Model-Based Testability Assessment and Directed Troubleshooting of Shuttle Wiring Systems

Science.gov (United States)

Deb, Somnath; Domagala, Chuck; Shrestha, Roshan; Malepati, Venkatesh; Cavanaugh, Kevin; Patterson-Hine, Ann; Sanderfer, Dwight; Cockrell, Jim; Norvig, Peter (Technical Monitor)

2000-01-01

We have recently completed a pilot study on the Space shuttle wiring system commissioned by the Wiring Integrity Research (WIRe) team at NASA Ames Research Center, As the space shuttle ages, it is experiencing wiring degradation problems including arcing, chaffing insulation breakdown and broken conductors. A systematic and comprehensive test process is required to thoroughly test and quality assure (QA) the wiring systems. The NASA WIRe team recognized the value of a formal model based analysis for risk-assessment and fault coverage analysis. However. wiring systems are complex and involve over 50,000 wire segments. Therefore, NASA commissioned this pilot study with Qualtech Systems. Inc. (QSI) to explore means of automatically extracting high fidelity multi-signal models from wiring information database for use with QSI's Testability Engineering and Maintenance System (TEAMS) tool.

Software testability and its application to avionic software

Science.gov (United States)

Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffery E.

1993-01-01

Randomly generated black-box testing is an established yet controversial method of estimating software reliability. Unfortunately, as software applications have required higher reliabilities, practical difficulties with black-box testing have become increasingly problematic. These practical problems are particularly acute in life-critical avionics software, where requirements of 10 exp -7 failures per hour of system reliability can translate into a probability of failure (POF) of perhaps 10 exp -9 or less for each individual execution of the software. This paper describes the application of one type of testability analysis called 'sensitivity analysis' to B-737 avionics software; one application of sensitivity analysis is to quantify whether software testing is capable of detecting faults in a particular program and thus whether we can be confident that a tested program is not hiding faults. We so 80 by finding the testabilities of the individual statements of the program, and then use those statement testabilities to find the testabilities of the functions and modules. For the B-737 system we analyzed, we were able to isolate those functions that are more prone to hide errors during system/reliability testing.

A Fault Sample Simulation Approach for Virtual Testability Demonstration Test

Institute of Scientific and Technical Information of China (English)

ZHANG Yong; QIU Jing; LIU Guanjun; YANG Peng

2012-01-01

Virtual testability demonstration test has many advantages,such as low cost,high efficiency,low risk and few restrictions.It brings new requirements to the fault sample generation.A fault sample simulation approach for virtual testability demonstration test based on stochastic process theory is proposed.First,the similarities and differences of fault sample generation between physical testability demonstration test and virtual testability demonstration test are discussed.Second,it is pointed out that the fault occurrence process subject to perfect repair is renewal process.Third,the interarrival time distribution function of the next fault event is given.Steps and flowcharts of fault sample generation are introduced.The number of faults and their occurrence time are obtained by statistical simulation.Finally,experiments are carried out on a stable tracking platform.Because a variety of types of life distributions and maintenance modes are considered and some assumptions are removed,the sample size and structure of fault sample simulation results are more similar to the actual results and more reasonable.The proposed method can effectively guide the fault injection in virtual testability demonstration test.

Survey of source code metrics for evaluating testability of object oriented systems

OpenAIRE

Shaheen , Muhammad Rabee; Du Bousquet , Lydie

2010-01-01

Software testing is costly in terms of time and funds. Testability is a software characteristic that aims at producing systems easy to test. Several metrics have been proposed to identify the testability weaknesses. But it is sometimes difficult to be convinced that those metrics are really related with testability. This article is a critical survey of the source-code based metrics proposed in the literature for object-oriented software testability. It underlines the necessity to provide test...

A Fuzzy Approach for Integrated Measure of Object-Oriented Software Testability

OpenAIRE

Vandana Gupta; K. K. Aggarwal; Yogesh Singh

2005-01-01

For large software systems, testing phase seems to have profound effect on the overall acceptability and quality of the final product. The success of this activity can be judged by measuring the testability of the software. A good measure for testability can better manage the testing effort and time. Different Object Oriented Metrics are used in measurement of object-oriented testability but none of them is alone sufficient to give an overall reflection of software testabi...

What we know about software testability: a survey

OpenAIRE

Garousi, Vahid; Felderer, Michael; Kilicaslan, Feyza Nur

2018-01-01

Software testability is the degree to which a software system or a unit under test supports its own testing. To predict and improve software testability, a large number of techniques and metrics have been proposed by both practitioners and researchers in the last several decades. Reviewing and getting an overview of the entire state-of-the-art and -practice in this area is often challenging for a practitioner or a new researcher. Our objective is to summarize the state-of-the-art and -practic...

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...

A FUZZY LOGIC APPROACH TO MEASURE THE PRECISE TESTABILITY INDEX OF SOFTWARE

OpenAIRE

NAVDEEP KAUR,; MANINDERPAL SINGH

2011-01-01

Many of the software fails as a result of poor quality. For large software projects testing has a deep influence on the overall acceptability and quality of the final software. Testability of the software can be effectively measured form the testability effort and the time required to test the software. In today’s software development environment, object oriented design and development become important. There is strong relationship between the object oriented metrics and the testability effor...

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...

Testable physics by design

International Nuclear Information System (INIS)

Choi, Chansoo; Han, Min Cheol; Kim, Chan Hyeong; Kim, Sung Hun; Hoff, Gabriela; Pia, Maria Grazia; Saracco, Paolo; Weidenspointner, Georg

2015-01-01

The ability to test scientific software needs to be supported by adequate software design. Legacy software systems are often characterized by the difficulty to test parts of the software, mainly due to existing dependencies on other parts. Methods to improve the testability of physics software are discussed, along with open issues specific to physics software for Monte Carlo particle transport. The discussion is supported by examples drawn from the experience with validating Geant4 physics. (paper)

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.

Testing digital safety system software with a testability measure based on a software fault tree

International Nuclear Information System (INIS)

Sohn, Se Do; Hyun Seong, Poong

2006-01-01

Using predeveloped software, a digital safety system is designed that meets the quality standards of a safety system. To demonstrate the quality, the design process and operating history of the product are reviewed along with configuration management practices. The application software of the safety system is developed in accordance with the planned life cycle. Testing, which is a major phase that takes a significant time in the overall life cycle, can be optimized if the testability of the software can be evaluated. The proposed testability measure of the software is based on the entropy of the importance of basic statements and the failure probability from a software fault tree. To calculate testability, a fault tree is used in the analysis of a source code. With a quantitative measure of testability, testing can be optimized. The proposed testability can also be used to demonstrate whether the test cases based on uniform partitions, such as branch coverage criteria, result in homogeneous partitions that is known to be more effective than random testing. In this paper, the testability measure is calculated for the modules of a nuclear power plant's safety software. The module testing with branch coverage criteria required fewer test cases if the module has higher testability. The result shows that the testability measure can be used to evaluate whether partitions have homogeneous characteristics

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.

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...

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...

Design for testability and diagnosis at the system-level

Science.gov (United States)

Simpson, William R.; Sheppard, John W.

1993-01-01

The growing complexity of full-scale systems has surpassed the capabilities of most simulation software to provide detailed models or gate-level failure analyses. The process of system-level diagnosis approaches the fault-isolation problem in a manner that differs significantly from the traditional and exhaustive failure mode search. System-level diagnosis is based on a functional representation of the system. For example, one can exercise one portion of a radar algorithm (the Fast Fourier Transform (FFT) function) by injecting several standard input patterns and comparing the results to standardized output results. An anomalous output would point to one of several items (including the FFT circuit) without specifying the gate or failure mode. For system-level repair, identifying an anomalous chip is sufficient. We describe here an information theoretic and dependency modeling approach that discards much of the detailed physical knowledge about the system and analyzes its information flow and functional interrelationships. The approach relies on group and flow associations and, as such, is hierarchical. Its hierarchical nature allows the approach to be applicable to any level of complexity and to any repair level. This approach has been incorporated in a product called STAMP (System Testability and Maintenance Program) which was developed and refined through more than 10 years of field-level applications to complex system diagnosis. The results have been outstanding, even spectacular in some cases. In this paper we describe system-level testability, system-level diagnoses, and the STAMP analysis approach, as well as a few STAMP applications.

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.

Investigating the Partial Relationships Between Testability and the Dynamic Range-to-Domain Ratio

Directory of Open Access Journals (Sweden)

Zuhoor Al-Khanjari

2003-11-01

Full Text Available The word ‘testability’ has been used variously in the software community to represent a number of different concepts such as how easy it is to test a program or how easy it is to achieve execution coverage of certain program components. Voas and colleagues have used the word to capture a slightly different notion, namely the ease with which faults, if present in a program, can be revealed by the testing process. The significance of this concept is twofold. First, if it is possible to measure or estimate testability, it can guide the tester in deciding where to focus the testing effort. Secondly, knowledge about what makes some programs more testable than others can guide the developer so that design-for-test features are built in to the software. The propagation, infection and execution (PIE analysis technique has been proposed as a way of estimating the Voas notion of testability. Unfortunately, estimating testability via the PIE technique is a difficult and costly process. However, Voas has suggested a link with the metric, domain-to-range ratio (DRR. This paper reviews the various testability concepts and summarises the PIE technique. A prototype tool developed by the authors to automate part of the PIE analysis is described and a method is proposed for dynamically determining the inverse of the domain-to-range ratio. This inverse ratio can be considered more natural in some sense and the idea of calculating its value from program execution leads to the possibility of automating its determination. Some experiments have been performed to investigate empirically whether there is a partial link between testability and this dynamic range-to-domain ratio (DRDR. Statistical tests have shown that for some programs and computational functions there is a strong relationship, but for others the relationship is weak.

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...

A framework for quantifying net benefits of alternative prognostic models

NARCIS (Netherlands)

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

2012-01-01

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

On boolean combinations forming piecewise testable languages

Czech Academy of Sciences Publication Activity Database

Masopust, Tomáš; Thomazo, M.

2017-01-01

Roč. 682, June 19 (2017), s. 165-179 ISSN 0304-3975 Institutional support: RVO:67985840 Keywords : automata * language s * k-piecewise testability Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.698, year: 2016 http://www.sciencedirect.com/science/article/pii/S030439751730066X

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...

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.

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.

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

Science.gov (United States)

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

2014-09-01

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

Bayesian naturalness, simplicity, and testability applied to the B ‑ L MSSM GUT

Science.gov (United States)

Fundira, Panashe; Purves, Austin

2018-04-01

Recent years have seen increased use of Bayesian model comparison to quantify notions such as naturalness, simplicity, and testability, especially in the area of supersymmetric model building. After demonstrating that Bayesian model comparison can resolve a paradox that has been raised in the literature concerning the naturalness of the proton mass, we apply Bayesian model comparison to GUTs, an area to which it has not been applied before. We find that the GUTs are substantially favored over the nonunifying puzzle model. Of the GUTs we consider, the B ‑ L MSSM GUT is the most favored, but the MSSM GUT is almost equally favored.

Prognostic modelling options for remaining useful life estimation by industry

Science.gov (United States)

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

2011-07-01

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

[A prognostic model of a cholera epidemic].

Science.gov (United States)

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

1994-01-01

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

A molecular prognostic model predicts esophageal squamous cell carcinoma prognosis.

Directory of Open Access Journals (Sweden)

Hui-Hui Cao

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

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...

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Modeling for Battery Prognostics

Science.gov (United States)

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

2017-01-01

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

A framework for quantifying net benefits of alternative prognostic models

OpenAIRE

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

2012-01-01

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

Separability by piecewise testable languages is PTime-complete

Czech Academy of Sciences Publication Activity Database

Masopust, Tomáš

2018-01-01

Roč. 711, February 8 (2018), s. 109-114 ISSN 0304-3975 Institutional support: RVO:67985840 Keywords : separability * piecewise testable languages * complexity Subject RIV: BA - General Mathematics OBOR OECD: Computer science s, information science , bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.698, year: 2016 https://www. science direct.com/ science /article/pii/S0304397517308319?via%3Dihub

Separability by piecewise testable languages is PTime-complete

Czech Academy of Sciences Publication Activity Database

Masopust, Tomáš

2018-01-01

Roč. 711, February 8 (2018), s. 109-114 ISSN 0304-3975 Institutional support: RVO:67985840 Keywords : separability * piecewise testable languages * complexity Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.698, year: 2016 https://www.sciencedirect.com/science/article/pii/S0304397517308319?via%3Dihub

An empirical comparison of a dynamic software testability metric to static cyclomatic complexity

Science.gov (United States)

Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffrey E.

1993-01-01

This paper compares the dynamic testability prediction technique termed 'sensitivity analysis' to the static testability technique termed cyclomatic complexity. The application that we chose in this empirical study is a CASE generated version of a B-737 autoland system. For the B-737 system we analyzed, we isolated those functions that we predict are more prone to hide errors during system/reliability testing. We also analyzed the code with several other well-known static metrics. This paper compares and contrasts the results of sensitivity analysis to the results of the static metrics.

Prognostics for Steam Generator Tube Rupture using Markov Chain model

International Nuclear Information System (INIS)

Kim, Gibeom; Heo, Gyunyoung; Kim, Hyeonmin

2016-01-01

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

A framework for quantifying net benefits of alternative prognostic models.

Science.gov (United States)

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

2012-01-30

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Systematic review of prognostic models in traumatic brain injury

Directory of Open Access Journals (Sweden)

Roberts Ian

2006-11-01

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

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.

PISCES: A Tool for Predicting Software Testability

Science.gov (United States)

Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffery E.

1991-01-01

Before a program can fail, a software fault must be executed, that execution must alter the data state, and the incorrect data state must propagate to a state that results directly in an incorrect output. This paper describes a tool called PISCES (developed by Reliable Software Technologies Corporation) for predicting the probability that faults in a particular program location will accomplish all three of these steps causing program failure. PISCES is a tool that is used during software verification and validation to predict a program's testability.

Model-based Prognostics with Fixed-lag Particle Filters

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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...

DEVELOPMENT OF METHODOLOGY FOR DESIGNING TESTABLE COMPONENT STRUCTURE OF DISCIPLINARY COMPETENCE

Directory of Open Access Journals (Sweden)

Vladimir I. Freyman

2014-01-01

Full Text Available The aim of the study is to present new methods of quality results assessment of the education corresponding to requirements of Federal State Educational Standards (FSES of the Third Generation developed for the higher school. The urgency of search of adequate tools for quality competency measurement and its elements formed in the course of experts’ preparation are specified. Methods. It is necessary to consider interference of competency components such as knowledge, abilities, possession in order to make procedures of assessment of students’ achievements within the limits of separate discipline or curriculum section more convenient, effective and exact. While modeling of component structure of the disciplinary competence the testable design of components is used; the approach borrowed from technical diagnostics. Results. The research outcomes include the definition and analysis of general iterative methodology for testable designing component structure of the disciplinary competence. Application of the proposed methodology is illustrated as the example of an abstract academic discipline with specified data and index of labour requirement. Methodology restrictions are noted; practical recommendations are given. Scientific novelty. Basic data and a detailed step-by-step implementation phase of the proposed common iterative approach to the development of disciplinary competence testable component structure are considered. Tests and diagnostic tables for different options of designing are proposed. Practical significance. The research findings can help promoting learning efficiency increase, a choice of adequate control devices, accuracy of assessment, and also efficient use of personnel, temporal and material resources of higher education institutions. Proposed algorithms, methods and approaches to procedure of control results organization and realization of developed competences and its components can be used as methodical base while

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.

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

DEFF Research Database (Denmark)

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

2009-01-01

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

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

Science.gov (United States)

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

2018-03-01

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

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

NARCIS (Netherlands)

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

2017-01-01

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

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

Science.gov (United States)

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

2018-04-11

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

Computer-aided design of microfluidic very large scale integration (mVLSI) biochips design automation, testing, and design-for-testability

CERN Document Server

Hu, Kai; Ho, Tsung-Yi

2017-01-01

This book provides a comprehensive overview of flow-based, microfluidic VLSI. The authors describe and solve in a comprehensive and holistic manner practical challenges such as control synthesis, wash optimization, design for testability, and diagnosis of modern flow-based microfluidic biochips. They introduce practical solutions, based on rigorous optimization and formal models. The technical contributions presented in this book will not only shorten the product development cycle, but also accelerate the adoption and further development of modern flow-based microfluidic biochips, by facilitating the full exploitation of design complexities that are possible with current fabrication techniques. Offers the first practical problem formulation for automated control-layer design in flow-based microfluidic biochips and provides a systematic approach for solving this problem; Introduces a wash-optimization method for cross-contamination removal; Presents a design-for-testability (DfT) technique that can achieve 100...

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...

Model Adaptation for Prognostics in a Particle Filtering Framework

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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....

Prognostic methods in medicine

NARCIS (Netherlands)

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

1999-01-01

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

Layout level design for testability strategy applied to a CMOS cell library

NARCIS (Netherlands)

Blom, F.C.; Oliver, J.; Rullan, M.; Ferrer, C.

1993-01-01

The layout level design for testability (LLDFT) rules used here allow to avoid some hard to detect faults or even undetectable faults on a cell library by modifying the cell layout without changing their behavior and achieving a good level of reliability. These rules avoid some open faults or reduce

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

Directory of Open Access Journals (Sweden)

Liu Yufeng

2011-01-01

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

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

Science.gov (United States)

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

2017-07-14

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

Prognostics Health Management and Physics based failure Models for Electrolytic Capacitors

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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...

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.

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

National Research Council Canada - National Science Library

Kacprzynski, Gregory

2002-01-01

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

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

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

Aircraft Anomaly Prognostics, Phase I

Data.gov (United States)

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

Testable solution of the cosmological constant and coincidence problems

International Nuclear Information System (INIS)

Shaw, Douglas J.; Barrow, John D.

2011-01-01

We present a new solution to the cosmological constant (CC) and coincidence problems in which the observed value of the CC, Λ, is linked to other observable properties of the Universe. This is achieved by promoting the CC from a parameter that must be specified, to a field that can take many possible values. The observed value of Λ≅(9.3 Gyrs) -2 [≅10 -120 in Planck units] is determined by a new constraint equation which follows from the application of a causally restricted variation principle. When applied to our visible Universe, the model makes a testable prediction for the dimensionless spatial curvature of Ω k0 =-0.0056(ζ b /0.5), where ζ b ∼1/2 is a QCD parameter. Requiring that a classical history exist, our model determines the probability of observing a given Λ. The observed CC value, which we successfully predict, is typical within our model even before the effects of anthropic selection are included. When anthropic selection effects are accounted for, we find that the observed coincidence between t Λ =Λ -1/2 and the age of the Universe, t U , is a typical occurrence in our model. In contrast to multiverse explanations of the CC problems, our solution is independent of the choice of a prior weighting of different Λ values and does not rely on anthropic selection effects. Our model includes no unnatural small parameters and does not require the introduction of new dynamical scalar fields or modifications to general relativity, and it can be tested by astronomical observations in the near future.

Application of Prognostic Mesoscale Modeling in the Southeast United States

International Nuclear Information System (INIS)

Buckley, R.L.

1999-01-01

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

Online testable concept maps: benefits for learning about the pathogenesis of disease.

Science.gov (United States)

Ho, Veronica; Kumar, Rakesh K; Velan, Gary

2014-07-01

Concept maps have been used to promote meaningful learning and critical thinking. Although these are crucially important in all disciplines, evidence for the benefits of concept mapping for learning in medicine is limited. We performed a randomised crossover study to assess the benefits of online testable concept maps for learning in pathology by volunteer junior medical students. Participants (n = 65) were randomly allocated to either of two groups with equivalent mean prior academic performance, in which they were given access to either online maps or existing online resources for a 2-week block on renal disease. Groups then crossed over for a 2-week block on hepatic disease. Outcomes were assessed using timed online quizzes, which included questions unrelated to topics in the pathogenesis maps as an internal control. Questionnaires were administered to evaluate students' acceptance of the maps. In both blocks, the group with access to pathogenesis maps achieved significantly higher average scores than the control group on quiz questions related to topics covered by the maps (Block 1: p online testable pathogenesis maps are well accepted and can improve learning of concepts in pathology by medical students. © 2014 John Wiley & Sons Ltd.

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

International Nuclear Information System (INIS)

Fang, Xiaolei; Paynabar, Kamran; Gebraeel, Nagi

2017-01-01

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

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.

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

Generic testability and test methods guidelines for ASIC devices

International Nuclear Information System (INIS)

Puri, K.; Takeda, H.

1996-04-01

Many industries are switching from analog equipment to digital equipment. This change has become desirable because digital devices have become cost-effective, easily available, highly reliable, easy to qualify and easy to test and replace when needed. The nuclear power industry is beginning to upgrade some of its instrumentation and control equipment from an analog design to digital design. A digital application specific integrated circuit (ASIC) device can be designed to perform the same functions as performed by analog modules. However, the ASIC must be designed for cost-effective testability and qualification. This report provides generic guidelines for designing cost-effective methods for testing and characterizing ASIC devices to accomplish qualification

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.

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

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

NARCIS (Netherlands)

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

2018-01-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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.

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

DEFF Research Database (Denmark)

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

2011-01-01

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

Testable baryogenesis in seesaw models

Energy Technology Data Exchange (ETDEWEB)

Hernández, P.; Kekic, M. [Instituto de Física Corpuscular, Universidad de Valencia and CSIC,Edificio Institutos Investigación,Catedrático José Beltrán 2, 46980 (Spain); López-Pavón, J. [INFN, Sezione di Genova,via Dodecaneso 33, 16146 Genova (Italy); Racker, J.; Salvado, J. [Instituto de Física Corpuscular, Universidad de Valencia and CSIC,Edificio Institutos Investigación,Catedrático José Beltrán 2, 46980 (Spain)

2016-08-26

We revisit the production of baryon asymmetries in the minimal type I seesaw model with heavy Majorana singlets in the GeV range. In particular we include “washout” effects from scattering processes with gauge bosons, Higgs decays and inverse decays, besides the dominant top scatterings. We show that in the minimal model with two singlets, and for an inverted light neutrino ordering, future measurements from SHiP and neutrinoless double beta decay could in principle provide sufficient information to predict the matter-antimatter asymmetry in the universe. We also show that SHiP measurements could provide very valuable information on the PMNS CP phases.

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

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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...

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.

Fault Sample Generation for Virtual Testability Demonstration Test Subject to Minimal Maintenance and Scheduled Replacement

Directory of Open Access Journals (Sweden)

Yong Zhang

2015-01-01

Full Text Available Virtual testability demonstration test brings new requirements to the fault sample generation. First, fault occurrence process is described by stochastic process theory. It is discussed that fault occurrence process subject to minimal repair is nonhomogeneous Poisson process (NHPP. Second, the interarrival time distribution function of the next fault event is proposed and three typical kinds of parameterized NHPP are discussed. Third, the procedure of fault sample generation is put forward with the assumptions of minimal maintenance and scheduled replacement. The fault modes and their occurrence time subject to specified conditions and time period can be obtained. Finally, an antenna driving subsystem in automatic pointing and tracking platform is taken as a case to illustrate the proposed method. Results indicate that both the size and structure of the fault samples generated by the proposed method are reasonable and effective. The proposed method can be applied to virtual testability demonstration test well.

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.

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.

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

Science.gov (United States)

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

2008-07-01

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

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...

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

Science.gov (United States)

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

2016-09-01

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

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.

Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud; Sørensen, John Dalsgaard

2018-01-01

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

Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud; Sørensen, John Dalsgaard

2018-01-01

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

Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud

2017-01-01

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

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

DEFF Research Database (Denmark)

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

2016-01-01

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

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.

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

NARCIS (Netherlands)

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

2017-01-01

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

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.

Testability, Test Automation and Test Driven Development for the Trick Simulation Toolkit

Science.gov (United States)

Penn, John

2014-01-01

This paper describes the adoption of a Test Driven Development approach and a Continuous Integration System in the development of the Trick Simulation Toolkit, a generic simulation development environment for creating high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. It describes the approach, and the significant benefits seen, such as fast, thorough and clear test feedback every time code is checked into the code repository. It also describes an approach that encourages development of code that is testable and adaptable.

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.

Cytogenetic prognostication within medulloblastoma subgroups.

Science.gov (United States)

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

2014-03-20

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

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

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.

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

Science.gov (United States)

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

2018-03-31

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

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

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.

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.

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

Science.gov (United States)

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

2010-01-01

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

Survey on Prognostics Techniques for Updating Initiating Event Frequency in PSA

International Nuclear Information System (INIS)

Kim, Hyeonmin; Heo, Gyunyoung

2015-01-01

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

Survey on Prognostics Techniques for Updating Initiating Event Frequency in PSA

Energy Technology Data Exchange (ETDEWEB)

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

2015-05-15

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

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

Science.gov (United States)

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

2018-05-28

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

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.

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

International Nuclear Information System (INIS)

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

1996-01-01

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

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.

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

DEFF Research Database (Denmark)

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

2016-01-01

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

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

Ocular biometric parameters among 3-year-old Chinese children: testability, distribution and association with anthropometric parameters

Science.gov (United States)

Huang, Dan; Chen, Xuejuan; Gong, Qi; Yuan, Chaoqun; Ding, Hui; Bai, Jing; Zhu, Hui; Fu, Zhujun; Yu, Rongbin; Liu, Hu

2016-01-01

This survey was conducted to determine the testability, distribution and associations of ocular biometric parameters in Chinese preschool children. Ocular biometric examinations, including the axial length (AL) and corneal radius of curvature (CR), were conducted on 1,688 3-year-old subjects by using an IOLMaster in August 2015. Anthropometric parameters, including height and weight, were measured according to a standardized protocol, and body mass index (BMI) was calculated. The testability was 93.7% for the AL and 78.6% for the CR overall, and both measures improved with age. Girls performed slightly better in AL measurements (P = 0.08), and the difference in CR was statistically significant (P < 0.05). The AL distribution was normal in girls (P = 0.12), whereas it was not in boys (P < 0.05). For CR1, all subgroups presented normal distributions (P = 0.16 for boys; P = 0.20 for girls), but the distribution varied when the subgroups were combined (P < 0.05). CR2 presented a normal distribution (P = 0.11), whereas the AL/CR ratio was abnormal (P < 0.001). Boys exhibited a significantly longer AL, a greater CR and a greater AL/CR ratio than girls (all P < 0.001). PMID:27384307

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

DEFF Research Database (Denmark)

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

2011-01-01

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

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.

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

Science.gov (United States)

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

2018-06-01

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

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.

PERBANDINGAN MAINTAINABILITY, FLEKSIBILITY, TESTABILITY PADA CMS OPEN SOURCE E-COMMERCE

Directory of Open Access Journals (Sweden)

Rini Anggrainingsih

2017-09-01

Full Text Available Content Management System (CMS open source banyak digunakan dalam website e-commerce. CMS open source e-commerce tumbuh semakin canggih dan lebih kompetitif. Artikel ini berisi perbandingan kualitas software dari top three CMS open sourece e-commerce yaitu Magento, Woocomerce,dan OpenCart. perbandingan dilakukan terhadap kualitas revision software yaitu maintainability, fleksibility, dan testability. Kualitas revison diuji sebab maintenance dan testing merupakan proses yang sangat penting dalam pembuatan sebuah software dan memerlukan banyak resource. Pengukuran dilakukan dengan menggunakan phpmetric untuk menghitung maintainability index, afferent coupling, efferent couping, lack of cohesion method, cyclomatic complexity. Tujuan dari penulisan artikel ini adalah untuk menentukkan open source e-commerce terbaik dalam proses maintenance, adaptasi, dan modifikasi. Hasil menunjukkan bahwa magento memiliki kemampuan terbaik untuk maintenance, testing, dan perubahan kode dibandingkan Woocommerce dan Opencart, dimana nilai maintainaility indenxnya 111,36, afferent coupling 0,826, efferent coupling 1,83, Lack of cohesion method 2,10 dan Cyclomatic Complexity 11,02.

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...

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 3^rd 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.

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

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

The use of prognostic factors in metastatic renal cell carcinoma.

Science.gov (United States)

Li, Haoran; Samawi, Haider; Heng, Daniel Y C

2015-12-01

Over the last decade, the treatment landscape of metastatic renal cell carcinoma (mRCC) has evolved tremendously. The outcome of patients with mRCC has been improved since the advent of targeted therapy. In this review, we address the use of prognostic schema in the era of targeted treatment. This article summarizes the current available prognostic models and the evidence to support their use in clinical settings. Prognostic models can help guide clinicians in their decision making, as they have been validated in the first- and second-line targeted therapy settings as well as in non-clear cell mRCC. Prognostic factors are important in patient counseling, clinical trial stratification, and therapy planning. Very selected favorable-risk patients with minimal bulk and slow-growing disease could potentially be observed before needing treatment. Patients with poor-risk disease may be eligible for treatment with temsirolimus. Patients with a very poor prognosis may not be suitable candidates for cytoreductive nephrectomy. New biomarkers are on the horizon, though their roles need to be validated and their additive contribution to improve existing prognostic models examined. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Prognostic Value of Quantitative Stress Perfusion Cardiac Magnetic Resonance.

Science.gov (United States)

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

2018-05-01

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

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

Science.gov (United States)

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

2017-09-01

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

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

DEFF Research Database (Denmark)

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

2018-01-01

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

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.

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.

A Distributed Approach to System-Level Prognostics

Science.gov (United States)

2012-09-01

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

Nottingham Prognostic Index in Triple-Negative Breast Cancer: a reliable prognostic tool?

International Nuclear Information System (INIS)

Albergaria, André; Ricardo, Sara; Milanezi, Fernanda; Carneiro, Vítor; Amendoeira, Isabel; Vieira, Daniella; Cameselle-Teijeiro, Jorge; Schmitt, Fernando

2011-01-01

A breast cancer prognostic tool should ideally be applicable to all types of invasive breast lesions. A number of studies have shown histopathological grade to be an independent prognostic factor in breast cancer, adding prognostic power to nodal stage and tumour size. The Nottingham Prognostic Index has been shown to accurately predict patient outcome in stratified groups with a follow-up period of 15 years after primary diagnosis of breast cancer. Clinically, breast tumours that lack the expression of Oestrogen Receptor, Progesterone Receptor and Human Epidermal growth factor Receptor 2 (HER2) are identified as presenting a 'triple-negative' phenotype or as triple-negative breast cancers. These poor outcome tumours represent an easily recognisable prognostic group of breast cancer with aggressive behaviour that currently lack the benefit of available systemic therapy. There are conflicting results on the prevalence of lymph node metastasis at the time of diagnosis in triple-negative breast cancer patients but it is currently accepted that triple-negative breast cancer does not metastasize to axillary nodes and bones as frequently as the non-triple-negative carcinomas, favouring instead, a preferentially haematogenous spread. Hypothetically, this particular tumour dissemination pattern would impair the reliability of using Nottingham Prognostic Index as a tool for triple-negative breast cancer prognostication. The present study tested the effectiveness of the Nottingham Prognostic Index in stratifying breast cancer patients of different subtypes with special emphasis in a triple-negative breast cancer patient subset versus non- triple-negative breast cancer. We demonstrated that besides the fact that TNBC disseminate to axillary lymph nodes as frequently as luminal or HER2 tumours, we also showed that TNBC are larger in size compared with other subtypes and almost all grade 3. Additionally, survival curves demonstrated that these prognostic factors are

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-01-15

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

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

NARCIS (Netherlands)

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

2017-01-01

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

Plaque Brachytherapy for Uveal Melanoma: A Vision Prognostication Model

International Nuclear Information System (INIS)

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

2012-01-01

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

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.

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

DEFF Research Database (Denmark)

You, Benoit; Colomban, Olivier; Heywood, Mark

2013-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Surface Prognostic Charts

Data.gov (United States)

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

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

DEFF Research Database (Denmark)

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

1996-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

Comparison on testability of visual acuity, stereo acuity and colour vision tests between children with learning disabilities and children without learning disabilities in government primary schools.

Science.gov (United States)

Abu Bakar, Nurul Farhana; Chen, Ai-Hong

2014-02-01

Children with learning disabilities might have difficulties to communicate effectively and give reliable responses as required in various visual function testing procedures. The purpose of this study was to compare the testability of visual acuity using the modified Early Treatment Diabetic Retinopathy Study (ETDRS) and Cambridge Crowding Cards, stereo acuity using Lang Stereo test II and Butterfly stereo tests and colour perception using Colour Vision Test Made Easy (CVTME) and Ishihara's Test for Colour Deficiency (Ishihara Test) between children in mainstream classes and children with learning disabilities in special education classes in government primary schools. A total of 100 primary school children (50 children from mainstream classes and 50 children from special education classes) matched in age were recruited in this cross-sectional comparative study. The testability was determined by the percentage of children who were able to give reliable respond as required by the respective tests. 'Unable to test' was defined as inappropriate response or uncooperative despite best efforts of the screener. The testability of the modified ETDRS, Butterfly stereo test and Ishihara test for respective visual function tests were found lower among children in special education classes ( P learning disabilities. Modifications of vision testing procedures are essential for children with learning disabilities.

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

Science.gov (United States)

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

2017-10-01

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

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

NARCIS (Netherlands)

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

2015-01-01

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

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

NARCIS (Netherlands)

Loutas, T.; Eleftheroglou, N.

2016-01-01

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

A framework for quantifying net benefits of alternative prognostic models‡

Science.gov (United States)

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

2012-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

Ivan M. Tsidylo

2012-12-01

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

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

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....

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

Science.gov (United States)

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

2018-05-02

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

Systematic review of renal carcinoma prognostic factors.

Science.gov (United States)

Lorente, D; Trilla, E; Meseguer, A; Planas, J; Placer, J; Celma, A; Salvador, C; Regis, L; Morote, J

2017-05-01

The natural history of renal cell carcinoma is heterogeneous. Some scenarios can be found in terms of clinical presentation, clinical evolution or type of recurrence (local/metastatic). The aim of this publication is to analyze the most important prognostic factors published in the literature. A literature review ob published papers was performed using the Pubmed, from first Motzer's classification published in 1999 to 2015, according to PRISMA declaration. Search was done using the following keywords: kidney neoplasm, kidney cancer, renal cell carcinoma, prognostic factors, mortality, survival and disease progression. Papers were classified according to level of evidence, the number of patients included and the type of study performed. The evolution in the knowledge of molecular pathways related to renal oncogenesis and the new targeted therapies has left to remain obsolete the old prognostic models. It's necessary to perform a continuous review to actualize nomograms and to adapt them to the new scenarios. Is necessary to perform a proper external validation of existing prognostic factors using prospective and multicentric studies to add them into the daily urologist clinical practice. Copyright © 2016 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Prognostic factors of breast cancer

International Nuclear Information System (INIS)

Gonzalez Ortega, Jose Maria; Morales Wong, Mario Miguel; Lopez Cuevas, Zoraida; Diaz Valdez, Marilin

2011-01-01

The prognostic factors must to be differentiated of the predictive ones. A prognostic factor is any measurement used at moment of the surgery correlated with the free interval of disease or global survival in the absence of the systemic adjuvant treatment and as result is able to correlate with the natural history of the disease. In contrast, a predictive factor is any measurement associated with the response to a given treatment. Among the prognostic factors of the breast cancer are included the clinical, histological, biological, genetic and psychosocial factors. In present review of psychosocial prognostic factors has been demonstrated that the stress and the depression are negative prognostic factors in patients presenting with breast cancer. It is essential to remember that the assessment of just one prognostic parameter is a help but it is not useful to clinical and therapeutic management of the patient.(author)

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.

Improvement of PSA Models Using Monitoring and Prognostics

Energy Technology Data Exchange (ETDEWEB)

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

2014-08-15

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

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

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Felipe Andreiuolo

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

Prognostic cloud water in the Los Alamos general circulation model

International Nuclear Information System (INIS)

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

1994-01-01

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

Diagnostic Reasoning using Prognostic Information for Unmanned Aerial Systems

Science.gov (United States)

Schumann, Johann; Roychoudhury, Indranil; Kulkarni, Chetan

2015-01-01

With increasing popularity of unmanned aircraft, continuous monitoring of their systems, software, and health status is becoming more and more important to ensure safe, correct, and efficient operation and fulfillment of missions. The paper presents integration of prognosis models and prognostic information with the R2U2 (REALIZABLE, RESPONSIVE, and UNOBTRUSIVE Unit) monitoring and diagnosis framework. This integration makes available statistically reliable health information predictions of the future at a much earlier time to enable autonomous decision making. The prognostic information can be used in the R2U2 model to improve diagnostic accuracy and enable decisions to be made at the present time to deal with events in the future. This will be an advancement over the current state of the art, where temporal logic observers can only do such valuation at the end of the time interval. Usefulness and effectiveness of this integrated diagnostics and prognostics framework was demonstrated using simulation experiments with the NASA Dragon Eye electric unmanned aircraft.

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

Science.gov (United States)

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

2015-06-01

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

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

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.

Real-Time Prognostics of a Rotary Valve Actuator

Science.gov (United States)

Daigle, Matthew

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Wen-An Yang

2016-01-01

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

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

Science.gov (United States)

Avissar, Roni; Chen, Fei

1993-01-01

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

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.

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

Science.gov (United States)

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

2014-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-10-15

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

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...

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

Science.gov (United States)

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

2013-01-01

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

Factors Affecting Physicians' Intentions to Communicate Personalized Prognostic Information to Cancer Patients at the End of Life: An Experimental Vignette Study.

Science.gov (United States)

Han, Paul K J; Dieckmann, Nathan F; Holt, Christina; Gutheil, Caitlin; Peters, Ellen

2016-08-01

To explore the effects of personalized prognostic information on physicians' intentions to communicate prognosis to cancer patients at the end of life, and to identify factors that moderate these effects. A factorial experiment was conducted in which 93 family medicine physicians were presented with a hypothetical vignette depicting an end-stage gastric cancer patient seeking prognostic information. Physicians' intentions to communicate prognosis were assessed before and after provision of personalized prognostic information, while emotional distress of the patient and ambiguity (imprecision) of the prognostic estimate were varied between subjects. General linear models were used to test the effects of personalized prognostic information, patient distress, and ambiguity on prognostic communication intentions, and potential moderating effects of 1) perceived patient distress, 2) perceived credibility of prognostic models, 3) physician numeracy (objective and subjective), and 4) physician aversion to risk and ambiguity. Provision of personalized prognostic information increased prognostic communication intentions (P < 0.001, η(2) = 0.38), although experimentally manipulated patient distress and prognostic ambiguity had no effects. Greater change in communication intentions was positively associated with higher perceived credibility of prognostic models (P = 0.007, η(2) = 0.10), higher objective numeracy (P = 0.01, η(2) = 0.09), female sex (P = 0.01, η(2) = 0.08), and lower perceived patient distress (P = 0.02, η(2) = 0.07). Intentions to communicate available personalized prognostic information were positively associated with higher perceived credibility of prognostic models (P = 0.02, η(2) = 0.09), higher subjective numeracy (P = 0.02, η(2) = 0.08), and lower ambiguity aversion (P = 0.06, η(2) = 0.04). Provision of personalized prognostic information increases physicians' prognostic communication intentions to a hypothetical end-stage cancer patient, and

A copula-based sampling method for data-driven prognostics

International Nuclear Information System (INIS)

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

2014-01-01

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

Evaluating biomarkers for prognostic enrichment of clinical trials.

Science.gov (United States)

Kerr, Kathleen F; Roth, Jeremy; Zhu, Kehao; Thiessen-Philbrook, Heather; Meisner, Allison; Wilson, Francis Perry; Coca, Steven; Parikh, Chirag R

2017-12-01

A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

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

International Nuclear Information System (INIS)

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

2009-01-01

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

Application of molecular biology of differentiated thyroid cancer for clinical prognostication.

Science.gov (United States)

Marotta, Vincenzo; Sciammarella, Concetta; Colao, Annamaria; Faggiano, Antongiulio

2016-11-01

Although cancer outcome results from the interplay between genetics and environment, researchers are making a great effort for applying molecular biology in the prognostication of differentiated thyroid cancer (DTC). Nevertheless, role of molecular characterisation in the prognostic setting of DTC is still nebulous. Among the most common and well-characterised genetic alterations related to DTC, including mutations of BRAF and RAS and RET rearrangements, BRAF V600E is the only mutation showing unequivocal association with clinical outcome. Unfortunately, its accuracy is strongly limited by low specificity. Recently, the introduction of next-generation sequencing techniques led to the identification of TERT promoter and TP53 mutations in DTC. These genetic abnormalities may identify a small subgroup of tumours with highly aggressive behaviour, thus improving specificity of molecular prognostication. Although knowledge of prognostic significance of TP53 mutations is still anecdotal, mutations of the TERT promoter have showed clear association with clinical outcome. Nevertheless, this genetic marker needs to be analysed according to a multigenetic model, as its prognostic effect becomes negligible when present in isolation. Given that any genetic alteration has demonstrated, taken alone, enough specificity, the co-occurrence of driving mutations is emerging as an independent genetic signature of aggressiveness, with possible future application in clinical practice. DTC prognostication may be empowered in the near future by non-tissue molecular prognosticators, including circulating BRAF V600E and miRNAs. Although promising, use of these markers needs to be refined by the technical sight, and the actual prognostic value is still yet to be validated. © 2016 Society for Endocrinology.

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

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

Data.gov (United States)

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

Serum prognostic biomarkers in head and neck cancer patients.

Science.gov (United States)

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

2014-08-01

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

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.

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

A flexible and testable software architecture: applying presenter first to a device server for the DOOCS accelerator control system of the European XFEL

International Nuclear Information System (INIS)

Beckmann, A.; Karabekyan, S.; Pflüger, J.

2012-01-01

Presenter First (PF) uses a variant of Model View Presenter design pattern to add implementation flexibility and to improve testability of complex event-driven applications. It has been introduced in the context of GUI applications, but can easily be adapted to server applications. This paper describes how Presenter First methodology is used to develop a device server for the Programmable Logic Controls (PLC) of the European XFEL undulator systems, which are Windows PCs running PLC software from Beckhoff. The server implements a ZeroMQ message interface to the PLC allowing the DOOCS accelerator control system of the European XFEL to exchange data with the PLC by sending messages over the network. Our challenge is to develop a well-tested device server with a flexible architecture that allows integrating the server into other accelerator control systems like EPICS. (author)

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.

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

Science.gov (United States)

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

2012-10-01

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

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

Science.gov (United States)

Daigle, Matthew John; Goebel, Kai Frank

2010-01-01

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

Statistical methods for the assessment of prognostic biomarkers(part II): calibration and re-classification

NARCIS (Netherlands)

Tripepi, Giovanni; Jager, Kitty J.; Dekker, Friedo W.; Zoccali, Carmine

2010-01-01

Calibration is the ability of a prognostic model to correctly estimate the probability of a given event across the whole range of prognostic estimates (for example, 30% probability of death, 40% probability of myocardial infarction, etc.). The key difference between calibration and discrimination is

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.)

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

Science.gov (United States)

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

2013-01-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Comparison of Two Probabilistic Fatigue Damage Assessment Approaches Using Prognostic Performance Metrics

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Xuefei Guan

2011-01-01

Full Text Available In this paper, two probabilistic prognosis updating schemes are compared. One is based on the classical Bayesian approach and the other is based on newly developed maximum relative entropy (MRE approach. The algorithm performance of the two models is evaluated using a set of recently developed prognostics-based metrics. Various uncertainties from measurements, modeling, and parameter estimations are integrated into the prognosis framework as random input variables for fatigue damage of materials. Measures of response variables are then used to update the statistical distributions of random variables and the prognosis results are updated using posterior distributions. Markov Chain Monte Carlo (MCMC technique is employed to provide the posterior samples for model updating in the framework. Experimental data are used to demonstrate the operation of the proposed probabilistic prognosis methodology. A set of prognostics-based metrics are employed to quantitatively evaluate the prognosis performance and compare the proposed entropy method with the classical Bayesian updating algorithm. In particular, model accuracy, precision, robustness and convergence are rigorously evaluated in addition to the qualitative visual comparison. Following this, potential development and improvement for the prognostics-based metrics are discussed in detail.

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

International Nuclear Information System (INIS)

Fang, Xiaolei; Zhou, Rensheng; Gebraeel, Nagi

2015-01-01

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

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.

Testable flipped SU(5)xU(1){sub X} models

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Jiang Jing [Institute of Theoretical Science, University of Oregon, Eugene, OR 97403 (United States); Li Tianjun [George P. and Cynthia W. Mitchell Institute for Fundamental Physics, Texas A and M University, College Station, TX 77843 (United States) and Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100080 (China) and Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854 (United States)]. E-mail: tjli@physics.rutgers.edu; Nanopoulos, Dimitri V. [George P. and Cynthia W. Mitchell Institute for Fundamental Physics, Texas A and M University, College Station, TX 77843 (United States); Astroparticle Physics Group, Houston Advanced Research Center (HARC), Mitchell Campus, Woodlands, TX 77381 (United States); Academy of Athens, Division of Natural Sciences, 28 Panepistimiou Avenue, Athens 10679 (Greece)

2007-06-11

The little hierarchy between the GUT scale and the string scale may give us some hints that can be tested at the LHC. To achieve string-scale gauge coupling unification, we introduce additional vector-like particles. We require that these vector-like particles be standard, form complete GUT multiplets, and have masses around the TeV scale or close to the string scale. Interestingly, only the flipped SU(5)xU(1){sub X} models can work elegantly. We consider all possible sets of vector-like particles with masses around the TeV scale. And we introduce vector-like particles with masses close to the string scale which can mimic the string-scale threshold corrections. We emphasize that all of these vector-like particles can be obtained in the interesting flipped SU(5)xU(1){sub X} string models from the four-dimensional free fermionic string construction. Assuming the low-energy supersymmetry, high-scale supersymmetry, and split supersymmetry, we show that the string-scale gauge coupling unification can indeed be achieved in the flipped SU(5)xU(1){sub X} models. These models can be tested at the LHC by observing simple sets of vector-like particles at the TeV scale. Moreover, we discuss a simple flipped SU(5)xU(1){sub X} model with string-scale gauge coupling unification and high-scale supersymmetry by introducing only one pair of the vector-like particles at the TeV scale, and we predict the corresponding Higgs boson masses. Also, we briefly comment on the string-scale gauge coupling unification in the model with low-energy supersymmetry by introducing only one pair of the vector-like particles at the intermediate scale. And we briefly comment on the mixings among the SM fermions and the corresponding extra vector-like particles.

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.

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

Science.gov (United States)

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

1992-01-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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....

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.

Extended Higgs sectors in radiative neutrino models

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Oleg Antipin

2017-05-01

Full Text Available Testable Higgs partners may be sought within the extensions of the SM Higgs sector aimed at generating neutrino masses at the loop level. We study a viability of extended Higgs sectors for two selected models of radiative neutrino masses: a one-loop mass model, providing the Higgs partner within a real triplet scalar representation, and a three-loop mass model, providing it within its two-Higgs-doublet sector. The Higgs sector in the one-loop model may remain stable and perturbative up to the Planck scale, whereas the three-loop model calls for a UV completion around 106 GeV. Additional vector-like lepton and exotic scalar fields, which are required to close one- and three-loop neutrino-mass diagrams, play a decisive role for the testability of the respective models. We constrain the parameter space of these models using LHC bounds on diboson resonances.

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

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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.

Thai venous stroke prognostic score: TV-SPSS.

Science.gov (United States)

Poungvarin, Niphon; Prayoonwiwat, Naraporn; Ratanakorn, Disya; Towanabut, Somchai; Tantirittisak, Tassanee; Suwanwela, Nijasri; Phanthumchinda, Kamman; Tiamkoa, Somsak; Chankrachang, Siwaporn; Nidhinandana, Samart; Laptikultham, Somsak; Limsoontarakul, Sansern; Udomphanthuruk, Suthipol

2009-11-01

Prognosis of cerebral venous sinus thrombosis (CVST) has never been studied in Thailand. A simple prognostic score to predict poor prognosis of CVST has also never been reported. The authors are aiming to establish a simple and reliable prognostic score for this condition. The medical records of CVST patients from eight neurological training centers in Thailand who received between April 1993 and September 2005 were reviewed as part of this retrospective study. Clinical features included headache, seizure, stroke risk factors, Glasgow coma scale (GCS), blood pressure on arrival, papilledema, hemiparesis, meningeal irritation sign, location of occluded venous sinuses, hemorrhagic infarction, cerebrospinal fluid opening pressure, treatment options, length of stay, and other complications were analyzed to determine the outcome using modified Rankin scale (mRS). Poor prognosis (defined as mRS of 3-6) was determined on the discharge date. One hundred ninety four patients' records, 127 females (65.5%) and mean age of 36.6 +/- 14.4 years, were analyzed Fifty-one patients (26.3%) were in the poor outcome group (mRS 3-6). Overall mortality was 8.4%. Univariate analysis and then multivariate analysis using SPSS version 11.5 revealed only four statistically significant predictors influencing outcome of CVST They were underlying malignancy, low GCS, presence of hemorrhagic infarction (for poor outcome), and involvement of lateral sinus (for good outcome). Thai venous stroke prognostic score (TV-SPSS) was derived from these four factors using a multiple logistic model. A simple and pragmatic prognostic score for CVST outcome has been developed with high sensitivity (93%), yet low specificity (33%). The next study should focus on the validation of this score in other prospective populations.

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

Science.gov (United States)

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

2018-01-02

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

The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study.

Science.gov (United States)

Gnanapragasam, V J; Bratt, O; Muir, K; Lee, L S; Huang, H H; Stattin, P; Lophatananon, A

2018-02-28

The purpose of this study is to validate a new five-tiered prognostic classification system to better discriminate cancer-specific mortality in men diagnosed with primary non-metastatic prostate cancer. We applied a recently described five-strata model, the Cambridge Prognostic Groups (CPGs 1-5), in two international cohorts and tested prognostic performance against the current standard three-strata classification of low-, intermediate- or high-risk disease. Diagnostic clinico-pathological data for men obtained from the Prostate Cancer data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality. The PCBaSe cohort included 72,337 men, of whom 7162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk regression confirming significant intergroup distinction (p study of nearly 75,000 men confirms that the CPG five-tiered prognostic model has superior discrimination compared to the three-tiered model in predicting prostate cancer death across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes. We therefore propose adoption of the CPG model as a simple-to-use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer.

A prognostic tool to identify adolescents at high risk of becoming daily smokers

Directory of Open Access Journals (Sweden)

Paradis Gilles

2011-08-01

Full Text Available Abstract Background The American Academy of Pediatrics advocates that pediatricians should be involved in tobacco counseling and has developed guidelines for counseling. We present a prognostic tool for use by health care practitioners in both clinical and non-clinical settings, to identify adolescents at risk of becoming daily smokers. Methods Data were drawn from the Nicotine Dependence in Teens (NDIT Study, a prospective investigation of 1293 adolescents, initially aged 12-13 years, recruited in 10 secondary schools in Montreal, Canada in 1999. Questionnaires were administered every three months for five years. The prognostic tool was developed using estimated coefficients from multivariable logistic models. Model overfitting was corrected using bootstrap cross-validation. Goodness-of-fit and predictive ability of the models were assessed by R2, the c-statistic, and the Hosmer-Lemeshow test. Results The 1-year and 2-year probability of initiating daily smoking was a joint function of seven individual characteristics: age; ever smoked; ever felt like you needed a cigarette; parent(s smoke; sibling(s smoke; friend(s smoke; and ever drank alcohol. The models were characterized by reasonably good fit and predictive ability. They were transformed into user-friendly tables such that the risk of daily smoking can be easily computed by summing points for responses to each item. The prognostic tool is also available on-line at http://episerve.chumontreal.qc.ca/calculation_risk/daily-risk/daily_smokingadd.php. Conclusions The prognostic tool to identify youth at high risk of daily smoking may eventually be an important component of a comprehensive tobacco control system.

[Prognostic value of JAK2, MPL and CALR mutations in Chinese patients with primary myelofibrosis].

Science.gov (United States)

Xu, Z F; Li, B; Liu, J Q; Li, Y; Ai, X F; Zhang, P H; Qin, T J; Zhang, Y; Wang, J Y; Xu, J Q; Zhang, H L; Fang, L W; Pan, L J; Hu, N B; Qu, S Q; Xiao, Z J

2016-07-01

To evaluate the prognostic value of JAK2, MPL and CALR mutations in Chinese patients with primary myelofibrosis (PMF). Four hundred and two Chinese patients with PMF were retrospectively analyzed. The Kaplan-Meier method, the Log-rank test, the likelihood ratio test and the Cox proportional hazards regression model were used to evaluate the prognostic scoring system. This cohort of patients included 209 males and 193 females with a median age of 55 years (range: 15- 89). JAK2V617F mutations were detected in 189 subjects (47.0% ), MPLW515 mutations in 13 (3.2%) and CALR mutations in 81 (20.1%) [There were 30 (37.0%) type-1, 48 (59.3%) type-2 and 3 (3.7%) less common CALR mutations], respectively. 119 subjects (29.6%) had no detectable mutation in JAK2, MPL or CALR. Univariate analysis indicated that patients with CALR type-2 mutations or no detectable mutations had inferior survival compared to those with JAK2, MPL or CALR type- 1 or other less common CALR mutations (the median survival was 74vs 168 months, respectively [HR 2.990 (95% CI 1.935-4.619),P<0.001]. Therefore, patients were categorized into the high-risk with CALR type- 2 mutations or no detectable driver mutations and the low- risk without aforementioned mutations status. The DIPSS-Chinese molecular prognostic model was proposed by adopting mutation categories and DIPSS-Chinese risk group. The median survival of patients classified in low risk (132 subjects, 32.8% ), intermediate- 1 risk (143 subjects, 35.6%), intermediate- 2 risk (106 subjects, 26.4%) and high risk (21 subjects, 5.2%) were not reached, 156 (95% CI 117- 194), 60 (95% CI 28- 91) and 22 (95% CI 10- 33) months, respectively, and there was a statistically significant difference in overall survival among the four risk groups (P<0.001). There was significantly higher predictive power for survival according to the DIPSS-Chinese molecular prognostic model compared with the DIPSS-Chinese model (P=0.005, -2 log-likelihood ratios of 855.6 and 869

Prognostic Factors of Uterine Serous Carcinoma-A Multicenter Study.

Science.gov (United States)

Zhong, Xiaozhu; Wang, Jianliu; Kaku, Tengen; Wang, Zhiqi; Li, Xiaoping; Wei, Lihui

2018-04-04

The prognostic factors of uterine serous carcinoma (USC) vary among studies, and there is no report of Chinese USC patients. The aim of this study was to investigate the clinicopathological characteristics and prognostic factors in Chinese patients with USC. Patients with USC from 13 authoritative university hospitals in China and treated between 2004 and 2014 were retrospectively reviewed. Three-year disease-free survival rate (DFSR), cumulative recurrence, and cumulative mortality were estimated by Kaplan-Meier analyses and log-rank tests. Multivariate Cox regression analysis was used to model the association of potential prognostic factors with clinical outcomes. Data of a total of 241 patients were reviewed. The median follow-up was 26 months (range, 1-128 months). Median age was 60 years (range, 39-84 years), and 58.0% had stages I-II disease. The 3-year DFSR and cumulative recurrence were 46.8% and 27.7%. Advanced stage (III and IV) (P = 0.004), myometrial invasion (P = 0.001), adnexal involvement (P USC. Prospective studies are needed to confirm these results.

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

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.

Prognostic Factors for Persistent Leg-Pain in Patients Hospitalized With Acute Sciatica.

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Fjeld, Olaf; Grotle, Margreth; Siewers, Vibeke; Pedersen, Linda M; Nilsen, Kristian Bernhard; Zwart, John-Anker

2017-03-01

Prospective cohort study. To identify potential prognostic factors for persistent leg-pain at 12 months among patients hospitalized with acute severe sciatica. The long-term outcome for patients admitted to hospital with sciatica is generally unfavorable. Results concerning prognostic factors for persistent sciatica are limited and conflicting. A total of 210 patients acutely admitted to hospital for either surgical or nonsurgical treatment of sciatica were consecutively recruited and received a thorough clinical and radiographic examination in addition to responding to a comprehensive questionnaire. Follow-up assessments were done at 6 weeks, 6 months, and 12 months. Potential prognostic factors were measured at baseline and at 6 weeks. The impact of these factors on leg-pain was analyzed by multiple linear regression modeling. A total of 151 patients completed the entire study, 93 receiving nonrandomized surgical treatment. The final multivariate models showed that the following factors were significantly associated with leg-pain at 12 months: high psychosocial risk according to the Örebro Musculosceletal Pain Questionnaire (unstandardized beta coefficient 1.55, 95% confidence interval [CI] 0.72-2.38, P sciatica. 2.

Prognostic and survival analysis of 837 Chinese colorectal cancer patients.

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Yuan, Ying; Li, Mo-Dan; Hu, Han-Guang; Dong, Cai-Xia; Chen, Jia-Qi; Li, Xiao-Fen; Li, Jing-Jing; Shen, Hong

2013-05-07

To develop a prognostic model to predict survival of patients with colorectal cancer (CRC). Survival data of 837 CRC patients undergoing surgery between 1996 and 2006 were collected and analyzed by univariate analysis and Cox proportional hazard regression model to reveal the prognostic factors for CRC. All data were recorded using a standard data form and analyzed using SPSS version 18.0 (SPSS, Chicago, IL, United States). Survival curves were calculated by the Kaplan-Meier method. The log rank test was used to assess differences in survival. Univariate hazard ratios and significant and independent predictors of disease-specific survival and were identified by Cox proportional hazard analysis. The stepwise procedure was set to a threshold of 0.05. Statistical significance was defined as P analysis suggested age, preoperative obstruction, serum carcinoembryonic antigen level at diagnosis, status of resection, tumor size, histological grade, pathological type, lymphovascular invasion, invasion of adjacent organs, and tumor node metastasis (TNM) staging were positive prognostic factors (P analysis showed a significant statistical difference in 3-year survival among these groups: LNR1, 73%; LNR2, 55%; and LNR3, 42% (P analysis results showed that histological grade, depth of bowel wall invasion, and number of metastatic lymph nodes were the most important prognostic factors for CRC if we did not consider the interaction of the TNM staging system (P < 0.05). When the TNM staging was taken into account, histological grade lost its statistical significance, while the specific TNM staging system showed a statistically significant difference (P < 0.0001). The overall survival of CRC patients has improved between 1996 and 2006. LNR is a powerful factor for estimating the survival of stage III CRC patients.

Performance of critical care prognostic scoring systems in low and middle-income countries: a systematic review.

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Haniffa, Rashan; Isaam, Ilhaam; De Silva, A Pubudu; Dondorp, Arjen M; De Keizer, Nicolette F

2018-01-26

Prognostic models-used in critical care medicine for mortality predictions, for benchmarking and for illness stratification in clinical trials-have been validated predominantly in high-income countries. These results may not be reproducible in low or middle-income countries (LMICs), not only because of different case-mix characteristics but also because of missing predictor variables. The study objective was to systematically review literature on the use of critical care prognostic models in LMICs and assess their ability to discriminate between survivors and non-survivors at hospital discharge of those admitted to intensive care units (ICUs), their calibration, their accuracy, and the manner in which missing values were handled. The PubMed database was searched in March 2017 to identify research articles reporting the use and performance of prognostic models in the evaluation of mortality in ICUs in LMICs. Studies carried out in ICUs in high-income countries or paediatric ICUs and studies that evaluated disease-specific scoring systems, were limited to a specific disease or single prognostic factor, were published only as abstracts, editorials, letters and systematic and narrative reviews or were not in English were excluded. Of the 2233 studies retrieved, 473 were searched and 50 articles reporting 119 models were included. Five articles described the development and evaluation of new models, whereas 114 articles externally validated Acute Physiology and Chronic Health Evaluation, the Simplified Acute Physiology Score and Mortality Probability Models or versions thereof. Missing values were only described in 34% of studies; exclusion and or imputation by normal values were used. Discrimination, calibration and accuracy were reported in 94.0%, 72.4% and 25% respectively. Good discrimination and calibration were reported in 88.9% and 58.3% respectively. However, only 10 evaluations that reported excellent discrimination also reported good calibration

Prognostic Performance Metrics

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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...

TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

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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.

Prognostic nomograms for predicting survival and distant metastases in locally advanced rectal cancers.

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Junjie Peng

Full Text Available To develop prognostic nomograms for predicting outcomes in patients with locally advanced rectal cancers who do not receive preoperative treatment.A total of 883 patients with stage II-III rectal cancers were retrospectively collected from a single institution. Survival analyses were performed to assess each variable for overall survival (OS, local recurrence (LR and distant metastases (DM. Cox models were performed to develop a predictive model for each endpoint. The performance of model prediction was validated by cross validation and on an independent group of patients.The 5-year LR, DM and OS rates were 22.3%, 32.7% and 63.8%, respectively. Two prognostic nomograms were successfully developed to predict 5-year OS and DM-free survival rates, with c-index of 0.70 (95% CI = [0.66, 0.73] and 0.68 (95% CI = [0.64, 0.72] on the original dataset, and 0.76 (95% CI = [0.67, 0.86] and 0.73 (95% CI = [0.63, 0.83] on the validation dataset, respectively. Factors in our models included age, gender, carcinoembryonic antigen value, tumor location, T stage, N stage, metastatic lymph nodes ratio, adjuvant chemotherapy and chemoradiotherapy. Predicted by our nomogram, substantial variability in terms of 5-year OS and DM-free survival was observed within each TNM stage category.The prognostic nomograms integrated demographic and clinicopathological factors to account for tumor and patient heterogeneity, and thereby provided a more individualized outcome prognostication. Our individualized prediction nomograms could help patients with preoperatively under-staged rectal cancer about their postoperative treatment strategies and follow-up protocols.

PROGNOSTICAL COMPETENCE OF THE FUTURE TEACHERS-ACTORS: TO THE ISSUE OF THE CONCEPT DEFINITION

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Elena Viktorovna Tsalko

2016-02-01

Full Text Available In this paper on the basis of the notions of competence, forecasting, prognostical competence the author’s definition of future actors-teachers’ prognostical competence is developed. Under prognostic competence of future actors-teachers we understand a special competence that allows the subject, engaged in professional activities as a performer of roles in the theater (movies, TV, as well as performing teaching activities in the field of arts, to receive the necessary anticipatory information about the phenomenon under investigation (on performing roles in the theatre, films, and television, on the learning process and actors-teachers training. Components of prognostical competence as a type of competencies (cognitive, instrumental and operational and motivational-value are singled out. The feature of the future actor-teacher’s professional activities in the context of prognostical competence is viewed. It is the simultaneous solving the artistic-creative, organizational and teaching-upbringing problems.Purpose. The purpose of the paper is the definition of prognostical competence of future teachers-actors.Methodology. In the research the methods of theoretical level are used: comparison, analysis and synthesis, generalization, concretization; analytical methods; idealization and modeling.Result. The result of the research is the development of the author’s concept of «prognostical competence of the future teachers-actors».Practical implications. Application of the results: The results may be applied to the work of teachers-actors’ trainers as well as the researchers in Pedagogy.

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

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

2001-01-01

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

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

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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

Conceptualizing prognostic awareness in advanced cancer: a systematic review.

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Applebaum, Allison J; Kolva, Elissa A; Kulikowski, Julia R; Jacobs, Jordana D; DeRosa, Antonio; Lichtenthal, Wendy G; Olden, Megan E; Rosenfeld, Barry; Breitbart, William

2014-09-01

This systematic review synthesizes the complex literature on prognostic awareness in cancer. A total of 37 studies examining cancer patients' understanding of their prognosis were included. Prognostic awareness definitions and assessment methods were inconsistent across studies. A surprisingly high percentage of patients (up to 75%) were unaware of their poor prognosis, and in several studies, even their cancer diagnosis (up to 96%), particularly in studies conducted outside of North America. This review highlights surprisingly low rates of prognostic awareness in patients with advanced cancer as well as discrepancies in prognostic awareness assessment, suggesting the need for empirically validated measures of prognostic awareness. © The Author(s) 2013.

Mode of detection: an independent prognostic factor for women with breast cancer.

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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.

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

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

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

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

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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...

Prognostic risk stratification derived from individual patient level data for men with advanced penile squamous cell carcinoma receiving first-line systemic therapy.

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Pond, Gregory R; Di Lorenzo, Giuseppe; Necchi, Andrea; Eigl, Bernhard J; Kolinsky, Michael P; Chacko, Raju T; Dorff, Tanya B; Harshman, Lauren C; Milowsky, Matthew I; Lee, Richard J; Galsky, Matthew D; Federico, Piera; Bolger, Graeme; DeShazo, Mollie; Mehta, Amitkumar; Goyal, Jatinder; Sonpavde, Guru

2014-05-01

Prognostic factors in men with penile squamous cell carcinoma (PSCC) receiving systemic therapy are unknown. A prognostic classification system in this disease may facilitate interpretation of outcomes and guide rational drug development. We performed a retrospective analysis to identify prognostic factors in men with PSCC receiving first-line systemic therapy for advanced disease. Individual patient level data were obtained from 13 institutions to study prognostic factors in the context of first-line systemic therapy for advanced PSCC. Cox proportional hazards regression analysis was conducted to examine the prognostic effect of these candidate factors on progression-free survival (PFS) and overall survival (OS): age, stage, hemoglobin, neutrophil count, lymphocyte count, albumin, site of metastasis (visceral or nonvisceral), smoking, circumcision, regimen, ECOG performance status (PS), lymphovascular invasion, precancerous lesion, and surgery following chemotherapy. The effect of different treatments was then evaluated adjusting for factors in the prognostic model. The study included 140 eligible men. Mean age across all men was 57.0 years. Among them, 8.6%, 21.4%, and 70.0% of patients had stage 2, 3, and 4 diseases, respectively; 40.7% had ECOG PS ≥ 1, 47.4% had visceral metastases, and 73.6% received cisplatin-based chemotherapy. The multivariate model of poor prognostic factors included visceral metastases (Pstatistic of 0.657 and 0.677 for OS and PFS, respectively). The median OS for the entire population was 9 months. Median OS was not reached, 8, and 7 months for those with 0, 1, and both risk factors, respectively. Cisplatin-based regimens were associated with better OS (P = 0.017) but not PFS (P = 0.37) compared with noncisplatin-based regimens after adjusting for the 2 prognostic factors. In men with advanced PSCC receiving first-line systemic therapy, visceral metastases and ECOG PS ≥ 1 were poor prognostic factors. A prognostic model including

Prognostic factors in Guillain-Barre syndrome

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Semra Mungan

2014-12-01

Full Text Available Objective: Guillain–Barre syndrome (GBS is an immune-mediated disorder of peripheral nerves resulting as acute inflammatory demyelinating polyradiculoneuropathy. GBS has a heterogeneous clinical course and laboratory findings. Acute onset and progressive course, and is usually associated with a good prognosis but some forms have a poor prognosis. Factors that can affect the prognosis of GBS have been investigated in several studies. Assessment of poor prognostic factors of GBS plays a vital role in the management and monitorization of patients. Methods: In this retrospective study of patients admitted to the acute phase of GBS removing clinical and laboratory profiles and was planned to investigate the prognostic factors. Results: Totally 23 patients (Female/male: 16/7 were recruited. Mean age was 47 (range: 17-70 years. Statistically significant poor prognostic factors were advanced age (p=0.042, erythrocyte sedimentation rate (p=0.027 and serum albumin level (p=0.007. Conclusion: Advanced age, increased ESR and decreased albumin levels were found as poor prognostic factors in GBS.

Forecasting municipal solid waste generation using prognostic tools and regression analysis.

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Ghinea, Cristina; Drăgoi, Elena Niculina; Comăniţă, Elena-Diana; Gavrilescu, Marius; Câmpean, Teofil; Curteanu, Silvia; Gavrilescu, Maria

2016-11-01

For an adequate planning of waste management systems the accurate forecast of waste generation is an essential step, since various factors can affect waste trends. The application of predictive and prognosis models are useful tools, as reliable support for decision making processes. In this paper some indicators such as: number of residents, population age, urban life expectancy, total municipal solid waste were used as input variables in prognostic models in order to predict the amount of solid waste fractions. We applied Waste Prognostic Tool, regression analysis and time series analysis to forecast municipal solid waste generation and composition by considering the Iasi Romania case study. Regression equations were determined for six solid waste fractions (paper, plastic, metal, glass, biodegradable and other waste). Accuracy Measures were calculated and the results showed that S-curve trend model is the most suitable for municipal solid waste (MSW) prediction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development and Validation of a New Prognostic System for Patients with Hepatocellular Carcinoma.

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Fabio Farinati

2016-04-01

Full Text Available Prognostic assessment in patients with hepatocellular carcinoma (HCC remains controversial. Using the Italian Liver Cancer (ITA.LI.CA database as a training set, we sought to develop and validate a new prognostic system for patients with HCC.Prospective collected databases from Italy (training cohort, n = 3,628; internal validation cohort, n = 1,555 and Taiwan (external validation cohort, n = 2,651 were used to develop the ITA.LI.CA prognostic system. We first defined ITA.LI.CA stages (0, A, B1, B2, B3, C using only tumor characteristics (largest tumor diameter, number of nodules, intra- and extrahepatic macroscopic vascular invasion, extrahepatic metastases. A parametric multivariable survival model was then used to calculate the relative prognostic value of ITA.LI.CA tumor stage, Eastern Cooperative Oncology Group (ECOG performance status, Child-Pugh score (CPS, and alpha-fetoprotein (AFP in predicting individual survival. Based on the model results, an ITA.LI.CA integrated prognostic score (from 0 to 13 points was constructed, and its prognostic power compared with that of other integrated systems (BCLC, HKLC, MESIAH, CLIP, JIS. Median follow-up was 58 mo for Italian patients (interquartile range, 26-106 mo and 39 mo for Taiwanese patients (interquartile range, 12-61 mo. The ITA.LI.CA integrated prognostic score showed optimal discrimination and calibration abilities in Italian patients. Observed median survival in the training and internal validation sets was 57 and 61 mo, respectively, in quartile 1 (ITA.LI.CA score ≤ 1, 43 and 38 mo in quartile 2 (ITA.LI.CA score 2-3, 23 and 23 mo in quartile 3 (ITA.LI.CA score 4-5, and 9 and 8 mo in quartile 4 (ITA.LI.CA score > 5. Observed and predicted median survival in the training and internal validation sets largely coincided. Although observed and predicted survival estimations were significantly lower (log-rank test, p < 0.001 in Italian than in Taiwanese patients, the ITA.LI.CA score maintained

Current status of accurate prognostic awareness in advanced/terminally ill cancer patients: Systematic review and meta-regression analysis.

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Chen, Chen Hsiu; Kuo, Su Ching; Tang, Siew Tzuh

2017-05-01

No systematic meta-analysis is available on the prevalence of cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. To examine the prevalence of advanced/terminal cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. Systematic review and meta-analysis. MEDLINE, Embase, The Cochrane Library, CINAHL, and PsycINFO were systematically searched on accurate prognostic awareness in adult patients with advanced/terminal cancer (1990-2014). Pooled prevalences were calculated for accurate prognostic awareness by a random-effects model. Differences in weighted estimates of accurate prognostic awareness were compared by meta-regression. In total, 34 articles were retrieved for systematic review and meta-analysis. At best, only about half of advanced/terminal cancer patients accurately understood their prognosis (49.1%; 95% confidence interval: 42.7%-55.5%; range: 5.4%-85.7%). Accurate prognostic awareness was independent of service received and publication year, but highest in Australia, followed by East Asia, North America, and southern Europe and the United Kingdom (67.7%, 60.7%, 52.8%, and 36.0%, respectively; p = 0.019). Accurate prognostic awareness was higher by clinician assessment than by patient report (63.2% vs 44.5%, p cancer patients accurately understood their prognosis, with significant variations by region and assessment method. Healthcare professionals should thoroughly assess advanced/terminal cancer patients' preferences for prognostic information and engage them in prognostic discussion early in the cancer trajectory, thus facilitating their accurate prognostic awareness and the quality of end-of-life care decision-making.

Retrospective cohort study of prognostic factors in patients with oral cavity and oropharyngeal squamous cell carcinoma.

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Carrillo, José F; Carrillo, Liliana C; Cano, Ana; Ramirez-Ortega, Margarita C; Chanona, Jorge G; Avilés, Alejandro; Herrera-Goepfert, Roberto; Corona-Rivera, Jaime; Ochoa-Carrillo, Francisco J; Oñate-Ocaña, Luis F

2016-04-01

Prognostic factors in oral cavity and oropharyngeal squamous cell carcinoma (SCC) are debated. The purpose of this study was to investigate the association of prognostic factors with oncologic outcomes. Patients with oral cavity and oropharyngeal SCC treated from 1997 to 2012 were included in this retrospective cohort study. Associations of prognostic factors with locoregional recurrence (LRR) or overall survival (OS) were analyzed using the logistic regression and the Cox models. Six hundred thirty-four patients were included in this study; tumor size, surgical margins, and N classification were associated with LRR (p oral cavity and oropharyngeal SCC. © 2015 Wiley Periodicals, Inc.

Prognostic Assessment in Patients with Indolent B-Cell Lymphomas

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Luca Arcaini

2012-01-01

Full Text Available Follicular lymphoma (FL is an indolent lymphoma with long median survival. Many studies have been performed to build up prognostic scores potentially useful to identify patients with poorer outcome. In 2004, an international consortium coordinated by the International Follicular Lymphoma Prognostic Factor project was established and a new prognostic study was launched (FLIPI2 using progression-free survival (PFS as main endpoint and integrating all the modern parameters prospectively collected. Low-grade non-Hodgkin lymphomas were once considered as a heterogenous group of lymphomas characterized by an indolent clinical course. Each entity is characterized by unique clinicobiologic features. Some studies have been focused on prognostic factors in single lymphoma subtypes, with the development of specific-entity scores based on retrospective series, for instance splenic marginal zone lymphoma (SMZL. A widely accepted prognostic tool for clinical usage for indolent non-follicular B-cell lymphomas is largely awaited. In this paper we summarized the current evidence regarding prognostic assessment of indolent follicular and non-follicular lymphomas.

Prognostic indicators for failed nonsurgical reduction of intussusception

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Khorana J

2016-08-01

Full Text Available Jiraporn Khorana,1 Jesda Singhavejsakul,1 Nuthapong Ukarapol,2 Mongkol Laohapensang,3 Jakraphan Siriwongmongkol,1 Jayanton Patumanond4 1Division of Pediatric Surgery, Department of Surgery, 2Division of Gastroenterology, Department of Pediatrics, Chiang Mai University Hospital, Chiang Mai, 3Division of Pediatric Surgery, Department of Surgery, Siriraj Hospital, Mahidol University, Bangkok, 4Center of Excellence in Applied Epidemiology, Thammasat University Hospital, Pathumthani, Thailand Purpose: To identify the risk factors for failure of nonsurgical reduction of intussusception. Methods: Data from intussusception patients who were treated with nonsurgical reduction in Chiang Mai University Hospital and Siriraj Hospital between January 2006 and December 2012 were collected. Patients aged 0–15 years and without contraindications (peritonitis, abdominal X-ray signs of perforation, and/or hemodynamic instability were included for nonsurgical reduction. The success and failure groups were divided according to the results of the reduction. Prognostic indicators for failed reduction were identified by using generalized linear model for exponential risk regression. The risk ratio (RR was used to report each factor. Results: One hundred and ninety cases of intussusception were enrolled. Twenty cases were excluded due to contraindications. A total of 170 cases of intussusception were included for the final analysis. The significant risk factors for reduction failure clustered by an age of 3 years were weight <12 kg (RR =1.48, P=0.004, symptom duration >3 days (RR =1.26, P<0.001, vomiting (RR =1.63, P<0.001, rectal bleeding (RR =1.50, P<0.001, abdominal distension (RR =1.60, P=0.003, temperature >37.8°C (RR =1.51, P<0.001, palpable abdominal mass (RR =1.26, P<0.001, location of mass (left over right side (RR =1.48, P<0.001, poor prognostic signs on ultrasound scans (RR =1.35, P<0.001, and method of reduction (hydrostatic over pneumatic (RR =1

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

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

2017-12-01

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

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

DEFF Research Database (Denmark)

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

2016-01-01

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

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

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

2016-08-01

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

Communication Optimizations for a Wireless Distributed Prognostic Framework

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National Aeronautics and Space Administration — Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication...

On a testable unification of electromagnetics, general relativity, and quantum mechanics

International Nuclear Information System (INIS)

Bearden, T.E.; Rosenthal, W.

1991-01-01

Unrecognized for what it was, in 1903-1904 E.T. Whittaker (W) published a fundamental, engineerable theory of electogravitation (EG) in two profound papers. The first (W-1903) demonstrated a hidden bidirectional EM wave structure in the scalar potential of vacuum, and showed how to produce a standing scalar EM potential wave -- the same wave discovered experimentally four years earlier by Nikola Tesla. W-1903 is a hidden variable theory that shows how to determinsitically curve the local and/or distant spacetime using EM. W-1904 shows that all force field EM can be replaced by interferometry of two scalar potentials, anticipating the Aharonov-Bohm effect by 55 years and extending it to the engineerable macroscopic world. W-1903 shows how to turn EM into G-potential, curve local and/or distant spacetime, and directly engineer the virtual particle flux of vacuum. W-1904 shows how to turn G-potential and curvature of spacetime back into force-field EM, even at a distance. The papers implement Sahkarov's 1968 statement that gravitation is not a fundamental field of nature, gut a conglomerate of other fields. Separately applied to electromagnetic (EM), quantum mechanics (QM), and general relativity (GR), an extended superset of each results. The three supersets are Whittaker-unified, so that a testable, engineerable, unified field theory is generated. EM, QM, and GR each contained a fundamental error that blocked unification, and these three errors are explain. The Schroedinger potential can also be structured and altered, indicating the direct engineering of physical quantum change. Recently Ignatovich has pointed out this hidden bidirectional EM wave structure in the Schroedinger potential, without referencing Whittaker's 1903 discovery of the basic effect

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

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SokolovI.M.

2012-09-01

Full Text Available

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

Comparison of colorectal and gastric cancer: Survival and prognostic factors

International Nuclear Information System (INIS)

Moghimi-Dehkordi, Bijan; Safaee, Azadeh; Zali, Mohammad R

2009-01-01

Gastric and colorectal cancers are the most common gastrointestinal malignancies in Iran. We aim to compare the survival rates and prognostic factors between these two cancers. We studied 1873 patients with either gastric or colorectal cancer who were registered in one referral cancer registry center in Tehran, Iran. All patients were followed from their time of diagnosis until December 2006 (as failure time). Survival curves were calculated according to the Kaplan-Meier Method and compared by the Log-rank test. Multivariate analysis of prognostic factors was carried out using the Cox proportional hazard model. Of 1873 patients, there were 746 with gastric cancer and 1138 with colorectal cancer. According to the Kaplan-Meier method 1, 3, 5, and 7-year survival rates were 71.2, 37.8, 25.3, and 19.5%, respectively, in gastric cancer patients and 91.1, 73.1, 61, and 54.9%, respectively, in patients with colorectal cancer. Also, univariate analysis showed that age at diagnosis, sex, grade of tumor, and distant metastasis were of prognostic significance in both cancers ( P < 0.0001). However, in multivariate analysis, only distant metastasis in colorectal cancer and age at diagnosis, grade of tumor, and distant metastasis in colorectal cancer were identified as independent prognostic factors influencing survival. According to our findings, survival is significantly related to histological differentiation of tumor and distant metastasis in colorectal cancer patients and only to distant metastasis in gastric cancer patients. (author)

Distributed Prognostics System Implementation on Wireless Embedded Devices

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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...

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

Science.gov (United States)

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

2013-03-01

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

Model building

International Nuclear Information System (INIS)

Frampton, Paul H.

1998-01-01

In this talk I begin with some general discussion of model building in particle theory, emphasizing the need for motivation and testability. Three illustrative examples are then described. The first is the Left-Right model which provides an explanation for the chirality of quarks and leptons. The second is the 331-model which offers a first step to understanding the three generations of quarks and leptons. Third and last is the SU(15) model which can accommodate the light leptoquarks possibly seen at HERA

Prognostic, predictive and pharmacogenomic assessments of CDX2 refine stratification of colorectal cancer.

Science.gov (United States)

Bruun, Jarle; Sveen, Anita; Barros, Rita; Eide, Peter W; Eilertsen, Ina; Kolberg, Matthias; Pellinen, Teijo; David, Leonor; Svindland, Aud; Kallioniemi, Olli; Guren, Marianne G; Nesbakken, Arild; Almeida, Raquel; Lothe, Ragnhild A

2018-06-14

We aimed to refine the value of CDX2 as an independent prognostic and predictive biomarker in colorectal cancer (CRC) according to disease stage and chemotherapy sensitivity in preclinical models. CDX2 expression was evaluated in 1045 stage I-IV primary CRCs by gene expression (n=403) or immunohistochemistry (n=642) and in relation to 5-year relapse-free survival (RFS), overall survival (OS), and chemotherapy. Pharmacogenomic associations between CDX2 expression and 69 chemotherapeutics were assessed by drug screening of 35 CRC cell lines. CDX2 expression was lost in 11.6% of cases and showed independent poor prognostic value in multivariable models. For individual stages, CDX2 was prognostic only in stage IV, independent of chemotherapy. Among stage I-III patients not treated in an adjuvant setting, CDX2 loss was associated with a particularly poor survival in the BRAF-mutated subgroup, but prognostic value was independent of microsatellite instability status and the consensus molecular subtypes In stage III, the 5-year RFS rate was higher among patients with loss of CDX2 who received adjuvant chemotherapy than among patients who did not. The CDX2-negative cell lines were significantly more sensitive to chemotherapeutics than CDX2-positive cells, and the multidrug resistance genes MDR1 and CFTR were significantly downregulated both in CDX2-negative cells and patient tumors. Molecular Oncology (2018) © 2018 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

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

A simulation study on estimating biomarker-treatment interaction effects in randomized trials with prognostic variables.

Science.gov (United States)

Haller, Bernhard; Ulm, Kurt

2018-02-20

To individualize treatment decisions based on patient characteristics, identification of an interaction between a biomarker and treatment is necessary. Often such potential interactions are analysed using data from randomized clinical trials intended for comparison of two treatments. Tests of interactions are often lacking statistical power and we investigated if and how a consideration of further prognostic variables can improve power and decrease the bias of estimated biomarker-treatment interactions in randomized clinical trials with time-to-event outcomes. A simulation study was performed to assess how prognostic factors affect the estimate of the biomarker-treatment interaction for a time-to-event outcome, when different approaches, like ignoring other prognostic factors, including all available covariates or using variable selection strategies, are applied. Different scenarios regarding the proportion of censored observations, the correlation structure between the covariate of interest and further potential prognostic variables, and the strength of the interaction were considered. The simulation study revealed that in a regression model for estimating a biomarker-treatment interaction, the probability of detecting a biomarker-treatment interaction can be increased by including prognostic variables that are associated with the outcome, and that the interaction estimate is biased when relevant prognostic variables are not considered. However, the probability of a false-positive finding increases if too many potential predictors are included or if variable selection is performed inadequately. We recommend undertaking an adequate literature search before data analysis to derive information about potential prognostic variables and to gain power for detecting true interaction effects and pre-specifying analyses to avoid selective reporting and increased false-positive rates.

Prognostic value of 18F-FLT PET in patients with neuroendocrine neoplasms

DEFF Research Database (Denmark)

Johnbeck, Camilla B.; Knigge, Ulrich; Langer, Seppo W.

2016-01-01

Neuroendocrine neoplasms (NENs) constitute a heterogeneous group of tumors arising in various organs and with a large span of aggressiveness and survival rates. The Ki-67 proliferation index is presently used as the key marker of prognosis, and treatment guidelines are largely based on this index...... study was to investigate 18F-FLT PET as a prognostic marker for NENs in comparison with 18F-FDG PET and Ki-67 index. Methods: One hundred patients were PET-scanned with both 18F-FLT and 18F-FDG within the same week, and the prognostic value of a positive scan was examined in terms of progression...... prognostic value in NEN patients but when 18F-FDG PET and Ki-67 index are also available, a multivariate model revealed that 18F-FLT PET only adds information regarding PFS but not OS, whereas 18F-FDG PET remains predictive of both PFS and OS. However, a clinically robust algorithm including 18F...

Systematic profiling of alternative splicing signature reveals prognostic predictor for ovarian cancer.

Science.gov (United States)

Zhu, Junyong; Chen, Zuhua; Yong, Lei

2018-02-01

The majority of genes are alternatively spliced and growing evidence suggests that alternative splicing is modified in cancer and is associated with cancer progression. Systematic analysis of alternative splicing signature in ovarian cancer is lacking and greatly needed. We profiled genome-wide alternative splicing events in 408 ovarian serous cystadenocarcinoma (OV) patients in TCGA. Seven types of alternative splicing events were curated and prognostic analyses were performed with predictive models and splicing network built for OV patients. Among 48,049 mRNA splicing events in 10,582 genes, we detected 2,611 alternative splicing events in 2,036 genes which were significant associated with overall survival of OV patients. Exon skip events were the most powerful prognostic factors among the seven types. The area under the curve of the receiver-operator characteristic curve for prognostic predictor, which was built with top significant alternative splicing events, was 0.937 at 2,000 days of overall survival, indicating powerful efficiency in distinguishing patient outcome. Interestingly, splicing correlation network suggested obvious trends in the role of splicing factors in OV. In summary, we built powerful prognostic predictors for OV patients and uncovered interesting splicing networks which could be underlying mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

A CVAR scenario for a standard monetary model using theory-consistent expectations

DEFF Research Database (Denmark)

Juselius, Katarina

2017-01-01

A theory-consistent CVAR scenario describes a set of testable regularities capturing basic assumptions of the theoretical model. Using this concept, the paper considers a standard model for exchange rate determination and shows that all assumptions about the model's shock structure and steady...

Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

Science.gov (United States)

Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

2018-05-02

The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Prognostic DNA Methylation Markers for Prostate Cancer

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Siri H. Strand

2014-09-01

Full Text Available Prostate cancer (PC is the most commonly diagnosed neoplasm and the third most common cause of cancer-related death amongst men in the Western world. PC is a clinically highly heterogeneous disease, and distinction between aggressive and indolent disease is a major challenge for the management of PC. Currently, no biomarkers or prognostic tools are able to accurately predict tumor progression at the time of diagnosis. Thus, improved biomarkers for PC prognosis are urgently needed. This review focuses on the prognostic potential of DNA methylation biomarkers for PC. Epigenetic changes are hallmarks of PC and associated with malignant initiation as well as tumor progression. Moreover, DNA methylation is the most frequently studied epigenetic alteration in PC, and the prognostic potential of DNA methylation markers for PC has been demonstrated in multiple studies. The most promising methylation marker candidates identified so far include PITX2, C1orf114 (CCDC181 and the GABRE~miR-452~miR-224 locus, in addition to the three-gene signature AOX1/C1orf114/HAPLN3. Several other biomarker candidates have also been investigated, but with less stringent clinical validation and/or conflicting evidence regarding their possible prognostic value available at this time. Here, we review the current evidence for the prognostic potential of DNA methylation markers in PC.

EPID-28. PROGNOSTIC AND PREDICTIVE BIOMARKERS IN RECURRENT WHO GRADE 3 GLIOMA PATIENTS TREATED WITH BEVACIZUMAB AND IRINOTECAN

DEFF Research Database (Denmark)

Toft, Anders; Urup, Thomas; Grunnet, Kirsten

2015-01-01

BACKGROUND: Bevacizumab, a monoclonal antibody targeting vascular endothelial growth factor A (VEGF-A) has shown activity in the treatment of recurrent malignant glioma. Predictive markers and prognostic models are required in order to individualize treatment for grade 3 glioma patients. The prim......BACKGROUND: Bevacizumab, a monoclonal antibody targeting vascular endothelial growth factor A (VEGF-A) has shown activity in the treatment of recurrent malignant glioma. Predictive markers and prognostic models are required in order to individualize treatment for grade 3 glioma patients...... response MRI (RANO criteria). Responders had significantly prolonged OS (p ¼ 0.007) and trended toward longer PFS (p ¼ 0.067) as compared to non-responders (OS: 12.4 vs 4.3 months, PFS: 5.6 vs 3.2 months). A favorable WHO performance status (PS) and absence of necrosis were significantly more common...... in responders than nonresponders. Multivariate analysis also identified a poor PS as the only prognostic factor for PFS, while an unfavorable PS and immunohistochemical p53 accumulation were prognostic of reducedOS.CONCLUSIONS:Apoor baseline PS and the presence of necrosis were negatively associated...

True-and-error models violate independence and yet they are testable

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Michael H. Birnbaum

2013-11-01

Full Text Available Birnbaum (2011 criticized tests of transitivity that are based entirely on binary choice proportions. When assumptions of independence and stationarity (iid of choice responses are violated, choice proportions could lead to wrong conclusions. Birnbaum (2012a proposed two statistics (correlation and variance of preference reversals to test iid, using random permutations to simulate p-values. Cha, Choi, Guo, Regenwetter, and Zwilling (2013 defended methods based on marginal proportions but conceded that such methods wrongly diagnose hypothetical examples of Birnbaum (2012a. However, they also claimed that ``true and error'' models also satisfy independence and also fail in such cases unless they become untestable. This article presents correct true-and-error models; it shows how these models violate iid, how they might correctly identify cases that would be misdiagnosed by marginal proportions, and how they can be tested and rejected. This note also refutes other arguments of Cha et al. (2013, including contentions that other tests failed to violate iid ``with flying colors'', that violations of iid ``do not replicate'', that type I errors are not appropriately estimated by the permutation method, and that independence assumptions are not critical to interpretation of marginal choice proportions.

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...

Model building

International Nuclear Information System (INIS)

Frampton, P.H.

1998-01-01

In this talk I begin with some general discussion of model building in particle theory, emphasizing the need for motivation and testability. Three illustrative examples are then described. The first is the Left-Right model which provides an explanation for the chirality of quarks and leptons. The second is the 331-model which offers a first step to understanding the three generations of quarks and leptons. Third and last is the SU(15) model which can accommodate the light leptoquarks possibly seen at HERA. copyright 1998 American Institute of Physics

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.

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment

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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.

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

Science.gov (United States)

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

Directory of Open Access Journals (Sweden)

Liao X

2018-04-01

Full Text Available Xiwen Liao,1 Guangzhi Zhu,1 Rui Huang,2 Chengkun Yang,1 Xiangkun Wang,1 Ketuan Huang,1 Tingdong Yu,1 Chuangye Han,1 Hao Su,1 Tao Peng1 1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China Background: The aim of the present study was to identify potential prognostic microRNA (miRNA biomarkers for hepatocellular carcinoma (HCC prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA. Materials and methods: A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs, and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results: Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394, and time-dependent receiver–operating characteristic (ROC analysis showed an area under the curve (AUC of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration

Prognostic indices for brain metastases – usefulness and challenges

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Nieder Carsten

2009-03-01

Full Text Available Abstract Background This review addresses the strengths and weaknesses of 6 different prognostic indices, published since the Radiation Therapy Oncology Group (RTOG developed and validated the widely used 3-tiered prognostic index known as recursive partitioning analysis (RPA classes, i.e. between 1997 and 2008. In addition, other analyses of prognostic factors in groups of patients, which typically are underrepresented in large trials or databases, published in the same time period are reviewed. Methods Based on a systematic literature search, studies with more than 20 patients were included. The methods and results of prognostic factor analyses were extracted and compared. The authors discuss why current data suggest a need for a more refined index than RPA. Results So far, none of the indices has been derived from analyses of all potential prognostic factors. The 3 most recently published indices, including the RTOG's graded prognostic assessment (GPA, all expanded from the primary 3-tiered RPA system to a 4-tiered system. The authors' own data confirm the results of the RTOG GPA analysis and support further evaluation of this tool. Conclusion This review provides a basis for further refinement of the current prognostic indices by identifying open questions regarding, e.g., performance of the ideal index, evaluation of new candidate parameters, and separate analyses for different cancer types. Unusual primary tumors and their potential differences in biology or unique treatment approaches are not well represented in large pooled analyses.

Expression and prognostic significance of lysozyme in male breast cancer

International Nuclear Information System (INIS)

Serra, Carlos; Baltasar, Aniceto; Medrano, Justo; Vizoso, Francisco; Alonso, Lorena; Rodríguez, Juan C; González, Luis O; Fernández, María; Lamelas, María L; Sánchez, Luis M; García-Muñiz, José L

2002-01-01

Lysozyme, one of the major protein components of human milk that is also synthesized by a significant percentage of breast carcinomas, is associated with lesions that have a favorable outcome in female breast cancer. Here we evaluate the expression and prognostic value of lysozyme in male breast cancer (MBC). Lysozyme expression was examined by immunohistochemical methods in a series of 60 MBC tissue sections and in 15 patients with gynecomastia. Staining was quantified using the HSCORE (histological score) system, which considers both the intensity and the percentage of cells staining at each intensity. Prognostic value of lysozyme was retrospectively evaluated by multivariate analysis taking into account conventional prognostic factors. Lysozyme immunostaining was negative in all cases of gynecomastia. A total of 27 of 60 MBC sections (45%) stained positively for this protein, but there were clear differences among them with regard to the intensity and percentage of stained cells. Statistical analysis showed that lysozyme HSCORE values in relation to age, tumor size, nodal status, histological grade, estrogen receptor status, metastasis and histological type did not increase the statistical significance. Univariate analysis confirmed that both nodal involvement and lysozyme values were significant predictors of short-term relapse-free survival. Multivariate analysis, according to Cox's regression model, also showed that nodal status and lysozyme levels were significant independent indicators of short-term relapse-free survival. Tumor expression of lysozyme is associated with lesions that have an unfavorable outcome in male breast cancer. This milk protein may be a new prognostic factor in patients with breast cancer

Stage-dependent prognostic impact of molecular signatures in clear cell renal cell carcinoma

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Weber T

2014-05-01

Full Text Available Thomas Weber,1,2 Matthias Meinhardt,3 Stefan Zastrow,1 Andreas Wienke,4 Kati Erdmann,1 Jörg Hofmann,1 Susanne Fuessel,1 Manfred P Wirth11Department of Urology, Technische Universität Dresden, Dresden, Germany; 2Department of Oncology and Hematology, Martin-Luther-University Halle-Wittenberg, Halle (Saale, Germany; 3Institute of Pathology, Technische Universität Dresden, Dresden, Germany; 4Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale, GermanyPurpose: To enhance prognostic information of protein biomarkers for clear cell renal cell carcinomas (ccRCCs, we analyzed them within prognostic groups of ccRCC harboring different tumor characteristics of this clinically and molecularly heterogeneous tumor entity.Methods: Tissue microarrays from 145 patients with primary ccRCC were immunohistochemically analyzed for VHL (von Hippel-Lindau tumor suppressor, Ki67 (marker of proliferation 1, p53 (tumor protein p53, p21 (cyclin-dependent kinase inhibitor 1A, survivin (baculoviral IAP repeat containing 5, and UEA-1 (ulex europaeus agglutinin I to assess microvessel-density.Results: When analyzing all patients, nuclear staining of Ki67 (hazard ratio [HR] 1.08, 95% confidence interval [CI] 1.04–1.12 and nuclear survivin (nS; HR 1.04, 95% CI 1.01–1.08 were significantly associated with disease-specific survival (DSS. In the cohort of patients with advanced localized or metastasized ccRCC, high staining of Ki67, p53 and nS predicted shorter DSS (Ki67: HR 1.07, 95% CI 1.02–1.11; p53: HR 1.05, 95% CI 1.01–1.09; nS: HR 1.08, 95% CI 1.02–1.14. In organ-confined ccRCC, patients with high p21-staining had a longer DSS (HR 0.96, 95% CI 0.92–0.99. In a multivariate model with stepwise backward elimination, tumor size and p21-staining showed a significant association with DSS in patients with "organ-confined" ccRCCs. The p21-staining increased the concordance index of tumor size from

Validation of a new prognostic index score for disseminated nasopharyngeal carcinoma

OpenAIRE

Toh, C-K; Heng, D; Ong, Y-K; Leong, S-S; Wee, J; Tan, E-H

2005-01-01

Patients with metastatic nasopharyngeal carcinoma have variable survival outcomes. We previously designed a scoring system to better prognosticate these patients. Here, we report results on validation of this new prognostic index score in a separate cohort of patients. Clinical features and laboratory parameters were examined in 172 patients with univariate and multivariate analyses and a numerical score was derived for each independent prognostic variable. Significant independent prognostic ...

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...

Early prognostication markers in cardiac arrest patients treated with hypothermia.

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Karapetkova, M; Koenig, M A; Jia, X

2016-03-01

Established prognostication markers, such as clinical findings, electroencephalography (EEG) and biochemical markers, used by clinicians to predict neurological outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. MEDLINE and Embase were searched for evidence on the current standards for neurological outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers and multimodal approaches for prognostication are included and reviewed. Whilst the prognostic accuracy of various tests after TH has been questioned, pupillary light reflexes and somatosensory evoked potentials are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 h after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as magnetic resonance imaging and computed tomography, can identify functional and structural brain injury but are not readily available at the patient's bedside because of limited availability and high costs. A multimodal algorithm composed of neurological examination, EEG-based quantitative testing and somatosensory evoked potentials, in conjunction with newer magnetic resonance imaging sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed more than 72 h after CA. © 2015 EAN.

Prognostic Marker before Treatment of Patients with Malignant Glioma

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Norbert Galldiks

2012-11-01

Full Text Available The purpose of this positron emission tomography (PET study was to compare the prognostic value of pretreatment volume of [11C] methionine (MET uptake and semiquantitative MET uptake ratio in patients with malignant glioma. The study population comprised 40 patients with malignant glioma. Pretreatment magnetic resonance imaging (MRI and MET-PET imaging were performed before the initiation of glioma treatment in all patients. The pretreatment MET uptake ratios and volumes were assessed. To create prognostically homogeneous subgroups, patients′ pretreatment prognostic factors were stratified according to the six classes of Radiation Therapy Oncology Group recursive partitioning analysis (RTOG RPA. Univariate and multivariate analyses were performed to determine significant prognostic factors. Survival analyses identified the pretreatment volume of MET uptake and a higher RTOG RPA class as significant predictors. In contrast, pretreatment maximum areas of contrast enhancement on MRI and semiquantitative MET uptake ratios could not be identified as significant prognostic factors. The patients′ outcomes and Karnofsky Performance Scale scores were significantly correlated with pretreatment volume of MET uptake but not with semiquantitative MET uptake ratio. The data suggest that pretreatment volumetry of MET uptake but not the semiquantitative MET uptake ratio is a useful biologic prognostic marker in patients with malignant glioma.

Clinicopathological Features and Prognostic Factors of Colorectal Neuroendocrine Neoplasms

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Mengjie Jiang

2017-01-01

Full Text Available Background. Limited research is available regarding colorectal NENs and the prognostic factors remain controversial. Materials and Methods. A total of 68 patients with colorectal NENs were studied retrospectively. Clinical characteristics and prognosis between colonic and rectal NENs were compared. The Cox regression models were used to evaluate the predictive capacity. Results. Of the 68 colorectal NENs patients, 43 (63.2% had rectal NENs, and 25 (36.8% had colonic NENs. Compared with rectal NENs, colonic NENs more frequently exhibited larger tumor size (P<0.0001 and distant metastasis (P<0.0001. Colonic NENs had a worse prognosis (P=0.027, with 5-year overall survival rates of 66.7% versus 88.1%. NET, NEC, and MANEC were noted in 61.8%, 23.5%, and 14.7% of patients, respectively. Multivariate analyses revealed that tumor location was not an independent prognostic factor (P=0.081, but tumor size (P=0.037 and pathological classification (P=0.012 were independent prognostic factors. Conclusion. Significant differences exist between colonic and rectal NENs. Multivariate analysis indicated that tumor size and pathological classification were associated with prognosis. Tumor location was not an independent factor. The worse outcome of colonic NENs observed in clinical practice might be due not only to the biological differences, but also to larger tumor size in colonic NENs caused by the delayed diagnosis.

The prognostic effect of perineural invasion in esophageal squamous cell carcinoma

International Nuclear Information System (INIS)

Chen, Jie-Wei; Cai, Mu-Yan; Xie, Jing-Dun; Ling, Yi-Hong; Li, Peng; Yan, Shu-Mei; Xi, Shao-Yan; Luo, Rong-Zhen; Yun, Jing-Ping; Xie, Dan

2014-01-01

Perineural invasion (PNI) is correlated with adverse survival in several malignancies, but its significance in esophageal squamous cell carcinoma (ESCC) remains to be clearly defined. The objective of this study was to determine the association between PNI status and clinical outcomes. We retrospectively evaluated the PNI of 433 patients with ESCC treated with surgery between 2000 and 2007 at a single academic center. The resulting data were analyzed using Spearman’s rank correlation, the Kaplan-Meier method, Cox proportional hazards regression modeling and Harrell’s concordance index (C-index). PNI was identified in 209 of the 433 (47.7%) cases of ESCC. The correlation analysis demonstrated that PNI in ESCC was significantly correlated with tumor differentiation, infiltration depth, pN classification and stage (P < 0.05). The five-year overall survival rate was 0.570 for PNI-negative tumors versus 0.326 for PNI-positive tumors. Patients with PNI-negative tumors exhibited a 1.7-fold increase in five-year recurrence-free survival compared with patients with PNI-positive tumors (0.531 v 0.305, respectively; P < 0.0001). In the subset of patients with node-negative disease, PNI was evaluated as a prognostic predictor as well (P < 0.05). In the multivariate analysis, PNI was an independent prognostic factor for overall survival (P = 0.027). The C-index estimate for the combined model (PNI, gender and pN status) was a significant improvement on the C-index estimate of the clinicopathologic model alone (0.739 v 0.706, respectively). PNI can function as an independent prognostic factor of outcomes in ESCC patients, and the PNI status in primary ESCC specimens should be considered for therapy stratification

Incremental Prognostic Value of Apparent Diffusion Coefficient Histogram Analysis in Head and Neck Squamous Cell Carcinoma.

Science.gov (United States)

Li, Xiaoxia; Yuan, Ying; Ren, Jiliang; Shi, Yiqian; Tao, Xiaofeng

2018-03-26

We aimed to investigate the incremental prognostic value of apparent diffusion coefficient (ADC) histogram analysis in patients with head and neck squamous cell carcinoma (HNSCC) and integrate it into a multivariate prognostic model. A retrospective review of magnetic resonance imaging findings was conducted in patients with pathologically confirmed HNSCC between June 2012 and December 2015. For each tumor, six histogram parameters were derived: the 10th, 50th, and 90th percentiles of ADC (ADC 10 , ADC 50 , and ADC 90 ); mean ADC values (ADC mean ); kurtosis; and skewness. The clinical variables included age, sex, smoking status, tumor volume, and tumor node metastasis stage. The association of these histogram and clinical variables with overall survival (OS) was determined. Further validation of the histogram parameters as independent biomarkers was performed using multivariate Cox proportional hazard models combined with clinical variables, which was compared to the clinical model. Models were assessed with C index and receiver operating characteristic curve analyses for the 12- and 36-month OS. Ninety-six patients were eligible for analysis. Median follow-up was 877 days (range, 54-1516 days). A total of 29 patients died during follow-up (30%). Patients with higher ADC values (ADC 10  > 0.958 × 10 -3 mm 2 /s, ADC 50  > 1.089 × 10 -3 mm 2 /s, ADC 90  > 1.152 × 10 -3 mm 2 /s, ADC mean  > 1.047 × 10 -3 mm 2 /s) and lower kurtosis (≤0.967) were significant predictors of poor OS (P histogram analysis has incremental prognostic value in patients with HNSCC and increases the performance of a multivariable prognostic model in addition to clinical variables. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Prognostic role of ABO blood type in patients with extranodal natural killer/T cell lymphoma, nasal type: a triple-center study.

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Li, Ya-Jun; Yi, Ping-Yong; Li, Ji-Wei; Liu, Xian-Ling; Tang, Tian; Zhang, Pei-Ying; Jiang, Wen-Qi

2017-07-31

The prognostic significance of ABO blood type for lymphoma is largely unknown. We evaluated the prognostic role of ABO blood type in patients with extranodal natural killer (NK)/T-cell lymphoma (ENKTL). We retrospectively analyzed clinical data of 697 patients with newly diagnosed ENKTL from three cancer centers. The prognostic value of ABO blood type was evaluated using Kaplan-Meier curves and Cox proportional hazard models. The prognostic values of the International Prognostic Index (IPI) and the Korean Prognostic Index (KPI) were also evaluated. Compared with patients with blood type O, those with blood type non-O tended to display elevated baseline serum C-reactive protein levels (P = 0.038), lower rate of complete remission (P = 0.005), shorter progression-free survival (PFS, P 60 years (P KPI in distinguishing between the intermediate-to-low- and high-to-intermediate-risk groups. ABO blood type was an independent predictor of clinical outcome for patients with ENKTL.

Prognostics-Enabled Power Supply for ADAPT Testbed, Phase II

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National Aeronautics and Space Administration — Ridgetop's role is to develop electronic prognostics for sensing power systems in support of NASA/Ames ADAPT testbed. The prognostic enabled power systems from...

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

Science.gov (United States)

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

2006-06-01

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

Heterogeneity of Prognostic Profiles in Non-small Cell Lung Cancer: Too Many Variables but a Few Relevant

International Nuclear Information System (INIS)

Camara, Agustin Gomez de la; Lopez-Encuentra, Angel; Ferrando, Paloma

2005-01-01

Objective: Many prognostic factors, exceeding 150, for non-small cell lung cancer (NSCLC) are mentioned in the literature. The different statistical weight of the some variables at issue, their heterogeneity and their clinical uselessness is reviewed. Study design and setting: Survival analysis of a cohort of NSCLC operated (n = 1730, 1993-1997) was carried out utilizing different statistical approaches: Cox proportional hazard analysis (CPHA), logistic regression (LRA), and recursive partitioning (CART). Results: CPHA identified 13 prognostic variables and 11 LRA. Of the 17 possible variables, 10 are coincident. CART provided five different diagnostic groups but only three differentiated survival levels. Parsimonious models were constructed including only T and N cancer staging variables. Areas under the ROC curve of 0.68 and 0.68 were found for CPHA and LGA parsimonious models respectively, and 0.72 and 0.71 for complete models. Conclusion: Variables with a minimal impact on the respective models and thus with little or scarce predictive clinical repercussion were identified. Differences in the prognostic profile of survival can be caused by the different methodological approaches used. No relevant differences were found between the parsimonious and complete models. Although the amount of information managed is considerable, there continues to be a large predictive gap yet to be explained

Prognostic Disclosure and its Influence on Cancer Patients

Directory of Open Access Journals (Sweden)

Chen-Hsiu Chen

2014-09-01

Conclusions: In order to close the gap between patients’ preferences for prognostic disclosure and actual receipt of prognostic information, healthcare professionals should develop interventions to overcome the physicians’ difficulty in revealing prognosis, thus facilitating cancer patients’ awareness of prognosis and providing high quality end-of-life care.

A Prognostic Method for Fault Detection in Wind Turbine Drivetrains

DEFF Research Database (Denmark)

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

2014-01-01

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

DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

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Amandine Etcheverry

Full Text Available Consistently reported prognostic factors for glioblastoma (GBM are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors that responded poorly to the standard regimen. We further evaluated the potential prognostic value of DGKI methylation status.399 patients with newly diagnosed GBM and treated with a standard regimen were retrospectively included in this study. Survival modelling was performed on two patient populations: intention-to-treat population of all included patients (population 1 and MGMT-methylated patients (population 2. Cox proportional hazard models were fitted to identify the main prognostic factors. A nomogram was developed for population 1. The prognostic value of DGKI promoter methylation status was evaluated on population 1 and population 2.The nomogram-based stratification of the cohort identified two risk groups (high/low with significantly different median survival. We validated the prognostic value of DGKI methylation status for MGMT-methylated patients. We also demonstrated that the DGKI methylation status identified 22% of poorly responding patients in the low-risk group defined by the nomogram.Our results improve the conventional MGMT stratification of GBM patients receiving standard treatment. These results could help the interpretation of published or ongoing clinical trial outcomes and refine patient recruitment in the future.

DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

Science.gov (United States)

Etcheverry, Amandine; Aubry, Marc; Idbaih, Ahmed; Vauleon, Elodie; Marie, Yannick; Menei, Philippe; Boniface, Rachel; Figarella-Branger, Dominique; Karayan-Tapon, Lucie; Quillien, Veronique; Sanson, Marc; de Tayrac, Marie; Delattre, Jean-Yves; Mosser, Jean

2014-01-01

Consistently reported prognostic factors for glioblastoma (GBM) are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors that responded poorly to the standard regimen. We further evaluated the potential prognostic value of DGKI methylation status. 399 patients with newly diagnosed GBM and treated with a standard regimen were retrospectively included in this study. Survival modelling was performed on two patient populations: intention-to-treat population of all included patients (population 1) and MGMT-methylated patients (population 2). Cox proportional hazard models were fitted to identify the main prognostic factors. A nomogram was developed for population 1. The prognostic value of DGKI promoter methylation status was evaluated on population 1 and population 2. The nomogram-based stratification of the cohort identified two risk groups (high/low) with significantly different median survival. We validated the prognostic value of DGKI methylation status for MGMT-methylated patients. We also demonstrated that the DGKI methylation status identified 22% of poorly responding patients in the low-risk group defined by the nomogram. Our results improve the conventional MGMT stratification of GBM patients receiving standard treatment. These results could help the interpretation of published or ongoing clinical trial outcomes and refine patient recruitment in the future.

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

DEFF Research Database (Denmark)

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

2015-01-01

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

A new prognostic score for AIDS-related lymphomas in the rituximab-era

Science.gov (United States)

Barta, Stefan K.; Xue, Xiaonan; Wang, Dan; Lee, Jeannette Y.; Kaplan, Lawrence D.; Ribera, Josep-Maria; Oriol, Albert; Spina, Michele; Tirelli, Umberto; Boue, Francois; Wilson, Wyndham H.; Wyen, Christoph; Dunleavy, Kieron; Noy, Ariela; Sparano, Joseph A.

2014-01-01

While the International Prognostic Index is commonly used to predict outcomes in immunocompetent patients with aggressive B-cell non-Hodgkin lymphomas, HIV-infection is an important competing risk for death in patients with AIDS-related lymphomas. We investigated whether a newly created prognostic score (AIDS-related lymphoma International Prognostic Index) could better assess risk of death in patients with AIDS-related lymphomas. We randomly divided a dataset of 487 patients newly diagnosed with AIDS-related lymphomas and treated with rituximab-containing chemoimmunotherapy into a training (n=244) and validation (n=243) set. We examined the association of HIV-related and other known risk factors with overall survival in both sets independently. We defined a new score (AIDS-related lymphoma International Prognostic Index) by assigning weights to each significant predictor [age-adjusted International Prognostic Index, extranodal sites, HIV-score (composed of CD4 count, viral load, and prior history of AIDS)] with three risk categories similar to the age-adjusted International Prognostic Index (low, intermediate and high risk). We compared the prognostic value for overall survival between AIDS-related lymphoma International Prognostic Index and age-adjusted International Prognostic Index in the validation set and found that the AIDS-related lymphoma International Prognostic Index performed significantly better in predicting risk of death than the age-adjusted International Prognostic Index (P=0.004) and better discriminated risk of death between each risk category (P=0.015 vs. P=0.13). Twenty-eight percent of patients were defined as low risk by the ARL-IPI and had an estimated 5-year overall survival (OS) of 78% (52% intermediate risk, 5-year OS 60%; 20% high risk, 5-year OS 50%). PMID:25150257

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

Lifecycle Prognostics Architecture for Selected High-Cost Active Components

International Nuclear Information System (INIS)

Lybeck, N.; Pham, B.; Tawfik, M.; Coble, J.B.; Meyer, R.M.; Ramuhalli, P.; Bond, L.J.

2011-01-01

There are an extensive body of knowledge and some commercial products available for calculating prognostics, remaining useful life, and damage index parameters. The application of these technologies within the nuclear power community is still in its infancy. Online monitoring and condition-based maintenance is seeing increasing acceptance and deployment, and these activities provide the technological bases for expanding to add predictive/prognostics capabilities. In looking to deploy prognostics there are three key aspects of systems that are presented and discussed: (1) component/system/structure selection, (2) prognostic algorithms, and (3) prognostics architectures. Criteria are presented for component selection: feasibility, failure probability, consequences of failure, and benefits of the prognostics and health management (PHM) system. The basis and methods commonly used for prognostics algorithms are reviewed and summarized. Criteria for evaluating PHM architectures are presented: open, modular architecture; platform independence; graphical user interface for system development and/or results viewing; web enabled tools; scalability; and standards compatibility. Thirteen software products were identified and discussed in the context of being potentially useful for deployment in a PHM program applied to systems in a nuclear power plant (NPP). These products were evaluated by using information available from company websites, product brochures, fact sheets, scholarly publications, and direct communication with vendors. The thirteen products were classified into four groups of software: (1) research tools, (2) PHM system development tools, (3) deployable architectures, and (4) peripheral tools. Eight software tools fell into the deployable architectures category. Of those eight, only two employ all six modules of a full PHM system. Five systems did not offer prognostic estimates, and one system employed the full health monitoring suite but lacked operations and

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

Science.gov (United States)

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

2010-08-01

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

Prognostic value of baseline seric Syndecan-1 in initially unresectable metastatic colorectal cancer patients: a simple biological score.

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Jary, Marine; Lecomte, Thierry; Bouché, Olivier; Kim, Stefano; Dobi, Erion; Queiroz, Lise; Ghiringhelli, Francois; Etienne, Hélène; Léger, Julie; Godet, Yann; Balland, Jérémy; Lakkis, Zaher; Adotevi, Olivier; Bonnetain, Franck; Borg, Christophe; Vernerey, Dewi

2016-11-15

In first-line metastatic colorectal cancer (mCRC), baseline prognostic factors allowing death risk and treatment strategy stratification are lacking. Syndecan-1 (CD138) soluble form was never described as a prognostic biomarker in mCRC. We investigated its additional prognostic value for overall survival (OS). mCRC patients with unresectable disease at diagnosis were treated with bevacizumab-based chemotherapy in two independent prospective clinical trials (development set: n = 126, validation set: n = 51, study NCT00489697 and study NCT00544011, respectively). Serums were collected at baseline for CD138 measurement. OS determinants were assessed and, based on the final multivariate model, a prognostic score was proposed. Two independent OS prognostic factors were identified: Lactate Dehydrogenase (LDH) high level (p = 0.0066) and log-CD138 high level (p = 0.0190). The determination of CD138 binary information (cutoff: 75 ng/mL) allowed the assessment of a biological prognostic score with CD138 and LDH values, identifying three risk groups for death (median OS= 38.9, 30.1 and 19.8 months for the low, intermediate and high risk groups, respectively; p value for OS, in mCRC patients. A simple biological scoring system is proposed including LDH and CD138 binary status values. © 2016 UICC.

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

Science.gov (United States)

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

2011-07-01

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

PROGNOSTIC SIGNIFICANCE OF CD56 EXPRESSION IN ACUTE LEUKEMIAS

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B. M. Ahmed

2014-12-01

Conclusions. CD56 antigenic expression in AML cases represents an adverse prognostic factor. It should be regularly investigated in cases of AML for better prognostic stratification and assessment. KEY WORDS: CD56; leukemia, myeloid; prognosis

Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions

Science.gov (United States)

2012-09-01

make end of life ( EOL ) and remaining useful life (RUL) estimations. Model-based prognostics approaches perform these tasks with the help of first...in parameters Degradation Modeling Parameter estimation Prediction Thermal / Electrical Stress Experimental Data State Space model RUL EOL ...distribution at given single time point kP , and use this for multi-step predictions to EOL . There are several methods which exits for selecting the sigma

Prognostic factors of synkinesis after Bell's palsy and Ramsay Hunt syndrome.

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Morishima, Naohito; Yagi, Ryo; Shimizu, Kazuhiko; Ota, Susumu

2013-10-01

This study evaluated the prognostic factors of synkinesis following Bell's palsy and Ramsay Hunt syndrome. A total of 345 patients consisting of 309 cases of Bell's palsy and 36 cases of Ramsay Hunt syndrome were enrolled in our study. The following 13 factors were considered as candidate prognostic factors for the presence of synkinesis at 6 months from onset: age, sex, diagnosis, diabetes mellitus, initial onset or recurrence, electroneurography (ENoG), number of days from onset to first visit to our hospital, the lowest Yanagihara grading system score, the change in Yanagihara score after 1 month, otalgia, hearing loss, vertigo and taste disturbances. These factors were analyzed by logistic regression. Logistic regression analysis clarified the lowest Yanagihara score, the change in Yanagihara score after 1 month, and the ENoG value for a prognosis of synkinesis. The most predictive prognostic factor was the lowest Yanagihara score, and the adjusted odds ratio in the multivariate model was 11.415. As for other prognostic factors, the adjusted odds ratios ranged from 7.017 (ENoG value) to 8.310 (the change in Yanagihara score after 1 month). These findings were therefore considered as high risk factors for synkinesis. It is possible to predict synkinesis following Bell's palsy and Ramsay Hunt syndrome on the basis of clinical symptoms. The lowest Yanagihara score, and the change in Yanagihara score after 1 month, together with the ENoG value at the onset, were found to be especially important factors for predicting synkinesis following Bell's palsy and Ramsay Hunt syndrome. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Prognostic accuracy of antenatal neonatology consultation.

Science.gov (United States)

Kukora, S; Gollehon, N; Weiner, G; Laventhal, N

2017-01-01

Neonatologists provide antenatal counseling to support shared decision-making for complicated pregnancies. Poor or ambiguous prognostication can lead to inappropriate treatment and parental distress. We sought to evaluate the accuracy of antenatal prognosticaltion. A retrospective cohort was assembled from a prospectively populated database of all outpatient neonatology consultations. On the basis of the written consultation, fetuses were characterized by diagnosis groups (multiple anomalies or genetic disorders, single major anomaly and obstetric complications), assigned to five prognostic categories (I=survivable, IIA=uncertain but likely survivable, II=uncertain, IIB=uncertain but likely non-survivable, III non-survivable) and two final outcome categories (fetal demise/in-hospital neonatal death or survival to hospital discharge). When possible, status at last follow-up was recorded for those discharged from the hospital. Prognostic accuracy was assessed using unweighted, multi-level likelihood ratios (LRs). The final cohort included 143 fetuses/infants distributed nearly evenly among the three diagnosis groups. Over half (64%) were assigned an uncertain prognosis, but most of these could be divided into 'likely survivable' or 'likely non-survivable' subgroups. Overall survival for the entire cohort was 62% (89/143). All but one of the fetuses assigned a non-survivable prognosis suffered fetal demise or died before hospital discharge. The neonatologist's antenatal prognosis accurately predicted the probability of survival by prognosis group (LR I=4.56, LR IIA=10.53, LR II=4.71, LR IIB=0.099, LR III=0.040). The LRs clearly differentiated between fetuses with high and low probability of survival. Eleven fetuses (7.7%) had misalignment between the predicted prognosis and outcome. Five died before discharge despite being given category I or IIA prognoses, whereas six infants with category IIB or III prognoses survived to discharge, though some of these were

Prognostic value of the Glasgow Prognostic Score for glioblastoma multiforme patients treated with radiotherapy and temozolomide.

Science.gov (United States)

Topkan, Erkan; Selek, Ugur; Ozdemir, Yurday; Yildirim, Berna A; Guler, Ozan C; Ciner, Fuat; Mertsoylu, Huseyin; Tufan, Kadir

2018-04-25

To evaluate the prognostic value of the Glasgow Prognostic Score (GPS), the combination of C-reactive protein (CRP) and albumin, in glioblastoma multiforme (GBM) patients treated with radiotherapy (RT) and concurrent plus adjuvant temozolomide (GPS). Data of newly diagnosed GBM patients treated with partial brain RT and concurrent and adjuvant TMZ were retrospectively analyzed. The patients were grouped into three according to the GPS criteria: GPS-0: CRP L and albumin > 35 g/L; GPS-1: CRP L and albumin L or CRP > 10 mg/L and albumin > 35 g/L; and GPS-2: CRP > 10 mg/L and albumin L. Primary end-point was the association between the GPS groups and the overall survival (OS) outcomes. A total of 142 patients were analyzed (median age: 58 years, 66.2% male). There were 64 (45.1%), 40 (28.2%), and 38 (26.7%) patients in GPS-0, GPS-1, and GPS-2 groups, respectively. At median 15.7 months follow-up, the respective median and 5-year OS rates for the whole cohort were 16.2 months (95% CI 12.7-19.7) and 9.5%. In multivariate analyses GPS grouping emerged independently associated with the median OS (P GPS grouping and the RTOG RPA classification were found to be strongly correlated in prognostic stratification of GBM patients (correlation coefficient: 0.42; P GPS appeared to be useful in prognostic stratification of GBM patients into three groups with significantly different survival durations resembling the RTOG RPA classification.

Current status of top-specific variant axion model

Science.gov (United States)

Chiang, Cheng-Wei; Fukuda, Hajime; Takeuchi, Michihisa; Yanagida, Tsutomu T.

2018-02-01

The invisible variant axion model is one of the very attractive models which solves the strong C P problem but does not provoke the domain wall problem. At the electroweak scale, this model requires at least two Higgs doublets, one of which carries a nonzero Peccei-Quinn (PQ) charge and the other is neutral. We consider a scenario where only the right-handed top quark is charged under the PQ symmetry and couples with the PQ-charged Higgs doublet. As a general prediction of this model, the top quark can decay to the observed standard model-like Higgs boson h and the charm or up quark, t →h c /u , which recently exhibited slight excesses at LHC run-I and run-II and will soon be testable at the LHC run-II. If the rare top decay excess stays at the observed central value, we show that tan β ˜1 or smaller is preferred by the Higgs data. The chiral nature of the Higgs flavor-changing interaction is a distinctive feature of this model and testable using the angular distribution of the t →c h decays at the LHC.

Individual participant data meta-analysis of prognostic factor studies: state of the art?

Directory of Open Access Journals (Sweden)

Abo-Zaid Ghada

2012-04-01

Full Text Available Abstract Background Prognostic factors are associated with the risk of a subsequent outcome in people with a given disease or health condition. Meta-analysis using individual participant data (IPD, where the raw data are synthesised from multiple studies, has been championed as the gold-standard for synthesising prognostic factor studies. We assessed the feasibility and conduct of this approach. Methods A systematic review to identify published IPD meta-analyses of prognostic factors studies, followed by detailed assessment of a random sample of 20 articles published from 2006. Six of these 20 articles were from the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials in traumatic brain injury collaboration, for which additional information was also used from simultaneously published companion papers. Results Forty-eight published IPD meta-analyses of prognostic factors were identified up to March 2009. Only three were published before 2000 but thereafter a median of four articles exist per year, with traumatic brain injury the most active research field. Availability of IPD offered many advantages, such as checking modelling assumptions; analysing variables on their continuous scale with the possibility of assessing for non-linear relationships; and obtaining results adjusted for other variables. However, researchers also faced many challenges, such as large cost and time required to obtain and clean IPD; unavailable IPD for some studies; different sets of prognostic factors in each study; and variability in study methods of measurement. The IMPACT initiative is a leading example, and had generally strong design, methodological and statistical standards. Elsewhere, standards are not always as high and improvements in the conduct of IPD meta-analyses of prognostic factor studies are often needed; in particular, continuous variables are often categorised without reason; publication bias and availability bias are rarely

Prognostic factors in Acanthamoeba keratitis.

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Kaiserman, Igor; Bahar, Irit; McAllum, Penny; Srinivasan, Sathish; Elbaz, Uri; Slomovic, Allan R; Rootman, David S

2012-06-01

To assess the prognostic factors influencing visual prognosis and length of treatment after acanthamoeba keratitis (AK). Forty-two AK eyes of 41 patients treated between 1999 and 2006 were included. A diagnosis of AK was made on the basis of culture results with a corresponding clinical presentation. We calculated the prognostic effect of the various factors on final visual acuity and the length of treatment. Multivariate regression analysis was used to adjust for the simultaneous effects of the various prognostic factors. Mean follow-up was 19.7 ± 21.0 months. Sixty-four percent of cases had > 1 identified risk factor for AK, the most common risk factor being contact lens wear (92.9% of eyes). At presentation, median best spectacle corrected visual acuity (BCVA) was 20/200 (20/30 to Hand Motion [HM]) that improved after treatment to 20/50 (20/20 to Counting Fingers [CF]). Infection acquired by swimming or related to contact lenses had significantly better final BCVA (p = 0.03 and p = 0.007, respectively). Neuritis and pseudodendrites were also associated with better final BCVA (p = 0.04 and p = 0.05, respectively). Having had an epithelial defect on presentation and having been treated with topical steroid were associated with worse final best spectacle corrected visual acuity (BSCVA) (p = 0.0006 and p = 0.04). Multivariate regression analysis found a good initial visual acuity (p = 0.002), infections related to swimming (p = 0.01), the absence of an epithelial defect (p = 0.03), having been treated with chlorhexidine (p = 0.05), and not having receive steroids (p = 0.003) to significantly forecast a good final BCVA. We identified several prognostic factors that can help clinicians evaluate the expected visual damage of the AK infection and thus tailor treatment accordingly. Copyright © 2012 Canadian Ophthalmological Society. All rights reserved.

Prognostic markers for colorectal cancer: estimating ploidy and stroma.

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Danielsen, H E; Hveem, T S; Domingo, E; Pradhan, M; Kleppe, A; Syvertsen, R A; Kostolomov, I; Nesheim, J A; Askautrud, H A; Nesbakken, A; Lothe, R A; Svindland, A; Shepherd, N; Novelli, M; Johnstone, E; Tomlinson, I; Kerr, R; Kerr, D J

2018-03-01

We report here the prognostic value of ploidy and digital tumour-stromal morphometric analyses using material from 2624 patients with early stage colorectal cancer (CRC). DNA content (ploidy) and stroma-tumour fraction were estimated using automated digital imaging systems and DNA was extracted from sections of formalin-fixed paraffin-embedded (FFPE) tissue for analysis of microsatellite instability. Samples were available from 1092 patients recruited to the QUASAR 2 trial and two large observational series (Gloucester, n = 954; Oslo University Hospital, n = 578). Resultant biomarkers were analysed for prognostic impact using 5-year cancer-specific survival (CSS) as the clinical end point. Ploidy and stroma-tumour fraction were significantly prognostic in a multivariate model adjusted for age, adjuvant treatment, and pathological T-stage in stage II patients, and the combination of ploidy and stroma-tumour fraction was found to stratify these patients into three clinically useful groups; 5-year CSS 90% versus 83% versus 73% [hazard ratio (HR) = 1.77 (95% confidence interval (95% CI): 1.13-2.77) and HR = 2.95 (95% CI: 1.73-5.03), P < 0.001]. A novel biomarker, combining estimates of ploidy and stroma-tumour fraction, sampled from FFPE tissue, identifies stage II CRC patients with low, intermediate or high risk of CRC disease specific death, and can reliably stratify clinically relevant patient sub-populations with differential risks of tumour recurrence and may support choice of adjuvant therapy for these individuals.

A novel prognostic six-CpG signature in glioblastomas.

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Yin, An-An; Lu, Nan; Etcheverry, Amandine; Aubry, Marc; Barnholtz-Sloan, Jill; Zhang, Lu-Hua; Mosser, Jean; Zhang, Wei; Zhang, Xiang; Liu, Yu-He; He, Ya-Long

2018-03-01

We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM). A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation. An integrative analysis of multidimensional TCGA data was performed to molecularly characterize different risk tumors. The six-CpG risk-score signature robustly predicted overall survival (OS) in all discovery and validation cohorts and in a treatment-independent manner. It also predicted progression-free survival (PFS) in available patients. The multimarker epigenetic signature was demonstrated as an independent prognosticator and had better performance than known molecular indicators such as glioma-CpG island methylator phenotype (G-CIMP) and proneural subtype. The defined risk subgroups were molecularly distinct; high-risk tumors were biologically more aggressive with concordant activation of proangiogenic signaling at multimolecular levels. Accordingly, we observed better OS benefits of bevacizumab-contained therapy to high-risk patients in independent sets, supporting its implication in guiding usage of antiangiogenic therapy. Finally, the six-CpG signature refined the risk classification based on G-CIMP and MGMT methylation status. The novel six-CpG signature is a robust and independent prognostic indicator for GBMs and is of promising value to improve personalized management. © 2018 John Wiley & Sons Ltd.

The value of prognostic factors for uterine cervical cancer patients treated with irradiation alone

International Nuclear Information System (INIS)

Grigienė, Rūta; Valuckas, Konstantinas P; Aleknavičius, Eduardas; Kurtinaitis, Juozas; Letautienė, Simona R

2007-01-01

The aim of our study was to investigate and evaluate the prognostic value of and correlations between preclinical and clinical factors such as the stage of the disease, blood Hb level before treatment, size of cervix and lymph nodes evaluated by CT, age, dose of irradiation and duration of radiotherapy related to overall survival, disease-free survival, local control and metastases-free survival in cervical cancer patients receiving radiotherapy alone. 162 patients with International Federation of Gynecology and Obstetrics (FIGO) stage IIA-IIIB cervical carcinoma treated with irradiation were analysed. Univariate and multivariate analyses using the Cox regression model were performed to determine statistical significance of some tumor-related factors. The Hb level before treatment showed significant influence on overall survival (p = 0.001), desease free survival (p = 0.040) and local control (p = 0.038). The lymph node status (>10 mm) assessed on CT had impact on overall survival (p = 0,030) and local control (p = 0,036). The dose at point A had impact on disease free survival (p = 0,028) and local control (p = 0,021) and the radiotherapy duration had showed significant influence on overall survival (p = 0,045), disease free survival (p = 0,006) and local control (p = 0,033). Anemia is a significant and independent prognostic factor of overall survival, disease-free survival and local control in cervical cancer patients treated with irradiation. The size of lymph nodes in CT is an independent prognostic factor for overall survival and local control in cervical cancer patients. The size of cervix uteri evaluated by CT has no prognostic significance in cervical cancer patients treated with radiotherapy. The prognostic value of FIGO stage of cervical cancer is influenced by other factors, analyzed in this study and is not an independent prognostic factor

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.

Glioblastoma treated with postoperative radio-chemotherapy: Prognostic value of apparent diffusion coefficient at MR imaging

Energy Technology Data Exchange (ETDEWEB)

Yamasaki, Fumiyuki; Sugiyama, Kazuhiko [Department of Neurosurgery, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551 (Japan); Ohtaki, Megu [Department of Environmetrics and Biometrics, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima (Japan); Takeshima, Yukio [Department of Pathology, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima (Japan); Abe, Nobukazu; Akiyama, Yuji; Takaba, Junko [Department of Radiology, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima (Japan); Amatya, Vishwa Jeet [Department of Pathology, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima (Japan); Saito, Taiichi; Kajiwara, Yoshinori; Hanaya, Ryosuke [Department of Neurosurgery, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551 (Japan); Kurisu, Kaoru [Department of Neurosurgery, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551 (Japan)], E-mail: kuka422@hiroshima-u.ac.jp

2010-03-15

Purpose: To retrospectively evaluate whether the mean, minimum, and maximum apparent diffusion coefficient (ADC) of glioblastomas obtained from pretreatment MR images is of prognostic value in patients with glioblastoma. Materials and methods: The institutional review board approved our study and waived the requirement for informed patient consent. Between February 1998 and January 2006, 33 patients (24 males, 9 females; age range 10-76 years) with supratentorial glioblastoma underwent pretreatment magnetic resonance (MR) imaging. The values of the mean, minimum, and maximum ADC (ADC{sub mean}, ADC{sub MIN}, and ADC{sub MAX}, respectively) of each tumor were preoperatively determined from several regions of interest defined in the tumors. After surgical intervention, all patients underwent irradiation and chemotherapy performed according to our hospital protocol. The patient age, symptom duration, Karnofsky performance scale score, extent of surgery, and ADC were assessed using factor analysis of overall survival. Prognostic factors were evaluated using Kaplan-Meier survival curves, the log-rank test, and multiple regression analysis with the Cox proportional hazards model. Results: Likelihood ratio tests confirmed that ADC{sub MIN} was the strongest among the three prognostic factors. Total surgical removal was the most important predictive factor for overall survival (P < 0.01). ADC{sub MIN} was also statistically correlated with overall survival (P < 0.05) and could be used to classify patients into different prognostic groups. Interestingly, ADC{sub MIN} was also the strongest prognostic factor (P < 0.01) in the group of patients in whom total tumor removal was not possible. Conclusion: The ADC{sub MIN} value obtained from pretreatment MR images is a useful clinical prognostic biomarker in patients with glioblastoma.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Applicability of RFID in the prognostics of logistic systems

NARCIS (Netherlands)

Lopez De La Cruz, A.M.; Veeke, H.P.M.; Lodewijks, G.

2007-01-01

The objective of this paper is to investigate the applicability of RFID in prognostic logistics. Starting from a general introduction of prognostic logistics, the system structure, and technical requirements are discussed. Based on this discussion the issues and concerns regarding the applicability

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

Science.gov (United States)

Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike

2018-04-01

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

Prognostic significance of Glasgow prognostic score in patients undergoing esophagectomy for esophageal squamous cell carcinoma.

Science.gov (United States)

Feng, Ji-Feng; Zhao, Qiang; Chen, Qi-Xun

2014-01-01

Recent studies have revealed that Glasgow prognostic score (GPS), an inflammation-based prognostic score, is inversely related to prognosis in a variety of cancers; high levels of GPS is associated with poor prognosis. However, few studies regarding GPS in esophageal cancer (EC) are available. The aim of this study was to determine whether the GPS is useful for predicting cancer-specific survival (CSS) of patients for esophageal squamous cell carcinoma (ESCC). The GPS was calculated on the basis of admission data as follows: Patients with elevated C-reactive protein (CRP) level (>10 mg/L) and hypoalbuminemia (L) were assigned to GPS2. Patients with one or no abnormal value were assigned to GPS1 or GPS0, respectively. Our study showed that GPS was associated with tumor size, depth of invasion, and nodal metastasis (PGPS0, GPS1, and GPS2 were 60.8%, 34.7% and 10.7%, respectively (PGPS was a significant predictor of CSS. GPS1-2 had a hazard ratio (HR) of 2.399 [95% confidence interval (CI): 1.805-3.190] for 1-year CSS (PGPS is associated with tumor progression. GPS can be considered as an independent prognostic factor in patients who underwent esophagectomy for ESCC.

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

Science.gov (United States)

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

2016-12-01

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

Prognostic durability of liver fibrosis tests and improvement in predictive performance for mortality by combining tests.

Science.gov (United States)

Bertrais, Sandrine; Boursier, Jérôme; Ducancelle, Alexandra; Oberti, Frédéric; Fouchard-Hubert, Isabelle; Moal, Valérie; Calès, Paul

2017-06-01

There is currently no recommended time interval between noninvasive fibrosis measurements for monitoring chronic liver diseases. We determined how long a single liver fibrosis evaluation may accurately predict mortality, and assessed whether combining tests improves prognostic performance. We included 1559 patients with chronic liver disease and available baseline liver stiffness measurement (LSM) by Fibroscan, aspartate aminotransferase to platelet ratio index (APRI), FIB-4, Hepascore, and FibroMeter V2G . Median follow-up was 2.8 years during which 262 (16.8%) patients died, with 115 liver-related deaths. All fibrosis tests were able to predict mortality, although APRI (and FIB-4 for liver-related mortality) showed lower overall discriminative ability than the other tests (differences in Harrell's C-index: P fibrosis, 1 year in patients with significant fibrosis, and liver disease (MELD) score testing sets. In the training set, blood tests and LSM were independent predictors of all-cause mortality. The best-fit multivariate model included age, sex, LSM, and FibroMeter V2G with C-index = 0.834 (95% confidence interval, 0.803-0.862). The prognostic model for liver-related mortality included the same covariates with C-index = 0.868 (0.831-0.902). In the testing set, the multivariate models had higher prognostic accuracy than FibroMeter V2G or LSM alone for all-cause mortality and FibroMeter V2G alone for liver-related mortality. The prognostic durability of a single baseline fibrosis evaluation depends on the liver fibrosis level. Combining LSM with a blood fibrosis test improves mortality risk assessment. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Incremental prognostic value of coronary computed tomographic angiography high-risk plaque characteristics in newly symptomatic patients.

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Fujimoto, Shinichiro; Kondo, Takeshi; Takamura, Kazuhisa; Baber, Usman; Shinozaki, Tomohiro; Nishizaki, Yuji; Kawaguchi, Yuko; Matsumori, Rie; Hiki, Makoto; Miyauchi, Katsumi; Daida, Hiroyuki; Hecht, Harvey; Stone, Gregg W; Narula, Jagat

2016-06-01

The incremental prognostic value of the plaque features in coronary computed tomographic angiography (CTA) has not been well assessed. This study was designed to determine whether CTA high-risk plaques have prognostic value incremental to the Framingham risk score (FRS) and the severity of luminal obstruction. A total of 628 newly symptomatic patients without known coronary artery disease underwent CTA. They were followed for a median of 677 days during which there were 26 cardiac events, including cardiac death, acute myocardial infarction, and hospitalization for unstable angina. Incremental prognostic value of adding plaque characteristics to the number of diseased vessels and the FRS was evaluated using 3 Cox models and net reclassification indexes. The discrimination index was significantly increased by adding the number of diseased vessels to the FRS (change in c-statistic from 65.8% to 78.6%, p=0.028) but not significantly by further adding plaque characteristics (change in c-statistic from 78.6% to 80.0%, p=0.812). However, improved model-fitting by adding plaque characteristics into the linear combination with risk score and the number of diseased vessels (p=0.007 from likelihood ratio test) and the lowest value of Akaike's information criteria of that model indicated that plaque characteristics improved both predictive accuracy and discrimination perspective. More subjects reclassified by plaque characteristics were moved to directions consistent with their subsequent cardiac event status than in an inconsistent direction. Evaluation of CTA plaque characteristics may provide incremental prognostic value to the number of diseased vessels and the FRS. Copyright © 2015 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Towards Prognostics for Electronics Components

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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...

Prognostic value of anemia for patients with cervical cancer treated with irradiation

International Nuclear Information System (INIS)

Grigiene, R.; Aleknavicius, E.; Kurtinaitis, J.

2005-01-01

The objective of this study was to evaluate the prognostic value of anemia in uterine cervical carcinoma patients treated with irradiation. A total of 162 patients diagnosed with stage IIA-IIIB cervical carcinoma by the criteria of International Federation of Gynecology and Obstetrics and treated with irradiation were analyzed. Univariate and multivariate analyses using the Cox regression model were performed to determine statistical significance of some tumor-related factors. Patients were divided into two groups according to the hemoglobin level before treatment: 10 mm) assessed by computed tomography had impact on overall survival (p=0.008), disease-free survival (p=0.023) and relapse-free survival (p=0.028). Using multivariate analysis, the hemoglobin level before treatment was found to be an independent prognostic factor for overall survival (p=0.001), disease-free survival (p=0.040) and local relapse-free survival (p=0.013); Iymph node status assessed by computed tomography had impact on overall survival (p=0.030) and local relapse-free survival (p=0.038). Hemoglobin level before treatment is a significant prognostic factor for patients with uterine cervical carcinoma treated with irradiation. (author)

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

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

2014-09-01

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

Neurological prognostication of outcome in patients in coma after cardiac arrest.

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Rossetti, Andrea O; Rabinstein, Alejandro A; Oddo, Mauro

2016-05-01

Management of coma after cardiac arrest has improved during the past decade, allowing an increasing proportion of patients to survive, thus prognostication has become an integral part of post-resuscitation care. Neurologists are increasingly confronted with raised expectations of next of kin and the necessity to provide early predictions of long-term prognosis. During the past decade, as technology and clinical evidence have evolved, post-cardiac arrest prognostication has moved towards a multimodal paradigm combining clinical examination with additional methods, consisting of electrophysiology, blood biomarkers, and brain imaging, to optimise prognostic accuracy. Prognostication should never be based on a single indicator; although some variables have very low false positive rates for poor outcome, multimodal assessment provides resassurance about the reliability of a prognostic estimate by offering concordant evidence. Copyright © 2016 Elsevier Ltd. All rights reserved.

Incidence and prognostic factors for postoperative frozen shoulder after shoulder surgery: a prospective cohort study.

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Koorevaar, Rinco C T; Van't Riet, Esther; Ipskamp, Marcel; Bulstra, Sjoerd K

2017-03-01

Frozen shoulder is a potential complication after shoulder surgery. It is a clinical condition that is often associated with marked disability and can have a profound effect on the patient's quality of life. The incidence, etiology, pathology and prognostic factors of postoperative frozen shoulder after shoulder surgery are not known. The purpose of this explorative study was to determine the incidence of postoperative frozen shoulder after various operative shoulder procedures. A second aim was to identify prognostic factors for postoperative frozen shoulder after shoulder surgery. 505 consecutive patients undergoing elective shoulder surgery were included in this prospective cohort study. Follow-up was 6 months after surgery. A prediction model was developed to identify prognostic factors for postoperative frozen shoulder after shoulder surgery using the TRIPOD guidelines. We nominated five potential predictors: gender, diabetes mellitus, type of physiotherapy, arthroscopic surgery and DASH score. Frozen shoulder was identified in 11% of the patients after shoulder surgery and was more common in females (15%) than in males (8%). Frozen shoulder was encountered after all types of operative procedures. A prediction model based on four variables (diabetes mellitus, specialized shoulder physiotherapy, arthroscopic surgery and DASH score) discriminated reasonably well with an AUC of 0.712. Postoperative frozen shoulder is a serious complication after shoulder surgery, with an incidence of 11%. Four prognostic factors were identified for postoperative frozen shoulder: diabetes mellitus, arthroscopic surgery, specialized shoulder physiotherapy and DASH score. The combination of these four variables provided a prediction rule for postoperative frozen shoulder with reasonable fit. Level II, prospective cohort study.

The Biochemical Prognostic Factors of Subclinical Hypothyroidism

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Myung Won Lee

2014-06-01

Full Text Available BackgroundPatients with subclinical hypothyroidism (SHT are common in clinical practice. However, the clinical significance of SHT, including prognosis, has not been established. Further clarifying SHT will be critical in devising a management plan and treatment guidelines for SHT patients. Thus, the aim of this study was to investigate the prognostic factors of SHT.MethodsWe reviewed the medical records of Korean patients who visited the endocrinology outpatient clinic of Severance Hospital from January 2008 to September 2012. Newly-diagnosed patients with SHT were selected and reviewed retrospectively. We compared two groups: the SHT maintenance group and the spontaneous improvement group.ResultsThe SHT maintenance group and the spontaneous improvement group had initial thyroid-stimulating hormone (TSH levels that were significantly different (P=0.035. In subanalysis for subjects with TSH levels between 5 to 10 µIU/mL, the spontaneous improvement group showed significantly lower antithyroid peroxidase antibody (anti-TPO-Ab titer than the SHT maintenance group (P=0.039. Regarding lipid profiles, only triglyceride level, unlike total cholesterol and low density lipoprotein cholesterol, was related to TSH level, which is correlated with the severity of SHT. Diffuse thyroiditis on ultrasonography only contributed to the severity of SHT, not to the prognosis. High sensitivity C-reactive protein and urine iodine excretion, generally regarded as possible prognostic factors, did not show any significant relation with the prognosis and severity of SHT.ConclusionOnly initial TSH level was a definite prognostic factor of SHT. TPO-Ab titer was also a helpful prognostic factor for SHT in cases with mildly elevated TSH. Other than TSH and TPO-Ab, we were unable to validate biochemical prognostic factors in this retrospective study for Korean SHT patients.

Prognostic role of syncytin expression in breast cancer

DEFF Research Database (Denmark)

Larsson, Lars-Inge; Holck, Susanne; Christensen, Ib Jarle

2007-01-01

Breast cancer cells were recently found to produce syncytin, an endogenous retroviral protein implicated in cell fusion, immune regulation, and nitric oxide synthase expression. To determine whether syncytin has a prognostic role in breast cancer, we investigated a series of 165 premenopausal lymph...... node-negative women for syncytin expression using an immunocytochemical scoring system. Results were analyzed with the Kaplan-Meier method and with the Cox proportional hazard model. Syncytin expression was observed in 38% of the patients, and the degree of syncytin expression constituted a positive...

LAMININS IN COLORECTAL CANCER: EXPRESSION, FUNCTION, PROGNOSTIC POWER AND MOLECULAR MECHANISMS

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S. A. Rodin

2017-01-01

Full Text Available Extracellular matrix (ECM proteins are a major component of the tumor stroma. Laminins emerge as one of the main families of ECM proteins with signaling properties. Apart from the structural function, laminins and products of their degradation affect survival and differentiation of cancer cells, motility of cancer and stromal cells, angiogenesis, invasion into distant organs, and other aspects of cancer development. Here, we discus expression of laminins in colorectal cancer (CRC, studying of laminin functions in in vitro and in vivo models of CRC, and using laminins as prognostic markers of CRC. Recently, we have reported a new approach to assessing prognostic power using classifiers constructed from sets of laminin genes. The method allows for accurate prognosis of CRC and provides additional information that may suggest possible molecular mechanisms of laminin function in CRC progression.

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

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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.

Prognostic markers for diet-induced weight loss in obese women

DEFF Research Database (Denmark)

Astrup, A; Buemann, B; Gluud, C

1995-01-01

To identify prognostic metabolic and hormonal markers for long-term weight loss outcome in obese women.......To identify prognostic metabolic and hormonal markers for long-term weight loss outcome in obese women....

Comparison of Glasgow prognostic score and prognostic index in patients with advanced non-small cell lung cancer.

Science.gov (United States)

Jiang, Ai-Gui; Chen, Hong-Lin; Lu, Hui-Yu

2015-03-01

Previous studies have shown that Glasgow prognostic score (GPS) and prognostic index (PI) are also powerful prognostic tool for patients with advanced non-small cell lung cancer (NSCLC). The aim of this study was to compare the prognostic value between GPS and PI. We enrolled consecutive patients with advanced NSCLC in this prospective cohort. GPS and PI were calculated before the onset of chemotherapy. The prognosis outcomes included 1-, 3-, and 5-year progression-free survival and overall survival (OS). The performance of two scores in predicting prognosis was analyzed regarding discrimination and calibration. 138 patients were included in the study. The area under the receiver operating characteristic curve for GPS predicting 1-year DFS was 0.62 (95 % confidence interval (CI) 0.56-0.68, P statistic showed good fit of the predicted 1-year DFS to the actual 1-year DFS by GPS (χ(2) = 4.326, P = 0.462), while no fit was found between the predicted 1-year DFS and the actual 1-year DFS by PI (χ(2) = 15.234, P = 0.091). Similar results of calibration power were found for predicting 3-year DFS, 5-year DFS, 1-year OS, 3-year OS, and 5-year OS by GPS and PI. GPS is more accurate than PI in predicting prognosis for patients with advanced NSCLC. GPS can be used as a useful and simple tool for predicting prognosis in patients with NSCLC. However, GPS only can be used for preliminary assessment because of low predicting accuracy.

A framework to establish credibility of computational models in biology.

Science.gov (United States)

Patterson, Eann A; Whelan, Maurice P

2017-10-01

Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Some interesting prognostic factors related to cutaneous malignant melanoma

International Nuclear Information System (INIS)

Figueroa, Alejandro Yuri Joan; Diaz Anaya, Amnia; Montero Leon, Jorge Felipe; Jimenez Mendes, Lourdes

2009-01-01

The aim of present research was to determine the independent prognostic value and the 3 and 5 years survival of more significant clinicopathological prognostic factors and in each stage, according to pathological staging system of tumor-nodule-metastasis (TNM) in patients with cutaneous malignant melanoma (CMM)

Requirements Flowdown for Prognostics and Health Management

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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.

Evaluation of meteorological fields generated by a prognostic mesoscale model using data collected during the 1993 GMAQS/COAST field study

International Nuclear Information System (INIS)

Lolk, N.K.; Douglas, S.G.

1996-01-01

In 1993, the US Interior Department's Minerals Management Service (MMS) sponsored the Gulf of Mexico Air Quality Study (GMAQS). Its purpose was to assess potential impacts of offshore petrochemical development on ozone concentrations in nonattainment areas in the Texas/Louisiana Gulf Coast region as mandated by the 1990 Clean Air Act Amendments. The GMAQS comprised data collection, data analysis, and applications of an advanced photochemical air quality model, the variable-grid Urban Airshed Model (UAM-V), and a prognostic mesoscale meteorological model (SAIMM -- Systems Applications International Mesoscale Model) to simulate two ozone episodes that were captured during the summer field study. The primary purpose of this paper is to evaluate the SAIMM-simulated meteorological fields using graphical analysis that utilize the comprehensive GMAQS/COAST (Gulf of Mexico Air Quality Study/Coastal Oxidant Assessment for Southeast Texas) database and to demonstrate the ability of the SAIMM to simulate the day-to-day variations in the evolution and structure of the gulf breeze and the mixed layer

Prognostic factorsin inoperable adenocarcinoma of the lung: A multivariate regression analysis of 259 patiens

DEFF Research Database (Denmark)

Sørensen, Jens Benn; Badsberg, Jens Henrik; Olsen, Jens

1989-01-01

The prognostic factors for survival in advanced adenocarcinoma of the lung were investigated in a consecutive series of 259 patients treated with chemotherapy. Twenty-eight pretreatment variables were investigated by use of Cox's multivariate regression model, including histological subtypes and ...

The Prognostic Value of Haplotypes in the Vascular Endothelial Growth Factor

DEFF Research Database (Denmark)

Hansen, Torben Frøstrup; Spindler, Karen-Lise Garm; Andersen, Rikke Fredslund

2010-01-01

Abstract: New prognostic markers in patients with colorectal cancer (CRC) are a prerequisite for individualized treatment. Prognostic importance of single nucleotide polymorphisms (SNPs) in the vascular endothelial growth factor A (VEGF-A) gene has been proposed. The objective of the present study...... using the PHASE program. The prognostic influence was evaluated using Kaplan-Meir plots and log rank tests. Cox regression method was used to analyze the independent prognostic importance of different markers. All three SNPs were significantly related to survival. A haplotype combination, responsible...... findings in a second and independent cohort. Haplotype combinations call for further investigation. Keywords: colorectal neoplasm; single nucleotide polymorphisms; haplotypes; vascular endothelial growth factor A; survival...

Prognostic, quantitative histopathologic variables in lobular carcinoma of the breast

DEFF Research Database (Denmark)

Ladekarl, M; Sørensen, Flemming Brandt

1993-01-01

BACKGROUND: A retrospective investigation of 53 consecutively treated patients with operable lobular carcinoma of the breast, with a median follow-up of 6.6 years, was performed to examine the prognostic value of quantitative histopathologic parameters.METHODS: The measurements were performed...... of disease, vv(nuc), MI, and NI were of significant independent, prognostic value. On the basis of the multivariate analyses, a prognostic index with highly distinguishing capacity between prognostically poor and favorable cases was constructed.CONCLUSION: Quantitative histopathologic variables are of value...... for objective grading of malignancy in lobular carcinomas. The new parameter--estimates of the mean nuclear volume--is highly reproducible and suitable for routine use. However, larger and prospective studies are needed to establish the true value of the quantitative histopathologic variables in the clinical...

Prognostic, quantitative histopathologic variables in lobular carcinoma of the breast

DEFF Research Database (Denmark)

Ladekarl, M; Sørensen, Flemming Brandt

1993-01-01

BACKGROUND: A retrospective investigation of 53 consecutively treated patients with operable lobular carcinoma of the breast, with a median follow-up of 6.6 years, was performed to examine the prognostic value of quantitative histopathologic parameters. METHODS: The measurements were performed...... of disease, vv(nuc), MI, and NI were of significant independent, prognostic value. On the basis of the multivariate analyses, a prognostic index with highly distinguishing capacity between prognostically poor and favorable cases was constructed. CONCLUSION: Quantitative histopathologic variables are of value...... for objective grading of malignancy in lobular carcinomas. The new parameter--estimates of the mean nuclear volume--is highly reproducible and suitable for routine use. However, larger and prospective studies are needed to establish the true value of the quantitative histopathologic variables in the clinical...

Prognostic value of Child-Turcotte criteria in medically treated cirrhosis

DEFF Research Database (Denmark)

Christensen, E; Schlichting, P; Fauerholdt, L

1984-01-01

The Child- Turcotte criteria (CTC) (based on serum bilirubin and albumin, ascites, neurological disorder and nutrition) are established prognostic factors in patients with cirrhosis having portacaval shunt surgery. The objective of this study was to evaluate the prognostic value of CTC in conserv......The Child- Turcotte criteria (CTC) (based on serum bilirubin and albumin, ascites, neurological disorder and nutrition) are established prognostic factors in patients with cirrhosis having portacaval shunt surgery. The objective of this study was to evaluate the prognostic value of CTC...... compared using the log-rank test. Survival decreased significantly with increasing degree of abnormality (A----B----C) of albumin (p less than 0.001), ascites (p less than 0.001), bilirubin (p = 0.02) and nutritional status (p = 0.03). Survival was insignificantly influenced by neurological status (p = 0...

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...

Prognostic factors in canine appendicular osteosarcoma - a meta-analysis.

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Boerman, Ilse; Selvarajah, Gayathri T; Nielen, Mirjam; Kirpensteijn, Jolle

2012-05-15

Appendicular osteosarcoma is the most common malignant primary canine bone tumor. When treated by amputation or tumor removal alone, median survival times (MST) do not exceed 5 months, with the majority of dogs suffering from metastatic disease. This period can be extended with adequate local intervention and adjuvant chemotherapy, which has become common practice. Several prognostic factors have been reported in many different studies, e.g. age, breed, weight, sex, neuter status, location of tumor, serum alkaline phosphatase (SALP), bone alkaline phosphatase (BALP), infection, percentage of bone length affected, histological grade or histological subtype of tumor. Most of these factors are, however, only reported as confounding factors in larger studies. Insight in truly significant prognostic factors at time of diagnosis may contribute to tailoring adjuvant therapy for individual dogs suffering from osteosarcoma. The objective of this study was to systematically review the prognostic factors that are described for canine appendicular osteosarcoma and validate their scientific importance. A literature review was performed on selected studies and eligible data were extracted. Meta-analyses were done for two of the three selected possible prognostic factors (SALP and location), looking at both survival time (ST) and disease free interval (DFI). The third factor (age) was studied in a qualitative manner. Both elevated SALP level and the (proximal) humerus as location of the primary tumor are significant negative prognostic factors for both ST and DFI in dogs with appendicular osteosarcoma. Increasing age was associated with shorter ST and DFI, however, was not statistically significant because information of this factor was available in only a limited number of papers. Elevated SALP and proximal humeral location are significant negative prognosticators for canine osteosarcoma.

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

DEFF Research Database (Denmark)

Poulsen, Sidsel Højklint; Urup, Thomas; Grunnet, Kirsten

2017-01-01

the prognostic value of FET PET biological tumor volume (BTV). RESULTS: 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 ...-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. CONCLUSION: Large...

Biological Prognostic Markers in Chronic Lymphocytic Leukemia

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Vladimíra Vroblová

2009-01-01

Full Text Available Chronic lymphocytic leukemia (CLL is the most frequent leukemic disease of adults in the Western world. It is remarkable by an extraordinary heterogeneity of clinical course with overall survival ranging from several months to more than 15 years. Classical staging sytems by Rai and Binet, while readily available and useful for initial assessment of prognosis, are not able to determine individual patient’s ongoing clinical course of CLL at the time of diagnosis, especially in early stages. Therefore, newer biological prognostic parameters are currently being clinically evaluated. Mutational status of variable region of immunoglobulin heavy chain genes (IgVH, cytogenetic aberrations, and both intracellular ZAP- 70 and surface CD38 expression are recognized as parameters with established prognostic value. Molecules regulating the process of angiogenesis are also considered as promising markers. The purpose of this review is to summarize in detail the specific role of these prognostic factors in chronic lymphocytic leukemia.

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

Science.gov (United States)

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

2018-03-09

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

Research on prognostics and health management of underground pipeline

Science.gov (United States)

Zhang, Guangdi; Yang, Meng; Yang, Fan; Ni, Na

2018-04-01

With the development of the city, the construction of the underground pipeline is more and more complex, which has relation to the safety and normal operation of the city, known as "the lifeline of the city". First of all, this paper introduces the principle of PHM (Prognostics and Health Management) technology, then proposed for fault diagnosis, prognostics and health management in view of underground pipeline, make a diagnosis and prognostics for the faults appearing in the operation of the underground pipeline, and then make a health assessment of the whole underground pipe network in order to ensure the operation of the pipeline safely. Finally, summarize and prospect the future research direction.

Study of Updating Initiating Event Frequency using Prognostics

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyeonmin; Lee, Sang-Hwan; Park, Jun-seok; Kim, Hyungdae; Chang, Yoon-Suk; Heo, Gyunyoung [Kyung Hee Univ., Yongin (Korea, Republic of)

2014-10-15

The Probabilistic Safety Assessment (PSA) model enables to find the relative priority of accident scenarios, weak points in achieving accident prevention or mitigation, and insights to improve those vulnerabilities. Thus, PSA consider realistic calculation for precise and confidence results. However, PSA model still 'conservative' aspects in the procedures of developing a PSA model. One of the sources for the conservatism is caused by the assumption of safety analysis and the estimation of failure frequency. Recently, Surveillance, Diagnosis, and Prognosis (SDP) is a growing trend in applying space and aviation systems in particular. Furthermore, a study dealing with the applicable areas and state-of-the-art status of the SDP in nuclear industry was published. SDP utilizing massive database and information technology among such enabling techniques is worthwhile to be highlighted in terms of the capability of alleviating the conservatism in the conventional PSA. This paper review the concept of integrating PSA and SDP and suggest the updated methodology of Initiating Event (IE) using prognostics. For more detailed, we focus on IE of the Steam Generator Tube Rupture (SGTR) considering tube degradation. This paper is additional research of previous our suggested the research. In this paper, the concept of integrating PSA and SDP are suggested. Prognostics algorithms in SDP are applied at IE, Bes in the Level 1 PSA. As an example, updating SGTR IE and its ageing were considered. Tube ageing were analyzed by using PASTA and Monte Carlo method. After analyzing the tube ageing, conventional SGTR IE were updated by using Bayesian approach. The studied method can help to cover the static and conservatism in PSA.

Study of Updating Initiating Event Frequency using Prognostics

International Nuclear Information System (INIS)

Kim, Hyeonmin; Lee, Sang-Hwan; Park, Jun-seok; Kim, Hyungdae; Chang, Yoon-Suk; Heo, Gyunyoung

2014-01-01

The Probabilistic Safety Assessment (PSA) model enables to find the relative priority of accident scenarios, weak points in achieving accident prevention or mitigation, and insights to improve those vulnerabilities. Thus, PSA consider realistic calculation for precise and confidence results. However, PSA model still 'conservative' aspects in the procedures of developing a PSA model. One of the sources for the conservatism is caused by the assumption of safety analysis and the estimation of failure frequency. Recently, Surveillance, Diagnosis, and Prognosis (SDP) is a growing trend in applying space and aviation systems in particular. Furthermore, a study dealing with the applicable areas and state-of-the-art status of the SDP in nuclear industry was published. SDP utilizing massive database and information technology among such enabling techniques is worthwhile to be highlighted in terms of the capability of alleviating the conservatism in the conventional PSA. This paper review the concept of integrating PSA and SDP and suggest the updated methodology of Initiating Event (IE) using prognostics. For more detailed, we focus on IE of the Steam Generator Tube Rupture (SGTR) considering tube degradation. This paper is additional research of previous our suggested the research. In this paper, the concept of integrating PSA and SDP are suggested. Prognostics algorithms in SDP are applied at IE, Bes in the Level 1 PSA. As an example, updating SGTR IE and its ageing were considered. Tube ageing were analyzed by using PASTA and Monte Carlo method. After analyzing the tube ageing, conventional SGTR IE were updated by using Bayesian approach. The studied method can help to cover the static and conservatism in PSA

An integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process

International Nuclear Information System (INIS)

Moghaddass, Ramin; Zuo, Ming J.

2014-01-01

Efficient asset management is of paramount importance, particularly for systems with costly downtime and failure. As in energy and capital-intensive industries, the economic loss of downtime and failure is huge, the need for a low-cost and integrated health monitoring system has increased significantly over the years. Timely detection of faults and failures through an efficient prognostics and health management (PHM) framework can lead to appropriate maintenance actions to be scheduled proactively to avoid catastrophic failures and minimize the overall maintenance cost of the systems. This paper aims at practical challenges of online diagnostics and prognostics of mechanical systems under unobservable degradation. First, the elements of a multistate degradation structure are reviewed and then a model selection framework is introduced. Important dynamic performance measures are introduced, which can be used for online diagnostics and prognostics. The effectiveness of the result of this paper is demonstrated with a case study on the health monitoring of turbofan engines

First Order Electroweak Phase Transition from (Non)Conformal Extensions of the Standard Model

DEFF Research Database (Denmark)

Sannino, Francesco; Virkajärvi, Jussi

2015-01-01

We analyse and compare the finite-temperature electroweak phase transition properties of classically (non)conformal extensions of the Standard Model. In the classically conformal scenarios the breaking of the electroweak symmetry is generated radiatively. The models feature new scalars coupled co...... the associated models are testable at the upcoming Large Hadron Collider run two experiments....

Measurement of a model of implementation for health care : toward a testable theory

NARCIS (Netherlands)

Cook, Joan M.; O'Donnell, Casey; Dinnen, Stephanie; Coyne, James C.; Ruzek, Josef I.; Schnurr, Paula P.

2012-01-01

Background: Greenhalgh et al. used a considerable evidence-base to develop a comprehensive model of implementation of innovations in healthcare organizations [1]. However, these authors did not fully operationalize their model, making it difficult to test formally. The present paper represents a

Survival prognostic value of morphological and metabolic variables in patients with stage I and II non-small cell lung cancer

Energy Technology Data Exchange (ETDEWEB)

Domachevsky, L. [Rabin Medical Center, Department of Nuclear Medicine, Petah Tikva (Israel); Beilinson Hospital, Petah Tikva (Israel); Groshar, D.; Bernstine, H. [Rabin Medical Center, Department of Nuclear Medicine, Petah Tikva (Israel); Tel Aviv University, Sackler Faculty of Medicine, Tel Aviv (Israel); Galili, R. [Lady Davis-Carmel Medical Center, Department of Cardiothoracic Surgery, Haifa (Israel); Saute, M. [Rabin Medical Center, Department of Cardiothoracic Surgery, Petah Tiqva (Israel)

2015-11-15

The prognosis of patients with non-small cell lung cancer (NSCLC) is important, as patients with resectable disease and poor prognostic variables might benefit from neoadjuvant therapy. The goal of this study is to evaluate SUVmax, SUVmax ratio, CT volume (CTvol), metabolic tumour volume (MTV) and total lesion glycolisis (TLG) as survival prognostic markers. In addition, we defined two variables; MTV x SUVmax (MTVmax) and CTvol x SUVmax (CTvolmax) and assessed whether they can be used as prognostic markers. Patients with stage I-II NSCLC who underwent 18 F FDG PET/CT and surgery were evaluated. Cox proportional-hazard model was used to determine the association between variables and survival. Similar analysis was performed in cases with no lymph node (LN) involvement. One hundred and eighty-one patients were included (at the end of the study, 140 patients were alive). SUVmax with a cut-off value of 8.2 was significant survival prognostic factor regardless of LN involvement (P = 0.012). In cases with no LN involvement, SUVmax and CTvol (≥7.1 ml) were significant survival prognostic factors with P = 0.004 and 0.03, respectively. SUVmax may be a useful prognostic variable in stage I-II NSCLC while morphologic tumour volume might be useful in cases with no lymph node involvement. (orig.)

Postoperative outcome after oesophagectomy for cancer: Nutritional status is the missing ring in the current prognostic scores.

Science.gov (United States)

Filip, B; Scarpa, M; Cavallin, F; Cagol, M; Alfieri, R; Saadeh, L; Ancona, E; Castoro, C

2015-06-01

Several prognostic scores were designed in order to estimate the risk of postoperative adverse events. None of them includes a component directly associated to the nutritional status. The aims of the study were the evaluation of performance of risk-adjusted models for early outcomes after oesophagectomy and to develop a score for severe complication prediction with special consideration regarding nutritional status. A comparison of POSSUM and Charlson score and their derivates, ASA, Lagarde score and nutritional index (PNI) was performed on 167 patients undergoing oesophagectomy for cancer. A logistic regression model was also estimated to obtain a new prognostic score for severe morbidity prediction. Overall morbidity was 35.3% (59 cases), severe complications (grade III-V of Clavien-Dindo classification) occurred in 20 cases. Discrimination was poor for all the scores. Multivariable analysis identified pulse, connective tissue disease, PNI and potassium as independent predictors of severe morbidity. This model showed good discrimination and calibration. Internal validation using standard bootstrapping techniques confirmed the good performance. Nutrition could be an independent risk factor for major complications and a nutritional status coefficient could be included in current prognostic scores to improve risk estimation of major postoperative complications after oesophagectomy for cancer. Copyright © 2015. Published by Elsevier Ltd.

Independent Prognostic Value of Stroke Volume Index in Patients With Immunoglobulin Light Chain Amyloidosis.

Science.gov (United States)

2018-05-01

Heart involvement is the most important prognostic determinant in AL amyloidosis patients. Echocardiography is a cornerstone for the diagnosis and provides important prognostic information. We studied 754 patients with AL amyloidosis who underwent echocardiographic assessment at the Mayo Clinic, including a Doppler-derived measurement of stroke volume (SV) within 30 days of their diagnosis to explore the prognostic role of echocardiographic variables in the context of a well-established soluble cardiac biomarker staging system. Reproducibility of SV, myocardial contraction fraction, and left ventricular strain was assessed in a separate, yet comparable, study cohort of 150 patients from the Pavia Amyloidosis Center. The echocardiographic measures most predictive for overall survival were SV index <33 mL/min, myocardial contraction fraction <34%, and cardiac index <2.4 L/min/m 2 with respective hazard ratios (95% confidence intervals) of 2.95 (2.37-3.66), 2.36 (1.96-2.85), and 2.32 (1.91-2.80). For the subset that had left ventricular strain performed, the prognostic cut point was -14% (hazard ratios, 2.70; 95% confidence intervals, 1.84-3.96). Each parameter was independent of systolic blood pressure, Mayo staging system (NT-proBNP [N-terminal pro-B-type natriuretic peptide] and troponin), and ejection fraction on multivariable analysis. Simple predictive models for survival, including biomarker staging along with SV index or left ventricular strain, were generated. SV index prognostic performance was similar to left ventricular strain in predicting survival in AL amyloidosis, independently of biomarker staging. Because SV index is routinely calculated and widely available, it could serve as the preferred echocardiographic measure to predict outcomes in AL amyloidosis patients. © 2018 American Heart Association, Inc.

Towards Prognostics for Electronics Components

Science.gov (United States)

Saha, Bhaskar; Celaya, Jose R.; Wysocki, Philip F.; Goebel, Kai F.

2013-01-01

Electronics components have an increasingly critical role in avionics systems and in the development of future aircraft systems. Prognostics of such components is becoming a very important research field as a result of the need to provide aircraft systems with system level health management information. This paper focuses on a prognostics application for electronics components within avionics systems, and in particular its application to an Isolated Gate Bipolar Transistor (IGBT). This application utilizes the remaining useful life prediction, accomplished by employing the particle filter framework, leveraging data from accelerated aging tests on IGBTs. These tests induced thermal-electrical overstresses by applying thermal cycling to the IGBT devices. In-situ state monitoring, including measurements of steady-state voltages and currents, electrical transients, and thermal transients are recorded and used as potential precursors of failure.

The prognostic importance of heart failure and age in patients treated with primary angioplasty

NARCIS (Netherlands)

Henriques, Jose P. S.; Zijlstra, Felix; de Boer, Menko-Jan; van 't Hof, Arnoud W. J.; Gosselink, A. T. Marcel; Dambrink, Jan-Henk E.; Suryapranata, Harry; Hoorntje, Jan C. A.

2003-01-01

Effective risk stratification is essential in the management of patients with acute myocardial infarction. Available models have not yet been studied and validated in patients treated with primary angioplasty for acute myocardial infarction. The prognostic value of heart failure defined by Killip

A Novel UAV Electric Propulsion Testbed for Diagnostics and Prognostics

Science.gov (United States)

Gorospe, George E., Jr.; Kulkarni, Chetan S.

2017-01-01

This paper presents a novel hardware-in-the-loop (HIL) testbed for systems level diagnostics and prognostics of an electric propulsion system used in UAVs (unmanned aerial vehicle). Referencing the all electric, Edge 540T aircraft used in science and research by NASA Langley Flight Research Center, the HIL testbed includes an identical propulsion system, consisting of motors, speed controllers and batteries. Isolated under a controlled laboratory environment, the propulsion system has been instrumented for advanced diagnostics and prognostics. To produce flight like loading on the system a slave motor is coupled to the motor under test (MUT) and provides variable mechanical resistance, and the capability of introducing nondestructive mechanical wear-like frictional loads on the system. This testbed enables the verification of mathematical models of each component of the propulsion system, the repeatable generation of flight-like loads on the system for fault analysis, test-to-failure scenarios, and the development of advanced system level diagnostics and prognostics methods. The capabilities of the testbed are extended through the integration of a LabVIEW-based client for the Live Virtual Constructive Distributed Environment (LVCDC) Gateway which enables both the publishing of generated data for remotely located observers and prognosers and the synchronization the testbed propulsion system with vehicles in the air. The developed HIL testbed gives researchers easy access to a scientifically relevant portion of the aircraft without the overhead and dangers encountered during actual flight.

Psychological Models of Art Reception must be Empirically Grounded

DEFF Research Database (Denmark)

Nadal, Marcos; Vartanian, Oshin; Skov, Martin

2017-01-01

We commend Menninghaus et al. for tackling the role of negative emotions in art reception. However, their model suffers from shortcomings that reduce its applicability to empirical studies of the arts: poor use of evidence, lack of integration with other models, and limited derivation of testable...... hypotheses. We argue that theories about art experiences should be based on empirical evidence....

Preoperative prognostic factors for mortality in peptic ulcer perforation: a systematic review

DEFF Research Database (Denmark)

Møller, Morten Hylander; Adamsen, S.; Thomsen, R.W.

2010-01-01

in the review. The overall methodological quality was acceptable, yet only two-thirds of the studies provided confounder adjusted estimates. The studies provided strong evidence for an association of older age, comorbidity, and use of NSAIDs or steroids with mortality. Shock upon admission, preoperative...... was to summarize available evidence on these prognostic factors. Material and methods. MEDLINE (January 1966 to June 2009), EMBASE (January 1980 to June 2009), and the Cochrane Library (Issue 3, 2009) were screened for studies reporting preoperative prognostic factors for mortality in patients with PPU....... The methodological quality of the included studies was assessed. Summary relative risks with 95% confidence intervals for the identified prognostic factors were calculated and presented as Forest plots. Results. Fifty prognostic studies with 37 prognostic factors comprising a total of 29,782 patients were included...

Value of five-stage prognostic system in predicting short-term outcome of patients with liver cirrhosis

Directory of Open Access Journals (Sweden)

TIAN Yan

2015-03-01

Full Text Available ObjectiveTo evaluate the clinical value of five-stage prognostic system in predicting the short-term outcome of patients with liver cirrhosis, and to compare it with the Child-Turcotte-Pugh (CTP and Model of End-Stage Liver Disease (MELD scores. MethodsTwo hundred and one hospitalized patients with liver cirrhosis in the Department of Gastroenterology in the First Affiliated Hospital of Anhui Medical University from January 2011 to January 2014 were enrolled in the study and followed up for at least six months. Patients were classified accorded to the five-stage prognostic system, and the mortality rate in each stage was measured. The receiver operating characteristic (ROC curve and the area under the ROC curve (AUC were used to assess the accuracy of the five-stage prognostic system in predicting the short-term death risk of cirrhotic patients, which was then compared with the CTP and MELD scores. Categorical data were analyzed by chi-square test. Comparison of AUC was made by normal distribution Z test. Spearman′s correlation analysis was used to investigate the correlation of the five-stage prognostic system with the CTP and MELD scores. ResultsThe study used the admission time as the starting point and the death of patients or study termination time as the endpoint. Among the 201 patients, 50 (24.9% died within six months. Based on the five-stage prognostic system, the mortality rates for stages 1 to 5 were 0(0/11, 0（0/18, 4.2%（2/48, 16.3% (7/43, and 50.6%（41/81, respectively. In patients with decompensated cirrhosis (stages 3, 4, and 5, the mortality increased with stage, and the differences in mortality between patients in stages 3 and 4, 3 and 5, and 4 and 5 were all significant (χ2=3.89, 35.33, and 13.96, respectively; P=0.049, 0.000, and 0.049, respectively. The AUC for the five-stage prognostic system, five-stage prognostic system combined with CTP and MELD score, and CTP score were 0820, 0.915, 0.888, and 0

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Prognostic factors of non-functioning pancreatic neuroendocrine tumor revisited: The value of WHO 2010 classification.

Science.gov (United States)

Bu, Jiyoung; Youn, Sangmin; Kwon, Wooil; Jang, Kee Taek; Han, Sanghyup; Han, Sunjong; You, Younghun; Heo, Jin Seok; Choi, Seong Ho; Choi, Dong Wook

2018-02-01

Various factors have been reported as prognostic factors of non-functional pancreatic neuroendocrine tumors (NF-pNETs). There remains some controversy as to the factors which might actually serve to successfully prognosticate future manifestation and diagnosis of NF-pNETs. As well, consensus regarding management strategy has never been achieved. The aim of this study is to further investigate potential prognostic factors using a large single-center cohort to help determine the management strategy of NF-pNETs. During the time period 1995 through 2013, 166 patients with NF-pNETs who underwent surgery in Samsung Medical Center were entered in a prospective database, and those factors thought to represent predictors of prognosis were tested in uni- and multivariate models. The median follow-up time was 46.5 months; there was a maximum follow-up period of 217 months. The five-year overall survival and disease-free survival rates were 88.5% and 77.0%, respectively. The 2010 WHO classification was found to be the only prognostic factor which affects overall survival and disease-free survival in multivariate analysis. Also, pathologic tumor size and preoperative image tumor size correlated strongly with the WHO grades ( p <0.001, and p <0.001). Our study demonstrates that 2010 WHO classification represents a valuable prognostic factor of NF-pNETs and tumor size on preoperative image correlated with WHO grade. In view of the foregoing, the preoperative image size is thought to represent a reasonable reference with regard to determination and development of treatment strategy of NF-pNETs.

Assessment of diagnostic and prognostic condition indices for efficient and robust maintenance decision-making of systems subject to stress corrosion cracking

International Nuclear Information System (INIS)

Huynh, K.T.; Grall, A.; Bérenguer, C.

2017-01-01

Seeking condition indices characterizing the health state of a system is a key problem in condition-based maintenance. For this purpose, diagnostic and prognostic models have been unceasingly developed and improved over the past few decades; nevertheless none of them explains thoroughly the impacts of such indices on the effectiveness of maintenance operations. As a complement to these efforts, this paper analyzes the effectiveness of some well-known diagnostic and prognostic indices for maintenance decision-making. The study is based on a system subject to competing risks due to multiple crack paths. A periodic inspection scheme is used to monitor the system health state. Each inspection returns the perfect diagnostic information: the number of cracks, corresponding crack sizes, and the system failure/working state. Based on this information, two kinds of prognostic condition indices are predicted: the average value and probability law of the system residual useful life. The associated condition-based maintenance strategies and cost models are then developed and compared with the ones whose maintenance decisions are based on diagnostic condition indices. The comparison results allow us to conclude on the performance and on the robustness of these strategies, hence giving some suggestions on the choice of reliable condition indices for maintenance decision-making. - Highlights: • Developing a new and generic degradation and failure model. • Synthesizing diagnostic and prognostic condition indices on the basis of the developed degradation and failure model. • Building diagnosis and prognosis-based maintenance strategies, and developing the associated cost models. • Assessing the performance and robustness of the considered strategies to find out reliable indices.

New prognostic factors and scoring system for patients with skeletal metastasis.

Science.gov (United States)

Katagiri, Hirohisa; Okada, Rieko; Takagi, Tatsuya; Takahashi, Mitsuru; Murata, Hideki; Harada, Hideyuki; Nishimura, Tetsuo; Asakura, Hirofumi; Ogawa, Hirofumi

2014-10-01

The aim of this study was to update a previous scoring system for patients with skeletal metastases, that was proposed by Katagiri et al. in 2005, by introducing a new factor (laboratory data) and analyzing a new patient cohort. Between January 2005 and January 2008, we treated 808 patients with symptomatic skeletal metastases. They were prospectively registered regardless of their treatments, and the last follow-up evaluation was performed in 2012. There were 441 male and 367 female patients with a median age of 64 years. Of these patients, 749 were treated nonsurgically while the remaining 59 underwent surgery for skeletal metastasis. A multivariate analysis was conducted using the Cox proportional hazards model. We identified six significant prognostic factors for survival, namely, the primary lesion, visceral or cerebral metastases, abnormal laboratory data, poor performance status, previous chemotherapy, and multiple skeletal metastases. The first three factors had a larger impact than the remaining three. The prognostic score was calculated by adding together all the scores for individual factors. With a prognostic score of ≥7, the survival rate was 27% at 6 months, and only 6% at 1 year. In contrast, patients with a prognostic score of ≤3 had a survival rate of 91% at 1 year, and 78% at 2 years. Comparing the revised system with the previous one, there was a significantly lower number of wrongly predicted patients using the revised system. This revised scoring system was able to predict the survival rates of patients with skeletal metastases more accurately than the previous system and may be useful for selecting an optimal treatment. © 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

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

Science.gov (United States)

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

2014-03-01

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

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

Science.gov (United States)

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

2013-09-01

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

Prognostic significance of blood-brain barrier disruption in patients with severe nonpenetrating traumatic brain injury requiring decompressive craniectomy.

Science.gov (United States)

Ho, Kwok M; Honeybul, Stephen; Yip, Cheng B; Silbert, Benjamin I

2014-09-01

The authors assessed the risk factors and outcomes associated with blood-brain barrier (BBB) disruption in patients with severe, nonpenetrating, traumatic brain injury (TBI) requiring decompressive craniectomy. At 2 major neurotrauma centers in Western Australia, a retrospective cohort study was conducted among 97 adult neurotrauma patients who required an external ventricular drain (EVD) and decompressive craniectomy during 2004-2012. Glasgow Outcome Scale scores were used to assess neurological outcomes. Logistic regression was used to identify factors associated with BBB disruption, defined by a ratio of total CSF protein concentrations to total plasma protein concentration > 0.007 in the earliest CSF specimen collected after TBI. Of the 252 patients who required decompressive craniectomy, 97 (39%) required an EVD to control intracranial pressure, and biochemical evidence of BBB disruption was observed in 43 (44%). Presence of disruption was associated with more severe TBI (median predicted risk for unfavorable outcome 75% vs 63%, respectively; p = 0.001) and with worse outcomes at 6, 12, and 18 months than was absence of BBB disruption (72% vs 37% unfavorable outcomes, respectively; p = 0.015). The only risk factor significantly associated with increased risk for BBB disruption was presence of nonevacuated intracerebral hematoma (> 1 cm diameter) (OR 3.03, 95% CI 1.23-7.50; p = 0.016). Although BBB disruption was associated with more severe TBI and worse long-term outcomes, when combined with the prognostic information contained in the Corticosteroid Randomization after Significant Head Injury (CRASH) prognostic model, it did not seem to add significant prognostic value (area under the receiver operating characteristic curve 0.855 vs 0.864, respectively; p = 0.453). Biochemical evidence of BBB disruption after severe nonpenetrating TBI was common, especially among patients with large intracerebral hematomas. Disruption of the BBB was associated with more severe

Distributed Prognostics and Health Management with a Wireless Network Architecture

Science.gov (United States)

Goebel, Kai; Saha, Sankalita; Sha, Bhaskar

2013-01-01

A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the

Lymphopenia: A new independent prognostic factor for survival in patients treated with whole brain radiotherapy for brain metastases from breast carcinoma

International Nuclear Information System (INIS)

Claude, Line; Perol, David; Ray-Coquard, Isabelle; Petit, Thierry; Blay, Jean-Yves; Carrie, Christian; Bachelot, Thomas

2005-01-01

Background and purpose: To determine overall survival (OS) and independent prognostic factors in patients with brain metastases (BM) from breast cancer treated by whole brain radiotherapy (WBR). Patients and methods: One hundred and twenty (120) women with BM, treated in a single French cancer center between 02/91 and 06/01, were reviewed. BM were confirmed by computed tomography or magnetic resonance imaging. Survival time was defined as the time interval from the date of BM to the date of death or last follow-up. A Cox proportional hazards regression model was used to determine significant prognostic factors in a multivariate analysis. Results: Surgery was followed by WBR in 5 patients. One hundred and four (104) patients received exclusive WBR, eight received concomitant chemo-radiation, and one received chemo-radiation after surgery. The median survival time was 5 months (95% CI: 3-7 months). In the multivariate analysis, performance status over 1 and lymphopenia (<0.7 G/L) were found to be independent prognostic factors for poor survival. Based on the number of these independent prognostic factors, we propose a predictive model for survival in brain metastatic cancer patients. Median survival was 7 months for patients presenting none or one poor prognosis factor at diagnosis versus 2 months for patients with 2 poor prognosis factors (p<0.0001) Conclusion: Brain metastases from breast cancer remain associated with very poor prognosis and there is a need for better treatment procedures. If confirmed in predictive models, the identification of prognostic subgroups, based on KPS and lymphopenia, among patients with BM from breast cancer would help physicians select patients for future clinical trials

Prognostic relevance and performance characteristics of serum IGFBP-2 and PAPP-A in women with breast cancer: a long-term Danish cohort study.

Science.gov (United States)

Espelund, Ulrick; Renehan, Andrew G; Cold, Søren; Oxvig, Claus; Lancashire, Lee; Su, Zhenqiang; Flyvbjerg, Allan; Frystyk, Jan

2018-05-03

Measurement of circulating insulin-like growth factors (IGFs), in particular IGF-binding protein (IGFBP)-2, at the time of diagnosis, is independently prognostic in many cancers, but its clinical performance against other routinely determined prognosticators has not been examined. We measured IGF-I, IGF-II, pro-IGF-II, IGF bioactivity, IGFBP-2, -3, and pregnancy-associated plasma protein A (PAPP-A), an IGFBP regulator, in baseline samples of 301 women with breast cancer treated on four protocols (Odense, Denmark: 1993-1998). We evaluated performance characteristics (expressed as area under the curve, AUC) using Cox regression models to derive hazard ratios (HR) with 95% confidence intervals (CIs) for 10-year recurrence-free survival (RFS) and overall survival (OS), and compared those against the clinically used Nottingham Prognostic Index (NPI). We measured the same biomarkers in 531 noncancer individuals to assess multidimensional relationships (MDR), and evaluated additional prognostic models using survival artificial neural network (SANN) and survival support vector machines (SSVM), as these enhance capture of MDRs. For RFS, increasing concentrations of circulating IGFBP-2 and PAPP-A were independently prognostic [HR biomarker doubling : 1.474 (95% CIs: 1.160, 1.875, P = 0.002) and 1.952 (95% CIs: 1.364, 2.792, P < 0.001), respectively]. The AUC RFS for NPI was 0.626 (Cox model), improving to 0.694 (P = 0.012) with the addition of IGFBP-2 plus PAPP-A. Derived AUC RFS using SANN and SSVM did not perform superiorly. Similar patterns were observed for OS. These findings illustrate an important principle in biomarker qualification-measured circulating biomarkers may demonstrate independent prognostication, but this does not necessarily translate into substantial improvement in clinical performance. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Contemporary approach to neurologic prognostication of coma after cardiac arrest.

Science.gov (United States)

Ben-Hamouda, Nawfel; Taccone, Fabio S; Rossetti, Andrea O; Oddo, Mauro

2014-11-01

Coma after cardiac arrest (CA) is an important cause of admission to the ICU. Prognosis of post-CA coma has significantly improved over the past decade, particularly because of aggressive postresuscitation care and the use of therapeutic targeted temperature management (TTM). TTM and sedatives used to maintain controlled cooling might delay neurologic reflexes and reduce the accuracy of clinical examination. In the early ICU phase, patients' good recovery may often be indistinguishable (based on neurologic examination alone) from patients who eventually will have a poor prognosis. Prognostication of post-CA coma, therefore, has evolved toward a multimodal approach that combines neurologic examination with EEG and evoked potentials. Blood biomarkers (eg, neuron-specific enolase [NSE] and soluble 100-β protein) are useful complements for coma prognostication; however, results vary among commercial laboratory assays, and applying one single cutoff level (eg, > 33 μg/L for NSE) for poor prognostication is not recommended. Neuroimaging, mainly diffusion MRI, is emerging as a promising tool for prognostication, but its precise role needs further study before it can be widely used. This multimodal approach might reduce false-positive rates of poor prognosis, thereby providing optimal prognostication of comatose CA survivors. The aim of this review is to summarize studies and the principal tools presently available for outcome prediction and to describe a practical approach to the multimodal prognostication of coma after CA, with a particular focus on neuromonitoring tools. We also propose an algorithm for the optimal use of such multimodal tools during the early ICU phase of post-CA coma.

Artificial Intelligence Systems as Prognostic and Predictive Tools in Ovarian Cancer.

Science.gov (United States)

Enshaei, A; Robson, C N; Edmondson, R J

2015-11-01

The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation.

Gastric lymphomas in Turkey. Analysis of prognostic factors with special emphasis on flow cytometric DNA content.

Science.gov (United States)

Aydin, Z D; Barista, I; Canpinar, H; Sungur, A; Tekuzman, G

2000-07-01

In contrast to DNA ploidy, to the authors' knowledge the prognostic significance of S-phase fraction (SPF) in gastric lymphomas has not been determined. In the current study, the prognostic significance of various parameters including SPF and DNA aneuploidy were analyzed and some distinct epidemiologic and biologic features of gastric lymphomas in Turkey were found. A series of 78 gastric lymphoma patients followed at Hacettepe University is reported. DNA flow cytometry was performed for 34 patients. The influence of various parameters on survival was investigated with the log rank test. The Cox proportional hazards model was fitted to identify independent prognostic factors. The median age of the patients was 50 years. There was no correlation between patient age and tumor grade. DNA content analysis revealed 4 of the 34 cases to be aneuploid with DNA index values < 1.0. The mean SPF was 33.5%. In the univariate analysis, surgical resection of the tumor, modified Ann Arbor stage, performance status, response to first-line chemotherapy, lactate dehydrogenase (LDH) level, and SPF were important prognostic factors for disease free survival (DFS). The same parameters, excluding LDH level, were important for determining overall survival (OS). In the multivariate analysis, surgical resection of the tumor, disease stage, performance status, and age were found to be important prognostic factors for OS. To the authors' knowledge the current study is the first to demonstrate the prognostic significance of SPF in gastric lymphomas. The distinguishing features of Turkish gastric lymphoma patients are 1) DNA indices of aneuploid cases that all are < 1.0, which is a unique feature; 2) a lower percentage of aneuploid cases; 3) a higher SPF; 4) a younger age distribution; and 5) lack of an age-grade correlation. The authors conclude that gastric lymphomas in Turkey have distinct biologic and epidemiologic characteristics. Copyright 2000 American Cancer Society.

Prognostic implication of NQO1 overexpression in hepatocellular carcinoma.

Science.gov (United States)

Lin, Lijuan; Sun, Jie; Tan, Yan; Li, Zhenling; Kong, Fanyong; Shen, Yue; Liu, Chao; Chen, Litian

2017-11-01

To explore the role of NQO1 overexpression for prognostic implication in hepatocellular carcinoma (HCC), NQO1 mRNA levels were detected in HCC fresh tissue samples of HCC and nontumor tissues, respectively. One hundred fifty-six cases of HCC meeting strict follow-up criteria were selected for immunohistochemical staining of NQO1 protein. Correlations between NQO1 overexpression and clinicopathological features of HCC were evaluated using χ 2 tests, survival rates were calculated using the Kaplan-Meier method, and the relationship between prognostic factors and patient 5-year survival was analyzed using Cox proportional hazards analysis. In results, the levels of NQO1 mRNA were significantly up-regulated in 14 fresh tissue samples of HCC. Immunohistochemical analysis showed that the NQO1 expression and overexpression rates were significantly higher in HCC samples compared with either adjacent nontumor tissues or normal liver tissues. NQO1 overexpression correlated to tumor size, venous infiltration and late pTNM stage of HCC. NQO1 overexpression was also related to low disease-free survival and 5-year survival rates. In the late-stage group, disease-free and 5-year survival rates of patients with NQO1 overexpression were significantly lower than those of patients without NQO1 expression. Further analysis using a Cox proportional hazards regression model revealed that NQO1 expression emerged as a significant independent hazard factor for the 5-year survival rate of patients with HCC. Therefore, NQO1 plays an important role in the progression of HCC. NQO1 may potentially be used as an independent biomarker for prognostic evaluation of HCC. Copyright © 2017. Published by Elsevier Inc.

A DISTRIBUTED PROGNOSTIC HEALTH MANAGEMENT ARCHITECTURE

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National Aeronautics and Space Administration — This paper introduces a generic distributed prognostic health management (PHM) architecture with specific application to the electrical power systems domain. Current...

Crystal study and econometric model

Science.gov (United States)

1975-01-01

An econometric model was developed that can be used to predict demand and supply figures for crystals over a time horizon roughly concurrent with that of NASA's Space Shuttle Program - that is, 1975 through 1990. The model includes an equation to predict the impact on investment in the crystal-growing industry. Actually, two models are presented. The first is a theoretical model which follows rather strictly the standard theoretical economic concepts involved in supply and demand analysis, and a modified version of the model was developed which, though not quite as theoretically sound, was testable utilizing existing data sources.

A review on prognostic techniques for non-stationary and non-linear rotating systems

Science.gov (United States)

Kan, Man Shan; Tan, Andy C. C.; Mathew, Joseph

2015-10-01

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

Prognostic factors for medulloblastoma

International Nuclear Information System (INIS)

Jenkin, Derek; Al Shabanah, Mohamed; Al Shail, Essam; Gray, Alan; Hassounah, Maher; Khafaga, Yasser; Kofide, Amani; Mustafa, Mahmoud; Schultz, Henrik

2000-01-01

Purpose: To evaluate prognostic factors for medulloblastoma. Methods and Materials: One hundred and seventy-three consecutive patients with medulloblastoma, treated at King Faisal Specialist Hospital (KFSH) from 1988-1997, were reviewed. Eighty-four percent were children less than 15 years old. From 1988-1994, treatment was at the discretion of the investigator. From 1994-1998, patients entered a single-arm best practice protocol in which, in staged patients, the surgical intent was total resection, standard radiation treatment was defined, and adjuvant chemotherapy was given to a 'high-risk' subset. Results: For 150 patients who completed surgical and radiation treatment, the 5-year survival rate was 58%, compared with 0% for 16 patients who were unable to start or complete radiation treatment. For staged patients, the 5-year survival was M0 + M1, 78% and M2 + M3, 21% (p 14 years and gross cystic/necrotic features in the primary tumor. The size of the primary tumor, the degree of hydrocephalus at diagnosis, the presence of residual tumor in the post-operative CT/MRI, and the functional status of the patient prior to radiation treatment were not significant factors. Conclusions: Stage M0 + M1 was the most powerful favorable prognostic factor. In Saudi Arabia more patients present with advanced disseminated disease, 41% M2 + M3, than in the West, and this impacts adversely on overall survival. Total resection and standard radiation treatment were not sensitive prognostic factors in a treatment environment in which 78% of patients underwent at least 90% tumor resection and 60% received standard radiation treatment. In order to improve the proportion of patients able to complete radiation treatment, consideration should be given to limiting resection when the attainment of total resection is likely to be morbid, and to delaying rather than omitting radiation treatment in the patient severely compromised postoperatively

Upper digestive bleeding in cirrhosis. Post-therapeutic outcome and prognostic indicators.

Science.gov (United States)

D'Amico, Gennaro; De Franchis, Roberto

2003-09-01

Several treatments have been proven to be effective for variceal bleeding in patients with cirrhosis. The aim of this multicenter, prospective, cohort study was to assess how these treatments are used in clinical practice and what are the posttherapeutic prognosis and prognostic indicators of upper digestive bleeding in patients with cirrhosis. A training set of 291 and a test set of 174 bleeding cirrhotic patients were included. Treatment was according to the preferences of each center and the follow-up period was 6 weeks. Predictive rules for 5-day failure (uncontrolled bleeding, rebleeding, or death) and 6-week mortality were developed by the logistic model in the training set and validated in the test set. Initial treatment controlled bleeding in 90% of patients, including vasoactive drugs in 27%, endoscopic therapy in 10%, combined (endoscopic and vasoactive) in 45%, balloon tamponade alone in 1%, and none in 17%. The 5-day failure rate was 13%, 6-week rebleeding was 17%, and mortality was 20%. Corresponding findings for variceal versus nonvariceal bleeding were 15% versus 7% (P =.034), 19% versus 10% (P =.019), and 20% versus 15% (P =.22). Active bleeding on endoscopy, hematocrit levels, aminotransferase levels, Child-Pugh class, and portal vein thrombosis were significant predictors of 5-day failure; alcohol-induced etiology, bilirubin, albumin, encephalopathy, and hepatocarcinoma were predictors of 6-week mortality. Prognostic reassessment including blood transfusions improved the predictive accuracy. All the developed prognostic models were superior to the Child-Pugh score. In conclusion, prognosis of digestive bleeding in cirrhosis has much improved over the past 2 decades. Initial treatment stops bleeding in 90% of patients. Accurate predictive rules are provided for early recognition of high-risk patients.

Tumor markers as prognostic factors in non-small-cell lung cancer

International Nuclear Information System (INIS)

Nieder, C.; Nestle, U.; Ukena, D.; Niewald, M.; Sybrecht, G.W.; Schnabel, K.

1995-01-01

The data of 300 patients who had been irradiated for their primary tumor were analysed retrospectively. The serum concentrations of CEA, SCCA, NSE, and LDH were available before treatment and 3 months thereafter in a sufficient number of cases. The prognostic factors for survival and progression-free survival resulting from univariate tests were further evaluated by a Cox-proportional-hazards model. The serum levels of the particular tumor markers were pathologically elevated in 25 to 36.5% of the cases. Their values correlated with the stage of the disease and separately the N-stage too. A normalization of increased marker levels after irradiation occurred in 37.5 to 67% of the cases. Survival of patients with increased pretherapeutic values of CEA, SCCA, and LDH was significantly worse compared to those with normal values. In the case of a posttherapeutic return to normal levels, prognosis was significantly better than for those where the elevation persistet. However, after inclusion of all other parameters in multivariate analysis the tumor markers were meaningless. Karnofsky-performance status, total dose of radiotherapy, stage of the disease, and weight-loss evolved as independent prognostic factors for survival. For progression-free survival only stage of the disease was important. All subgroup analyses (restriction on patients with favorable prognosis) showed the same results. A prognostic importance of NSE could not be demonstrated. CEA, SCCA, and LDH were univariate predictors for survival and progression-free survival. But they proved to be dependent on the stage of the disease and were not confirmed as independent variables in the Cox-model. Their importance during the follow-up is diminished by the frequent lack of therapeutic approaches in the case of disease progression. Certainly a more favorable prognosis in case of a posttherapeutic normalization of previously elevated values was found. (orig./MG) [de

Effect of gender on the prognostic value of dobutamine stress myocardial contrast echocardiography

Directory of Open Access Journals (Sweden)

Constantina Aggeli

2017-11-01

Full Text Available Background: Dobutamine stress contrast echo (DSCE has a well-established prognostic value in the context of coronary artery disease (CAD. However, data regarding its prognostic capability separately in men and women are scarce. The aim of the current study was to assess gender-related differences in the prognostic performance of DSCE. Methods: DSCE was performed in 2645 consecutive patients, who were classified into two groups depending on gender. Follow-up lasted 57.1±10.1 months. End points included all-cause mortality, cardiac death, late revascularization, and hospitalizations. Survival analysis was performed comparing men and women. Results: Of the 2645 patients (59.3±8.7 years, 69.1% were men. DSCE was positive in 23.4% of male patients, while in females, the respective percentage was 14.3%. There was statistically significant difference between the two groups with regard to end point occurrence (11.6% vs. 6.1%, p<0.05. Multivariate analysis revealed that the DSCE response was the strongest predictor of adverse outcomes (Exp(B=51.9, p<0.05 in both groups. The predictive model including DSCE results along with clinical data performed well without significant differences between males and females (C-index 0.93 vs. 0.87 respectively, p=NS. Conclusion: DSCE has a strong prognostic value for patients with known or suspected CAD, regardless of patient gender. This makes DSCE an attractive screening option for women in whom CAD assessment can be challenging. Keywords: stress echocardiography, women, gender, prognosis, coronary artery disease

Prognostic stratification of ulcerated melanoma

DEFF Research Database (Denmark)

Bønnelykke-Behrndtz, Marie L; Schmidt, Henrik; Christensen, Ib J

2014-01-01

OBJECTIVES: For patients with melanoma, ulceration is an important prognostic marker and interestingly also a predictive marker for the response of adjuvant interferon. A consensual definition and accurate assessment of ulceration are therefore crucial for proper staging and clinical management. We...

Prognostic Impact of Inflammation-related Biomarkers on Overall Survival of Patients with Inoperable Malignant Pleural Mesothelioma.

Science.gov (United States)

Otoshi, Takehiro; Kataoka, Yuki; Kaku, Sawako; Iki, Reika; Hirabayashi, Masataka

2018-01-01

The aim of the present study was to assess the prognostic utility of the pretreatment blood neutrophil-to-lymphocyte ratio (NLR) and the C-reactive protein-to-albumin ratio (CAR) in patients with inoperable malignant pleural mesothelioma (MPM). The medical records of consecutive patients with histologically confirmed MPM from our hospital between January 2007 and August 2017 were retrospectively reviewed. The primary outcome was overall survival (OS). Univariate and multivariate analyses for the prognostic factors were performed using a Cox proportional hazards model. A total of 143 patients with inoperable MPM were included. On multivariate analysis, pretreatment CAR was an independent factor associated with worse OS (hazard ratio(HR)=1.72; 95% confidence interval(CI)=1.11-2.67; p=0.016). However, NLR was not associated with OS in any of the analyses. CAR appears to be a prognostic factor in patients with inoperable MPM. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Prognostic factors after intra-articular hyaluronic acid injection in ankle osteoarthritis.

Science.gov (United States)

Han, Seung Hwan; Park, Do Young; Kim, Tae Hun

2014-07-01

The goal of this study was to identify baseline prognostic factors of outcome in ankle osteoarthritis patients after intra-articular hyaluronic acid injection. Patients with ankle osteoarthritis who received hyaluronic acid injection therapy were retrospectively reviewed. Each patient received weekly intra-articular hyaluronic acid injections (2 mL) for 3 weeks. Six predictors including gender, age, symptom duration, radiographic osteoarthritis stage, radiographic subchondral cyst, and fracture history were evaluated. Visual analogue scale (VAS) and patient satisfaction were evaluated as outcome measures. These predictors and outcome measurements were included in a logistic regression model for statistical analysis. Total of 40 consecutive patients (21 male, 19 female) were included in this study. Mean age was 60.6. Average follow up period was 13 months. The mean VAS recorded 3, 6, and 12 months after the first injection was 3.6 (SD 2.54, phyaluronic acid injection for ankle osteoarthritis is a safe and effective treatment, careful selection of patients should be made according to the above prognostic predictors.

Prognostic factors for progression-free and overall survival in advanced biliary tract cancer

DEFF Research Database (Denmark)

Bridgewater, J; Lopes, A; Wasan, H

2016-01-01

independently with outcome. This score was validated externally by receiver operating curve (ROC) analysis using the independent international dataset. RESULTS: A total of 410 patients were included from the ABC-02 study and 753 from the international dataset. An overall survival (OS) and progression......BACKGROUND: Biliary tract cancer is an uncommon cancer with a poor outcome. We assembled data from the National Cancer Research Institute (UK) ABC-02 study and 10 international studies to determine prognostic outcome characteristics for patients with advanced disease. METHODS: Multivariable...... biliary tract cancer derived from the ABC-02 study that are validated in an international dataset. Although these findings establish the benchmark for the prognostic evaluation of patients with ABC and confirm the value of longheld clinical observations, the ability of the model to correctly predict...

Differing prognostic value of pulse pressure in patients with heart failure with reduced or preserved ejection fraction

DEFF Research Database (Denmark)

Jackson, Colette E; Castagno, Davide; Maggioni, Aldo P

2015-01-01

) and 5008 with HF-PEF (828 deaths). Pulse pressure was analysed in quintiles in a multivariable model adjusted for the previously reported Meta-Analysis Global Group in Chronic Heart Failure prognostic variables. Heart failure and reduced ejection fraction patients in the lowest pulse pressure quintile had...... in patients with HF-PEF [ejection fraction (EF) ≥ 50%] and HF-REF. METHODS AND RESULTS: Data from 22 HF studies were examined. Preserved left ventricular ejection fraction (LVEF) was defined as LVEF ≥ 50%. All-cause mortality at 3 years was evaluated in 27 046 patients: 22 038 with HF-REF (4980 deaths......AIMS: Low pulse pressure is a marker of adverse outcome in patients with heart failure (HF) and reduced ejection fraction (HF-REF) but the prognostic value of pulse pressure in patients with HF and preserved ejection fraction (HF-PEF) is unknown. We examined the prognostic value of pulse pressure...

Follicular lymphoma international prognostic index

NARCIS (Netherlands)

Solal-Céligny, Philippe; Roy, Pascal; Colombat, Philippe; White, Josephine; Armitage, Jim O.; Arranz-Saez, Reyes; Au, Wing Y.; Bellei, Monica; Brice, Pauline; Caballero, Dolores; Coiffier, Bertrand; Conde-Garcia, Eulogio; Doyen, Chantal; Federico, Massimo; Fisher, Richard I.; Garcia-Conde, Javier F.; Guglielmi, Cesare; Hagenbeek, Anton; Haïoun, Corinne; LeBlanc, Michael; Lister, Andrew T.; Lopez-Guillermo, Armando; McLaughlin, Peter; Milpied, Noël; Morel, Pierre; Mounier, Nicolas; Proctor, Stephen J.; Rohatiner, Ama; Smith, Paul; Soubeyran, Pierre; Tilly, Hervé; Vitolo, Umberto; Zinzani, Pier-Luigi; Zucca, Emanuele; Montserrat, Emili

2004-01-01

The prognosis of follicular lymphomas (FL) is heterogeneous and numerous treatments may be proposed. A validated prognostic index (PI) would help in evaluating and choosing these treatments. Characteristics at diagnosis were collected from 4167 patients with FL diagnosed between 1985 and 1992.

Evaluation of miR-21 and miR-375 as prognostic biomarkers in esophageal cancer

DEFF Research Database (Denmark)

Winther, Mette; Alsner, Jan; Tramm, Trine

2015-01-01

analyses identified miR-21 as an independent prognostic marker for DSS in EAC [HR 3.52 (95% CI 1.06-11.69)]. High miR-375 was not correlated with improved prognosis in either histology. However, Forest plots demonstrated that both miR-21 and miR-375 were of prognostic impact in ESCC. CONCLUSION...... chemotherapy were analyzed. Expression levels of miR-21 and miR-375 were quantified using Affymetrix GeneChip miRNA 1.0 Array. The Cox proportional hazards model was used to assess the correlation of miR-21 and miR-375 with disease-specific survival (DSS) and overall survival (OS). Forest plots were performed...... to evaluate the prognostic impact of miR-21 and miR-375 in the present study and previously published reports. RESULTS: In ESCC, patients with miR-21 expression levels above median showed a trend towards poorer DSS and OS. When dividing miR-21 expression by tertiles, high levels of miR-21 significantly...

Does C-reactive Protein Add Prognostic Value to GRACE Score in Acute Coronary Syndromes?

International Nuclear Information System (INIS)

Correia, Luis Cláudio Lemos; Vasconcelos, Isis; Garcia, Guilherme; Kalil, Felipe; Ferreira, Felipe; Silva, André; Oliveira, Ruan; Carvalhal, Manuela; Freitas, Caio; Noya-Rabelo, Márcia Maria

2014-01-01

The incremental prognostic value of plasma levels of C-reactive protein (CRP) in relation to GRACE score has not been established in patients with acute coronary syndrome (ACS) with non-ST segment elevation. To test the hypothesis that CRP measurements at admission increases the prognostic value of GRACE score in patients with ACS. A total of 290 subjects, consecutively admitted for ACS, with plasma material obtained upon admission CRP measurement using a high-sensitivity method (nephelometry) were studied. Cardiovascular outcomes during hospitalization were defined by the combination of death, nonfatal myocardial infarction or nonfatal refractory angina. The incidence of cardiovascular events during hospitalization was 15% (18 deaths, 11 myocardial infarctions, 13 angina episodes) with CRP showing C-statistics of 0.60 (95% CI = 0.51-0.70, p = 0.034) in predicting these outcomes. After adjustment for the GRACE score, elevated CRP (defined as the best cutoff point) tended to be associated with hospital events (OR = 1.89, 95% CI = 0.92 to 3.88, p = 0.08). However, the addition of the variable elevated CRP in the GRACE model did not result in significant increase in C-statistics, which ranged from 0.705 to 0.718 (p = 0.46). Similarly, there was no significant reclassification of risk with the addition of CRP in the predictor model (net reclassification = 5.7 %, p = 0.15). Although CRP is associated with hospital outcomes, this inflammatory marker does not increase the prognostic value of the GRACE score

Does C-reactive Protein Add Prognostic Value to GRACE Score in Acute Coronary Syndromes?

Energy Technology Data Exchange (ETDEWEB)

Correia, Luis Cláudio Lemos, E-mail: lccorreia@terra.com.br; Vasconcelos, Isis; Garcia, Guilherme; Kalil, Felipe; Ferreira, Felipe; Silva, André; Oliveira, Ruan; Carvalhal, Manuela; Freitas, Caio; Noya-Rabelo, Márcia Maria [Escola Bahiana de Medicina e Saúde Pública, Salvador, BA (Brazil); Hospital São Rafael, Salvador, BA (Brazil)

2014-05-15

The incremental prognostic value of plasma levels of C-reactive protein (CRP) in relation to GRACE score has not been established in patients with acute coronary syndrome (ACS) with non-ST segment elevation. To test the hypothesis that CRP measurements at admission increases the prognostic value of GRACE score in patients with ACS. A total of 290 subjects, consecutively admitted for ACS, with plasma material obtained upon admission CRP measurement using a high-sensitivity method (nephelometry) were studied. Cardiovascular outcomes during hospitalization were defined by the combination of death, nonfatal myocardial infarction or nonfatal refractory angina. The incidence of cardiovascular events during hospitalization was 15% (18 deaths, 11 myocardial infarctions, 13 angina episodes) with CRP showing C-statistics of 0.60 (95% CI = 0.51-0.70, p = 0.034) in predicting these outcomes. After adjustment for the GRACE score, elevated CRP (defined as the best cutoff point) tended to be associated with hospital events (OR = 1.89, 95% CI = 0.92 to 3.88, p = 0.08). However, the addition of the variable elevated CRP in the GRACE model did not result in significant increase in C-statistics, which ranged from 0.705 to 0.718 (p = 0.46). Similarly, there was no significant reclassification of risk with the addition of CRP in the predictor model (net reclassification = 5.7 %, p = 0.15). Although CRP is associated with hospital outcomes, this inflammatory marker does not increase the prognostic value of the GRACE score.

Some interesting prognostic factors related to cutaneous malignant melanoma

International Nuclear Information System (INIS)

Joan Figueroa, AlejandroYuri; Diaz Anaya, Amnia; Montero Leon, Jorge Felipe; Jimenez Mendes, Lourdes

2010-01-01

INTRODUCTION: The aim of present research was to determine the independent prognostic value and the 3 and 5 years survival of more significant clinicopathological prognostic factors and in each stage, according to pathological staging system of tumor-nodule-metastasis (TNM) in patients with cutaneous malignant melanoma (CMM). METHODS: A longitudinal, descriptive and retrospective study was conducted applying the Cox proportional risk form and the Kaplan-Meier method, aimed to search of different risk variables in patients with CMM. We studied 157 patients with CMM, seen during 8 years (1993 to 2001), diagnosed and treated in National Institute of Oncology and Radiobiology of La Habana. RESULTS: The more powerful prognostic variables related to localized disease (stage I and II) were the Breslow density (P: 0,000), the mitosis rate (P: 0,004), and the Clark level (P: 0,04); among the variables related to the regional disease (stage III) the number of lymphatic ganglia involved was the more weighthy (P:0,000) and the more important in Stage IV was the distant visceral metastasis (P:0,003). Survival was decreasing according to the advance of the pathological stage of disease. CONCLUSIONS: The more involved independent prognostic factors were the Breslow rate, the number of involved regional lymphatic nodules and the distant visceral metastasis, which is endorsed by a world consensus. However, variables as age, sex, lesion site, ulceration, host-tumor inflammatory response, histological subtype, satellitosis and transient metastasis, considered as independent prognostic indicators in big casuistries, had not statistical significance in present paper. (author)

Molecular Pathology: Predictive, Prognostic, and Diagnostic Markers in Uterine Tumors.

Science.gov (United States)

Ritterhouse, Lauren L; Howitt, Brooke E

2016-09-01

This article focuses on the diagnostic, prognostic, and predictive molecular biomarkers in uterine malignancies, in the context of morphologic diagnoses. The histologic classification of endometrial carcinomas is reviewed first, followed by the description and molecular classification of endometrial epithelial malignancies in the context of histologic classification. Taken together, the molecular and histologic classifications help clinicians to approach troublesome areas encountered in clinical practice and evaluate the utility of molecular alterations in the diagnosis and subclassification of endometrial carcinomas. Putative prognostic markers are reviewed. The use of molecular alterations and surrogate immunohistochemistry as prognostic and predictive markers is also discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

[Prognostic factors of early breast cancer].

Science.gov (United States)

Almagro, Elena; González, Cynthia S; Espinosa, Enrique

2016-02-19

Decision about the administration of adjuvant therapy for early breast cancer depends on the evaluation of prognostic factors. Lymph node status, tumor size and grade of differentiation are classical variables in this regard, and can be complemented by hormonal receptor status and HER2 expression. These factors can be combined into prognostic indexes to better estimate the risk of relapse or death. Other factors are less important. Gene profiles have emerged in recent years to identify low-risk patients who can forgo adjuvant chemotherapy. A number of profiles are available and can be used in selected cases. In the future, gene profiling will be used to select patients for treatment with new targeted therapies. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Acute lymphoblastic leukemia in children and adolescents: prognostic factors and analysis of survival

Science.gov (United States)

Lustosa de Sousa, Daniel Willian; de Almeida Ferreira, Francisco Valdeci; Cavalcante Félix, Francisco Helder; de Oliveira Lopes, Marcos Vinicios

2015-01-01

Objective To describe the clinical and laboratory features of children and adolescents with acute lymphoblastic leukemia treated at three referral centers in Ceará and evaluate prognostic factors for survival, including age, gender, presenting white blood cell count, immunophenotype, DNA index and early response to treatment. Methods Seventy-six under 19-year-old patients with newly diagnosed acute lymphoblastic leukemia treated with the Grupo Brasileiro de Tratamento de Leucemia da Infância – acute lymphoblastic leukemia-93 and -99 protocols between September 2007 and December 2009 were analyzed. The diagnosis was based on cytological, immunophenotypic and cytogenetic criteria. Associations between variables, prognostic factors and response to treatment were analyzed using the chi-square test and Fisher's exact test. Overall and event-free survival were estimated by Kaplan–Meier analysis and compared using the log-rank test. A Cox proportional hazards model was used to identify independent prognostic factors. Results The average age at diagnosis was 6.3 ± 0.5 years and males were predominant (65%). The most frequently observed clinical features were hepatomegaly, splenomegaly and lymphadenopathy. Central nervous system involvement and mediastinal enlargement occurred in 6.6% and 11.8%, respectively. B-acute lymphoblastic leukemia was more common (89.5%) than T-acute lymphoblastic leukemia. A DNA index >1.16 was found in 19% of patients and was associated with favorable prognosis. On Day 8 of induction therapy, 95% of the patients had lymphoblast counts <1000/μL and white blood cell counts <5.0 × 109/L. The remission induction rate was 95%, the induction mortality rate was 2.6% and overall survival was 72%. Conclusion The prognostic factors identified are compatible with the literature. The 5-year overall and event-free survival rates were lower than those reported for developed countries. As shown by the multivariate analysis, age and baseline white

Acute lymphoblastic leukemia in children and adolescents: prognostic factors and analysis of survival

Directory of Open Access Journals (Sweden)

Daniel Willian Lustosa de Sousa

2015-08-01

Full Text Available OBJECTIVE: To describe the clinical and laboratory features of children and adolescents with acute lymphoblastic leukemia treated at three referral centers in Ceará and evaluate prognostic factors for survival, including age, gender, presenting white blood cell count, immunophenotype, DNA index and early response to treatment.METHODS: Seventy-six under 19-year-old patients with newly diagnosed acute lymphoblastic leukemia treated with the Grupo Brasileiro de Tratamento de Leucemia da Infância - acute lymphoblastic leukemia-93 and -99 protocols between September 2007 and December 2009 were analyzed. The diagnosis was based on cytological, immunophenotypic and cytogenetic criteria. Associations between variables, prognostic factors and response to treatment were analyzed using the chi-square test and Fisher's exact test. Overall and event-free survival were estimated by Kaplan-Meier analysis and compared using the log-rank test. A Cox proportional hazards model was used to identify independent prognostic factors.RESULTS: The average age at diagnosis was 6.3 ± 0.5 years and males were predominant (65%. The most frequently observed clinical features were hepatomegaly, splenomegaly and lymphadenopathy. Central nervous system involvement and mediastinal enlargement occurred in 6.6% and 11.8%, respectively. B-acute lymphoblastic leukemia was more common (89.5% than T-acute lymphoblastic leukemia. A DNA index >1.16 was found in 19% of patients and was associated with favorable prognosis. On Day 8 of induction therapy, 95% of the patients had lymphoblast counts <1000/µL and white blood cell counts <5.0 Ã- 109/L. The remission induction rate was 95%, the induction mortality rate was 2.6% and overall survival was 72%.CONCLUSION: The prognostic factors identified are compatible with the literature. The 5-year overall and event-free survival rates were lower than those reported for developed countries. As shown by the multivariate analysis, age

Risk factors and a prognostic score for survival after autologous stem-cell transplantation for relapsed or refractory Hodgkin lymphoma

DEFF Research Database (Denmark)

Bröckelmann, P J; Müller, H; Casasnovas, O

2017-01-01

study (n = 1045), precise and valid risk prognostication in HL patients undergoing ASCT can be achieved with five easily available clinical RFs. The proposed prognostic score hence allows reliable stratification of patients for innovative therapeutic approaches in clinical practice and future trials...... therapeutic approaches, we investigated a comprehensive set of risk factors (RFs) for survival after ASCT. Methods: In this multinational prognostic multivariable modeling study, 23 potential RFs were retrospectively evaluated in HL patients from nine prospective trials with multivariable Cox proportional...... of potential RFs had significant impact on progression-free survival (PFS) with hazard ratios (HR) ranging from 1.39 to 2.22. The multivariable analysis identified stage IV disease, time to relapse ≤3 months, ECOG performance status ≥1, bulk ≥5 cm and inadequate response to salvage chemotherapy [

Prognostic significance of perioperative nutritional parameters in patients with gastric cancer.

Science.gov (United States)

Oh, Sung Eun; Choi, Min-Gew; Seo, Jeong-Meen; An, Ji Yeong; Lee, Jun Ho; Sohn, Tae Sung; Bae, Jae Moon; Kim, Sung

2018-02-20

It has been suggested that nutritional status is related to the survival outcomes of cancer patients. The purpose of the current research is to evaluate the importance of the prognosis of various nutritional parameters during the perioperative period in patients with gastric cancer. This study enrolled patients with gastric cancer who underwent D2 gastrectomy at the Department of Surgery, Samsung Medical Center, in 2008. The prognostic significance of nutritional parameters was analyzed, along with other clinical and pathological variables, preoperatively and postoperatively at 3, 6, and 12 months. The total number of patients was 1415. The mean values of nutritional parameters, weight, body mass index (BMI), hemoglobin, total cholesterol, and total lymphocyte count (TLC) decreased significantly over time after surgery. On the contrary, albumin and prognostic nutritional index (PNI) score increased significantly during the postoperative follow-up period. Preoperatively, low BMI (nutritional prognostic indicators. Various perioperative nutritional parameters were confirmed as independent prognostic factors in patients with gastric cancer. Our results imply prognostic benefit from careful nutritional support for patients with poor nutritional parameters. Copyright © 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

MicroRNA dysregulation as a prognostic biomarker in colorectal cancer

International Nuclear Information System (INIS)

Dong, Yujuan; Yu, Jun; Ng, Simon SM

2014-01-01

Colorectal cancer (CRC) is one of the most potentially curable cancers, yet it remains the fourth most common overall cause of cancer death worldwide. The identification of robust molecular prognostic biomarkers can refine the conventional tumor–node–metastasis staging system, avoid understaging of tumor, and help pinpoint patients with early-stage CRC who may benefit from aggressive treatments. Recently, epigenetic studies have provided new molecular evidence to better categorize the CRC subtypes and predict clinical outcomes. In this review, we summarize recent findings concerning the prognostic potential of microRNAs (miRNAs) in CRC. We first discuss the prognostic value of three tissue miRNAs (miR-21-5p, miR-29-3p, miR-148-3p) that have been examined in multiple studies. We also summarize the dysregulation of miRNA processing machinery DICER in CRC and its association with risk for mortality. We also reviewe the potential application of miRNA-associated single-nucleotide polymorphisms as prognostic biomarkers for CRC, especially the miRNA-associated polymorphism in the KRAS gene. Last but not least, we discuss the microsatellite instability-related miRNA candidates. Among all these candidates, miR-21-5p is the most promising prognostic marker, yet further prospective validation studies are required before it can go into clinical usage

Prognostic features and markers for testicular cancer management

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Eddy S Leman

2010-01-01

Full Text Available Testicular neoplasm accounts for about 1% of all cancers in men. Over the last 40 years, the incidence of testicular cancer has increased in northern European male populations for unknown reasons. When diagnosed at early stage, testicular cancer is usually curable with a high survival rate. In the past three decades, successful multidisciplinary approaches for the management of testicular cancer have significantly increased patient survival rates. Utilization of tumor markers and accurate prognostic classification has also contributed to successful therapy. In this article, we highlight the most commonly used tumor markers and several potential "novel" markers for testicular cancer as part of the ongoing effort in biomarker research and discovery. In addition, this article also identifies several key prognostic features that have been demonstrated to play a role in predicting relapse. These features include tumor size, rete testis invasion, lymphovascular invasion, and tumor histology. Together with tumor markers, these prognostic factors should be taken into account for risk-adapted management of testicular cancer.

Prognostic value of depressed midwall systolic function in cardiac light-chain amyloidosis.

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Perlini, Stefano; Salinaro, Francesco; Musca, Francesco; Mussinelli, Roberta; Boldrini, Michele; Raimondi, Ambra; Milani, Paolo; Foli, Andrea; Cappelli, Francesco; Perfetto, Federico; Palladini, Giovanni; Rapezzi, Claudio; Merlini, Giampaolo

2014-05-01

Cardiac amyloidosis represents an archetypal form of restrictive heart disease, characterized by profound diastolic dysfunction. As ejection fraction is preserved until the late stage of the disease, the majority of patients do fulfill the definition of diastolic heart failure, that is, heart failure with preserved ejection fraction (HFpEF). In another clinical model of HFpEF, that is, pressure-overload hypertrophy, depressed midwall fractional shortening (mFS) has been shown to be a powerful prognostic factor. To assess the potential prognostic role of mFS in cardiac light-chain amyloidosis with preserved ejection fraction, we enrolled 221 consecutive untreated patients, in whom a first diagnosis of cardiac light-chain amyloidosis was concluded between 2008 and 2010. HFpEF was present in 181 patients. Patients in whom cardiac involvement was excluded served as controls (n = 121). Prognosis was assessed after a median follow-up of 561 days. When compared with light-chain amyloidosis patients without myocardial involvement, cardiac light-chain amyloidosis was characterized by increased wall thickness (P model. In cardiac light-chain amyloidosis with normal ejection fraction, depressed circumferential mFS, a marker of myocardial contractile dysfunction, is a powerful predictor of survival.

Prognostic utility of novel biomarkers of cardiovascular stress: the Framingham Heart Study.

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Wang, Thomas J; Wollert, Kai C; Larson, Martin G; Coglianese, Erin; McCabe, Elizabeth L; Cheng, Susan; Ho, Jennifer E; Fradley, Michael G; Ghorbani, Anahita; Xanthakis, Vanessa; Kempf, Tibor; Benjamin, Emelia J; Levy, Daniel; Vasan, Ramachandran S; Januzzi, James L

2012-09-25

Biomarkers for predicting cardiovascular events in community-based populations have not consistently added information to standard risk factors. A limitation of many previously studied biomarkers is their lack of cardiovascular specificity. To determine the prognostic value of 3 novel biomarkers induced by cardiovascular stress, we measured soluble ST2, growth differentiation factor-15, and high-sensitivity troponin I in 3428 participants (mean age, 59 years; 53% women) in the Framingham Heart Study. We performed multivariable-adjusted proportional hazards models to assess the individual and combined ability of the biomarkers to predict adverse outcomes. We also constructed a "multimarker" score composed of the 3 biomarkers in addition to B-type natriuretic peptide and high-sensitivity C-reactive protein. During a mean follow-up of 11.3 years, there were 488 deaths, 336 major cardiovascular events, 162 heart failure events, and 142 coronary events. In multivariable-adjusted models, the 3 new biomarkers were associated with each end point (Pstatistic (P=0.005 or lower) and net reclassification improvement (P=0.001 or lower). Multiple biomarkers of cardiovascular stress are detectable in ambulatory individuals and add prognostic value to standard risk factors for predicting death, overall cardiovascular events, and heart failure.

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

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

2014-06-01

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

Prognostic importance of troponin T and creatine kinase after elective angioplasty

NARCIS (Netherlands)

Nienhuis, Mark B.; Ottervanger, Jan Paul; Dikkeschei, Bert; Suryapranata, Harry; de Boer, Menko-Jan; Dambrink, Jan-Henk E.; Hoorntje, Jan C. A.; van't Hof, Arnoud W. J.; Gosselink, Marcel; Zijlstra, Felix

2007-01-01

Background: The prognostic importance of elevated cardiac enzymes after elective percutaneous coronary intervention has been debated. Therefore, we performed a prospective observational study to evaluate the prognostic value of postprocedural rise of troponin T and creatine kinase. Methods: Troponin

Prognostic significance of the prognostic nutritional index in esophageal cancer patients undergoing neoadjuvant chemotherapy.

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Nakatani, M; Migita, K; Matsumoto, S; Wakatsuki, K; Ito, M; Nakade, H; Kunishige, T; Kitano, M; Kanehiro, H

2017-08-01

Nutritional status is one of the most important issues faced by cancer patients. Several studies have shown that a low preoperative nutritional status is associated with a worse prognosis in patients with various types of cancer, including esophageal cancer (EC). Recently, neoadjuvant chemotherapy (NAC) and/or radiotherapy have been accepted as the standard treatment for resectable advanced EC. However, NAC has the potential to deteriorate the nutritional status of a patient. This study aimed to evaluate the prognostic significance of the nutritional status for EC patients who underwent NAC. We retrospectively reviewed 66 squamous cell EC patients who underwent NAC consisting of docetaxel, cisplatin, and 5-fluorouracil followed by subtotal esophagectomy at Nara Medical University Hospital between January 2009 and August 2015. To assess the patients' nutritional status, the prognostic nutritional index (PNI) before commencing NAC and prior to the operation was calculated as 10 × serum albumin (g/dl) + 0.005 × total lymphocyte count in the peripheral blood (per mm3). The cutoff value of the PNI was set at 45. A multivariable analysis was performed to identify prognostic factors for overall survival (OS) and relapse-free survival (RFS). The mean pre-NAC and preoperative PNI were 50.2 ± 5.7 and 48.1 ± 4.7, respectively (P = 0.005). The PNI decreased following NAC in 44 (66.7%) patients. Before initiating NAC, 9 (13.6%) patients had a low PNI, and 12 (18.2%) patients had a low PNI prior to the operation. The pre-NAC PNI and preoperative PNI were significantly associated with the OS (P = 0.013 and P = 0.004, respectively) and RFS (P = 0.036 and P = 0.005, respectively) rates. The multivariable analysis identified the preoperative PNI as an independent prognostic factor for poor OS and RFS, although the pre-NAC PNI was not an independent predictor. Our results suggest that the preoperative PNI is a useful marker for predicting the long-term outcomes of EC patients

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

International Nuclear Information System (INIS)

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

2009-01-01

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

[Clinical characteristics and prognostic factors of pulmonary tuberculosis with concurrent lung cancer].

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Gu, Yingchun; Song, Yelin; Liu, Yufeng

2014-09-30

To explore the clinical characteristics and prognostic factors of pulmonary tuberculosis with concurrent lung cancer. Comprehensive analyses were conducted for 58 cases of pulmonary tuberculosis patients with lung cancer. Their clinical symptoms, signs and imaging results were analyzed between January 1998 and January 2005 at Qingdao Chest Hospital. Kaplan-Meier method was utilized to calculate their survival rates. Nine prognostic characteristics were analyzed. Single factor analysis was performed with Logrank test and multi-factor analysis with Cox regression model. The initial symptoms were cough, chest tightness, fever and hemoptysis. Chest radiology showed the coexistence of two diseases was 36 in the same lobe and 22 in different lobes. And there were pulmonary nodules (n = 24), cavities (n = 19), infiltration (n = 8) and atelectasis (n = 7). According to the pathological characteristics, there were squamous carcinoma (n = 33), adenocarcinoma (n = 17), small cell carcinoma (n = 4) and unidentified (n = 4) respectively. The TNM stages were I (n = 13), II(n = 22), III (n = 16) and IV (n = 7) respectively. The median survival period was 24 months. And the 1, 3, 5-year survival rates were 65.5%, 65.5% and 29.0% respectively. Single factor analysis showed that lung cancer TNM staging (P = 0.000) and tuberculosis activity (P = 0.024) were significantly associated with patient prognosis. And multi-factor analysis showed that lung cancer TNM staging (RR = 2.629, 95%CI: 1.759-3.928, P = 0.000) and tuberculosis activity (RR = 1.885, 95%CI: 1.023-3.471, P = 0.042) were relatively independent prognostic factors. The clinical and radiological characteristics contribute jointly to early diagnosis and therapy of tuberculosis with concurrent lung cancer. And TNM staging of lung cancer and activity of tuberculosis are major prognostic factors.

PROGNOSTIC FACTORS OF SURVIVAL IN RENAL CANCER

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A. V. Seriogin

2014-08-01

Full Text Available The purpose of the study was to reveal the independent anatomic, histological, and clinical factors of cancer-specific survival in patients with renal-cell carcinoma (RCC. For this, the authors retrospectively analyzed their experience with radical surgical treatments in 73 RCC patients operated on at the Department of Urology and Surgical Andrology, Russian Medical Academy of Postgraduate Education, from January 1, 1999 to December 31, 2004; their outcomes have become known by the present time. There was a statistically significant correlation of cancer-specific survival with its parameters, such as pathological stage of a tumor, its maximum pathological size, differentiation grade, involvement of regional lymph nodes, venous tumor thrombosis, level of thrombocytosis, and degree of the clinical symptoms of the disease. Multivariate analysis of survival in RCC in relation to the prognostic factors could reveal odd ratios for the limit values of significant prognostic factors. The statistically significant prognostic values established in the present study, as well as the molecular factors the implication of which is being now investigated can become in future an effective addition to the TNM staging system to define indications for certain treatments and to predict survival in RCC  

PROGNOSTIC FACTORS OF SURVIVAL IN RENAL CANCER

Directory of Open Access Journals (Sweden)

A. V. Seriogin

2009-01-01

Full Text Available The purpose of the study was to reveal the independent anatomic, histological, and clinical factors of cancer-specific survival in patients with renal-cell carcinoma (RCC. For this, the authors retrospectively analyzed their experience with radical surgical treatments in 73 RCC patients operated on at the Department of Urology and Surgical Andrology, Russian Medical Academy of Postgraduate Education, from January 1, 1999 to December 31, 2004; their outcomes have become known by the present time. There was a statistically significant correlation of cancer-specific survival with its parameters, such as pathological stage of a tumor, its maximum pathological size, differentiation grade, involvement of regional lymph nodes, venous tumor thrombosis, level of thrombocytosis, and degree of the clinical symptoms of the disease. Multivariate analysis of survival in RCC in relation to the prognostic factors could reveal odd ratios for the limit values of significant prognostic factors. The statistically significant prognostic values established in the present study, as well as the molecular factors the implication of which is being now investigated can become in future an effective addition to the TNM staging system to define indications for certain treatments and to predict survival in RCC  

Comparison of clinical outcomes and prognostic utility of risk stratification tools in patients with therapy-related vs de novo myelodysplastic syndromes: a report on behalf of the MDS Clinical Research Consortium.

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Zeidan, A M; Al Ali, N; Barnard, J; Padron, E; Lancet, J E; Sekeres, M A; Steensma, D P; DeZern, A; Roboz, G; Jabbour, E; Garcia-Manero, G; List, A; Komrokji, R

2017-06-01

While therapy-related (t)-myelodysplastic syndromes (MDS) have worse outcomes than de novo MDS (d-MDS), some t-MDS patients have an indolent course. Most MDS prognostic models excluded t-MDS patients during development. The performances of the International Prognostic Scoring System (IPSS), revised IPSS (IPSS-R), MD Anderson Global Prognostic System (MPSS), WHO Prognostic Scoring System (WPSS) and t-MDS Prognostic System (TPSS) were compared among patients with t-MDS. Akaike information criteria (AIC) assessed the relative goodness of fit of the models. We identified 370 t-MDS patients (19%) among 1950 MDS patients. Prior therapy included chemotherapy alone (48%), chemoradiation (31%), and radiation alone in 21%. Median survival for t-MDS patients was significantly shorter than for d-MDS (19 vs 46 months, PMDS (PMDS had a significantly higher hazard of death relative to d-MDS in every risk model, and had inferior survival compared to patients with d-MDS within all risk group categories. AIC Scores (lower is better) were 2316 (MPSS), 2343 (TPSS), 2343 (IPSS-R), 2361 (WPSS) and 2364 (IPSS). In conclusion, subsets of t-MDS patients with varying clinical outcomes can be identified using conventional risk stratification models. The MPSS, TPSS and IPSS-R provide the best predictive power.

Prognostic Factors for Refractory Status Epilepticus

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J. Gordon Millichap

2013-03-01

Full Text Available Researchers at the Mayo Clinic, Rochester, MN studied the outcome and identified prognostic factors for refractory status epilepticus (RSE in 54 adult patients, median age 52 years [range 18-93].

Prognostic factors in canine appendicular osteosarcoma – a meta-analysis

Science.gov (United States)

2012-01-01

Background Appendicular osteosarcoma is the most common malignant primary canine bone tumor. When treated by amputation or tumor removal alone, median survival times (MST) do not exceed 5 months, with the majority of dogs suffering from metastatic disease. This period can be extended with adequate local intervention and adjuvant chemotherapy, which has become common practice. Several prognostic factors have been reported in many different studies, e.g. age, breed, weight, sex, neuter status, location of tumor, serum alkaline phosphatase (SALP), bone alkaline phosphatase (BALP), infection, percentage of bone length affected, histological grade or histological subtype of tumor. Most of these factors are, however, only reported as confounding factors in larger studies. Insight in truly significant prognostic factors at time of diagnosis may contribute to tailoring adjuvant therapy for individual dogs suffering from osteosarcoma. The objective of this study was to systematically review the prognostic factors that are described for canine appendicular osteosarcoma and validate their scientific importance. Results A literature review was performed on selected studies and eligible data were extracted. Meta-analyses were done for two of the three selected possible prognostic factors (SALP and location), looking at both survival time (ST) and disease free interval (DFI). The third factor (age) was studied in a qualitative manner. Both elevated SALP level and the (proximal) humerus as location of the primary tumor are significant negative prognostic factors for both ST and DFI in dogs with appendicular osteosarcoma. Increasing age was associated with shorter ST and DFI, however, was not statistically significant because information of this factor was available in only a limited number of papers. Conclusions Elevated SALP and proximal humeral location are significant negative prognosticators for canine osteosarcoma. PMID:22587466

Prognostic factors in canine appendicular osteosarcoma – a meta-analysis

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Boerman Ilse

2012-05-01

Full Text Available Abstract Background Appendicular osteosarcoma is the most common malignant primary canine bone tumor. When treated by amputation or tumor removal alone, median survival times (MST do not exceed 5 months, with the majority of dogs suffering from metastatic disease. This period can be extended with adequate local intervention and adjuvant chemotherapy, which has become common practice. Several prognostic factors have been reported in many different studies, e.g. age, breed, weight, sex, neuter status, location of tumor, serum alkaline phosphatase (SALP, bone alkaline phosphatase (BALP, infection, percentage of bone length affected, histological grade or histological subtype of tumor. Most of these factors are, however, only reported as confounding factors in larger studies. Insight in truly significant prognostic factors at time of diagnosis may contribute to tailoring adjuvant therapy for individual dogs suffering from osteosarcoma. The objective of this study was to systematically review the prognostic factors that are described for canine appendicular osteosarcoma and validate their scientific importance. Results A literature review was performed on selected studies and eligible data were extracted. Meta-analyses were done for two of the three selected possible prognostic factors (SALP and location, looking at both survival time (ST and disease free interval (DFI. The third factor (age was studied in a qualitative manner. Both elevated SALP level and the (proximal humerus as location of the primary tumor are significant negative prognostic factors for both ST and DFI in dogs with appendicular osteosarcoma. Increasing age was associated with shorter ST and DFI, however, was not statistically significant because information of this factor was available in only a limited number of papers. Conclusions Elevated SALP and proximal humeral location are significant negative prognosticators for canine osteosarcoma.

Association of Telomere Length with Breast Cancer Prognostic Factors.

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Kaoutar Ennour-Idrissi

Full Text Available Telomere length, a marker of cell aging, seems to be affected by the same factors thought to be associated with breast cancer prognosis.To examine associations of peripheral blood cell-measured telomere length with traditional and potential prognostic factors in breast cancer patients.We conducted a cross-sectional analysis of data collected before surgery from 162 breast cancer patients recruited consecutively between 01/2011 and 05/2012, at a breast cancer reference center. Data on the main lifestyle factors (smoking, alcohol consumption, physical activity were collected using standardized questionnaires. Anthropometric factors were measured. Tumor biological characteristics were extracted from pathology reports. Telomere length was measured using a highly reproducible quantitative PCR method in peripheral white blood cells. Spearman partial rank-order correlations and multivariate general linear models were used to evaluate relationships between telomere length and prognostic factors.Telomere length was positively associated with total physical activity (rs = 0.17, P = 0.033; Ptrend = 0.069, occupational physical activity (rs = 0.15, P = 0.054; Ptrend = 0.054 and transportation-related physical activity (rs = 0.19, P = 0.019; P = 0.005. Among post-menopausal women, telomere length remained positively associated with total physical activity (rs = 0.27, P = 0.016; Ptrend = 0.054 and occupational physical activity (rs = 0.26, P = 0.021; Ptrend = 0.056 and was only associated with transportation-related physical activity among pre-menopausal women (rs = 0.27, P = 0.015; P = 0.004. No association was observed between telomere length and recreational or household activities, other lifestyle factors or traditional prognostic factors.Telomeres are longer in more active breast cancer patients. Since white blood cells are involved in anticancer immune responses, these findings suggest that even regular low-intensity physical activity, such as that

Prognostic and survival analysis of presbyopia: The healthy twin study

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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.

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

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

2015-05-21

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

The prognostic ability of the STarT Back Tool was affected by episode duration

DEFF Research Database (Denmark)

Morsø, Lars; Kongsted, Alice; Hestbæk, Lise

2016-01-01

were not systematically affected by SBT risk subgroup (non-stratified care). Using generalised estimating equations, we investigated statistical interactions between SBT risk subgroups and potentially influential factors on the prognostic ability of the SBT subgroups, when Roland Morris Disability...... Questionnaire scores were the outcome. RESULTS: SBT risk subgroup, age, care setting, and episode duration were all independent prognostic factors. The only investigated factor that modified the prognostic ability of the SBT subgroups was episode duration. CONCLUSIONS: These results indicate that the prognostic...

Heterogeneity of (18)F-FDG PET combined with expression of EGFR may improve the prognostic stratification of advanced oropharyngeal carcinoma.

Science.gov (United States)

Wang, Hung-Ming; Cheng, Nai-Ming; Lee, Li-Yu; Fang, Yu-Hua Dean; Chang, Joseph Tung-Chieh; Tsan, Din-Li; Ng, Shu-Hang; Liao, Chun-Ta; Yang, Lan-Yan; Yen, Tzu-Chen

2016-02-01

The Ang's risk profile (based on p16, smoking and cancer stage) is a well-known prognostic factor in oropharyngeal squamous cell carcinoma (OPSCC). Whether heterogeneity in (18)F-fluorodeoxyglucose (FDG) positron emission tomographic (PET) images and epidermal growth factor receptor (EGFR) expression could provide additional information on clinical outcomes in advanced-stage OPSCC was investigated. Patients with stage III-IV OPSCC who completed primary therapy were eligible. Zone-size nonuniformity (ZSNU) extracted from pretreatment FDG PET scans was used as an index of image heterogeneity. EGFR and p16 expression were examined by immunohistochemistry. Disease-specific survival (DSS) and overall survival (OS) served as outcome measures. Kaplan-Meier estimates and Cox proportional hazards regression models were used for survival analysis. A bootstrap resampling technique was applied to investigate the stability of outcomes. Finally, a recursive partitioning analysis (RPA)-based model was constructed. A total of 113 patients were included, of which 28 were p16-positive. Multivariate analysis identified the Ang's profile, EGFR and ZSNU as independent predictors of both DSS and OS. Using RPA, the three risk factors were used to devise a prognostic scoring system that successfully predicted DSS in both p16-positive and -negative cases. The c-statistic of the prognostic index for DSS was 0.81, a value which was significantly superior to both AJCC stage (0.60) and the Ang's risk profile (0.68). In patients showing an Ang's high-risk profile (N = 77), the use of our scoring system clearly identified three distinct prognostic subgroups. It was concluded that a novel index may improve the prognostic stratification of patients with advanced-stage OPSCC. © 2015 UICC.

Reirradiation in progressive high-grade gliomas: outcome, role of concurrent chemotherapy, prognostic factors and validation of a new prognostic score with an independent patient cohort

International Nuclear Information System (INIS)

Scholtyssek, Felix; Kortmann, Rolf-Dieter; Müller, Klaus; Zwiener, Isabella; Schlamann, Annika; Seidel, Clemens; Meixensberger, Jürgen; Bauer, Manfred; Hoffmann, Karl-Titus; Combs, Stephanie E; Bueren, André O von

2013-01-01

First, to evaluate outcome, the benefit of concurrent chemotherapy and prognostic factors in a cohort of sixty-four high-grade glioma patients who underwent a second course of radiation therapy at progression. Second, to validate a new prognostic score for overall survival after reirradiation of progressive gliomas with an independent patient cohort. All patients underwent fractionated reirradiation with a median physical dose of 36 Gy. Median planned target volume was 110.4 ml. Thirty-six patients received concurrent chemotherapy consisting in 24/36 cases (67%) of carboplatin and etoposide and in 12/36 cases (33%) of temozolomide. We used the Kaplan Meier method, log rank test and proportional hazards regression analysis for statistical assessment. Median overall survival from the start of reirradiation was 7.7 ± 0.7 months. Overall survival rates at 6 and 12 months were 60 ± 6% and 24 ± 6%, respectively. Despite relatively large target volumes we did not observe any major acute toxicity. Concurrent chemotherapy did not appear to improve outcome. In contrast, female gender, young age, WHO grade III histology, favorable Karnofsky performance score and complete resection of the tumor prior to reirradiation were identified as positive prognostic factors for overall survival. We finally validated a recent suggestion for a prognostic score with our independent but small patient cohort. Our preliminary findings suggest that its ability to discriminate between different prognostic groups is limited. Outcome of our patients was comparable to previous studies. Even in case of large target volumes reirradiation seems to be feasible without observing major toxicity. The benefit of concurrent chemotherapy is still elusive. A reassessment of the prognostic score, tested in this study, using a larger patient cohort is needed

LGE Provides Incremental Prognostic Information Over Serum Biomarkers in AL Cardiac Amyloidosis.

Science.gov (United States)

Boynton, Samuel J; Geske, Jeffrey B; Dispenzieri, Angela; Syed, Imran S; Hanson, Theodore J; Grogan, Martha; Araoz, Philip A

2016-06-01

This study sought to determine the prognostic value of cardiac magnetic resonance (CMR) late gadolinium enhancement (LGE) in amyloid light chain (AL) cardiac amyloidosis. Cardiac involvement is the major determinant of mortality in AL amyloidosis. CMR LGE is a marker of amyloid infiltration of the myocardium. The purpose of this study was to evaluate retrospectively the prognostic value of CMR LGE for determining all-cause mortality in AL amyloidosis and to compare the prognostic power with the biomarker stage. Seventy-six patients with histologically proven AL amyloidosis underwent CMR LGE imaging. LGE was categorized as global, focal patchy, or none. Global LGE was considered present if it was visualized on LGE images or if the myocardium nulled before the blood pool on a cine multiple inversion time (TI) sequence. CMR morphologic and functional evaluation, echocardiographic diastolic evaluation, and cardiac biomarker staging were also performed. Subjects' charts were reviewed for all-cause mortality. Cox proportional hazards analysis was used to evaluate survival in univariate and multivariate analysis. There were 40 deaths, and the median study follow-up period was 34.4 months. Global LGE was associated with all-cause mortality in univariate analysis (hazard ratio = 2.93; p < 0.001). In multivariate modeling with biomarker stage, global LGE remained prognostic (hazard ratio = 2.43; p = 0.01). Diffuse LGE provides incremental prognosis over cardiac biomarker stage in patients with AL cardiac amyloidosis. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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

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Akihiko Kato

2013-10-01

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

Blood group antigen A type 3 expression is a favorable prognostic factor in advanced NSCLC.

Science.gov (United States)

Schmidt, L H; Kuemmel, A; Schliemann, C; Schulze, A; Humberg, J; Mohr, M; Görlich, D; Hartmann, W; Bröckling, S; Marra, A; Hillejan, L; Goletz, S; Karsten, U; Berdel, W E; Spieker, T; Wiewrodt, R

2016-02-01

Several blood group-related carbohydrate antigens are prognosis-relevant markers of tumor tissues. A type 3 (repetitive A) is a blood group antigen specific for A1 erythrocytes. Its potential expression in tumor tissues has so far not been examined. We have evaluated its expression in normal lung and in lung cancer using a novel antibody (A69-A/E8). For comparison an anti-A antibody specific to A types 1 and 2 was used, because its expression on lung cancer tissue has been previously reported to be of prognostic relevance. Resected tissue samples of 398 NSCLC patients were analyzed in immunohistochemistry using tissue microarrays. Expression of A type 3 was not observed in non-malignant lung tissues. A type 3 was expressed on tumor cells of around half of NSCLC patients of blood group A1 (ptype 1/2 antigen was observed (p=0.562), the expression of A type 3 by tumor cells indicated a highly significant favorable prognosis among advanced NSCLC patients (p=0.011) and in NSCLC patients with lymphatic spread (p=0.014). Univariate prognostic results were confirmed in a Cox proportional hazards model. In this study we present for the first time prognostic data for A type 3 antigen expression in lung cancer patients. Prospective studies should be performed to confirm the prognostic value of A type 3 expression for an improved risk stratification in NSCLC patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Prognostic factors in sensory recovery after digital nerve repair

OpenAIRE

Bulut, Tugrul; Akgun, Ulas; Citlak, Atilla; Aslan, Cihan; Sener, Ufuk; Sener, Muhittin

2018-01-01

Objective: The prognostic factors that affect sensory nerve recovery after digital nerve repair are variable because of nonhomogeneous data, subjective tests, and different assessment/scoring methods. The aim of this study was to evaluate the success of sensory nerve recovery after digital nerve repair and to investigate the prognostic factors in sensorial healing.Methods: Ninety-six digital nerve repairs of 63 patients were retrospectively evaluated. All nerves were repaired with end-to-end ...

Prognostic value of platelet-to-lymphocyte ratio in pancreatic cancer: a comprehensive meta-analysis of 17 cohort studies.

Science.gov (United States)

Zhou, Yongping; Cheng, Sijin; Fathy, Abdel Hamid; Qian, Haixin; Zhao, Yongzhao

2018-01-01

Several studies were conducted to explore the prognostic value of platelet-to-lymphocyte ratio (PLR) in pancreatic cancer and have reported contradictory results. This study aims to summarize the prognostic role of PLR in pancreatic cancer. Embase, PubMed and Cochrane Library were completely searched. The cohort studies focusing on the prognostic role of PLR in pancreatic cancer were eligible. The overall survival (OS) and progression-free survival (PFS) were analyzed. Fifteen papers containing 17 cohort studies with pancreatic cancer were identified. The results showed patients that with low PLR might have longer OS when compared to the patients with high PLR (hazard ratio=1.28, 95% CI=1.17-1.40, P analysis model, ethnicity, sample size and cut-off value. Further analyses based on the adjusted potential confounders were conducted, including CA199, neutrophil-to-lymphocyte ratio, modified Glasgow Prognostic Score, albumin, C-reactive protein, Eastern Cooperative Oncology Group, stage, tumor size, nodal involvement, tumor differentiation, margin status, age and gender, which confirmed that low PLR was a protective factor in pancreatic cancer. In addition, low PLR was significantly associated with longer PFS when compared to high PLR in pancreatic cancer (hazard ratio=1.27, 95% CI=1.03-1.57, P =0.03; I 2 =33%). In conclusion, it was found that high PLR is an unfavorable predictor of OS and PFS in patients with pancreatic cancer, and PLR is a promising prognostic biomarker for pancreatic cancer.

Prognostics and Health Management of Wind Turbines: Current Status and Future Opportunities

Energy Technology Data Exchange (ETDEWEB)

Sheng, Shuangwen

2016-10-04

This presentation was given at the 2016 Annual Conference of the Prognostics and Health Management Society. It covers the current status and challenges and opportunities of prognostics and health management of wind turbines.

Treatments Results and Prognostic Factors in Locally Advanced Hypopharyngeal Cancer

International Nuclear Information System (INIS)

Yoon, Mee-Sun; Chung, Woong-Ki; Ahn, Sung-Ja; Nam, Taek-Keun; Song, Ju-Young; Nah, Byung-Sik; Lim, Sang Cheol; Lee, Joon Kyoo

2007-01-01

The purpose of this study is to present the treatment results and to identify possible prognostic indicators in patients with locally advanced hypopharyngeal carcinoma. Materials and Methods: Between October 1985 to December 2000, 90 patients who had locally advanced stage IV hypopharyngeal carcinoma were studied retrospectively. Twelve patients were treated with radiotherapy alone, 65 patients were treated with a combination of chemotherapy and radiotherapy, and 13 patients were treated with surgery and postoperative radiotherapy with or without neoadjuvant chemotherapy. Total radiation dose ranged from 59.0 to 88.2 Gy (median 70 Gy) for radiotherapy alone. Most patients had ciplatin and 5-fluorouracil, and others had cisplatin and peplomycin or vincristin. Median follow-up period was 15 months. Kaplan-Meier method was used for survival rate and Cox proportional hazard model for multivariate analysis of prognostic factors. Results: Overall 3- and 5-year survival rates were 27% and 17%, respectively. The 2-year locoregional control rates were 33% for radiotherapy alone, 32% for combined chemotherapy and radiotherapy, and 81% for combined surgery and radiotherapy (p=0.006). The prognostic factors affecting overall survival were T stage, concurrent chemo radiation and treatment response. Overall 3- and 5-year laryngeal preservation rates in combined chemotherapy and radiotherapy were 26% and 22%, respectively. Of these, the 5-year laryngeal preservation rates were 52% for concurrent chemo radiation group (n=11), and 16% for neoadjuvant chemotherapy and radiotherapy (n=54, p=0.012). Conclusion: Surgery and postoperative radiotherapy showed better results than radiotherapy alone or with chemotherapy. Radiotherapy combined with concurrent chemotherapy is an effective modality to achieve organ preservation in locally advanced hypopharyngeal cancer. Further prospective randomized studies will be required

Clinical implications of six inflammatory biomarkers as prognostic indicators in Ewing sarcoma

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Li YJ

2017-09-01

Full Text Available Yong-Jiang Li, Xi Yang, Wen-Biao Zhang, Cheng Yi, Feng Wang, Ping Li Department of Oncology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China Abstract: Cancer-related systemic inflammation responses have been correlated with cancer development and progression. The prognostic significance of several inflammatory indicators, including neutrophil–lymphocyte ratio (NLR, platelet–lymphocyte ratio (PLR, Glasgow Prognostic Score (GPS, C-reactive protein to albumin ratio (CRP/Alb ratio, lymphocyte–monocyte ratio (LMR, and neutrophil–platelet score (NPS, were found to be correlated with prognosis in several cancers. However, the prognostic role of these inflammatory biomarkers in Ewing sarcoma has not been evaluated. This study enrolled 122 Ewing patients. Receiver operating characteristic (ROC analysis was generated to determine optimal cutoff values; areas under the curves (AUCs were assessed to show the discriminatory ability of the biomarkers; Kaplan–Meier analysis was conducted to plot the survival curves; and Cox multivariate survival analysis was performed to identify independent prognostic factors. The optimal cutoff values of CRP/Alb ratio, NLR, PLR, and LMR were 0.225, 2.38, 131, and 4.41, respectively. CRP/Alb ratio had a significantly larger AUC than NLR, PLR, LMR, and NPS. Higher levels of CRP/Alb ratio (hazard ratio [HR] 2.41, P=0.005, GPS (HR 2.27, P=0.006, NLR (HR 2.07, P=0.013, and PLR (HR 1.85, P=0.032 were significantly correlated with poor prognosis. As the biomarkers had internal correlations, only the CRP/Alb ratio was involved in the multivariate Cox analysis and remained an independent prognostic indicator. The study demonstrated that CRP/Alb ratio, GPS, and NLR were effective prognostic indicators for patients with Ewing sarcoma, and the CRP/Alb ratio was the most robust prognostic indicator with a discriminatory ability superior to that of the other indicators; however, PLR, LMR, and

Iodine 125 prostate brachytherapy: prognostic factors for long-term urinary, digestive and sexual toxicities

International Nuclear Information System (INIS)

Doyen, J.; Mohammed Ali, A.; Ginot, A.; Ferre, M.; Castelli, J.; Hannoun-Levi, J.M.; Chamorey, E.; Mohammed Ali, A.; Quintens, H.; Amiel, J.

2009-01-01

Purpose For patients with good urinary function and presenting with a low risk prostate cancer, prostate brachytherapy using iodine implants represents one of the techniques of reference. This retrospective analysis investigates urinary (U), digestive (D) and sexual (S) toxicities and their prognostic factors of duration. Material and methods From August 2000 to November 2007, 176 patients presenting with prostate adenocarcinoma underwent interstitial brachytherapy. Urinary, digestive and sexual toxicities were classified according to Common toxicities criteria for adverse events, version 3.0 (C.T.C.A.E. V 3.0). For each toxicity (U, D, S), the number of complications U (dysuria, nicturia), D (proctitis, diarrhea) and S (sexual dysfunction, loss of libido) was listed and analyzed according to criteria related to the patient, implant, dosimetric data and characteristics of the toxicity. Prognostic factors identified in univariate analysis (U.V.A.) (Log Rank) were further analyzed in multivariate analysis (M.V.A.) (Cox model). Results With a median follow-up of 26 months (1-87), 147 patients (83.5 %) presented urinary toxicities. Among them, 29.5 % (86 patients) and 2.4 % (seven patients) presented grade 2 and 3 U toxicity respectively. In U.V.A., urinary grade toxicity greater than or equal to 2 (p = 0.037), the presence of initial U symptoms (p = 0.027) and more than two urinary toxicities (p 0.00032) were recognized as prognostic factors. The number of U toxicities was the only prognostic factor in M.V.A. (p = 0.04). D toxicity accounted for 40.6 % (71 patients). Among them, 3 % (six patients) were grade 2. None were grade 3. Two factors were identified as prognostic factors either in U.V.A. and M.V.A.: the number of D toxicities greater than or equal to 2 (univariate analysis: p = 0,00129, multivariate analysis: p = 0,002) and age less than or equal to 65 years (univariate analysis: p = 0,004, multivariate analysis: p 0,007). Eighty-three patients (47

Establishing a Reproducible Hypertrophic Scar following Thermal Injury: A Porcine Model

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Scott J. Rapp, MD

2015-02-01

Conclusions: Deep partial-thickness thermal injury to the back of domestic swine produces an immature hypertrophic scar by 10 weeks following burn with thickness appearing to coincide with the location along the dorsal axis. With minimal pig to pig variation, we describe our technique to provide a testable immature scar model.

Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

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Sarah R. Haile

2017-12-01

Full Text Available Abstract Background Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Methods Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. Results We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. Conclusions We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties

Identification of Subtype-Specific Prognostic Genes for Early-Stage Lung Adenocarcinoma and Squamous Cell Carcinoma Patients Using an Embedded Feature Selection Algorithm.

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Suyan Tian

Full Text Available The existence of fundamental differences between lung adenocarcinoma (AC and squamous cell carcinoma (SCC in their underlying mechanisms motivated us to postulate that specific genes might exist relevant to prognosis of each histology subtype. To test on this research hypothesis, we previously proposed a simple Cox-regression model based feature selection algorithm and identified successfully some subtype-specific prognostic genes when applying this method to real-world data. In this article, we continue our effort on identification of subtype-specific prognostic genes for AC and SCC, and propose a novel embedded feature selection method by extending Threshold Gradient Descent Regularization (TGDR algorithm and minimizing on a corresponding negative partial likelihood function. Using real-world datasets and simulated ones, we show these two proposed methods have comparable performance whereas the new proposal is superior in terms of model parsimony. Our analysis provides some evidence on the existence of such subtype-specific prognostic genes, more investigation is warranted.

Stress testing on silicon carbide electronic devices for prognostics and health management.

Energy Technology Data Exchange (ETDEWEB)

Kaplar, Robert James; Brock, Reinhard C.; Marinella, Matthew; King, Michael Patrick; Smith, Mark A.; Atcitty, Stanley

2011-01-01

Power conversion systems for energy storage and other distributed energy resource applications are among the drivers of the important role that power electronics plays in providing reliable electricity. Wide band gap semiconductors such as silicon carbide (SiC) and gallium nitride (GaN) will help increase the performance and efficiency of power electronic equipment while condition monitoring (CM) and prognostics and health management (PHM) will increase the operational availability of the equipment and thereby make it more cost effective. Voltage and/or temperature stress testing were performed on a number of SiC devices in order to accelerate failure modes and to identify measureable shifts in electrical characteristics which may provide early indication of those failures. Those shifts can be interpreted and modeled to provide prognostic signatures for use in CM and/or PHM. Such experiments will also lead to a deeper understanding of basic device physics and the degradation mechanisms behind failure.

Prognostic significance of peripheral monocyte count in patients with extranodal natural killer/T-cell lymphoma

International Nuclear Information System (INIS)

Huang, Jia-Jia; Li, Zhi-Ming; Li, Ya-Jun; Xia, Yi; Wang, Yu; Wei, Wen-Xiao; Zhu, Ying-Jie; Lin, Tong-Yu; Huang, Hui-Qiang; Jiang, Wen-Qi

2013-01-01

Extranodal natural killer/T-cell lymphoma (ENKL) has heterogeneous clinical manifestations and prognosis. This study aims to evaluate the prognostic impact of absolute monocyte count (AMC) in ENKL, and provide some immunologically relevant information for better risk stratification in patients with ENKL. Retrospective data from 163 patients newly diagnosed with ENKL were analyzed. The absolute monocyte count (AMC) at diagnosis was analyzed as continuous and dichotomized variables. Independent prognostic factors of survival were determined by Cox regression analysis. The AMC at diagnosis were related to overall survival (OS) and progression-free survival (PFS) in patients with ENKL. Multivariate analysis identified AMC as independent prognostic factors of survival, independent of International Prognostic Index (IPI) and Korean prognostic index (KPI). The prognostic index incorporating AMC and absolute lymphocyte count (ALC), another surrogate factor of immune status, could be used to stratify all 163 patients with ENKL into different prognostic groups. For patients who received chemotherapy followed by radiotherapy (102 cases), the three AMC/ALC index categories identified patients with significantly different survivals. When superimposed on IPI or KPI categories, the AMC/ALC index was better able to identify high-risk patients in the low-risk IPI or KPI category. The baseline peripheral monocyte count is shown to be an effective prognostic indicator of survival in ENKL patients. The prognostic index related to tumor microenvironment might be helpful to identify high-risk patients with ENKL

Prognostic significance of peripheral monocyte count in patients with extranodal natural killer/T-cell lymphoma.

Science.gov (United States)

Huang, Jia-Jia; Li, Ya-Jun; Xia, Yi; Wang, Yu; Wei, Wen-Xiao; Zhu, Ying-Jie; Lin, Tong-Yu; Huang, Hui-Qiang; Jiang, Wen-Qi; Li, Zhi-Ming

2013-05-03

Extranodal natural killer/T-cell lymphoma (ENKL) has heterogeneous clinical manifestations and prognosis. This study aims to evaluate the prognostic impact of absolute monocyte count (AMC) in ENKL, and provide some immunologically relevant information for better risk stratification in patients with ENKL. Retrospective data from 163 patients newly diagnosed with ENKL were analyzed. The absolute monocyte count (AMC) at diagnosis was analyzed as continuous and dichotomized variables. Independent prognostic factors of survival were determined by Cox regression analysis. The AMC at diagnosis were related to overall survival (OS) and progression-free survival (PFS) in patients with ENKL. Multivariate analysis identified AMC as independent prognostic factors of survival, independent of International Prognostic Index (IPI) and Korean prognostic index (KPI). The prognostic index incorporating AMC and absolute lymphocyte count (ALC), another surrogate factor of immune status, could be used to stratify all 163 patients with ENKL into different prognostic groups. For patients who received chemotherapy followed by radiotherapy (102 cases), the three AMC/ALC index categories identified patients with significantly different survivals. When superimposed on IPI or KPI categories, the AMC/ALC index was better able to identify high-risk patients in the low-risk IPI or KPI category. The baseline peripheral monocyte count is shown to be an effective prognostic indicator of survival in ENKL patients. The prognostic index related to tumor microenvironment might be helpful to identify high-risk patients with ENKL.

Developing Tools to Test the Thermo-Mechanical Models, Examples at Crustal and Upper Mantle Scale

Science.gov (United States)

Le Pourhiet, L.; Yamato, P.; Burov, E.; Gurnis, M.

2005-12-01

Testing geodynamical model is never an easy task. Depending on the spatio-temporal scale of the model, different testable predictions are needed and no magic reciepe exist. This contribution first presents different methods that have been used to test themo-mechanical modeling results at upper crustal, lithospheric and upper mantle scale using three geodynamical examples : the Gulf of Corinth (Greece), the Western Alps, and the Sierra Nevada. At short spatio-temporal scale (e.g. Gulf of Corinth). The resolution of the numerical models is usually sufficient to catch the timing and kinematics of the faults precisely enough to be tested by tectono-stratigraphic arguments. In active deforming area, microseismicity can be compared to the effective rheology and P and T axes of the focal mechanism can be compared with local orientation of the major component of the stress tensor. At lithospheric scale the resolution of the models doesn't permit anymore to constrain the models by direct observations (i.e. structural data from field or seismic reflection). Instead, synthetic P-T-t path may be computed and compared to natural ones in term of rate of exhumation for ancient orogens. Topography may also help but on continent it mainly depends on erosion laws that are complicated to constrain. Deeper in the mantle, the only available constrain are long wave length topographic data and tomographic "data". The major problem to overcome now at lithospheric and upper mantle scale, is that the so called "data" results actually from inverse models of the real data and that those inverse model are based on synthetic models. Post processing P and S wave velocities is not sufficient to be able to make testable prediction at upper mantle scale. Instead of that, direct wave propagations model must be computed. This allows checking if the differences between two models constitute a testable prediction or not. On longer term, we may be able to use those synthetic models to reduce the residue

Speech Motor Development in Childhood Apraxia of Speech : Generating Testable Hypotheses by Neurocomputational Modeling

NARCIS (Netherlands)

Terband, H.; Maassen, B.

2010-01-01

Childhood apraxia of speech (CAS) is a highly controversial clinical entity, with respect to both clinical signs and underlying neuromotor deficit. In the current paper, we advocate a modeling approach in which a computational neural model of speech acquisition and production is utilized in order to

Speech motor development in childhood apraxia of speech: generating testable hypotheses by neurocomputational modeling.

NARCIS (Netherlands)

Terband, H.R.; Maassen, B.A.M.

2010-01-01

Childhood apraxia of speech (CAS) is a highly controversial clinical entity, with respect to both clinical signs and underlying neuromotor deficit. In the current paper, we advocate a modeling approach in which a computational neural model of speech acquisition and production is utilized in order to

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

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Yu-Li Su

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

A Survey of Artificial Intelligence for Prognostics

Data.gov (United States)

National Aeronautics and Space Administration — Integrated Systems Health Management includes as key elements fault detection, fault diagnostics, and failure prognostics. Whereas fault detection and diagnostics...

Metrics for Evaluating Performance of Prognostic Techniques

Data.gov (United States)

National Aeronautics and Space Administration — Prognostics is an emerging concept in condition basedmaintenance(CBM)ofcriticalsystems.Alongwith developing the fundamentals of being able to confidently predict...