Science.gov (United States)

    Peng, Yingwei; Taylor, Jeremy M G

    2017-06-01

    Model diagnosis, an important issue in statistical modeling, has not yet been addressed adequately for cure models. We focus on mixture cure models in this work and propose some residual-based methods to examine the fit of the mixture cure model, particularly the fit of the latency part of the mixture cure model. The new methods extend the classical residual-based methods to the mixture cure model. Numerical work shows that the proposed methods are capable of detecting lack-of-fit of a mixture cure model, particularly in the latency part, such as outliers, improper covariate functional form, or nonproportionality in hazards if the proportional hazards assumption is employed in the latency part. The methods are illustrated with two real data sets that were previously analyzed with mixture cure models. © 2016, The International Biometric Society.

  15. On the integration of object-