WorldWideScience

Sample records for survival time models

  1. Probabilistic Survivability Versus Time Modeling

    Science.gov (United States)

    Joyner, James J., Sr.

    2016-01-01

    This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.

  2. A generalized additive regression model for survival times

    DEFF Research Database (Denmark)

    Scheike, Thomas H.

    2001-01-01

    Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models......Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models...

  3. Modelling survival

    DEFF Research Database (Denmark)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight

    2016-01-01

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test...

  4. Modelling the joint distribution of competing risks survival times using copula functions

    OpenAIRE

    Kaishev, V. K.; Haberman, S.; Dimitrova, D. S.

    2005-01-01

    The problem of modelling the joint distribution of survival times in a competing risks model, using copula functions is considered. In order to evaluate this joint distribution and the related overall survival function, a system of non-linear differential equations is solved, which relates the crude and net survival functions of the modelled competing risks, through the copula. A similar approach to modelling dependent multiple decrements was applied by Carriere (1994) who used a Gaussian cop...

  5. Modeling the effects of binary mixtures on survival in time.

    NARCIS (Netherlands)

    Baas, J.; van Houte, B.P.P.; van Gestel, C.A.M.; Kooijman, S.A.L.M.

    2007-01-01

    In general, effects of mixtures are difficult to describe, and most of the models in use are descriptive in nature and lack a strong mechanistic basis. The aim of this experiment was to develop a process-based model for the interpretation of mixture toxicity measurements, with effects of binary

  6. Modeling time-to-event (survival) data using classification tree analysis.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2017-12-01

    Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

  7. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

    Science.gov (United States)

    Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

    2016-01-01

    Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  8. An approach to the drone fleet survivability assessment based on a stochastic continues-time model

    Science.gov (United States)

    Kharchenko, Vyacheslav; Fesenko, Herman; Doukas, Nikos

    2017-09-01

    An approach and the algorithm to the drone fleet survivability assessment based on a stochastic continues-time model are proposed. The input data are the number of the drones, the drone fleet redundancy coefficient, the drone stability and restoration rate, the limit deviation from the norms of the drone fleet recovery, the drone fleet operational availability coefficient, the probability of the drone failure-free operation, time needed for performing the required tasks by the drone fleet. The ways for improving the recoverable drone fleet survivability taking into account amazing factors of system accident are suggested. Dependencies of the drone fleet survivability rate both on the drone stability and the number of the drones are analysed.

  9. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

    Science.gov (United States)

    Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

    2016-01-01

    Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

  10. Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models

    Directory of Open Access Journals (Sweden)

    Lois A Gelfand

    2016-03-01

    Full Text Available Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH and fully parametric accelerated failure time (AFT approaches for illustration.Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively under varied data conditions, some including censoring. A simulated data set illustrates the findings.Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome – underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  11. Factors associated with supermarket and convenience store closure: a discrete time spatial survival modelling approach.

    Science.gov (United States)

    Warren, Joshua L; Gordon-Larsen, Penny

    2018-06-01

    While there is a literature on the distribution of food stores across geographic and social space, much of this research uses cross-sectional data. Analyses attempting to understand whether the availability of stores across neighborhoods is associated with diet and/or health outcomes are limited by a lack of understanding of factors that shape the emergence of new stores and the closure of others. We used quarterly data on supermarket and convenience store locations spanning seven years (2006-2012) and tract-level census data in four US cities: Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; San Francisco, California. A spatial discrete-time survival model was used to identify factors associated with an earlier and/or later closure time of a store. Sales volume was typically the strongest indicator of store survival. We identified heterogeneity in the association between tract-level poverty and racial composition with respect to store survival. Stores in high poverty, non-White tracts were often at a disadvantage in terms of survival length. The observed patterns of store survival varied by some of the same neighborhood sociodemographic factors associated with lifestyle and health outcomes, which could lead to confusion in interpretation in studies of the estimated effects of introduction of food stores into neighborhoods on health.

  12. Application of accelerated failure time models for breast cancer patients' survival in Kurdistan Province of Iran.

    Science.gov (United States)

    Karimi, Asrin; Delpisheh, Ali; Sayehmiri, Kourosh

    2016-01-01

    Breast cancer is the most common cancer and the second common cause of cancer-induced mortalities in Iranian women. There has been a rapid development in hazard models and survival analysis in the last decade. The aim of this study was to evaluate the prognostic factors of overall survival (OS) in breast cancer patients using accelerated failure time models (AFT). This was a retrospective-analytic cohort study. About 313 women with a pathologically proven diagnosis of breast cancer who had been treated during a 7-year period (since January 2006 until March 2014) in Sanandaj City, Kurdistan Province of Iran were recruited. Performance among AFT was assessed using the goodness of fit methods. Discrimination among the exponential, Weibull, generalized gamma, log-logistic, and log-normal distributions was done using Akaik information criteria and maximum likelihood. The 5 years OS was 75% (95% CI = 74.57-75.43). The main results in terms of survival were found for the different categories of the clinical stage covariate, tumor metastasis, and relapse of cancer. Survival time in breast cancer patients without tumor metastasis and relapse were 4, 2-fold longer than other patients with metastasis and relapse, respectively. One of the most important undermining prognostic factors in breast cancer is metastasis; hence, knowledge of the mechanisms of metastasis is necessary to prevent it so occurrence and treatment of metastatic breast cancer and ultimately extend the lifetime of patients.

  13. A special case of reduced rank models for identification and modelling of time varying effects in survival analysis.

    Science.gov (United States)

    Perperoglou, Aris

    2016-12-10

    Flexible survival models are in need when modelling data from long term follow-up studies. In many cases, the assumption of proportionality imposed by a Cox model will not be valid. Instead, a model that can identify time varying effects of fixed covariates can be used. Although there are several approaches that deal with this problem, it is not always straightforward how to choose which covariates should be modelled having time varying effects and which not. At the same time, it is up to the researcher to define appropriate time functions that describe the dynamic pattern of the effects. In this work, we suggest a model that can deal with both fixed and time varying effects and uses simple hypotheses tests to distinguish which covariates do have dynamic effects. The model is an extension of the parsimonious reduced rank model of rank 1. As such, the number of parameters is kept low, and thus, a flexible set of time functions, such as b-splines, can be used. The basic theory is illustrated along with an efficient fitting algorithm. The proposed method is applied to a dataset of breast cancer patients and compared with a multivariate fractional polynomials approach for modelling time-varying effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  14. The comparison of proportional hazards and accelerated failure time models in analyzing the first birth interval survival data

    Science.gov (United States)

    Faruk, Alfensi

    2018-03-01

    Survival analysis is a branch of statistics, which is focussed on the analysis of time- to-event data. In multivariate survival analysis, the proportional hazards (PH) is the most popular model in order to analyze the effects of several covariates on the survival time. However, the assumption of constant hazards in PH model is not always satisfied by the data. The violation of the PH assumption leads to the misinterpretation of the estimation results and decreasing the power of the related statistical tests. On the other hand, the accelerated failure time (AFT) models do not assume the constant hazards in the survival data as in PH model. The AFT models, moreover, can be used as the alternative to PH model if the constant hazards assumption is violated. The objective of this research was to compare the performance of PH model and the AFT models in analyzing the significant factors affecting the first birth interval (FBI) data in Indonesia. In this work, the discussion was limited to three AFT models which were based on Weibull, exponential, and log-normal distribution. The analysis by using graphical approach and a statistical test showed that the non-proportional hazards exist in the FBI data set. Based on the Akaike information criterion (AIC), the log-normal AFT model was the most appropriate model among the other considered models. Results of the best fitted model (log-normal AFT model) showed that the covariates such as women’s educational level, husband’s educational level, contraceptive knowledge, access to mass media, wealth index, and employment status were among factors affecting the FBI in Indonesia.

  15. Using simulation to interpret a discrete time survival model in a complex biological system: fertility and lameness in dairy cows.

    Directory of Open Access Journals (Sweden)

    Christopher D Hudson

    Full Text Available The ever-growing volume of data routinely collected and stored in everyday life presents researchers with a number of opportunities to gain insight and make predictions. This study aimed to demonstrate the usefulness in a specific clinical context of a simulation-based technique called probabilistic sensitivity analysis (PSA in interpreting the results of a discrete time survival model based on a large dataset of routinely collected dairy herd management data. Data from 12,515 dairy cows (from 39 herds were used to construct a multilevel discrete time survival model in which the outcome was the probability of a cow becoming pregnant during a given two day period of risk, and presence or absence of a recorded lameness event during various time frames relative to the risk period amongst the potential explanatory variables. A separate simulation model was then constructed to evaluate the wider clinical implications of the model results (i.e. the potential for a herd's incidence rate of lameness to influence its overall reproductive performance using PSA. Although the discrete time survival analysis revealed some relatively large associations between lameness events and risk of pregnancy (for example, occurrence of a lameness case within 14 days of a risk period was associated with a 25% reduction in the risk of the cow becoming pregnant during that risk period, PSA revealed that, when viewed in the context of a realistic clinical situation, a herd's lameness incidence rate is highly unlikely to influence its overall reproductive performance to a meaningful extent in the vast majority of situations. Construction of a simulation model within a PSA framework proved to be a very useful additional step to aid contextualisation of the results from a discrete time survival model, especially where the research is designed to guide on-farm management decisions at population (i.e. herd rather than individual level.

  16. Radiobilogical cell survival models

    International Nuclear Information System (INIS)

    Zackrisson, B.

    1992-01-01

    A central issue in clinical radiobiological research is the prediction of responses to different radiation qualities. The choice of cell survival and dose-response model greatly influences the results. In this context the relationship between theory and model is emphasized. Generally, the interpretations of experimental data depend on the model. Cell survival models are systematized with respect to their relations to radiobiological theories of cell kill. The growing knowlegde of biological, physical, and chemical mechanisms is reflected in the formulation of new models. The present overview shows that recent modelling has been more oriented towards the stochastic fluctuations connected to radiation energy deposition. This implies that the traditional cell surivival models ought to be complemented by models of stochastic energy deposition processes and repair processes at the intracellular level. (orig.)

  17. Accounting for Uncertainty in Decision Analytic Models Using Rank Preserving Structural Failure Time Modeling: Application to Parametric Survival Models.

    Science.gov (United States)

    Bennett, Iain; Paracha, Noman; Abrams, Keith; Ray, Joshua

    2018-01-01

    Rank Preserving Structural Failure Time models are one of the most commonly used statistical methods to adjust for treatment switching in oncology clinical trials. The method is often applied in a decision analytic model without appropriately accounting for additional uncertainty when determining the allocation of health care resources. The aim of the study is to describe novel approaches to adequately account for uncertainty when using a Rank Preserving Structural Failure Time model in a decision analytic model. Using two examples, we tested and compared the performance of the novel Test-based method with the resampling bootstrap method and with the conventional approach of no adjustment. In the first example, we simulated life expectancy using a simple decision analytic model based on a hypothetical oncology trial with treatment switching. In the second example, we applied the adjustment method on published data when no individual patient data were available. Mean estimates of overall and incremental life expectancy were similar across methods. However, the bootstrapped and test-based estimates consistently produced greater estimates of uncertainty compared with the estimate without any adjustment applied. Similar results were observed when using the test based approach on a published data showing that failing to adjust for uncertainty led to smaller confidence intervals. Both the bootstrapping and test-based approaches provide a solution to appropriately incorporate uncertainty, with the benefit that the latter can implemented by researchers in the absence of individual patient data. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  18. A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling.

    Science.gov (United States)

    Leger, Stefan; Zwanenburg, Alex; Pilz, Karoline; Lohaus, Fabian; Linge, Annett; Zöphel, Klaus; Kotzerke, Jörg; Schreiber, Andreas; Tinhofer, Inge; Budach, Volker; Sak, Ali; Stuschke, Martin; Balermpas, Panagiotis; Rödel, Claus; Ganswindt, Ute; Belka, Claus; Pigorsch, Steffi; Combs, Stephanie E; Mönnich, David; Zips, Daniel; Krause, Mechthild; Baumann, Michael; Troost, Esther G C; Löck, Steffen; Richter, Christian

    2017-10-16

    Radiomics applies machine learning algorithms to quantitative imaging data to characterise the tumour phenotype and predict clinical outcome. For the development of radiomics risk models, a variety of different algorithms is available and it is not clear which one gives optimal results. Therefore, we assessed the performance of 11 machine learning algorithms combined with 12 feature selection methods by the concordance index (C-Index), to predict loco-regional tumour control (LRC) and overall survival for patients with head and neck squamous cell carcinoma. The considered algorithms are able to deal with continuous time-to-event survival data. Feature selection and model building were performed on a multicentre cohort (213 patients) and validated using an independent cohort (80 patients). We found several combinations of machine learning algorithms and feature selection methods which achieve similar results, e.g. C-Index = 0.71 and BT-COX: C-Index = 0.70 in combination with Spearman feature selection. Using the best performing models, patients were stratified into groups of low and high risk of recurrence. Significant differences in LRC were obtained between both groups on the validation cohort. Based on the presented analysis, we identified a subset of algorithms which should be considered in future radiomics studies to develop stable and clinically relevant predictive models for time-to-event endpoints.

  19. Instrumental variables estimation of exposure effects on a time-to-event endpoint using structural cumulative survival models.

    Science.gov (United States)

    Martinussen, Torben; Vansteelandt, Stijn; Tchetgen Tchetgen, Eric J; Zucker, David M

    2017-12-01

    The use of instrumental variables for estimating the effect of an exposure on an outcome is popular in econometrics, and increasingly so in epidemiology. This increasing popularity may be attributed to the natural occurrence of instrumental variables in observational studies that incorporate elements of randomization, either by design or by nature (e.g., random inheritance of genes). Instrumental variables estimation of exposure effects is well established for continuous outcomes and to some extent for binary outcomes. It is, however, largely lacking for time-to-event outcomes because of complications due to censoring and survivorship bias. In this article, we make a novel proposal under a class of structural cumulative survival models which parameterize time-varying effects of a point exposure directly on the scale of the survival function; these models are essentially equivalent with a semi-parametric variant of the instrumental variables additive hazards model. We propose a class of recursive instrumental variable estimators for these exposure effects, and derive their large sample properties along with inferential tools. We examine the performance of the proposed method in simulation studies and illustrate it in a Mendelian randomization study to evaluate the effect of diabetes on mortality using data from the Health and Retirement Study. We further use the proposed method to investigate potential benefit from breast cancer screening on subsequent breast cancer mortality based on the HIP-study. © 2017, The International Biometric Society.

  20. The use of simple reparameterizations to improve the efficiency of Markov chain Monte Carlo estimation for multilevel models with applications to discrete time survival models.

    Science.gov (United States)

    Browne, William J; Steele, Fiona; Golalizadeh, Mousa; Green, Martin J

    2009-06-01

    We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in many situations in the medical and social sciences and we illustrate their use through two examples that differ in terms of both substantive area and data structure. A multilevel discrete time survival analysis involves expanding the data set so that the model can be cast as a standard multilevel binary response model. For such models it has been shown that MCMC methods have advantages in terms of reducing estimate bias. However, the data expansion results in very large data sets for which MCMC estimation is often slow and can produce chains that exhibit poor mixing. Any way of improving the mixing will result in both speeding up the methods and more confidence in the estimates that are produced. The MCMC methodological literature is full of alternative algorithms designed to improve mixing of chains and we describe three reparameterization techniques that are easy to implement in available software. We consider two examples of multilevel survival analysis: incidence of mastitis in dairy cattle and contraceptive use dynamics in Indonesia. For each application we show where the reparameterization techniques can be used and assess their performance.

  1. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data.

    Science.gov (United States)

    Nasejje, Justine B; Mwambi, Henry; Dheda, Keertan; Lesosky, Maia

    2017-07-28

    Random survival forest (RSF) models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (CIF) are known to correct the bias in RSF models by separating the procedure for the best covariate to split on from that of the best split point search for the selected covariate. In this study, we compare the random survival forest model to the conditional inference model (CIF) using twenty-two simulated time-to-event datasets. We also analysed two real time-to-event datasets. The first dataset is based on the survival of children under-five years of age in Uganda and it consists of categorical covariates with most of them having more than two levels (many split-points). The second dataset is based on the survival of patients with extremely drug resistant tuberculosis (XDR TB) which consists of mainly categorical covariates with two levels (few split-points). The study findings indicate that the conditional inference forest model is superior to random survival forest models in analysing time-to-event data that consists of covariates with many split-points based on the values of the bootstrap cross-validated estimates for integrated Brier scores. However, conditional inference forests perform comparably similar to random survival forests models in analysing time-to-event data consisting of covariates with fewer split-points. Although survival forests are promising methods in analysing time-to-event data, it is important to identify the best forest model for analysis based on the nature of covariates of the dataset in question.

  2. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data

    Directory of Open Access Journals (Sweden)

    Justine B. Nasejje

    2017-07-01

    Full Text Available Abstract Background Random survival forest (RSF models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (CIF are known to correct the bias in RSF models by separating the procedure for the best covariate to split on from that of the best split point search for the selected covariate. Methods In this study, we compare the random survival forest model to the conditional inference model (CIF using twenty-two simulated time-to-event datasets. We also analysed two real time-to-event datasets. The first dataset is based on the survival of children under-five years of age in Uganda and it consists of categorical covariates with most of them having more than two levels (many split-points. The second dataset is based on the survival of patients with extremely drug resistant tuberculosis (XDR TB which consists of mainly categorical covariates with two levels (few split-points. Results The study findings indicate that the conditional inference forest model is superior to random survival forest models in analysing time-to-event data that consists of covariates with many split-points based on the values of the bootstrap cross-validated estimates for integrated Brier scores. However, conditional inference forests perform comparably similar to random survival forests models in analysing time-to-event data consisting of covariates with fewer split-points. Conclusion Although survival forests are promising methods in analysing time-to-event data, it is important to identify the best forest model for analysis based on the nature of covariates of the dataset in question.

  3. Survival analysis models and applications

    CERN Document Server

    Liu, Xian

    2012-01-01

    Survival analysis concerns sequential occurrences of events governed by probabilistic laws.  Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis.Assumes only a minimal knowledge of SAS whilst enablin

  4. Survivability Assessment: Modeling A Recovery Process

    OpenAIRE

    Paputungan, Irving Vitra; Abdullah, Azween

    2009-01-01

    Survivability is the ability of a system to continue operating, in a timely manner, in the presence ofattacks, failures, or accidents. Recovery in survivability is a process of a system to heal or recover from damageas early as possible to fulfill its mission as condition permit. In this paper, we show a preliminary recoverymodel to enhance the system survivability. The model focuses on how we preserve the system and resumes itscritical service under attacks as soon as possible.Keywords: surv...

  5. Linking age, survival, and transit time distributions

    Science.gov (United States)

    Calabrese, Salvatore; Porporato, Amilcare

    2015-10-01

    Although the concepts of age, survival, and transit time have been widely used in many fields, including population dynamics, chemical engineering, and hydrology, a comprehensive mathematical framework is still missing. Here we discuss several relationships among these quantities by starting from the evolution equation for the joint distribution of age and survival, from which the equations for age and survival time readily follow. It also becomes apparent how the statistical dependence between age and survival is directly related to either the age dependence of the loss function or the survival-time dependence of the input function. The solution of the joint distribution equation also allows us to obtain the relationships between the age at exit (or death) and the survival time at input (or birth), as well as to stress the symmetries of the various distributions under time reversal. The transit time is then obtained as a sum of the age and survival time, and its properties are discussed along with the general relationships between their mean values. The special case of steady state case is analyzed in detail. Some examples, inspired by hydrologic applications, are presented to illustrate the theory with the specific results. This article was corrected on 11 Nov 2015. See the end of the full text for details.

  6. Survival analysis with covariates in combination with multinomial analysis to parametrize time to event for multi-state models

    NARCIS (Netherlands)

    Feenstra, T.L.; Postmus, D.; Quik, E.H.; Langendijk, H.; Krabbe, P.F.M.

    Objectives: Recent ISPOR Good practice guidelines as well as literature encourage to use a single distribution rather than the latent failure approach to model time to event for patient level simulation models with multiple competing outcomes. Aim was to apply the preferred method of a single

  7. Survival analysis with covariates in combination with multinomial analysis to parametrize time to event for multi-state models

    NARCIS (Netherlands)

    Feenstra, T.L.; Postmus, D.; Quik, E.H.; Langendijk, H.; Krabbe, P.F.M.

    2013-01-01

    Objectives: Recent ISPOR Good practice guidelines as well as literature encourage to use a single distribution rather than the latent failure approach to model time to event for patient level simulation models with multiple competing outcomes. Aim was to apply the preferred method of a single

  8. Predicting and Modelling of Survival Data when Cox's Regression Model does not hold

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...

  9. Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting

    Science.gov (United States)

    Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

    2018-01-01

    Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930

  10. Polygenic Score × Intervention Moderation: an Application of Discrete-Time Survival Analysis to Model the Timing of First Marijuana Use Among Urban Youth.

    Science.gov (United States)

    Musci, Rashelle J; Fairman, Brian; Masyn, Katherine E; Uhl, George; Maher, Brion; Sisto, Danielle Y; Kellam, Sheppard G; Ialongo, Nicholas S

    2018-01-01

    The present study examines the interaction between a polygenic score and an elementary school-based universal preventive intervention trial and its effects on a discrete-time survival analysis of time to first smoking marijuana. Research has suggested that initiation of substances is both genetically and environmentally driven (Rhee et al., Archives of general psychiatry 60:1256-1264, 2003; Verweij et al., Addiction 105:417-430, 2010). A previous work has found a significant interaction between the polygenic score and the same elementary school-based intervention with tobacco smoking (Musci et al., in press). The polygenic score reflects the contribution of multiple genes and has been shown in prior research to be predictive of smoking cessation, tobacco use, and marijuana use (Uhl et al., Molecular Psychiatry 19:50-54, 2014). Using data from a longitudinal preventive intervention study (N = 678), we examined age of first marijuana use from sixth grade to age 18. Genetic data were collected during emerging adulthood and were genotyped using the Affymetrix 6.0 microarray (N = 545). The polygenic score was computed using these data. Discrete-time survival analysis was employed to test for intervention main and interaction effects with the polygenic score. We found main effect of the polygenic score approaching significance, with the participants with higher polygenic scores reporting their first smoking marijuana at an age significantly later than controls (p = .050). We also found a significant intervention × polygenic score interaction effect at p = .003, with participants at the higher end of the polygenic score benefiting the most from the intervention in terms of delayed age of first use. These results suggest that genetics may play an important role in the age of first use of marijuana and that differences in genetics may account for the differential effectiveness of classroom-based interventions in delaying substance use experimentation.

  11. Extensions and Applications of the Cox-Aalen Survival Model

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2003-01-01

    Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects......Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects...

  12. TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

    International Nuclear Information System (INIS)

    Magome, T; Haga, A; Igaki, H; Sekiya, N; Masutani, Y; Sakumi, A; Mukasa, A; Nakagawa, K

    2014-01-01

    Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyo Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R 2 ) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R 2 between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R 2 was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by the JSPS Core

  13. Methodology for lognormal modelling of malignant pleural mesothelioma survival time distributions: a study of 5580 case histories from Europe and USA

    Energy Technology Data Exchange (ETDEWEB)

    Mould, Richard F [41 Ewhurst Avenue, South Croydon, Surrey CR2 0DH (United Kingdom); Lahanas, Michael [Klinikum Offenbach, Strahlenklinik, 66 Starkenburgring, 63069 Offenbach am Main (Germany); Asselain, Bernard [Institut Curie, Biostatistiques, 26 rue d' Ulm, 75231 Paris Cedex 05 (France); Brewster, David [Director, Scottish Cancer Registry, Information Services (NHS National Services Scotland) Area 155, Gyle Square, 1 South Gyle Crescent, Edinburgh EH12 9EB (United Kingdom); Burgers, Sjaak A [Department of Thoracic Oncology, Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, The (Netherlands); Damhuis, Ronald A M [Rotterdam Cancer Registry, Rochussenstraat 125, PO Box 289, 3000 AG Rotterdam, The (Netherlands); Rycke, Yann De [Institut Curie, Biostatistiques, 26 rue d' Ulm, 75231 Paris Cedex 05 (France); Gennaro, Valerio [Liguria Mesothelioma Cancer Registry, Etiology and Epidemiology Department, National Cancer Research Institute, Pad. Maragliano, Largo R Benzi, 10-16132 Genoa (Italy); Szeszenia-Dabrowska, Neonila [Department of Occupational and Environmental Epidemiology, National Institute of Occupational Medicine, PO Box 199, Swietej Teresy od Dzieciatka Jezus 8, 91-348 Lodz (Poland)

    2004-09-07

    A truncated left-censored and right-censored lognormal model has been validated for representing pleural mesothelioma survival times in the range 5-200 weeks for data subsets grouped by age for males, 40-49, 50-59, 60-69, 70-79 and 80+ years and for all ages combined for females. The cases available for study were from Europe and USA and totalled 5580. This is larger than any other pleural mesothelioma cohort accrued for study. The methodology describes the computation of reference baseline probabilities, 5-200 weeks, which can be used in clinical trials to assess results of future promising treatment methods. This study is an extension of previous lognormal modelling by Mould et al (2002 Phys. Med. Biol. 47 3893-924) to predict long-term cancer survival from short-term data where the proportion cured is denoted by C and the uncured proportion, which can be represented by a lognormal, by (1 - C). Pleural mesothelioma is a special case when C = 0.

  14. Methodology for lognormal modelling of malignant pleural mesothelioma survival time distributions: a study of 5580 case histories from Europe and USA

    International Nuclear Information System (INIS)

    Mould, Richard F; Lahanas, Michael; Asselain, Bernard; Brewster, David; Burgers, Sjaak A; Damhuis, Ronald A M; Rycke, Yann De; Gennaro, Valerio; Szeszenia-Dabrowska, Neonila

    2004-01-01

    A truncated left-censored and right-censored lognormal model has been validated for representing pleural mesothelioma survival times in the range 5-200 weeks for data subsets grouped by age for males, 40-49, 50-59, 60-69, 70-79 and 80+ years and for all ages combined for females. The cases available for study were from Europe and USA and totalled 5580. This is larger than any other pleural mesothelioma cohort accrued for study. The methodology describes the computation of reference baseline probabilities, 5-200 weeks, which can be used in clinical trials to assess results of future promising treatment methods. This study is an extension of previous lognormal modelling by Mould et al (2002 Phys. Med. Biol. 47 3893-924) to predict long-term cancer survival from short-term data where the proportion cured is denoted by C and the uncured proportion, which can be represented by a lognormal, by (1 - C). Pleural mesothelioma is a special case when C = 0

  15. Effects of Oral Administration of Fucoidan Extracted from Cladosiphon okamuranus on Tumor Growth and Survival Time in a Tumor-Bearing Mouse Model

    Directory of Open Access Journals (Sweden)

    Yoshiharu Okamoto

    2012-10-01

    Full Text Available We evaluated the anti-tumor activities of the oral administration of fucoidan extracted from Cladosiphon okamuranus using a tumor (colon 26-bearing mouse model. The materials used included low-molecular-weight fucoidan (LMWF: 6.5–40 kDa, intermediate-molecular-weight fucoidan (IMWF: 110–138 kDa and high-molecular-weight fucoidan (HMWF: 300–330 kDa. The IMWF group showed significantly suppressed tumor growth. The LMWF and HMWF groups showed significantly increased survival times compared with that observed in the control group (mice fed a fucoidan-free diet. The median survival times in the control, LMWF, IMWF and HMWF groups were 23, 46, 40 and 43 days, respectively. It was also found that oral administration of fucoidan increased the population of natural killer cells in the spleen. Furthermore, from the results of the experiment using Myd-88 knockout mice, it was found that these effects are related to gut immunity. These results suggest that fucoidan is a candidate anti-tumor functional food.

  16. Life-Cycle Models for Survivable Systems

    National Research Council Canada - National Science Library

    Linger, Richard

    2002-01-01

    .... Current software development life-cycle models are not focused on creating survivable systems, and exhibit shortcomings when the goal is to develop systems with a high degree of assurance of survivability...

  17. Fledgling survival increases with development time and adult survival across north and south temperate zones

    Science.gov (United States)

    Lloyd, Penn; Martin, Thomas E.

    2016-01-01

    Slow life histories are characterized by high adult survival and few offspring, which are thought to allow increased investment per offspring to increase juvenile survival. Consistent with this pattern, south temperate zone birds are commonly longer-lived and have fewer young than north temperate zone species. However, comparative analyses of juvenile survival, including during the first few weeks of the post-fledging period when most juvenile mortality occurs, are largely lacking. We combined our measurements of fledgling survival for eight passerines in South Africa with estimates from published studies of 57 north and south temperate zone songbird species to test three predictions: (1) fledgling survival increases with length of development time in the nest; (2) fledgling survival increases with adult survival and reduced brood size controlled for development time; and (3) south temperate zone species, with their higher adult survival and smaller brood sizes, exhibit higher fledgling survival than north temperate zone species controlled for development time. We found that fledgling survival was higher among south temperate zone species and generally increased with development time and adult survival within and between latitudinal regions. Clutch size did not explain additional variation, but was confounded with adult survival. Given the importance of age-specific mortality to life history evolution, understanding the causes of these geographical patterns of mortality is important.

  18. Times of analgesic efficacy of two drugs in the treatment of patients with renal-ureteral colic compared by survival models

    Directory of Open Access Journals (Sweden)

    Luis Reyes Velázquez

    2015-01-01

    Full Text Available Renourethral colic is a very painful clinical situation that requires a quick diagnosis and treatment. A study was done with patients who were administered two types of analgesics, and whose pain was measured through a visual analogue scale. Censored data results were obtained, considering the time when the pain disappeared as the random variable. Maximum likelihood and survival analysis give useful methods to estimate the distribution and parametric functions for this variable. This study will allow a more effective, timely, lower cost and suitable medical treatment for patients.

  19. Integral Time and the Varieties of Post-Mortem Survival

    Directory of Open Access Journals (Sweden)

    Sean M. Kelly

    2008-06-01

    Full Text Available While the question of survival of bodily death is usually approached by focusing on the mind/body relation (and often with the idea of the soul as a special kind of substance, this paper explores the issue in the context of our understanding of time. The argument of the paper is woven around the central intuition of time as an “ever-living present.” The development of this intuition allows for a more integral or “complex-holistic” theory of time, the soul, and the question of survival. Following the introductory matter, the first section proposes a re-interpretation of Nietzsche’s doctrine of eternal recurrence in terms of moments and lives as “eternally occurring.” The next section is a treatment of Julian Barbour’s neo-Machian model of instants of time as configurations in the n-dimensional phase-space he calls “Platonia.” While rejecting his claim to have done away with time, I do find his model suggestive of the idea of moments and lives as eternally occurring. The following section begins with Fechner’s visionary ideas of the nature of the soul and its survival of bodily death, with particular attention to the notion of holonic inclusion and the central analogy of the transition from perception to memory. I turn next to Whitehead’s equally holonic notions of prehension and the concrescence of actual occasions. From his epochal theory of time and certain ambiguities in his reflections on the “divine antinomies,” we are brought to the threshold of a potentially more integral or “complex-holistic” theory of time and survival, which is treated in the last section. This section draws from my earlier work on Hegel, Jung, and Edgar Morin, as well as from key insights of Jean Gebser, for an interpretation of Sri Aurobindo’s inspired but cryptic description of the “Supramental Time Vision.” This interpretation leads to an alternative understanding of reincarnation—and to the possibility of its reconciliation

  20. Integral Time and the Varieties of Post-Mortem Survival

    Directory of Open Access Journals (Sweden)

    Sean M. Kelly

    2008-06-01

    Full Text Available While the question of survival of bodily death is usually approached byfocusing on the mind/body relation (and often with the idea of the soul as a special kindof substance, this paper explores the issue in the context of our understanding of time.The argument of the paper is woven around the central intuition of time as an “everlivingpresent.” The development of this intuition allows for a more integral or “complexholistic”theory of time, the soul, and the question of survival. Following the introductorymatter, the first section proposes a re-interpretation of Nietzsche’s doctrine of eternalrecurrence in terms of moments and lives as “eternally occurring.” The next section is atreatment of Julian Barbour’s neo-Machian model of instants of time as configurations inthe n-dimensional phase-space he calls “Platonia.” While rejecting his claim to have doneaway with time, I do find his model suggestive of the idea of moments and lives aseternally occurring. The following section begins with Fechner’s visionary ideas of thenature of the soul and its survival of bodily death, with particular attention to the notionof holonic inclusion and the central analogy of the transition from perception to memory.I turn next to Whitehead’s equally holonic notions of prehension and the concrescence ofactual occasions. From his epochal theory of time and certain ambiguities in hisreflections on the “divine antinomies,” we are brought to the threshold of a potentiallymore integral or “complex-holistic” theory of time and survival, which is treated in thelast section. This section draws from my earlier work on Hegel, Jung, and Edgar Morin,as well as from key insights of Jean Gebser, for an interpretation of Sri Aurobindo’sinspired but cryptic description of the “Supramental Time Vision.” This interpretationleads to an alternative understanding of reincarnation—and to the possibility of itsreconciliation with the once-only view

  1. The Effect of Platelet-Rich Plasma on Survival of the Composite Graft and the Proper Time of Injection in a Rabbit Ear Composite Graft Model

    Directory of Open Access Journals (Sweden)

    Hyun Nam Choi

    2014-11-01

    Full Text Available BackgroundAdministration of growth factors has been associated with increased viability of composite grafts greater than 1-cm in diameter. Platelet-rich plasma (PRP contains many of the growth factors studied. In this study, we evaluate the effect of PRP injection on composite graft viability and the proper time for injection.MethodsA total of 24 New Zealand White rabbits were divided into four groups. Autologous PRP was injected into the recipient sites three days before grafting in group 1, on the day of grafting in group 2, and three days after grafting in group 3. Group 4 served as control without PRP administration. Auricular composite grafts of 3-cm diameter were harvested and grafted back into place after being rotated 180 degrees. Median graft viability and microvessel density were evaluated at day 21 of graft via macroscopic photographs and immunofluorescent staining, respectively.ResultsThe median graft survival rate was 97.8% in group 1, 69.2% in group 2, 55.7% in group 3, and 40.8% in the control group. The median vessel counts were 34 (per ×200 HPF in group 1, 24.5 in group 2, 19.5 in group 3, and 10.5 in the control group.ConclusionsThis study demonstrates that PRP administration is associated with increased composite graft viability. All experimental groups showed a significantly higher survival rate and microvessel density, compared with the control group. Pre-administration of PRP was followed by the highest graft survival rate and revascularization. PRP treatments are minimally invasive, fast, easily applicable, and inexpensive, and offer a potential clinical pathway to larger composite grafts.

  2. Time dependent ethnic convergence in colorectal cancer survival in hawaii

    Directory of Open Access Journals (Sweden)

    Hundahl Scott A

    2003-02-01

    Full Text Available Abstract Background Although colorectal cancer death rates have been declining, this trend is not consistent across all ethnic groups. Biological, environmental, behavioral and socioeconomic explanations exist, but the reason for this discrepancy remains inconclusive. We examined the hypothesis that improved cancer screening across all ethnic groups will reduce ethnic differences in colorectal cancer survival. Methods Through the Hawaii Tumor Registry 16,424 patients diagnosed with colorectal cancer were identified during the years 1960–2000. Cox regression analyses were performed for each of three cohorts stratified by ethnicity (Caucasian, Japanese, Hawaiian, Filipino, and Chinese. The models included stage of diagnosis, year of diagnosis, age, and sex as predictors of survival. Results Mortality rates improved significantly for all ethnic groups. Moreover, with the exception of Hawaiians, rates for all ethnic groups converged over time. Persistently lower survival for Hawaiians appeared linked with more cancer treatment. Conclusion Ethnic disparities in colorectal cancer mortality rates appear primarily the result of differential utilization of health care. If modern screening procedures can be provided equally to all ethnic groups, ethnic outcome differences can be virtually eliminated.

  3. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    DEFF Research Database (Denmark)

    Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

    2014-01-01

    A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

  4. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    DEFF Research Database (Denmark)

    Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

    2013-01-01

    A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

  5. Identifying Some Risk Factors for the Time to Death of the Elderly Using the Semi-Parametric Blended Model of Survival Analysis With Competing Risks

    Directory of Open Access Journals (Sweden)

    Samane Hajiabbasi

    2018-01-01

    Conclusion In single-variable fitting, age, history of myocardial infarction, history of stroke, and kidney problems were identified to have significant effects on the time to death of the elderly. Based on one-variable semi-parametric competing risk mixture fitted models, more significant risk factors for the time to death of elderly was identified when compared with a fitted multivariate mode to the data. This implies that the role of some independent variables can be explained by other independent variables.

  6. Modelling survival: exposure pattern, species sensitivity and uncertainty.

    Science.gov (United States)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

    2016-07-06

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

  7. Predictive model for survival in patients with gastric cancer.

    Science.gov (United States)

    Goshayeshi, Ladan; Hoseini, Benyamin; Yousefli, Zahra; Khooie, Alireza; Etminani, Kobra; Esmaeilzadeh, Abbas; Golabpour, Amin

    2017-12-01

    Gastric cancer is one of the most prevalent cancers in the world. Characterized by poor prognosis, it is a frequent cause of cancer in Iran. The aim of the study was to design a predictive model of survival time for patients suffering from gastric cancer. This was a historical cohort conducted between 2011 and 2016. Study population were 277 patients suffering from gastric cancer. Data were gathered from the Iranian Cancer Registry and the laboratory of Emam Reza Hospital in Mashhad, Iran. Patients or their relatives underwent interviews where it was needed. Missing values were imputed by data mining techniques. Fifteen factors were analyzed. Survival was addressed as a dependent variable. Then, the predictive model was designed by combining both genetic algorithm and logistic regression. Matlab 2014 software was used to combine them. Of the 277 patients, only survival of 80 patients was available whose data were used for designing the predictive model. Mean ?SD of missing values for each patient was 4.43?.41 combined predictive model achieved 72.57% accuracy. Sex, birth year, age at diagnosis time, age at diagnosis time of patients' family, family history of gastric cancer, and family history of other gastrointestinal cancers were six parameters associated with patient survival. The study revealed that imputing missing values by data mining techniques have a good accuracy. And it also revealed six parameters extracted by genetic algorithm effect on the survival of patients with gastric cancer. Our combined predictive model, with a good accuracy, is appropriate to forecast the survival of patients suffering from Gastric cancer. So, we suggest policy makers and specialists to apply it for prediction of patients' survival.

  8. Mean exit time and survival probability within the CTRW formalism

    Science.gov (United States)

    Montero, M.; Masoliver, J.

    2007-05-01

    An intense research on financial market microstructure is presently in progress. Continuous time random walks (CTRWs) are general models capable to capture the small-scale properties that high frequency data series show. The use of CTRW models in the analysis of financial problems is quite recent and their potentials have not been fully developed. Here we present two (closely related) applications of great interest in risk control. In the first place, we will review the problem of modelling the behaviour of the mean exit time (MET) of a process out of a given region of fixed size. The surveyed stochastic processes are the cumulative returns of asset prices. The link between the value of the MET and the timescale of the market fluctuations of a certain degree is crystal clear. In this sense, MET value may help, for instance, in deciding the optimal time horizon for the investment. The MET is, however, one among the statistics of a distribution of bigger interest: the survival probability (SP), the likelihood that after some lapse of time a process remains inside the given region without having crossed its boundaries. The final part of the manuscript is devoted to the study of this quantity. Note that the use of SPs may outperform the standard “Value at Risk" (VaR) method for two reasons: we can consider other market dynamics than the limited Wiener process and, even in this case, a risk level derived from the SP will ensure (within the desired quintile) that the quoted value of the portfolio will not leave the safety zone. We present some preliminary theoretical and applied results concerning this topic.

  9. Effect of liquid nitrogen storage time on the survival and ...

    African Journals Online (AJOL)

    Investigations were undertaken on the effect of liquid nitrogen (LN) storage time on survival and regeneration of somatic embryos of cocoa (Theobroma cacao l.). Somatic embryos from different cocoa genotypes (AMAZ 3-2, AMAZ 10-1, AMAZ 12, SIAL 93, and IMC 14) at 15.45% moisture content were cryopreserved in LN ...

  10. Effect of fibrinolysis inhibitors on survival time of irradiated rats

    International Nuclear Information System (INIS)

    Smok, W.

    1988-01-01

    The possibilities of alleviation of the gastrointestinal syndrome of acute radiation sickness by modification of haemorrhagic diathesis using EACA and traskolan were studied. A significant prolongation of the mean survival time was obtained in the irradiated rats treated with EACA. 7 tabs., 10 refs. (author)

  11. Repair models of cell survival and corresponding computer program for survival curve fitting

    International Nuclear Information System (INIS)

    Shen Xun; Hu Yiwei

    1992-01-01

    Some basic concepts and formulations of two repair models of survival, the incomplete repair (IR) model and the lethal-potentially lethal (LPL) model, are introduced. An IBM-PC computer program for survival curve fitting with these models was developed and applied to fit the survivals of human melanoma cells HX118 irradiated at different dose rates. Comparison was made between the repair models and two non-repair models, the multitar get-single hit model and the linear-quadratic model, in the fitting and analysis of the survival-dose curves. It was shown that either IR model or LPL model can fit a set of survival curves of different dose rates with same parameters and provide information on the repair capacity of cells. These two mathematical models could be very useful in quantitative study on the radiosensitivity and repair capacity of cells

  12. Sex-related time-dependent variations in post-stroke survival-evidence of a female stroke survival advantage

    DEFF Research Database (Denmark)

    Olsen, Tom Skyhøj; Dehlendorff, Christian; Andersen, Klaus Kaae

    2007-01-01

    the influence of gender on post-stroke mortality, from the time of admission through the subsequent years until death or censoring ( mean follow-up time: 538 days). All patients underwent an evaluation including stroke severity, computed tomography and cardiovascular risk factors. Independent predictors......Background: Women live longer than men, yet most studies show that gender has no influence on survival after stroke. Methods: A registry was started in 2001, with the aim of registering all hospitalized stroke patients in Denmark, and it now holds 39,484 patients of which 48% are female. We studied...... of death were identified by means of a survival model based on 22,222 individuals with a complete data set. Results: Females were older and had severer stroke. Interestingly, the risk of death between genders was time dependent. The female/male stroke mortality rate favoured women from the first day...

  13. Standard model group: Survival of the fittest

    Science.gov (United States)

    Nielsen, H. B.; Brene, N.

    1983-09-01

    The essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some "world (gauge) group". We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapses is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property.

  14. Standard model group: survival of the fittest

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, H.B. (Niels Bohr Inst., Copenhagen (Denmark); Nordisk Inst. for Teoretisk Atomfysik, Copenhagen (Denmark)); Brene, N. (Niels Bohr Inst., Copenhagen (Denmark))

    1983-09-19

    The essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapse is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property.

  15. Standard model group: survival of the fittest

    International Nuclear Information System (INIS)

    Nielsen, H.B.; Brene, N.

    1983-01-01

    Th essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapse is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property. (orig.)

  16. Standard model group survival of the fittest

    International Nuclear Information System (INIS)

    Nielsen, H.B.; Brene, N.

    1983-02-01

    The essential content of this note is related to random dynamics. The authors speculate that the world seen through a sub Planck scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. It is seen that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. It is further argued that the subgroup which survives as the end product of a possible chain of collapses is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property. (Auth.)

  17. The survival time of chocolates on hospital wards: covert observational study.

    Science.gov (United States)

    Gajendragadkar, Parag R; Moualed, Daniel J; Nicolson, Phillip L R; Adjei, Felicia D; Cakebread, Holly E; Duehmke, Rudolf M; Martin, Claire A

    2013-12-14

    To quantify the consumption of chocolates in a hospital ward environment. Multicentre, prospective, covert observational study. Four wards at three hospitals (where the authors worked) within the United Kingdom. Boxes of Quality Street (Nestlé) and Roses (Cadbury) on the ward and anyone eating these chocolates. Observers covertly placed two 350 g boxes of Quality Street and Roses chocolates on each ward (eight boxes were used in the study containing a total of 258 individual chocolates). These boxes were kept under continuous covert surveillance, with the time recorded when each chocolate was eaten. Median survival time of a chocolate. 191 out of 258 (74%) chocolates were observed being eaten. The mean total observation period was 254 minutes (95% confidence interval 179 to 329). The median survival time of a chocolate was 51 minutes (39 to 63). The model of chocolate consumption was non-linear, with an initial rapid rate of consumption that slowed with time. An exponential decay model best fitted these findings (model R(2)=0.844, P<0.001), with a survival half life (time taken for 50% of the chocolates to be eaten) of 99 minutes. The mean time taken to open a box of chocolates from first appearance on the ward was 12 minutes (95% confidence interval 0 to 24). Quality Street chocolates survived longer than Roses chocolates (hazard ratio for survival of Roses v Quality Street 0.70, 95% confidence interval 0.53 to 0.93, P=0.014). The highest percentages of chocolates were consumed by healthcare assistants (28%) and nurses (28%), followed by doctors (15%). From our observational study, chocolate survival in a hospital ward was relatively short, and was modelled well by an exponential decay model. Roses chocolates were preferentially consumed to Quality Street chocolates in a ward setting. Chocolates were consumed primarily by healthcare assistants and nurses, followed by doctors. Further practical studies are needed.

  18. Comparison of Cox and Gray's survival models in severe sepsis

    DEFF Research Database (Denmark)

    Kasal, Jan; Andersen, Zorana Jovanovic; Clermont, Gilles

    2004-01-01

    Although survival is traditionally modeled using Cox proportional hazards modeling, this approach may be inappropriate in sepsis, in which the proportional hazards assumption does not hold. Newer, more flexible models, such as Gray's model, may be more appropriate....

  19. What affects local community hospitals' survival in turbulent times?

    Science.gov (United States)

    Chiang, Hung-Che; Wang, Shiow-Ing

    2015-06-01

    Hospital closures became a prevalent phenomenon in Taiwan after the implementation of a national health insurance program. A wide range of causes contributes to the viability of hospitals, but little is known about the situation under universal coverage health systems. The purpose of present study is to recognize the factors that may contribute to hospital survival under the universal coverage health system. This is a retrospective case-control study. Local community hospitals that contracted with the Bureau of National Health Insurance in 1998 and remained open during the period 1998-2011 are the designated cases. Controls are local community hospitals that closed during the same period. Using longitudinal representative health claim data, 209 local community hospitals that closed during 1998-2011 were compared with 165 that remained open. Variables related to institutional characteristics, degree of competition, characteristics of patients and financial performance were analyzed by logistic regression models. Hospitals' survival was positively related to specialty hospital, the number of respiratory care beds, the physician to population ratio, the number of clinics in the same region, a highly competitive market and the occupancy rate of elderly patients in the hospital. Teaching hospitals, investor-owned hospitals, the provision of obstetrics services or home care, and the number of medical centers or other local community hospitals may jeopardize the chance of survival. Factors-enhanced local hospitals to survive under the universal coverage health system have been identified. Hospital managers could manipulate these findings and adapt strategies for subsistence. © The Author 2015. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

  20. Analyzing sickness absence with statistical models for survival data

    DEFF Research Database (Denmark)

    Christensen, Karl Bang; Andersen, Per Kragh; Smith-Hansen, Lars

    2007-01-01

    OBJECTIVES: Sickness absence is the outcome in many epidemiologic studies and is often based on summary measures such as the number of sickness absences per year. In this study the use of modern statistical methods was examined by making better use of the available information. Since sickness...... absence data deal with events occurring over time, the use of statistical models for survival data has been reviewed, and the use of frailty models has been proposed for the analysis of such data. METHODS: Three methods for analyzing data on sickness absences were compared using a simulation study...... involving the following: (i) Poisson regression using a single outcome variable (number of sickness absences), (ii) analysis of time to first event using the Cox proportional hazards model, and (iii) frailty models, which are random effects proportional hazards models. Data from a study of the relation...

  1. Survival times of pre-1950 US women radium dial workers

    International Nuclear Information System (INIS)

    Stehney, A.F.

    1994-01-01

    Survival times of US women radium dial workers to the end of 1989 were examined by life table methods. Included were 1301 women rust employed before 1930 and 1242 first employed in 1930-1949. Expected numbers of deaths were estimated from age- and time-specific death rates for US white females. In the early group, 85 deaths from the well-known radium-induced cancers - bone sarcomas and head carcinomas - were observed, but only 724 deaths from aH other causes were observed vs 755 expected. Life shortening (±S.E.) of 1.8 ±0.5 y compared to the general population of US white females was calculated from the time distribution of all deaths in the pre-1930 group. In the 1930--1949 group, 350 deaths were observed vs 343 expected and no bone sarcomas or head carcinomas occurred. Among women who survived at least 2 y after rust measurement of body radium, a significant excess of observed vs expected deaths was found only for radium intakes greater than 1.85 MBq of 226 Ra + 228 Ra, and no trend of deaths or reduction of life expectancy was found with length of employment

  2. Causal inference for long-term survival in randomised trials with treatment switching: Should re-censoring be applied when estimating counterfactual survival times?

    OpenAIRE

    Latimer, N.R.; White, I.R.; Abrams, K.R.; Sieburt, U.

    2017-01-01

    Treatment switching often has a crucial impact on estimates of effectiveness and cost-effectiveness of new oncology treatments. Rank preserving structural failure time models (RPSFTM) and two-stage estimation (TSE) methods estimate ‘counterfactual’ (i.e. had there been no switching) survival times and incorporate re-censoring to guard against informative censoring in the counterfactual dataset. However, re-censoring causes a loss of longer term survival information which is problematic when e...

  3. Measurement of Survival Time in Brachionus Rotifers: Synchronization of Maternal Conditions.

    Science.gov (United States)

    Kaneko, Gen; Yoshinaga, Tatsuki; Gribble, Kristin E; Welch, David M; Ushio, Hideki

    2016-07-22

    Rotifers are microscopic cosmopolitan zooplankton used as models in ecotoxicological and aging studies due to their several advantages such as short lifespan, ease of culture, and parthenogenesis that enables clonal culture. However, caution is required when measuring their survival time as it is affected by maternal age and maternal feeding conditions. Here we provide a protocol for powerful and reproducible measurement of the survival time in Brachionus rotifers following a careful synchronization of culture conditions over several generations. Empirically, poor synchronization results in early mortality and a gradual decrease in survival rate, thus resulting in weak statistical power. Indeed, under such conditions, calorie restriction (CR) failed to significantly extend the lifespan of B. plicatilis although CR-induced longevity has been demonstrated with well-synchronized rotifer samples in past and present studies. This protocol is probably useful for other invertebrate models, including the fruitfly Drosophila melanogaster and the nematode Caenorhabditis elegans, because maternal age effects have also been reported in these species.

  4. Increasing survival time decreases the cost-effectiveness of using "test & treat'' to eliminate HIV epidemics.

    Science.gov (United States)

    Wagner, Bradley G; Coburn, Brian J; Blower, Sally

    2013-01-01

    Treating HIV-infected individuals reduces their viral load, consequently increasing their survival time and decreasing their infectivity. It has been proposed that universal testing and treatment (i.e., universal "test & treat'') could lead to HIV elimination and would be extremely cost-effective. It is now being debated whether to use a universal "test & treat'' approach in the "real-world'' as a prevention strategy to control HIV epidemics. However current modeling predictions of the impact, and cost-effectiveness, of universal `"est & treat'' strategies are based on an unrealistically short survival time for treated individuals. Here we use mathematical modeling and a longer, more realistic, survival time. We model the potential impact of a universal "test & treat'' strategy in South Africa. Our results show that increasing the length of the survival time on treatment, although beneficial to individuals, reduces the probability of eliminating HIV and decreases the cost-effectiveness of using universal "test & treat'' strategies. Therefore our results show that individual-level benefits and public health benefits will conflict when using "test &treat'' strategies to reduce HIV transmission.

  5. Modeling Complex Time Limits

    Directory of Open Access Journals (Sweden)

    Oleg Svatos

    2013-01-01

    Full Text Available In this paper we analyze complexity of time limits we can find especially in regulated processes of public administration. First we review the most popular process modeling languages. There is defined an example scenario based on the current Czech legislature which is then captured in discussed process modeling languages. Analysis shows that the contemporary process modeling languages support capturing of the time limit only partially. This causes troubles to analysts and unnecessary complexity of the models. Upon unsatisfying results of the contemporary process modeling languages we analyze the complexity of the time limits in greater detail and outline lifecycles of a time limit using the multiple dynamic generalizations pattern. As an alternative to the popular process modeling languages there is presented PSD process modeling language, which supports the defined lifecycles of a time limit natively and therefore allows keeping the models simple and easy to understand.

  6. The time dependent association of adrenaline administration and survival from out-of-hospital cardiac arrest.

    Science.gov (United States)

    Ewy, Gordon A; Bobrow, Bentley J; Chikani, Vatsal; Sanders, Arthur B; Otto, Charles W; Spaite, Daniel W; Kern, Karl B

    2015-11-01

    Recommended for decades, the therapeutic value of adrenaline (epinephrine) in the resuscitation of patients with out-of-hospital cardiac arrest (OHCA) is controversial. To investigate the possible time-dependent outcomes associated with adrenaline administration by Emergency Medical Services personnel (EMS). A retrospective analysis of prospectively collected data from a near statewide cardiac resuscitation database between 1 January 2005 and 30 November 2013. Multivariable logistic regression was used to analyze the effect of the time interval between EMS dispatch and the initial dose of adrenaline on survival. The primary endpoints were survival to hospital discharge and favourable neurologic outcome. Data from 3469 patients with witnessed OHCA were analyzed. Their mean age was 66.3 years and 69% were male. An initially shockable rhythm was present in 41.8% of patients. Based on a multivariable logistic regression model with initial adrenaline administration time interval (AATI) from EMS dispatch as the covariate, survival was greatest when adrenaline was administered very early but decreased rapidly with increasing (AATI); odds ratio 0.94 (95% Confidence Interval (CI) 0.92-0.97). The AATI had no significant effect on good neurological outcome (OR=0.96, 95% CI=0.90-1.02). In patients with OHCA, survival to hospital discharge was greater in those treated early with adrenaline by EMS especially in the subset of patients with a shockable rhythm. However survival rapidly decreased with increasing adrenaline administration time intervals (AATI). Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  7. The Application of Extended Cox Proportional Hazard Method for Estimating Survival Time of Breast Cancer

    Science.gov (United States)

    Husain, Hartina; Astuti Thamrin, Sri; Tahir, Sulaiha; Mukhlisin, Ahmad; Mirna Apriani, M.

    2018-03-01

    Breast cancer is one type of cancer that is the leading cause of death worldwide. This study aims to model the factors that affect the survival time and rate of cure of breast cancer patients. The extended cox model, which is a modification of the proportional hazard cox model in which the proportional hazard assumptions are not met, is used in this study. The maximum likelihood estimation approach is used to estimate the parameters of the model. This method is then applied to medical record data of breast cancer patient in 2011-2016, which is taken from Hasanuddin University Education Hospital. The results obtained indicate that the factors that affect the survival time of breast cancer patients are malignancy and leukocyte levels.

  8. Stage-specific predictive models for breast cancer survivability.

    Science.gov (United States)

    Kate, Rohit J; Nadig, Ramya

    2017-01-01

    Survivability rates vary widely among various stages of breast cancer. Although machine learning models built in past to predict breast cancer survivability were given stage as one of the features, they were not trained or evaluated separately for each stage. To investigate whether there are differences in performance of machine learning models trained and evaluated across different stages for predicting breast cancer survivability. Using three different machine learning methods we built models to predict breast cancer survivability separately for each stage and compared them with the traditional joint models built for all the stages. We also evaluated the models separately for each stage and together for all the stages. Our results show that the most suitable model to predict survivability for a specific stage is the model trained for that particular stage. In our experiments, using additional examples of other stages during training did not help, in fact, it made it worse in some cases. The most important features for predicting survivability were also found to be different for different stages. By evaluating the models separately on different stages we found that the performance widely varied across them. We also demonstrate that evaluating predictive models for survivability on all the stages together, as was done in the past, is misleading because it overestimates performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. Repair-misrepair model of cell survival

    International Nuclear Information System (INIS)

    Tobias, C.A.; Blakely, E.A.; Ngo, F.Q.H.

    1980-01-01

    During the last three years a new model, the repair-misrepair model (RMR) has been proposed, to interpret radiobiological experiments with heavy ions. In using the RMR model it became apparent that some of its features are suitable for handling the effects produced by a variety of environmental agents in addition to ionizing radiation. Two separate sequences of events are assumed to take place in an irradiated cell. The first sequence begins with an initial energy transfer consisting of ionizations and excitations, culminating via fast secondary physical and chemical processes in established macromolecular lesions in essential cell structures. The second sequence contains the responses of the cell to the lesions and consists of the processes of recognition and molecular repair. In normal cells there exists one repair process or at most a few enzymatic repair processes for each essential macromolecular lesion. The enzymatic repair processes may last for hours and minutes, and can be separated in time from the initial physicochemical and later genetic phases

  10. Association of Bystander Cardiopulmonary Resuscitation and Survival According to Ambulance Response Times After Out-of-Hospital Cardiac Arrest.

    Science.gov (United States)

    Rajan, Shahzleen; Wissenberg, Mads; Folke, Fredrik; Hansen, Steen Møller; Gerds, Thomas A; Kragholm, Kristian; Hansen, Carolina Malta; Karlsson, Lena; Lippert, Freddy K; Køber, Lars; Gislason, Gunnar H; Torp-Pedersen, Christian

    2016-12-20

    Bystander-initiated cardiopulmonary resuscitation (CPR) increases patient survival after out-of-hospital cardiac arrest, but it is unknown to what degree bystander CPR remains positively associated with survival with increasing time to potential defibrillation. The main objective was to examine the association of bystander CPR with survival as time to advanced treatment increases. We studied 7623 out-of-hospital cardiac arrest patients between 2005 and 2011, identified through the nationwide Danish Cardiac Arrest Registry. Multiple logistic regression analysis was used to examine the association between time from 911 call to emergency medical service arrival (response time) and survival according to whether bystander CPR was provided (yes or no). Reported are 30-day survival chances with 95% bootstrap confidence intervals. With increasing response times, adjusted 30-day survival chances decreased for both patients with bystander CPR and those without. However, the contrast between the survival chances of patients with versus without bystander CPR increased over time: within 5 minutes, 30-day survival was 14.5% (95% confidence interval [CI]: 12.8-16.4) versus 6.3% (95% CI: 5.1-7.6), corresponding to 2.3 times higher chances of survival associated with bystander CPR; within 10 minutes, 30-day survival chances were 6.7% (95% CI: 5.4-8.1) versus 2.2% (95% CI: 1.5-3.1), corresponding to 3.0 times higher chances of 30-day survival associated with bystander CPR. The contrast in 30-day survival became statistically insignificant when response time was >13 minutes (bystander CPR vs no bystander CPR: 3.7% [95% CI: 2.2-5.4] vs 1.5% [95% CI: 0.6-2.7]), but 30-day survival was still 2.5 times higher associated with bystander CPR. Based on the model and Danish out-of-hospital cardiac arrest statistics, an additional 233 patients could potentially be saved annually if response time was reduced from 10 to 5 minutes and 119 patients if response time was reduced from 7 (the median

  11. Developing a scalable modeling architecture for studying survivability technologies

    Science.gov (United States)

    Mohammad, Syed; Bounker, Paul; Mason, James; Brister, Jason; Shady, Dan; Tucker, David

    2006-05-01

    To facilitate interoperability of models in a scalable environment, and provide a relevant virtual environment in which Survivability technologies can be evaluated, the US Army Research Development and Engineering Command (RDECOM) Modeling Architecture for Technology Research and Experimentation (MATREX) Science and Technology Objective (STO) program has initiated the Survivability Thread which will seek to address some of the many technical and programmatic challenges associated with the effort. In coordination with different Thread customers, such as the Survivability branches of various Army labs, a collaborative group has been formed to define the requirements for the simulation environment that would in turn provide them a value-added tool for assessing models and gauge system-level performance relevant to Future Combat Systems (FCS) and the Survivability requirements of other burgeoning programs. An initial set of customer requirements has been generated in coordination with the RDECOM Survivability IPT lead, through the Survivability Technology Area at RDECOM Tank-automotive Research Development and Engineering Center (TARDEC, Warren, MI). The results of this project are aimed at a culminating experiment and demonstration scheduled for September, 2006, which will include a multitude of components from within RDECOM and provide the framework for future experiments to support Survivability research. This paper details the components with which the MATREX Survivability Thread was created and executed, and provides insight into the capabilities currently demanded by the Survivability faculty within RDECOM.

  12. Partitioning of excess mortality in population-based cancer patient survival studies using flexible parametric survival models

    Directory of Open Access Journals (Sweden)

    Eloranta Sandra

    2012-06-01

    Full Text Available Abstract Background Relative survival is commonly used for studying survival of cancer patients as it captures both the direct and indirect contribution of a cancer diagnosis on mortality by comparing the observed survival of the patients to the expected survival in a comparable cancer-free population. However, existing methods do not allow estimation of the impact of isolated conditions (e.g., excess cardiovascular mortality on the total excess mortality. For this purpose we extend flexible parametric survival models for relative survival, which use restricted cubic splines for the baseline cumulative excess hazard and for any time-dependent effects. Methods In the extended model we partition the excess mortality associated with a diagnosis of cancer through estimating a separate baseline excess hazard function for the outcomes under investigation. This is done by incorporating mutually exclusive background mortality rates, stratified by the underlying causes of death reported in the Swedish population, and by introducing cause of death as a time-dependent effect in the extended model. This approach thereby enables modeling of temporal trends in e.g., excess cardiovascular mortality and remaining cancer excess mortality simultaneously. Furthermore, we illustrate how the results from the proposed model can be used to derive crude probabilities of death due to the component parts, i.e., probabilities estimated in the presence of competing causes of death. Results The method is illustrated with examples where the total excess mortality experienced by patients diagnosed with breast cancer is partitioned into excess cardiovascular mortality and remaining cancer excess mortality. Conclusions The proposed method can be used to simultaneously study disease patterns and temporal trends for various causes of cancer-consequent deaths. Such information should be of interest for patients and clinicians as one way of improving prognosis after cancer is

  13. Connecting single-stock assessment models through correlated survival

    DEFF Research Database (Denmark)

    Albertsen, Christoffer Moesgaard; Nielsen, Anders; Thygesen, Uffe Høgsbro

    2017-01-01

    times. We propose a simple alternative. In three case studies each with two stocks, we improve the single-stock models, as measured by Akaike information criterion, by adding correlation in the cohort survival. To limit the number of parameters, the correlations are parameterized through...... the corresponding partial correlations. We consider six models where the partial correlation matrix between stocks follows a band structure ranging from independent assessments to complex correlation structures. Further, a simulation study illustrates the importance of handling correlated data sufficiently...... by investigating the coverage of confidence intervals for estimated fishing mortality. The results presented will allow managers to evaluate stock statuses based on a more accurate evaluation of model output uncertainty. The methods are directly implementable for stocks with an analytical assessment and do...

  14. Efficient estimation of semiparametric copula models for bivariate survival data

    KAUST Repository

    Cheng, Guang

    2014-01-01

    A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. In this paper, we obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data. We construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions. We show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2013 Elsevier Inc.

  15. SEMI-COMPETING RISKS ON A TRIVARIATE WEIBULL SURVIVAL MODEL

    Directory of Open Access Journals (Sweden)

    Jenq-Daw Lee

    2008-07-01

    Full Text Available A setting of a trivairate survival function using semi-competing risks concept is proposed, in which a terminal event can only occur after other events. The Stanford Heart Transplant data is reanalyzed using a trivariate Weibull distribution model with the proposed survival function.

  16. [Survival time of HIV/AIDS cases and related factors in Beijing, 1995-2015].

    Science.gov (United States)

    Li, Y; Wang, J; He, S F; Chen, J; Lu, H Y

    2017-11-10

    Objective: To analyze the survival time of HIV/AIDS cases and related factors in Beijing from 1995 to 2015. Methods: A retrospective cohort study was conducted to analyze the data of 12 874 HIV/AIDS cases. The data were collected from Chinese HIV/AIDS Comprehensive Information Management System. Life table method was applied to calculate the survival proportion, and Cox proportion hazard regression model were used to identify the factors related with survival time. Results: Among 12 874 HIV/AIDS cases, 303 (2.4%) died of AIDS related diseases; 9 346 (72.6%) received antiretroviral therapy. The average survival time was 226.5 months (95 %CI : 223.0-230.1), and the survival rates of 1, 5, 10, and 15 years were 98.2%, 96.4%, 93.2%, and 91.9% respectively. Multivariate Cox proportion hazard regression model showed that AIDS phase ( HR =1.439, 95 %CI : 1.041-1.989), heterosexual transmission ( HR =1.646, 95 %CI : 1.184-2.289), being married ( HR =2.186, 95 %CI : 1.510-3.164); older age (≥60 years) at diagnosis ( HR =6.608, 95 %CI : 3.546-12.316); lower CD(4)(+)T cell counts at diagnosis (<350 cells/μl) ( HR =8.711, 95 %CI : 5.757-13.181); receiving no antiretroviral therapy (ART) ( HR =18.223, 95 %CI : 13.317-24.937) were the high risk factors influencing the survival of AIDS patients compared with HIV phase, homosexual transmission, being unmarried, younger age (≤30 years), higher CD(4)(+)T cell count (≥350 cell/μl) and receiving ART. Conclusion: The average survival time of HIV/AIDS cases was 226.5 months after diagnoses. Receiving ART, higher CD(4)(+)T cell counts at the first test, HIV phase, younger age, being unmarried and the homosexual transmission were related to the longer survival time of HIV/AIDS cases. Receiving no ART, the lower CD(4)(+)T cell counts at the first test, AIDS phase, older age, being married and heterosexual transmission indicated higher risk of death due to AIDS.

  17. Re-evaluating neonatal-age models for ungulates: does model choice affect survival estimates?

    Directory of Open Access Journals (Sweden)

    Troy W Grovenburg

    Full Text Available New-hoof growth is regarded as the most reliable metric for predicting age of newborn ungulates, but variation in estimated age among hoof-growth equations that have been developed may affect estimates of survival in staggered-entry models. We used known-age newborns to evaluate variation in age estimates among existing hoof-growth equations and to determine the consequences of that variation on survival estimates. During 2001-2009, we captured and radiocollared 174 newborn (≤24-hrs old ungulates: 76 white-tailed deer (Odocoileus virginianus in Minnesota and South Dakota, 61 mule deer (O. hemionus in California, and 37 pronghorn (Antilocapra americana in South Dakota. Estimated age of known-age newborns differed among hoof-growth models and varied by >15 days for white-tailed deer, >20 days for mule deer, and >10 days for pronghorn. Accuracy (i.e., the proportion of neonates assigned to the correct age in aging newborns using published equations ranged from 0.0% to 39.4% in white-tailed deer, 0.0% to 3.3% in mule deer, and was 0.0% for pronghorns. Results of survival modeling indicated that variability in estimates of age-at-capture affected short-term estimates of survival (i.e., 30 days for white-tailed deer and mule deer, and survival estimates over a longer time frame (i.e., 120 days for mule deer. Conversely, survival estimates for pronghorn were not affected by estimates of age. Our analyses indicate that modeling survival in daily intervals is too fine a temporal scale when age-at-capture is unknown given the potential inaccuracies among equations used to estimate age of neonates. Instead, weekly survival intervals are more appropriate because most models accurately predicted ages within 1 week of the known age. Variation among results of neonatal-age models on short- and long-term estimates of survival for known-age young emphasizes the importance of selecting an appropriate hoof-growth equation and appropriately defining intervals (i

  18. Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

    International Nuclear Information System (INIS)

    Garzon, Benjamin; Emblem, Kyrre E.; Mouridsen, Kim; Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K.; Bjoernerud, Atle; Haaberg, Asta K.; Kvinnsland, Yngve

    2011-01-01

    Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

  19. Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

    Energy Technology Data Exchange (ETDEWEB)

    Garzon, Benjamin (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway)), email: benjamin.garzon@ntnu.no; Emblem, Kyrre E. (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway); Dept. of Radiology, MGH-HST AA Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (United States)); Mouridsen, Kim (Center of Functionally Integrative Neuroscience, Aarhus Univ., Aarhus (Denmark)); Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K. (Dept. of Radiology and Nuclear Medicine, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Bjoernerud, Atle (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Haaberg, Asta K. (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway); Dept. of Medical Imaging, St Olav' s Hospital, Trondheim (Norway)); Kvinnsland, Yngve (NordicImagingLab, Bergen (Norway))

    2011-11-15

    Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

  20. Survival analysis

    International Nuclear Information System (INIS)

    Badwe, R.A.

    1999-01-01

    The primary endpoint in the majority of the studies has been either disease recurrence or death. This kind of analysis requires a special method since all patients in the study experience the endpoint. The standard method for estimating such survival distribution is Kaplan Meier method. The survival function is defined as the proportion of individuals who survive beyond certain time. Multi-variate comparison for survival has been carried out with Cox's proportional hazard model

  1. Association of bystander cardiopulmonary resuscitation and survival according to ambulance response-times after out-of-hospital cardiac arrest

    DEFF Research Database (Denmark)

    Rajan, Shahzleen; Wissenberg, Mads; Folke, Fredrik

    2016-01-01

    30-day survival chances decreased for both patients with bystander CPR and those without. However, the contrast between the survival chances of patients with versus without bystander CPR increased over time: within 5 minutes, 30-day survival was 14.5% (95% confidence interval [CI]: 12.8-16.4) versus...... 6.3% (95% CI: 5.1-7.6), corresponding to 2.3 times higher chances of survival associated with bystander CPR; within 10 minutes, 30-day survival chances were 6.7% (95% CI: 5.4-8.1) versus 2.2% (95% CI: 1.5-3.1), corresponding to 3.0 times higher chances of 30-day survival associated with bystander...... CPR. The contrast in 30-day survival became statistically insignificant when response time was >13 minutes (bystander CPR vs no bystander CPR: 3.7% [95% CI: 2.2-5.4] vs 1.5% [95% CI: 0.6-2.7]), but 30-day survival was still 2.5 times higher associated with bystander CPR. Based on the model and Danish...

  2. The role of donor age and ischemic time on survival following orthotopic heart transplantation.

    Science.gov (United States)

    Del Rizzo, D F; Menkis, A H; Pflugfelder, P W; Novick, R J; McKenzie, F N; Boyd, W D; Kostuk, W J

    1999-04-01

    The advances in immunotherapy, along with a liberalization of eligibility criteria have contributed significantly to the ever increasing demand for donor organs. In an attempt to expand the donor pool, transplant programs are now accepting older donors as well as donors from more remote areas. The purpose of this study is to determine the effect of donor age and organ ischemic time on survival following orthotopic heart transplantation (OHT). From April 1981 to December 1996 372 adult patients underwent OHT at the University of Western Ontario. Cox proportional hazards models were used to identify predictors of outcome. Variables affecting survival were then entered into a stepwise logistic regression model to develop probability models for 30-day- and 1-year-mortality. The mean age of the recipient population was 45.6 +/- 12.3 years (range 18-64 years: 54 56 years). The majority (329 patients, 86.1%) were male and the most common indications for OHT were ischemic (n = 180) and idiopathic (n = 171) cardiomyopathy. Total ischemic time (TIT) was 202.4 +/- 84.5 minutes (range 47-457 minutes). In 86 donors TIT was under 2 hours while it was between 2 and 4 hours in 168, and more than 4 hours in 128 donors. Actuarial survival was 80%, 73%, and 55% at 1, 5, and 10 years respectively. By Cox proportional hazards models, recipient status (Status I-II vs III-IV; risk ratio 1.75; p = 0.003) and donor age, examined as either a continuous or categorical variable ([age or = 35; risk ratio 1.98; p or = 50; risk ratio 2.20; p or = 50; risk ratio 1.83; p 50 years (p = 0.009). By stepwise logistic regression analysis, a probability model for survival was then developed based on donor age, the interaction between donor age and ischemic time, and patient status. Improvements in myocardial preservation and peri-operative management may allow for the safe utilization of donor organs with prolonged ischemic times. Older donors are associated with decreased peri-operative and long

  3. Modelling bursty time series

    International Nuclear Information System (INIS)

    Vajna, Szabolcs; Kertész, János; Tóth, Bálint

    2013-01-01

    Many human-related activities show power-law decaying interevent time distribution with exponents usually varying between 1 and 2. We study a simple task-queuing model, which produces bursty time series due to the non-trivial dynamics of the task list. The model is characterized by a priority distribution as an input parameter, which describes the choice procedure from the list. We give exact results on the asymptotic behaviour of the model and we show that the interevent time distribution is power-law decaying for any kind of input distributions that remain normalizable in the infinite list limit, with exponents tunable between 1 and 2. The model satisfies a scaling law between the exponents of interevent time distribution (β) and autocorrelation function (α): α + β = 2. This law is general for renewal processes with power-law decaying interevent time distribution. We conclude that slowly decaying autocorrelation function indicates long-range dependence only if the scaling law is violated. (paper)

  4. Rubber dam may increase the survival time of dental restorations.

    Science.gov (United States)

    Keys, William; Carson, Susan J

    2017-03-01

    Data sourcesCochrane Oral Health's Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL), Medline, Embase, LILACS, SciELO, Chinese BioMedical Literature Database, VIP, China National Knowledge Infrastructure, ClinicalTrials.gov, World Health Organization International Clinical Trials Registry Platform, OpenGrey and Sciencepaper Online databases. Handsearches in a number of journals.Study selectionRandomised controlled trials, including split-mouth studies assessing the effects of rubber dam isolation for restorative treatments in dental patients.Data extraction and synthesisTwo review authors independently screened the results of the electronic searches, extracted data and assessed the risk of bias of the included studies.ResultsFour studies involving a total of 1,270 patients were included. The studies were at high risk of bias. One trial was excluded from the analysis due to inconsistencies in the presented data. Restorations had a significantly higher survival rate in the rubber dam isolation group compared to the cotton roll isolation group at six months in participants receiving composite restorative treatment of non-carious cervical lesions (risk ratio (RR) 1.19, 95% confidence interval (CI) 1.04 to 1.37, very low-quality evidence). The rubber dam group had a lower risk of failure at two years in children undergoing proximal atraumatic restorative treatment in primary molars (hazard ratio (HR) 0.80, 95% CI 0.66 to 0.97, very low-quality evidence). One trial reported limited data showing that rubber dam usage during fissure sealing might shorten the treatment time. None of the included studies mentioned adverse effects or reported the direct cost of the treatment, or the level of patient acceptance/satisfaction. There was also no evidence evaluating the effects of rubber dam usage on the quality of the restorations.ConclusionsWe found some very low-quality evidence, from single studies, suggesting that rubber dam usage in dental direct

  5. Models for cell survival with low LET radiation

    International Nuclear Information System (INIS)

    Payne, M.G.; Garrett, W.R.

    1975-01-01

    A model for cell survival under low LET irradiation was developed in which the cell is considered to have N 0 -independent sensitive sites, each of which can exist in either an undamaged state (state A) or one of two damaged states. Radiation can change the sensitive sites from the undamaged state to either of two damaged states. The first damaged state (state B) can either be repaired or be promoted on the second damaged state (state C), which is irreparable. The promotion from the first damaged state to the second can occur due to any of the following: (1) further radiation damage, (2) an abortive attempt to repair the site, or (3) the arrival at a part of the cell cycle where the damage is ''fixed.'' Subject to the further assumptions that radiation damage can occur either indirectly (i.e., through radiation products) or due to direct interaction, and that repair of the first damaged state is a one-step process, expressions can be derived for P(N/sub A/, N/sub B/,t) = probability that after time t a cell will have N/sub A/ sites in state A and N/sub B/ in state B. The problem of determining P(N/sub A/, N/sub B/, t) is formulated for arbitrary time dependences of the radiation field and of all rate coefficients. A large family of cell-survival models can be described by interpreting the sensitive sites in different ways and by making different choices of rate coefficients and of the combinations of numbers of sites in different states that will lead to cell death. (U.S.)

  6. Study on the effect of the survival time and the T cells in the discordant heart xenotransplantation produced by intrathymic inoculation with xenogeneic antigen using the model of pig to monkey

    International Nuclear Information System (INIS)

    Qu Jichen; Jiang Gening; Ding Jiaan

    2005-01-01

    Objective: This study was designed to investigate the effect of survival time and T cells on the delayed xenograft rejection caused by intrathymic injection of xenogeneic antigen in the discordant cardiac xenotransplantation, and to investigate the possibility of inducing the tolerance for cardiac xenografts. Methods: In this experiment, pig and monkey were, respectively, selected as donor and recipient. Donor and recipient were divided randomly into four groups. In the blank group (group A) recipients didn't accept any treatments but heart xenotransplantation; In the whole body irradiation (WBI) group (group B) 3 Gy ( 60 Co) was received on d30 before transplantation. In the intrathymic injection group (group C) monkeys were pretreated by the intrathymic injection of pig spleen cells (5 x 10 7 ) on d21 before transplantation, the other treatments were the same as that in group A. In the irradiation and intrathymic injection group (group D) monkeys were pretreated by WBI and the intrathymic injection of pig spleen cells at the time just as that in group B and group C. In every group, monkeys were performed heterotopic heart xenotransplantation in abdomen in order to observe the survival time of cardiac xenografts. Results: (1) Survival time of donor heart in group D (91.1 ± 22.8 h) was significantly longer than group B(42.56 ± 1.4 h) and group A (35.6 ± 2.2 h) (P 0.05). (3) The results of MLR showed that there is significant reduction in group D than in group A and B (P + and CD8+ T cells in peripheral blood, but pretreatment with IT and WBI can induce T cells immune 4 suppression or immune tolerance, that is similar to allotransplantation in the rodent. (2) Pretreatment with IT and WBI can induce T cells immune suppression or immune tolerance. (authors)

  7. Travel time reliability modeling.

    Science.gov (United States)

    2011-07-01

    This report includes three papers as follows: : 1. Guo F., Rakha H., and Park S. (2010), "A Multi-state Travel Time Reliability Model," : Transportation Research Record: Journal of the Transportation Research Board, n 2188, : pp. 46-54. : 2. Park S.,...

  8. Association between time to disease progression end points and overall survival in patients with neuroendocrine tumors

    Directory of Open Access Journals (Sweden)

    Singh S

    2014-08-01

    Full Text Available Simron Singh,1 Xufang Wang,2 Calvin HL Law1 1Sunnybrook Odette Cancer Center, University of Toronto, Toronto, ON, Canada; 2Novartis Oncology, Florham Park, NJ, USA Abstract: Overall survival can be difficult to determine for slowly progressing malignancies, such as neuroendocrine tumors. We investigated whether time to disease progression is positively associated with overall survival in patients with such tumors. A literature review identified 22 clinical trials in patients with neuroendocrine tumors that reported survival probabilities for both time to disease progression (progression-free survival and time to progression and overall survival. Associations between median time to disease progression and median overall survival and between treatment effects on time to disease progression and treatment effects on overall survival were analyzed using weighted least-squares regression. Median time to disease progression was significantly associated with median overall survival (coefficient 0.595; P=0.022. In the seven randomized studies identified, the risk reduction for time to disease progression was positively associated with the risk reduction for overall survival (coefficient on −ln[HR] 0.151; 95% confidence interval −0.843, 1.145; P=0.713. The significant association between median time to disease progression and median overall survival supports the assertion that time to disease progression is an alternative end point to overall survival in patients with neuroendocrine tumors. An apparent albeit not significant trend correlates treatment effects on time to disease progression and treatment effects on overall survival. Informal surveys of physicians’ perceptions are consistent with these concepts, although additional randomized trials are needed. Keywords: neuroendocrine tumors, progression-free survival, disease progression, mortality

  9. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    Science.gov (United States)

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

  10. Measuring survival time: a probability-based approach useful in healthcare decision-making.

    Science.gov (United States)

    2011-01-01

    In some clinical situations, the choice between treatment options takes into account their impact on patient survival time. Due to practical constraints (such as loss to follow-up), survival time is usually estimated using a probability calculation based on data obtained in clinical studies or trials. The two techniques most commonly used to estimate survival times are the Kaplan-Meier method and the actuarial method. Despite their limitations, they provide useful information when choosing between treatment options.

  11. A Log Logistic Survival Model Applied to Hypobaric Decompression Sickness

    Science.gov (United States)

    Conkin, Johnny

    2001-01-01

    Decompression sickness (DCS) is a complex, multivariable problem. A mathematical description or model of the likelihood of DCS requires a large amount of quality research data, ideas on how to define a decompression dose using physical and physiological variables, and an appropriate analytical approach. It also requires a high-performance computer with specialized software. I have used published DCS data to develop my decompression doses, which are variants of equilibrium expressions for evolved gas plus other explanatory variables. My analytical approach is survival analysis, where the time of DCS occurrence is modeled. My conclusions can be applied to simple hypobaric decompressions - ascents lasting from 5 to 30 minutes - and, after minutes to hours, to denitrogenation (prebreathing). They are also applicable to long or short exposures, and can be used whether the sufferer of DCS is at rest or exercising at altitude. Ultimately I would like my models to be applied to astronauts to reduce the risk of DCS during spacewalks, as well as to future spaceflight crews on the Moon and Mars.

  12. Statistical models and methods for reliability and survival analysis

    CERN Document Server

    Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo

    2013-01-01

    Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical

  13. Integrated survival analysis using an event-time approach in a Bayesian framework.

    Science.gov (United States)

    Walsh, Daniel P; Dreitz, Victoria J; Heisey, Dennis M

    2015-02-01

    Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

  14. Integrated survival analysis using an event-time approach in a Bayesian framework

    Science.gov (United States)

    Walsh, Daniel P.; Dreitz, VJ; Heisey, Dennis M.

    2015-01-01

    Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

  15. Impact of censoring on learning Bayesian networks in survival modelling.

    Science.gov (United States)

    Stajduhar, Ivan; Dalbelo-Basić, Bojana; Bogunović, Nikola

    2009-11-01

    Bayesian networks are commonly used for presenting uncertainty and covariate interactions in an easily interpretable way. Because of their efficient inference and ability to represent causal relationships, they are an excellent choice for medical decision support systems in diagnosis, treatment, and prognosis. Although good procedures for learning Bayesian networks from data have been defined, their performance in learning from censored survival data has not been widely studied. In this paper, we explore how to use these procedures to learn about possible interactions between prognostic factors and their influence on the variate of interest. We study how censoring affects the probability of learning correct Bayesian network structures. Additionally, we analyse the potential usefulness of the learnt models for predicting the time-independent probability of an event of interest. We analysed the influence of censoring with a simulation on synthetic data sampled from randomly generated Bayesian networks. We used two well-known methods for learning Bayesian networks from data: a constraint-based method and a score-based method. We compared the performance of each method under different levels of censoring to those of the naive Bayes classifier and the proportional hazards model. We did additional experiments on several datasets from real-world medical domains. The machine-learning methods treated censored cases in the data as event-free. We report and compare results for several commonly used model evaluation metrics. On average, the proportional hazards method outperformed other methods in most censoring setups. As part of the simulation study, we also analysed structural similarities of the learnt networks. Heavy censoring, as opposed to no censoring, produces up to a 5% surplus and up to 10% missing total arcs. It also produces up to 50% missing arcs that should originally be connected to the variate of interest. Presented methods for learning Bayesian networks from

  16. Parent-child communication and marijuana initiation: evidence using discrete-time survival analysis.

    Science.gov (United States)

    Nonnemaker, James M; Silber-Ashley, Olivia; Farrelly, Matthew C; Dench, Daniel

    2012-12-01

    This study supplements existing literature on the relationship between parent-child communication and adolescent drug use by exploring whether parental and/or adolescent recall of specific drug-related conversations differentially impact youth's likelihood of initiating marijuana use. Using discrete-time survival analysis, we estimated the hazard of marijuana initiation using a logit model to obtain an estimate of the relative risk of initiation. Our results suggest that parent-child communication about drug use is either not protective (no effect) or - in the case of youth reports of communication - potentially harmful (leading to increased likelihood of marijuana initiation). Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. In-season retail sales forecasting using survival models

    African Journals Online (AJOL)

    Retail sales forecasting, survival analysis, time series analysis, Holt's smoothing .... where fx(t) is the probability density function of the future lifetime, Tx, of a .... Adjustments were made to the shape of the smoothed mortality rates in light of new.

  18. Gap timing and the spectral timing model.

    Science.gov (United States)

    Hopson, J W

    1999-04-01

    A hypothesized mechanism underlying gap timing was implemented in the Spectral Timing Model [Grossberg, S., Schmajuk, N., 1989. Neural dynamics of adaptive timing and temporal discrimination during associative learning. Neural Netw. 2, 79-102] , a neural network timing model. The activation of the network nodes was made to decay in the absence of the timed signal, causing the model to shift its peak response time in a fashion similar to that shown in animal subjects. The model was then able to accurately simulate a parametric study of gap timing [Cabeza de Vaca, S., Brown, B., Hemmes, N., 1994. Internal clock and memory processes in aminal timing. J. Exp. Psychol.: Anim. Behav. Process. 20 (2), 184-198]. The addition of a memory decay process appears to produce the correct pattern of results in both Scalar Expectancy Theory models and in the Spectral Timing Model, and the fact that the same process should be effective in two such disparate models argues strongly that process reflects a true aspect of animal cognition.

  19. Discrete dynamic modeling of T cell survival signaling networks

    Science.gov (United States)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  20. Estimating the average treatment effect on survival based on observational data and using partly conditional modeling.

    Science.gov (United States)

    Gong, Qi; Schaubel, Douglas E

    2017-03-01

    Treatments are frequently evaluated in terms of their effect on patient survival. In settings where randomization of treatment is not feasible, observational data are employed, necessitating correction for covariate imbalances. Treatments are usually compared using a hazard ratio. Most existing methods which quantify the treatment effect through the survival function are applicable to treatments assigned at time 0. In the data structure of our interest, subjects typically begin follow-up untreated; time-until-treatment, and the pretreatment death hazard are both heavily influenced by longitudinal covariates; and subjects may experience periods of treatment ineligibility. We propose semiparametric methods for estimating the average difference in restricted mean survival time attributable to a time-dependent treatment, the average effect of treatment among the treated, under current treatment assignment patterns. The pre- and posttreatment models are partly conditional, in that they use the covariate history up to the time of treatment. The pre-treatment model is estimated through recently developed landmark analysis methods. For each treated patient, fitted pre- and posttreatment survival curves are projected out, then averaged in a manner which accounts for the censoring of treatment times. Asymptotic properties are derived and evaluated through simulation. The proposed methods are applied to liver transplant data in order to estimate the effect of liver transplantation on survival among transplant recipients under current practice patterns. © 2016, The International Biometric Society.

  1. Modeling survival: application of the Andersen-Gill model to Yellowstone grizzly bears

    Science.gov (United States)

    Johnson, Christopher J.; Boyce, Mark S.; Schwartz, Charles C.; Haroldson, Mark A.

    2004-01-01

     Wildlife ecologists often use the Kaplan-Meier procedure or Cox proportional hazards model to estimate survival rates, distributions, and magnitude of risk factors. The Andersen-Gill formulation (A-G) of the Cox proportional hazards model has seen limited application to mark-resight data but has a number of advantages, including the ability to accommodate left-censored data, time-varying covariates, multiple events, and discontinuous intervals of risks. We introduce the A-G model including structure of data, interpretation of results, and assessment of assumptions. We then apply the model to 22 years of radiotelemetry data for grizzly bears (Ursus arctos) of the Greater Yellowstone Grizzly Bear Recovery Zone in Montana, Idaho, and Wyoming, USA. We used Akaike's Information Criterion (AICc) and multi-model inference to assess a number of potentially useful predictive models relative to explanatory covariates for demography, human disturbance, and habitat. Using the most parsimonious models, we generated risk ratios, hypothetical survival curves, and a map of the spatial distribution of high-risk areas across the recovery zone. Our results were in agreement with past studies of mortality factors for Yellowstone grizzly bears. Holding other covariates constant, mortality was highest for bears that were subjected to repeated management actions and inhabited areas with high road densities outside Yellowstone National Park. Hazard models developed with covariates descriptive of foraging habitats were not the most parsimonious, but they suggested that high-elevation areas offered lower risks of mortality when compared to agricultural areas.

  2. Survival behavior in the cyclic Lotka-Volterra model with a randomly switching reaction rate

    Science.gov (United States)

    West, Robert; Mobilia, Mauro; Rucklidge, Alastair M.

    2018-02-01

    We study the influence of a randomly switching reproduction-predation rate on the survival behavior of the nonspatial cyclic Lotka-Volterra model, also known as the zero-sum rock-paper-scissors game, used to metaphorically describe the cyclic competition between three species. In large and finite populations, demographic fluctuations (internal noise) drive two species to extinction in a finite time, while the species with the smallest reproduction-predation rate is the most likely to be the surviving one (law of the weakest). Here we model environmental (external) noise by assuming that the reproduction-predation rate of the strongest species (the fastest to reproduce and predate) in a given static environment randomly switches between two values corresponding to more and less favorable external conditions. We study the joint effect of environmental and demographic noise on the species survival probabilities and on the mean extinction time. In particular, we investigate whether the survival probabilities follow the law of the weakest and analyze their dependence on the external noise intensity and switching rate. Remarkably, when, on average, there is a finite number of switches prior to extinction, the survival probability of the predator of the species whose reaction rate switches typically varies nonmonotonically with the external noise intensity (with optimal survival about a critical noise strength). We also outline the relationship with the case where all reaction rates switch on markedly different time scales.

  3. Survival behavior in the cyclic Lotka-Volterra model with a randomly switching reaction rate.

    Science.gov (United States)

    West, Robert; Mobilia, Mauro; Rucklidge, Alastair M

    2018-02-01

    We study the influence of a randomly switching reproduction-predation rate on the survival behavior of the nonspatial cyclic Lotka-Volterra model, also known as the zero-sum rock-paper-scissors game, used to metaphorically describe the cyclic competition between three species. In large and finite populations, demographic fluctuations (internal noise) drive two species to extinction in a finite time, while the species with the smallest reproduction-predation rate is the most likely to be the surviving one (law of the weakest). Here we model environmental (external) noise by assuming that the reproduction-predation rate of the strongest species (the fastest to reproduce and predate) in a given static environment randomly switches between two values corresponding to more and less favorable external conditions. We study the joint effect of environmental and demographic noise on the species survival probabilities and on the mean extinction time. In particular, we investigate whether the survival probabilities follow the law of the weakest and analyze their dependence on the external noise intensity and switching rate. Remarkably, when, on average, there is a finite number of switches prior to extinction, the survival probability of the predator of the species whose reaction rate switches typically varies nonmonotonically with the external noise intensity (with optimal survival about a critical noise strength). We also outline the relationship with the case where all reaction rates switch on markedly different time scales.

  4. Parameter resolution in two models for cell survival after radiation

    International Nuclear Information System (INIS)

    Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.

    1989-01-01

    The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)

  5. Survival prediction model for postoperative hepatocellular carcinoma patients.

    Science.gov (United States)

    Ren, Zhihui; He, Shasha; Fan, Xiaotang; He, Fangping; Sang, Wei; Bao, Yongxing; Ren, Weixin; Zhao, Jinming; Ji, Xuewen; Wen, Hao

    2017-09-01

    This study is to establish a predictive index (PI) model of 5-year survival rate for patients with hepatocellular carcinoma (HCC) after radical resection and to evaluate its prediction sensitivity, specificity, and accuracy.Patients underwent HCC surgical resection were enrolled and randomly divided into prediction model group (101 patients) and model evaluation group (100 patients). Cox regression model was used for univariate and multivariate survival analysis. A PI model was established based on multivariate analysis and receiver operating characteristic (ROC) curve was drawn accordingly. The area under ROC (AUROC) and PI cutoff value was identified.Multiple Cox regression analysis of prediction model group showed that neutrophil to lymphocyte ratio, histological grade, microvascular invasion, positive resection margin, number of tumor, and postoperative transcatheter arterial chemoembolization treatment were the independent predictors for the 5-year survival rate for HCC patients. The model was PI = 0.377 × NLR + 0.554 × HG + 0.927 × PRM + 0.778 × MVI + 0.740 × NT - 0.831 × transcatheter arterial chemoembolization (TACE). In the prediction model group, AUROC was 0.832 and the PI cutoff value was 3.38. The sensitivity, specificity, and accuracy were 78.0%, 80%, and 79.2%, respectively. In model evaluation group, AUROC was 0.822, and the PI cutoff value was well corresponded to the prediction model group with sensitivity, specificity, and accuracy of 85.0%, 83.3%, and 84.0%, respectively.The PI model can quantify the mortality risk of hepatitis B related HCC with high sensitivity, specificity, and accuracy.

  6. Pre-hospital transport times and survival for Hypotensive patients with penetrating thoracic trauma

    Directory of Open Access Journals (Sweden)

    Mamta Swaroop

    2013-01-01

    Full Text Available Background: Achieving definitive care within the "Golden Hour" by minimizing response times is a consistent goal of regional trauma systems . This study hypothesizes that in urban Level I Trauma Centers, shorter pre-hospital times would predict outcomes in penetrating thoracic injuries. Materials and Methods: A retrospective cohort study was performed using a statewide trauma registry for the years 1999-2003 . Total pre-hospital times were measured for urban victims of penetrating thoracic trauma. Crude and adjusted mortality rates were compared by pre-hospital time using STATA statistical software. Results: During the study period, 908 patients presented to the hospital after penetrating thoracic trauma, with 79% surviving . Patients with higher injury severity scores (ISS were transported more quickly. Injury severity scores (ISS ≥16 and emergency department (ED hypotension (systolic blood pressure, SBP <90 strongly predicted mortality (P < 0.05 for each . In a logistic regression model including age, race, and ISS, longer transport times for hypotensive patients were associated with higher mortality rates (all P values <0.05. This was seen most significantly when comparing patient transport times 0-15 min and 46-60 min (P < 0.001. Conclusion: In victims of penetrating thoracic trauma, more severely injured patients arrive at urban trauma centers sooner . Mortality is strongly predicted by injury severity, although shorter pre-hospital times are associated with improved survival . These results suggest that careful planning to optimize transport time-encompassing hospital capacity and existing resources, traffic patterns, and trauma incident densities may be beneficial in areas with a high burden of penetrating trauma.

  7. Surviving in a metastable de Sitter space-time

    International Nuclear Information System (INIS)

    Kashyap, Sitender Pratap; Mondal, Swapnamay; Sen, Ashoke; Verma, Mritunjay

    2015-01-01

    In a metastable de Sitter space any object has a finite life expectancy beyond which it undergoes vacuum decay. However, by spreading into different parts of the universe which will fall out of causal contact of each other in future, a civilization can increase its collective life expectancy, defined as the average time after which the last settlement disappears due to vacuum decay. We study in detail the collective life expectancy of two comoving objects in de Sitter space as a function of the initial separation, the horizon radius and the vacuum decay rate. We find that even with a modest initial separation, the collective life expectancy can reach a value close to the maximum possible value of 1.5 times that of the individual object if the decay rate is less than 1% of the expansion rate. Our analysis can be generalized to any number of objects, general trajectories not necessarily at rest in the comoving coordinates and general FRW space-time. As part of our analysis we find that in the current state of the universe dominated by matter and cosmological constant, the vacuum decay rate is increasing as a function of time due to accelerated expansion of the volume of the past light cone. Present decay rate is about 3.7 times larger than the average decay rate in the past and the final decay rate in the cosmological constant dominated epoch will be about 56 times larger than the average decay rate in the past. This considerably weakens the lower bound on the half-life of our universe based on its current age.

  8. Surviving in a metastable de Sitter space-time

    Energy Technology Data Exchange (ETDEWEB)

    Kashyap, Sitender Pratap; Mondal, Swapnamay [Harish-Chandra Research Institute,Chhatnag Road, Jhusi, Allahabad 211019 (India); Sen, Ashoke [Harish-Chandra Research Institute,Chhatnag Road, Jhusi, Allahabad 211019 (India); School of Physics, Korea Institute for Advanced Study,Seoul 130-722 (Korea, Republic of); Verma, Mritunjay [Harish-Chandra Research Institute,Chhatnag Road, Jhusi, Allahabad 211019 (India); International Centre for Theoretical Sciences,Malleshwaram, Bengaluru 560 012 (India)

    2015-09-21

    In a metastable de Sitter space any object has a finite life expectancy beyond which it undergoes vacuum decay. However, by spreading into different parts of the universe which will fall out of causal contact of each other in future, a civilization can increase its collective life expectancy, defined as the average time after which the last settlement disappears due to vacuum decay. We study in detail the collective life expectancy of two comoving objects in de Sitter space as a function of the initial separation, the horizon radius and the vacuum decay rate. We find that even with a modest initial separation, the collective life expectancy can reach a value close to the maximum possible value of 1.5 times that of the individual object if the decay rate is less than 1% of the expansion rate. Our analysis can be generalized to any number of objects, general trajectories not necessarily at rest in the comoving coordinates and general FRW space-time. As part of our analysis we find that in the current state of the universe dominated by matter and cosmological constant, the vacuum decay rate is increasing as a function of time due to accelerated expansion of the volume of the past light cone. Present decay rate is about 3.7 times larger than the average decay rate in the past and the final decay rate in the cosmological constant dominated epoch will be about 56 times larger than the average decay rate in the past. This considerably weakens the lower bound on the half-life of our universe based on its current age.

  9. Adjuvant Radiation Therapy Treatment Time Impacts Overall Survival in Gastric Cancer

    International Nuclear Information System (INIS)

    McMillan, Matthew T.; Ojerholm, Eric; Roses, Robert E.; Plastaras, John P.; Metz, James M.; Mamtani, Ronac; Karakousis, Giorgos C.; Fraker, Douglas L.; Drebin, Jeffrey A.; Stripp, Diana; Ben-Josef, Edgar; Datta, Jashodeep

    2015-01-01

    Purpose: Prolonged radiation therapy treatment time (RTT) is associated with worse survival in several tumor types. This study investigated whether delays during adjuvant radiation therapy impact overall survival (OS) in gastric cancer. Methods and Materials: The National Cancer Data Base was queried for patients with resected gastric cancer who received adjuvant radiation therapy with National Comprehensive Cancer Network–recommended doses (45 or 50.4 Gy) between 1998 and 2006. RTT was classified as standard (45 Gy: 33-36 days, 50.4 Gy: 38-41 days) or prolonged (45 Gy: >36 days, 50.4 Gy: >41 days). Cox proportional hazards models evaluated the association between the following factors and OS: RTT, interval from surgery to radiation therapy initiation, interval from surgery to radiation therapy completion, radiation therapy dose, demographic/pathologic and operative factors, and other elements of adjuvant multimodality therapy. Results: Of 1591 patients, RTT was delayed in 732 (46%). Factors associated with prolonged RTT were non-private health insurance (OR 1.3, P=.005) and treatment at non-academic facilities (OR 1.2, P=.045). Median OS and 5-year actuarial survival were significantly worse in patients with prolonged RTT compared with standard RTT (36 vs 51 months, P=.001; 39 vs 47%, P=.005); OS worsened with each cumulative week of delay (P<.0004). On multivariable analysis, prolonged RTT was associated with inferior OS (hazard ratio 1.2, P=.002); the intervals from surgery to radiation therapy initiation or completion were not. Prolonged RTT was particularly detrimental in patients with node positivity, inadequate nodal staging (<15 nodes examined), and those undergoing a cycle of chemotherapy before chemoradiation therapy. Conclusions: Delays during adjuvant radiation therapy appear to negatively impact survival in gastric cancer. Efforts to minimize cumulative interruptions to <7 days should be considered

  10. Adjuvant Radiation Therapy Treatment Time Impacts Overall Survival in Gastric Cancer

    Energy Technology Data Exchange (ETDEWEB)

    McMillan, Matthew T. [Department of Radiation Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Ojerholm, Eric [Department of Radiation Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Roses, Robert E., E-mail: Robert.Roses@uphs.upenn.edu [Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Plastaras, John P.; Metz, James M. [Department of Radiation Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Mamtani, Ronac [Department of Hematology/Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Karakousis, Giorgos C.; Fraker, Douglas L.; Drebin, Jeffrey A. [Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Stripp, Diana; Ben-Josef, Edgar [Department of Radiation Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Datta, Jashodeep [Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States)

    2015-10-01

    Purpose: Prolonged radiation therapy treatment time (RTT) is associated with worse survival in several tumor types. This study investigated whether delays during adjuvant radiation therapy impact overall survival (OS) in gastric cancer. Methods and Materials: The National Cancer Data Base was queried for patients with resected gastric cancer who received adjuvant radiation therapy with National Comprehensive Cancer Network–recommended doses (45 or 50.4 Gy) between 1998 and 2006. RTT was classified as standard (45 Gy: 33-36 days, 50.4 Gy: 38-41 days) or prolonged (45 Gy: >36 days, 50.4 Gy: >41 days). Cox proportional hazards models evaluated the association between the following factors and OS: RTT, interval from surgery to radiation therapy initiation, interval from surgery to radiation therapy completion, radiation therapy dose, demographic/pathologic and operative factors, and other elements of adjuvant multimodality therapy. Results: Of 1591 patients, RTT was delayed in 732 (46%). Factors associated with prolonged RTT were non-private health insurance (OR 1.3, P=.005) and treatment at non-academic facilities (OR 1.2, P=.045). Median OS and 5-year actuarial survival were significantly worse in patients with prolonged RTT compared with standard RTT (36 vs 51 months, P=.001; 39 vs 47%, P=.005); OS worsened with each cumulative week of delay (P<.0004). On multivariable analysis, prolonged RTT was associated with inferior OS (hazard ratio 1.2, P=.002); the intervals from surgery to radiation therapy initiation or completion were not. Prolonged RTT was particularly detrimental in patients with node positivity, inadequate nodal staging (<15 nodes examined), and those undergoing a cycle of chemotherapy before chemoradiation therapy. Conclusions: Delays during adjuvant radiation therapy appear to negatively impact survival in gastric cancer. Efforts to minimize cumulative interruptions to <7 days should be considered.

  11. Survival Times of Meter-Sized Rock Boulders on the Surface of Airless Bodies

    Science.gov (United States)

    Basilevsky, A. T.; Head, J. W.; Horz, F.; Ramsley, K.

    2015-01-01

    This study considers the survival times of meter-sized rock boulders on the surfaces of several airless bodies. As the starting point, we employ estimates of the survival times of such boulders on the surface of the Moon by[1], then discuss the role of destruction due to day-night temperature cycling, consider the meteorite bombardment environment on the considered bodies in terms of projectile flux and velocities and finally estimate the survival times. Survival times of meter-sized rocks on lunar surface: The survival times of hand specimen-sized rocks exposed to the lunar surface environment were estimated based on experiments modeling the destruction of rocks by meteorite impacts, combined with measurements of the lunar surface meteorite flux, (e.g.,[2]). For estimations of the survival times of meter-sized lunar boulders, [1] suggested a different approach based on analysis of the spatial density of boulders on the rims of small lunar craters of known absolute age. It was found that for a few million years, only a small fraction of the boulders ejected by cratering process are destroyed, for several tens of million years approx.50% are destroyed, and for 200-300 Ma, 90 to 99% are destroyed. Following [2] and other works, [1] considered that the rocks are mostly destroyed by meteorite impacts. Destruction of rocks by thermal-stress. However, high diurnal temperature variations on the surface of the Moon and other airless bodies imply that thermal stresses may also be a cause of surface rock destruction. Delbo et al. [3] interpreted the observed presence of fine debris on the surface of small asteroids as due to thermal surface cycling. They stated that because of the very low gravity on the surface of these bodies, ejecta from meteorite impacts should leave the body, so formation there of fine debris has to be due to thermal cycling. Based on experiments on heating-cooling of cm-scale pieces of ordinary and carbonaceous chondrites and theoretical modeling of

  12. Lessons from Cacti: How to Survive the Prickles of Life during Tough Times

    Science.gov (United States)

    Bigger, Alan S.; Bigger, Linda B.

    2009-01-01

    The saguaro cactus looked a little like humans, in different shapes and sizes. How on earth do they survive in a climate that seems so inhospitable? It is possible to learn lessons for life from a cactus, if one can only get beyond the thorns, and that these lessons will assist one to survive during tough or prickly times. These plants survive…

  13. Enhancement of radiation effect on mouse intestinal crypt survival by timing of 5-fluorouracil administration

    International Nuclear Information System (INIS)

    Ho, E.; Coffey, C.; Maruyama, Y.

    1977-01-01

    There is a marked dependence of mouse crypt survival on the sequence of combined drug-radiation treatment and on the time lapse between irradiation and drug administration. When 5-fluorouracil is administered 6 hours after irradiation or later (up to 18 hours postirradiation), crypt survival drops significantly

  14. Survival and prognostic factors at time of diagnosis in high-grade appendicular osteosarcoma

    DEFF Research Database (Denmark)

    Colding-Rasmussen, Thomas; Thorn, Andrea Pohly; Horstmann, Peter

    2018-01-01

    BACKGROUND: Survival of patients with high-grade osteosarcoma (HOS), the most common primary bone cancer, has not improved significantly the last 30 years and the disease remains a major challenge. The purpose of this study is to evaluate survival in relation to prognostic factors at time of diag...

  15. Survival analysis using S analysis of time-to-event data

    CERN Document Server

    Tableman, Mara

    2003-01-01

    Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter ...

  16. Biologically-equivalent dose and long-term survival time in radiation treatments

    International Nuclear Information System (INIS)

    Zaider, Marco; Hanin, Leonid

    2007-01-01

    Within the linear-quadratic model the biologically-effective dose (BED)-taken to represent treatments with an equal tumor control probability (TCP)-is commonly (and plausibly) calculated according to BED(D) = -log[S(D)]/α. We ask whether in the presence of cellular proliferation this claim is justified and examine, as a related question, the extent to which BED approximates an isoeffective dose (IED) defined, more sensibly, in terms of an equal long-term survival probability, rather than TCP. We derive, under the assumption that cellular birth and death rates are time homogeneous, exact equations for the isoeffective dose, IED. As well, we give a rigorous definition of effective long-term survival time, T eff . By using several sets of radiobiological parameters, we illustrate potential differences between BED and IED on the one hand and, on the other, between T eff calculated as suggested here or by an earlier recipe. In summary: (a) the equations currently in use for calculating the effective treatment time may underestimate the isoeffective dose and should be avoided. The same is the case for the tumor control probability (TCP), only more so; (b) for permanent implants BED may be a poor substitute for IED; (c) for a fractionated treatment schedule, interpreting the observed probability of cure in terms of a TCP formalism that refers to the end of the treatment (rather than T eff ) may result in a miscalculation (underestimation) of the initial number of clonogens

  17. Using Concurrent Cardiovascular Information to Augment Survival Time Data for Evaluating Orthostatic Tilt Test Performance

    Science.gov (United States)

    Feiveson, Alan H.; Fiedler, James; Lee, Stuart M. C.; Koslovsky, Matthew D.; Stenger, Michael B.; Platts, Steven H.

    2018-01-01

    Head-up tilt (HUT) tests often are used in research to measure orthostatic intolerance (OI) (inability to appropriately control blood pressure while upright) in clinical populations and otherwise healthy individuals after interventions. Post-space flight orthostatic intolerance is a well-known phenomenon, and countermeasures to its development has been an active area of research at NASA. In the NASA HUT protocol, subjects lie horizontally on an automatic tilt table for baseline measurements before being raised to 80deg head-up tilt for a defined period of time or until signs or symptoms of presyncope ensues (light-headedness, nausea, dizziness, sweating, weakness or fainting). Multiple measures are collected to evaluate the cardiovascular system's ability to respond appropriately to the orthostatic challenge. However if the intended duration of the HUT is short, the ability to detect changes in OI due to an intervention or its prevention by a countermeasure may be limited by a small number of failures to permit comparisons based on survival time alone. Thus, the time-trajectory of the cardiovascular data becomes an important additional source of information. In particular, we will show how various measures of trajectory variability can effectively augment survival analysis for the assessment of OI in a joint model when high censoring rates are present.

  18. Gene expression profiling of canine osteosarcoma reveals genes associated with short and long survival times

    Directory of Open Access Journals (Sweden)

    Rao Nagesha AS

    2009-09-01

    Full Text Available Abstract Background Gene expression profiling of spontaneous tumors in the dog offers a unique translational opportunity to identify prognostic biomarkers and signaling pathways that are common to both canine and human. Osteosarcoma (OS accounts for approximately 80% of all malignant bone tumors in the dog. Canine OS are highly comparable with their human counterpart with respect to histology, high metastatic rate and poor long-term survival. This study investigates the prognostic gene profile among thirty-two primary canine OS using canine specific cDNA microarrays representing 20,313 genes to identify genes and cellular signaling pathways associated with survival. This, the first report of its kind in dogs with OS, also demonstrates the advantages of cross-species comparison with human OS. Results The 32 tumors were classified into two prognostic groups based on survival time (ST. They were defined as short survivors (dogs with poor prognosis: surviving fewer than 6 months and long survivors (dogs with better prognosis: surviving 6 months or longer. Fifty-one transcripts were found to be differentially expressed, with common upregulation of these genes in the short survivors. The overexpressed genes in short survivors are associated with possible roles in proliferation, drug resistance or metastasis. Several deregulated pathways identified in the present study, including Wnt signaling, Integrin signaling and Chemokine/cytokine signaling are comparable to the pathway analysis conducted on human OS gene profiles, emphasizing the value of the dog as an excellent model for humans. Conclusion A molecular-based method for discrimination of outcome for short and long survivors is useful for future prognostic stratification at initial diagnosis, where genes and pathways associated with cell cycle/proliferation, drug resistance and metastasis could be potential targets for diagnosis and therapy. The similarities between human and canine OS makes the

  19. Using cure models for analyzing the influence of pathogens on salmon survival

    Science.gov (United States)

    Ray, Adam R; Perry, Russell W.; Som, Nicholas A.; Bartholomew, Jerri L

    2014-01-01

    Parasites and pathogens influence the size and stability of wildlife populations, yet many population models ignore the population-level effects of pathogens. Standard survival analysis methods (e.g., accelerated failure time models) are used to assess how survival rates are influenced by disease. However, they assume that each individual is equally susceptible and will eventually experience the event of interest; this assumption is not typically satisfied with regard to pathogens of wildlife populations. In contrast, mixture cure models, which comprise logistic regression and survival analysis components, allow for different covariates to be entered into each part of the model and provide better predictions of survival when a fraction of the population is expected to survive a disease outbreak. We fitted mixture cure models to the host–pathogen dynamics of Chinook Salmon Oncorhynchus tshawytscha and Coho Salmon O. kisutch and the myxozoan parasite Ceratomyxa shasta. Total parasite concentration, water temperature, and discharge were used as covariates to predict the observed parasite-induced mortality in juvenile salmonids collected as part of a long-term monitoring program in the Klamath River, California. The mixture cure models predicted the observed total mortality well, but some of the variability in observed mortality rates was not captured by the models. Parasite concentration and water temperature were positively associated with total mortality and the mortality rate of both Chinook Salmon and Coho Salmon. Discharge was positively associated with total mortality for both species but only affected the mortality rate for Coho Salmon. The mixture cure models provide insights into how daily survival rates change over time in Chinook Salmon and Coho Salmon after they become infected with C. shasta.

  20. Modelling urban travel times

    NARCIS (Netherlands)

    Zheng, F.

    2011-01-01

    Urban travel times are intrinsically uncertain due to a lot of stochastic characteristics of traffic, especially at signalized intersections. A single travel time does not have much meaning and is not informative to drivers or traffic managers. The range of travel times is large such that certain

  1. Providing Survivable Real-Time Communication Service for Distributed Mission Critical Systems

    National Research Council Canada - National Science Library

    Zhao, Wei; Bettati, Riccardo; Vaidya, Nitin

    2005-01-01

    This document is the final report for Providing Survivable Real-Time Communication Service for Distributed Mission Critical Systems, a Texas A AND M project funded through the DARPA Fault Tolerant Networks Program...

  2. The accuracy of survival time prediction for patients with glioma is improved by measuring mitotic spindle checkpoint gene expression.

    Directory of Open Access Journals (Sweden)

    Li Bie

    Full Text Available Identification of gene expression changes that improve prediction of survival time across all glioma grades would be clinically useful. Four Affymetrix GeneChip datasets from the literature, containing data from 771 glioma samples representing all WHO grades and eight normal brain samples, were used in an ANOVA model to screen for transcript changes that correlated with grade. Observations were confirmed and extended using qPCR assays on RNA derived from 38 additional glioma samples and eight normal samples for which survival data were available. RNA levels of eight major mitotic spindle assembly checkpoint (SAC genes (BUB1, BUB1B, BUB3, CENPE, MAD1L1, MAD2L1, CDC20, TTK significantly correlated with glioma grade and six also significantly correlated with survival time. In particular, the level of BUB1B expression was highly correlated with survival time (p<0.0001, and significantly outperformed all other measured parameters, including two standards; WHO grade and MIB-1 (Ki-67 labeling index. Measurement of the expression levels of a small set of SAC genes may complement histological grade and other clinical parameters for predicting survival time.

  3. Introduction to Time Series Modeling

    CERN Document Server

    Kitagawa, Genshiro

    2010-01-01

    In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f

  4. Machine learning models in breast cancer survival prediction.

    Science.gov (United States)

    Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

    2016-01-01

    Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

  5. Estimating true instead of apparent survival using spatial Cormack-Jolly-Seber models

    Science.gov (United States)

    Schaub, Michael; Royle, J. Andrew

    2014-01-01

    Survival is often estimated from capture–recapture data using Cormack–Jolly–Seber (CJS) models, where mortality and emigration cannot be distinguished, and the estimated apparent survival probability is the product of the probabilities of true survival and of study area fidelity. Consequently, apparent survival is lower than true survival unless study area fidelity equals one. Underestimation of true survival from capture–recapture data is a main limitation of the method.

  6. Modeling discrete time-to-event data

    CERN Document Server

    Tutz, Gerhard

    2016-01-01

    This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are expla...

  7. Survival models for harvest management of mourning dove populations

    Science.gov (United States)

    Otis, D.L.

    2002-01-01

    Quantitative models of the relationship between annual survival and harvest rate of migratory game-bird populations are essential to science-based harvest management strategies. I used the best available band-recovery and harvest data for mourning doves (Zenaida macroura) to build a set of models based on different assumptions about compensatory harvest mortality. Although these models suffer from lack of contemporary data, they can be used in development of an initial set of population models that synthesize existing demographic data on a management-unit scale, and serve as a tool for prioritization of population demographic information needs. Credible harvest management plans for mourning dove populations will require a long-term commitment to population monitoring and iterative population analysis.

  8. Mixed Hitting-Time Models

    NARCIS (Netherlands)

    Abbring, J.H.

    2009-01-01

    We study mixed hitting-time models, which specify durations as the first time a Levy process (a continuous-time process with stationary and independent increments) crosses a heterogeneous threshold. Such models of substantial interest because they can be reduced from optimal-stopping models with

  9. Comparison of six different models describing survival of mammalian cells after irradiation

    International Nuclear Information System (INIS)

    Sontag, W.

    1990-01-01

    Six different cell-survival models have been compared. All models are based on the similar assumption that irradiated cells are able to exist in one of three states. S A is the state of a totally repaired cell, in state S C the cell contains lethal lesions and in state S b the cell contains potentially lethal lesions i.e. those which either can be repaired or converted into lethal lesions. The differences between the six models lie in the different mathematical relationships between the three states. To test the six models, six different sets of experimental data were used which describe cell survival at different repair times after irradiation with sparsely ionizing irradiation. In order to compare the models, a goodness-of-fit function was used. The differences between the six models were tested by use of the nonparametric Mann-Whitney two sample test. Based on the 95% confidence limit, this required separation into three groups. (orig.)

  10. On the Survival Time of a Duplex System: A Sokhotski-Plemelj Problem

    Directory of Open Access Journals (Sweden)

    Edmond J. Vanderperre

    2008-12-01

    Full Text Available We analyze the survival time of a renewable duplex system characterized by warm standby and subjected to a priority rule. In order to obtain the Laplace transform of the survival function, we employ a stochastic process endowed with time-dependent transition measures satisfying coupled partial differential equations. The solution procedure is based on the theory of sectionally holomorphic functions combined with the notion of dual transforms. Finally, we introduce a security interval related to a prescribed security level and a suitable risk criterion based on the survival function of the system. As an example, we consider the particular case of deterministic repair. A computer-plotted graph displays the survival function together with the security interval corresponding to a security level of 90%.

  11. Predicting water main failures using Bayesian model averaging and survival modelling approach

    International Nuclear Information System (INIS)

    Kabir, Golam; Tesfamariam, Solomon; Sadiq, Rehan

    2015-01-01

    To develop an effective preventive or proactive repair and replacement action plan, water utilities often rely on water main failure prediction models. However, in predicting the failure of water mains, uncertainty is inherent regardless of the quality and quantity of data used in the model. To improve the understanding of water main failure, a Bayesian framework is developed for predicting the failure of water mains considering uncertainties. In this study, Bayesian model averaging method (BMA) is presented to identify the influential pipe-dependent and time-dependent covariates considering model uncertainties whereas Bayesian Weibull Proportional Hazard Model (BWPHM) is applied to develop the survival curves and to predict the failure rates of water mains. To accredit the proposed framework, it is implemented to predict the failure of cast iron (CI) and ductile iron (DI) pipes of the water distribution network of the City of Calgary, Alberta, Canada. Results indicate that the predicted 95% uncertainty bounds of the proposed BWPHMs capture effectively the observed breaks for both CI and DI water mains. Moreover, the performance of the proposed BWPHMs are better compare to the Cox-Proportional Hazard Model (Cox-PHM) for considering Weibull distribution for the baseline hazard function and model uncertainties. - Highlights: • Prioritize rehabilitation and replacements (R/R) strategies of water mains. • Consider the uncertainties for the failure prediction. • Improve the prediction capability of the water mains failure models. • Identify the influential and appropriate covariates for different models. • Determine the effects of the covariates on failure

  12. Survival with Three-Times Weekly In-Center Nocturnal Versus Conventional Hemodialysis

    Science.gov (United States)

    Xu, Jianglin; Suri, Rita S.; Nesrallah, Gihad; Lindsay, Robert; Garg, Amit X.; Lester, Keith; Ofsthun, Norma; Lazarus, Michael; Hakim, Raymond M.

    2012-01-01

    Whether the duration of hemodialysis treatments improves outcomes remains controversial. Here, we evaluated survival and clinical changes associated with converting from conventional hemodialysis (mean=3.75 h/treatment) to in-center nocturnal hemodialysis (mean=7.85 h/treatment). All 959 consecutive patients who initiated nocturnal hemodialysis for the first time in 77 Fresenius Medical Care facilities during 2006 and 2007 were eligible. We used Cox models to compare risk for mortality during 2 years of follow-up in a 1:3 propensity score–matched cohort of 746 nocturnal and 2062 control patients on conventional hemodialysis. Two-year mortality was 19% among nocturnal hemodialysis patients compared with 27% among conventional patients. Nocturnal hemodialysis associated with a 25% reduction in the risk for death after adjustment for age, body mass index, and dialysis vintage (hazard ratio=0.75, 95% confidence interval=0.61–0.91, P=0.004). With respect to clinical features, interdialytic weight gain, albumin, hemoglobin, dialysis dose, and calcium increased on nocturnal therapy, whereas postdialysis weight, predialysis systolic blood pressure, ultrafiltration rate, phosphorus, and white blood cell count declined (all P<0.001). In summary, notwithstanding the possibility of residual selection bias, conversion to treatment with nocturnal hemodialysis associates with favorable clinical features, laboratory biomarkers, and improved survival compared with propensity score–matched controls. The potential impact of extended treatment time on clinical outcomes while maintaining a three times per week hemodialysis schedule requires evaluation in future clinical trials. PMID:22362905

  13. Modelling lecturer performance index of private university in Tulungagung by using survival analysis with multivariate adaptive regression spline

    Science.gov (United States)

    Hasyim, M.; Prastyo, D. D.

    2018-03-01

    Survival analysis performs relationship between independent variables and survival time as dependent variable. In fact, not all survival data can be recorded completely by any reasons. In such situation, the data is called censored data. Moreover, several model for survival analysis requires assumptions. One of the approaches in survival analysis is nonparametric that gives more relax assumption. In this research, the nonparametric approach that is employed is Multivariate Regression Adaptive Spline (MARS). This study is aimed to measure the performance of private university’s lecturer. The survival time in this study is duration needed by lecturer to obtain their professional certificate. The results show that research activities is a significant factor along with developing courses material, good publication in international or national journal, and activities in research collaboration.

  14. Median Survival Time of Endometrial Cancer Patients with Lymphovascular Invasion at the Hospital Universiti Sains Malaysia.

    Science.gov (United States)

    Asyikeen, Wan Adnan Wan Nor; Siti-Azrin, Ab Hamid; Jalil, Nur Asyilla Che; Zin, Anani Aila Mat; Othman, Nor Hayati

    2016-11-01

    Endometrial cancer is the most common gynaecologic malignancy among females worldwide. The purpose of this study was to determine the median survival time of endometrial cancer patients at the Hospital Universiti Sains Malaysia (USM). A list of 121 endometrial cancer cases registered at Hospital USM between 2000 until 2011 was retrospectively reviewed. The survival time of the endometrial cancer patients was estimated by Kaplan-Meier survival analysis. Log-rank tests were performed to compare the survival of the patients based on socio-demographics and clinical presentation. Only 108 patients, 87.0%, were included who were of Malay ethnicity. Previous history included menopause in 67.6% of patients and diabetes mellitus in 39.8% of patients; additionally, 63.4% of patients were nulliparous. Tumour staging was as follows: 24.5% stage I, 10.8% stage II, 26.5% stage III and 38.2% stage IV. The overall median survival time of the endometrial cancer patients was 70.20 months (95% confidence interval (CI): 51.79, 88.61). The significant factors were age, the presence of lymphovascular invasion and treatment received. The overall survival of endometrial cancer was low. A prospective study needs to be carried out to discover more effective and accurate tests for the early detection of endometrial cancer.

  15. Median survival time of patients after transcatheter chemo-embolization for hepatocellular carcinoma

    International Nuclear Information System (INIS)

    Haider, Z.; Haq, T.; Munir, K.; Usman, M.U.; Azeemuddin, M.

    2006-01-01

    Objective: To determine the effect on survival after trans arterial chemo embolization (TACE) in patients with unresectable hepatocellular carcinoma (HCC). Design: Longitudinal cohort study. Place and Duration of Study: Radiology Department, The Aga Khan University Hospital, Stadium Road, Karachi, from December 1997 to September 2005. Patients and Methods: Patients undergoing TACE procedure for HCC were prospectively followed. Forty three patients were enrolled from December 1997 to March 2003 in the study and subjected to chemo embolization therapy. Eight out of 43 patients were excluded from the study, who lost to follow-up. All the patients were followed till their death. Median and mean survival were calculated. Results: The median survival of these 35 patients was 410 days (13.6 months), with 95% confidence interval (236 days lower bound and 536 days upper bound). Mean survival time was 603 days (20.1 months) with 95% confidence interval (394 days lower bound and 812 days upper bound). There was significant difference in mean survival time (in days) by Child's Pugh class (X2 = 12.384; df=2, p-value=0.002). Conclusion: The study showed that TACE is an effective palliative treatment. TACE increases the median survival time. (author)

  16. Correlation between the CT manifestations and post-operative survival time in patients with thymic epithelial tumor

    International Nuclear Information System (INIS)

    Chen Juan; Tan Ye; Wang Xiangyang; Du Jun; Pan Jishu; Wei Jiahu

    2011-01-01

    Objective: To describe the CT manifestations of thymic epithelial tumor and explore the correlation between CT findings and post-operative tumor-related survival time. Methods: Ninety-one patients who underwent CT scan before operation were reviewed retrospectively. All cases had operation and were classified according to the WHO classification. The size, contour, shape, density and enhancement of the tumors on CT were assessed. Presence of mediastinal lymphadenopathy, great vessel invasion, metastasis to the lung or plural, myasthenia gravis (MG) were also analyzed. The survival rate was obtained using, the Kaplan-Meier method. The Cox model was applied to determine the factors affecting the tumor-related survivals. Chi square test was used to analyze the relationship between CT findings and WHO classification. Results: Two patients were excluded because of dying of myocardial infarction and colon cancer. The total 5-year survival rate was 84.3% (n=75). Eighty-nine patients had total 91 tumors. Tumors with diameter larger than 5 cm, lobular contour, heterogenous density, and presence of great vessel invasion, mediastinal lymphadenopathy, and metastasis were adverse factors which could significantly affect the survival time. Five-year survival rates of these factors were 72.7%, 77.3%, 76.7%, 73.8%, 30.0%, and 68.8%, respectively. Presence of MG was a favorable factor which also significantly affected the survival time (P 0.05). The result of the Cox multivariate analysis was consistent with that of the Log-rank test. For different WHO classification, there were significant different among the size or contour of the tumors, presence of great vessel invasion, mediastinal lymphadenopathy, and metastasis (χ 2 value were 6.598, 5.737, 18.307, 8.465, and 15.608, respectively P<0.05). Conclusions: CT findings may be served as predictors of clinical prognosis of the thymic epithelial tumors. Adverse factors for survival time are the size of the tumors and presence of

  17. Dose-rate dependent stochastic effects in radiation cell-survival models

    International Nuclear Information System (INIS)

    Sachs, R.K.; Hlatky, L.R.

    1990-01-01

    When cells are subjected to ionizing radiation the specific energy rate (microscopic analog of dose-rate) varies from cell to cell. Within one cell, this rate fluctuates during the course of time; a crossing of a sensitive cellular site by a high energy charged particle produces many ionizations almost simultaneously, but during the interval between events no ionizations occur. In any cell-survival model one can incorporate the effect of such fluctuations without changing the basic biological assumptions. Using stochastic differential equations and Monte Carlo methods to take into account stochastic effects we calculated the dose-survival rfelationships in a number of current cell survival models. Some of the models assume quadratic misrepair; others assume saturable repair enzyme systems. It was found that a significant effect of random fluctuations is to decrease the theoretically predicted amount of dose-rate sparing. In the limit of low dose-rates neglecting the stochastic nature of specific energy rates often leads to qualitatively misleading results by overestimating the surviving fraction drastically. In the opposite limit of acute irradiation, analyzing the fluctuations in rates merely amounts to analyzing fluctuations in total specific energy via the usual microdosimetric specific energy distribution function, and neglecting fluctuations usually underestimates the surviving fraction. The Monte Carlo methods interpolate systematically between the low dose-rate and high dose-rate limits. As in other approaches, the slope of the survival curve at low dose-rates is virtually independent of dose and equals the initial slope of the survival curve for acute radiation. (orig.)

  18. Helicopter crashes into water: warning time, final position, and other factors affecting survival.

    Science.gov (United States)

    Brooks, Christopher J; MacDonald, Conor V; Baker, Susan P; Shanahan, Dennis F; Haaland, Wren L

    2014-04-01

    According to 40 yr of data, the fatality rate for a helicopter crash into water is approximately 25%. Does warning time and the final position of the helicopter in the water influence the survival rate? The National Transportation Safety Board (NTSB) database was queried to identify helicopter crashes into water between 1981 and 2011 in the Gulf of Mexico and Hawaii. Fatality rate, amount of warning time prior to the crash, and final position of the helicopter were identified. There were 133 helicopters that crashed into water with 456 crew and passengers. Of these, 119 occupants (26%) did not survive; of those who did survive, 38% were injured. Twelve died after making a successful escape from the helicopter. Crashes with 1 min. However, more than half of fatalities (57%) came from crashes for which the warning time could not be determined. Lack of warning time and how to survive in the water after the crash should be a topic for study in all marine survival/aircraft ditching courses. Investigators should be trained to provide estimates of warning time when investigating helicopter crashes into water.

  19. Child mortality inequalities across Rwanda districts: a geoadditive continuous-time survival analysis

    Directory of Open Access Journals (Sweden)

    François Niragire

    2017-05-01

    Full Text Available Child survival programmes are efficient when they target the most significant and area-specific factors. This study aimed to assess the key determinants and spatial variation of child mortality at the district level in Rwanda. Data from the 2010 Rwanda Demographic and Health Survey were analysed for 8817 live births that occurred during five years preceding the survey. Out of the children born, 433 had died before survey interviews were carried out. A full Bayesian geo-additive continuous-time hazard model enabled us to maximise data utilisation and hence improve the accuracy of our estimates. The results showed substantial district- level spatial variation in childhood mortality in Rwanda. District-specific spatial characteristics were particularly associated with higher death hazards in two districts: Musanze and Nyabihu. The model estimates showed that there were lower death rates among children from households of medium and high economic status compared to those from low-economic status households. Factors, such as four antenatal care visits, delivery at a health facility, prolonged breastfeeding and mothers younger than 31 years were associated with lower child death rates. Long preceding birth intervals were also associated with fewer hazards. For these reasons, programmes aimed at reducing child mortality gaps between districts in Rwanda should target maternal factors and take into consideration district-specific spatial characteristics. Further, child survival gains require strengthening or scaling-up of existing programmes pertaining to access to, and utilisation of maternal and child health care services as well as reduction of the household gap in the economic status.

  20. Child mortality inequalities across Rwanda districts: a geoadditive continuous-time survival analysis.

    Science.gov (United States)

    Niragire, François; Achia, Thomas N O; Lyambabaje, Alexandre; Ntaganira, Joseph

    2017-05-11

    Child survival programmes are efficient when they target the most significant and area-specific factors. This study aimed to assess the key determinants and spatial variation of child mortality at the district level in Rwanda. Data from the 2010 Rwanda Demographic and Health Survey were analysed for 8817 live births that occurred during five years preceding the survey. Out of the children born, 433 had died before survey interviews were carried out. A full Bayesian geo-additive continuous-time hazard model enabled us to maximise data utilisation and hence improve the accuracy of our estimates. The results showed substantial district- level spatial variation in childhood mortality in Rwanda. District-specific spatial characteristics were particularly associated with higher death hazards in two districts: Musanze and Nyabihu. The model estimates showed that there were lower death rates among children from households of medium and high economic status compared to those from low-economic status households. Factors, such as four antenatal care visits, delivery at a health facility, prolonged breastfeeding and mothers younger than 31 years were associated with lower child death rates. Long preceding birth intervals were also associated with fewer hazards. For these reasons, programmes aimed at reducing child mortality gaps between districts in Rwanda should target maternal factors and take into consideration district-specific spatial characteristics. Further, child survival gains require strengthening or scaling-up of existing programmes pertaining to access to, and utilisation of maternal and child health care services as well as reduction of the household gap in the economic status.

  1. Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

    Science.gov (United States)

    Liu, Gang; Dong, Chuanpeng; Wang, Xing; Hou, Guojun; Zheng, Yu; Xu, Huilin; Zhan, Xiaohui; Liu, Lei

    2017-11-17

    Clinical and pathological indicators are inadequate for prognosis of stage II and III colorectal carcinoma (CRC). In this study, we utilized the activity of regulatory factors, univariate Cox regression and random forest for variable selection and developed a multivariate Cox model to predict the overall survival of Stage II/III colorectal carcinoma in GSE39582 datasets (469 samples). Patients in low-risk group showed a significant longer overall survival and recurrence-free survival time than those in high-risk group. This finding was further validated in five other independent datasets (GSE14333, GSE17536, GSE17537, GSE33113, and GSE37892). Besides, associations between clinicopathological information and risk score were analyzed. A nomogram including risk score was plotted to facilitate the utilization of risk score. The risk score model is also demonstrated to be effective on predicting both overall and recurrence-free survival of chemotherapy received patients. After performing Gene Set Enrichment Analysis (GSEA) between high and low risk groups, we found that several cell-cell interaction KEGG pathways were identified. Funnel plot results showed that there was no publication bias in these datasets. In summary, by utilizing the regulatory activity in stage II and III colorectal carcinoma, the risk score successfully predicts the survival of 1021 stage II/III CRC patients in six independent datasets.

  2. Combined treatment with atorvastatin and imipenem improves survival and vascular functions in mouse model of sepsis.

    Science.gov (United States)

    Choudhury, Soumen; Kannan, Kandasamy; Pule Addison, M; Darzi, Sazad A; Singh, Vishakha; Singh, Thakur Uttam; Thangamalai, Ramasamy; Dash, Jeevan Ranjan; Parida, Subhashree; Debroy, Biplab; Paul, Avishek; Mishra, Santosh Kumar

    2015-08-01

    We have recently reported that pre-treatment, but not the post-treatment with atorvastatin showed survival benefit and improved hemodynamic functions in cecal ligation and puncture (CLP) model of sepsis in mice. Here we examined whether combined treatment with atorvastatin and imipenem after onset of sepsis can prolong survival and improve vascular functions. At 6 and 18h after sepsis induction, treatment with atorvastatin plus imipenem, atorvastatin or imipenem alone or placebo was initiated. Ex vivo experiments were done on mouse aorta to examine the vascular reactivity to nor-adrenaline and acetylcholine and mRNA expressions of α1D AR, GRK2 and eNOS. Atorvastatin plus imipenem extended the survival time to 56.00±4.62h from 20.00±1.66h observed in CLP mice. The survival time with atorvastatin or imipenem alone was 20.50±1.89h and 27.00±4.09h, respectively. The combined treatment reversed the hyporeactivity to nor-adrenaline through preservation of α1D AR mRNA/protein expression and reversal of α1D AR desensitization mediated by GRK2/Gβγ pathway. The treatment also restored endothelium-dependent relaxation to ACh through restoration of aortic eNOS mRNA expression and NO availability. In conclusion, combined treatment with atorvastatin and imipenem exhibited survival benefit and improved vascular functions in septic mice. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. PSO-Based Robot Path Planning for Multisurvivor Rescue in Limited Survival Time

    Directory of Open Access Journals (Sweden)

    N. Geng

    2014-01-01

    Full Text Available Since the strength of a trapped person often declines with time in urgent and dangerous circumstances, adopting a robot to rescue as many survivors as possible in limited time is of considerable significance. However, as one key issue in robot navigation, how to plan an optimal rescue path of a robot has not yet been fully solved. This paper studies robot path planning for multisurvivor rescue in limited survival time using a representative heuristic, particle swarm optimization (PSO. First, the robot path planning problem including multiple survivors is formulated as a discrete optimization one with high constraint, where the number of rescued persons is taken as the unique objective function, and the strength of a trapped person is used to constrain the feasibility of a path. Then, a new integer PSO algorithm is presented to solve the mathematical model, and several new operations, such as the update of a particle, the insertion and inversion operators, and the rapidly local search method, are incorporated into the proposed algorithm to improve its effectiveness. Finally, the simulation results demonstrate the capacity of our method in generating optimal paths with high quality.

  4. Fluid Survival Tool: A Model Checker for Hybrid Petri Nets

    NARCIS (Netherlands)

    Postema, Björn Frits; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Ghasemieh, Hamed

    2014-01-01

    Recently, algorithms for model checking Stochastic Time Logic (STL) on Hybrid Petri nets with a single general one-shot transition (HPNG) have been introduced. This paper presents a tool for model checking HPNG models against STL formulas. A graphical user interface (GUI) not only helps to

  5. A comparative study of generalized linear mixed modelling and artificial neural network approach for the joint modelling of survival and incidence of Dengue patients in Sri Lanka

    Science.gov (United States)

    Hapugoda, J. C.; Sooriyarachchi, M. R.

    2017-09-01

    Survival time of patients with a disease and the incidence of that particular disease (count) is frequently observed in medical studies with the data of a clustered nature. In many cases, though, the survival times and the count can be correlated in a way that, diseases that occur rarely could have shorter survival times or vice versa. Due to this fact, joint modelling of these two variables will provide interesting and certainly improved results than modelling these separately. Authors have previously proposed a methodology using Generalized Linear Mixed Models (GLMM) by joining the Discrete Time Hazard model with the Poisson Regression model to jointly model survival and count model. As Aritificial Neural Network (ANN) has become a most powerful computational tool to model complex non-linear systems, it was proposed to develop a new joint model of survival and count of Dengue patients of Sri Lanka by using that approach. Thus, the objective of this study is to develop a model using ANN approach and compare the results with the previously developed GLMM model. As the response variables are continuous in nature, Generalized Regression Neural Network (GRNN) approach was adopted to model the data. To compare the model fit, measures such as root mean square error (RMSE), absolute mean error (AME) and correlation coefficient (R) were used. The measures indicate the GRNN model fits the data better than the GLMM model.

  6. Analysis of survival in breast cancer patients by using different parametric models

    Science.gov (United States)

    Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

    2017-09-01

    In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

  7. Examining the Influence of Campus Climate on Students' Time to Degree: A Multilevel Discrete-Time Survival Analysis

    Science.gov (United States)

    Zhou, Ji; Castellanos, Michelle

    2013-01-01

    Utilizing longitudinal data of 3477 students from 28 institutions, we examine the effects of structural diversity and quality of interracial relation on students' persistence towards graduation within six years. We utilize multilevel discrete-time survival analysis to account for the longitudinal persistence patterns as well as the nested…

  8. Childhood cancer survival in Switzerland (1976-2013): Time-trends and predictors.

    Science.gov (United States)

    Schindler, Matthias; Belle, Fabiën N; Grotzer, Michael A; von der Weid, Nicolas X; Kuehni, Claudia E

    2017-01-01

    Population-based studies on childhood cancer survival are key to monitor progress against cancer and to detect potential differences between regions and other subgroups in the population. We investigated time trends and factors associated with childhood cancer survival on a national level in Switzerland, from 1976 to 2013. We extracted data from the population-based Swiss Childhood Cancer Registry of 5,776 children (age 0-14 years) diagnosed with cancer from 1985 to 2014 in Switzerland. We calculated age-adjusted 5-year survival, defined the annual reduction in risk of death (ARR), and explored associations of survival with clinical and demographic factors. Overall, 5-year survival improved significantly, from 64% in 1976-1983 to 88% in 2004-2013. ARR over the whole period was 4% for all diagnostic groups, greatest for Hodgkin lymphomas (8%), ependymomas (6%), Burkitt's lymphomas (6%) and germ cell tumours (6%). Children treated in hospitals without specialised paediatric cancer centre for leukaemia (HR 12.9), lymphoma (HR 5.0) and neuroblastoma (HR 3.7) were at higher risk of death. In French-speaking Switzerland, risk of death was lower for lymphoma (HR 0.6), CNS tumours (HR 0.7) and neuroblastoma (HR 0.5). Children with migration background had a higher risk of death from all tumours except bone tumours. Childhood cancer survival significantly improved from 1976 to 2013, but there is room for further improvement. Survival rates varied by type of clinical treatment, language region and nationality. All paediatric cancer patients should be referred to a specialised paediatric cancer centre. Further research is needed to intervene and completely eliminate inequalities in survival. © 2016 UICC.

  9. Modelling of Attentional Dwell Time

    DEFF Research Database (Denmark)

    Petersen, Anders; Kyllingsbæk, Søren; Bundesen, Claus

    2009-01-01

    . This confinement of attentional resources leads to the impairment in identifying the second target. With the model, we are able to produce close fits to data from the traditional two target dwell time paradigm. A dwell-time experiment with three targets has also been carried out for individual subjects...... and the model has been extended to fit these data....

  10. Time to treatment as a quality metric in lung cancer: Staging studies, time to treatment, and patient survival

    International Nuclear Information System (INIS)

    Gomez, Daniel R.; Liao, Kai-Ping; Swisher, Stephen G.; Blumenschein, George R.; Erasmus, Jeremy J.; Buchholz, Thomas A.; Giordano, Sharon H.; Smith, Benjamin D.

    2015-01-01

    Purpose: Prompt staging and treatment are crucial for non-small cell lung cancer (NSCLC). We determined if predictors of treatment delay after diagnosis were associated with prognosis. Materials and methods: Medicare claims from 28,732 patients diagnosed with NSCLC in 2004–2007 were used to establish the diagnosis-to-treatment interval (ideally ⩽35 days) and identify staging studies during that interval. Factors associated with delay were identified with multivariate logistic regression, and associations between delay and survival by stage were tested with Cox proportional hazard regression. Results: Median diagnosis-to-treatment interval was 27 days. Receipt of PET was associated with delays (57.4% of patients with PET delayed [n = 6646/11,583] versus 22.8% of those without [n = 3908/17,149]; adjusted OR = 4.48, 95% CI 4.23–4.74, p < 0.001). Median diagnosis-to-PET interval was 15 days; PET-to-clinic, 5 days; and clinic-to-treatment, 12 days. Diagnosis-to-treatment intervals <35 days were associated with improved survival for patients with localized disease and those with distant disease surviving ⩾1 year but not for patients with distant disease surviving <1 year. Conclusion: Delays between diagnosing and treating NSCLC are common and associated with use of PET for staging. Reducing time to treatment may improve survival for patients with manageable disease at diagnosis

  11. Predictive modelling of Lactobacillus casei KN291 survival in fermented soy beverage.

    Science.gov (United States)

    Zielińska, Dorota; Dorota, Zielińska; Kołożyn-Krajewska, Danuta; Danuta, Kołożyn-Krajewska; Goryl, Antoni; Antoni, Goryl; Motyl, Ilona

    2014-02-01

    The aim of the study was to construct and verify predictive growth and survival models of a potentially probiotic bacteria in fermented soy beverage. The research material included natural soy beverage (Polgrunt, Poland) and the strain of lactic acid bacteria (LAB) - Lactobacillus casei KN291. To construct predictive models for the growth and survival of L. casei KN291 bacteria in the fermented soy beverage we design an experiment which allowed the collection of CFU data. Fermented soy beverage samples were stored at various temperature conditions (5, 10, 15, and 20°C) for 28 days. On the basis of obtained data concerning the survival of L. casei KN291 bacteria in soy beverage at different temperature and time conditions, two non-linear models (r(2)= 0.68-0.93) and two surface models (r(2)=0.76-0.79) were constructed; these models described the behaviour of the bacteria in the product to a satisfactory extent. Verification of the surface models was carried out utilizing the validation data - at 7°C during 28 days. It was found that applied models were well fitted and charged with small systematic errors, which is evidenced by accuracy factor - Af, bias factor - Bf and mean squared error - MSE. The constructed microbiological growth and survival models of L. casei KN291 in fermented soy beverage enable the estimation of products shelf life period, which in this case is defined by the requirement for the level of the bacteria to be above 10(6) CFU/cm(3). The constructed models may be useful as a tool for the manufacture of probiotic foods to estimate of their shelf life period.

  12. Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

    Science.gov (United States)

    Bernhardt, Paul W; Wang, Huixia Judy; Zhang, Daowen

    2014-01-01

    Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

  13. Predicting survival time in noncurative patients with advanced cancer: a prospective study in China.

    Science.gov (United States)

    Cui, Jing; Zhou, Lingjun; Wee, B; Shen, Fengping; Ma, Xiuqiang; Zhao, Jijun

    2014-05-01

    Accurate prediction of prognosis for cancer patients is important for good clinical decision making in therapeutic and care strategies. The application of prognostic tools and indicators could improve prediction accuracy. This study aimed to develop a new prognostic scale to predict survival time of advanced cancer patients in China. We prospectively collected items that we anticipated might influence survival time of advanced cancer patients. Participants were recruited from 12 hospitals in Shanghai, China. We collected data including demographic information, clinical symptoms and signs, and biochemical test results. Log-rank tests, Cox regression, and linear regression were performed to develop a prognostic scale. Three hundred twenty patients with advanced cancer were recruited. Fourteen prognostic factors were included in the prognostic scale: Karnofsky Performance Scale (KPS) score, pain, ascites, hydrothorax, edema, delirium, cachexia, white blood cell (WBC) count, hemoglobin, sodium, total bilirubin, direct bilirubin, aspartate aminotransferase (AST), and alkaline phosphatase (ALP) values. The score was calculated by summing the partial scores, ranging from 0 to 30. When using the cutoff points of 7-day, 30-day, 90-day, and 180-day survival time, the scores were calculated as 12, 10, 8, and 6, respectively. We propose a new prognostic scale including KPS, pain, ascites, hydrothorax, edema, delirium, cachexia, WBC count, hemoglobin, sodium, total bilirubin, direct bilirubin, AST, and ALP values, which may help guide physicians in predicting the likely survival time of cancer patients more accurately. More studies are needed to validate this scale in the future.

  14. Palliative Sedation in Advanced Cancer Patients: Does it Shorten Survival Time? - A Systematic Review.

    Science.gov (United States)

    Barathi, B; Chandra, Prabha S

    2013-01-01

    Patients with advanced cancer often suffer from multiple refractory symptoms in the terminal phase of their life. Palliative sedation is one of the few ways to relieve this refractory suffering. This systematic review investigated the effect of palliative sedation on survival time in terminally ill cancer patients. Six electronic databases were searched for both prospective and retrospective studies which evaluated the effect of palliative sedation on survival time. Only those studies which had a comparison group that did not receive palliative sedation were selected for the review. Abstracts of all retrieved studies were screened to include the most relevant studies and only studies which met inclusion criteria were selected. References of all retrieved studies were also screened for relevant studies. Selected studies were assessed for quality and data extraction was done using the structured data extraction form. Eleven studies including four prospective and seven retrospective studies were identified. Mean survival time (MST) was measured as the time from last admission until death. A careful analysis of the results of all the 11 studies indicated that MST of sedated and non-sedated group was not statistically different in any of the studies. This systematic review supports the fact that palliative sedation does not shorten survival in terminally ill cancer patients. However, this conclusion needs to be taken with consideration of the methodology, study design, and the population studied of the included studies in this review.

  15. Effect of bifidobacteria implantation on the survival time of whole-body irradiated mice

    International Nuclear Information System (INIS)

    Yokokura, Teruo; Onoue, Masaharu; Mutai, Masahiko

    1980-01-01

    Letahl dose (2 KR) of gamma-ray was irradiated on the whole bodies of mice. Survival time after irradiation was significantly longer in mice with administration of both Bifidobacterium breve YIT 4008 and transgalactosyl oligosaccharide than in mice with administration of either of the two or nothing. (Tsunoda, M.)

  16. Palliative sedation in advanced cancer patients: Does it shorten survival time? - A systematic review

    Directory of Open Access Journals (Sweden)

    B Barathi

    2013-01-01

    Full Text Available Background: Patients with advanced cancer often suffer from multiple refractory symptoms in the terminal phase of their life. Palliative sedation is one of the few ways to relieve this refractory suffering. Objectives: This systematic review investigated the effect of palliative sedation on survival time in terminally ill cancer patients. Materials and Methods: Six electronic databases were searched for both prospective and retrospective studies which evaluated the effect of palliative sedation on survival time. Only those studies which had a comparison group that did not receive palliative sedation were selected for the review. Abstracts of all retrieved studies were screened to include the most relevant studies and only studies which met inclusion criteria were selected. References of all retrieved studies were also screened for relevant studies. Selected studies were assessed for quality and data extraction was done using the structured data extraction form. Results: Eleven studies including four prospective and seven retrospective studies were identified. Mean survival time (MST was measured as the time from last admission until death. A careful analysis of the results of all the 11 studies indicated that MST of sedated and non-sedated group was not statistically different in any of the studies. Conclusion: This systematic review supports the fact that palliative sedation does not shorten survival in terminally ill cancer patients. However, this conclusion needs to be taken with consideration of the methodology, study design, and the population studied of the included studies in this review.

  17. It's Deja Vu All over Again: Using Multiple-Spell Discrete-Time Survival Analysis.

    Science.gov (United States)

    Willett, John B.; Singer, Judith D.

    1995-01-01

    The multiple-spell discrete-time survival analysis method is introduced and illustrated using longitudinal data on exit from and reentry into the teaching profession. The method is applicable to many educational problems involving the sequential occurrence of disparate events or episodes. (SLD)

  18. Effect of antibiotic decontamination of the GI tract on survival time after neutron and gamma irradiation

    International Nuclear Information System (INIS)

    Geraci, J.P.; Jackson, K.L.; Mariano, M.S.

    1984-01-01

    Antibiotic decontaminated and conventional rats were whole-body irradiated with 8 MeV neutrons (1.5 to 13 Gy) or 137 Cs gamma radiation (9 to 20 Gy). The animals were checked for survival at four hour intervals from the second to the seventh day postirradiation and at eight hour intervals on other days. Decontamination of the GI tract increased median survival time 1 to 5 days in this range of dose dependency, whereas the effect of decontamination was negligible for doses that produced mostly intestinal death. These results suggest that sepsis and endotoxin produced by bacteria from the intestinal tract play little role in acute intestinal radiation death

  19. A model of survival following pre-hospital cardiac arrest based on the Victorian Ambulance Cardiac Arrest Register.

    Science.gov (United States)

    Fridman, Masha; Barnes, Vanessa; Whyman, Andrew; Currell, Alex; Bernard, Stephen; Walker, Tony; Smith, Karen L

    2007-11-01

    This study describes the epidemiology of sudden cardiac arrest patients in Victoria, Australia, as captured via the Victorian Ambulance Cardiac Arrest Register (VACAR). We used the VACAR data to construct a new model of out-of-hospital cardiac arrest (OHCA), which was specified in accordance with observed trends. All cases of cardiac arrest in Victoria that were attended by Victorian ambulance services during the period of 2002-2005. Overall survival to hospital discharge was 3.8% among 18,827 cases of OHCA. Survival was 15.7% among 1726 bystander witnessed, adult cardiac arrests of presumed cardiac aetiology, presenting in ventricular fibrillation or ventricular tachycardia (VF/VT), where resuscitation was attempted. In multivariate logistic regression analysis, bystander CPR, cardiac arrest (CA) location, response time, age and sex were predictors of VF/VT, which, in turn, was a strong predictor of survival. The same factors that affected VF/VT made an additional contribution to survival. However, for bystander CPR, CA location and response time this additional contribution was limited to VF/VT patients only. There was no detectable association between survival and age younger than 60 years or response time over 15min. The new model accounts for relationships among predictors of survival. These relationships indicate that interventions such as reduced response times and bystander CPR act in multiple ways to improve survival.

  20. Models for dependent time series

    CERN Document Server

    Tunnicliffe Wilson, Granville; Haywood, John

    2015-01-01

    Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater

  1. 33 CFR 150.503 - What are the time interval requirements for maintenance on survival craft falls?

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false What are the time interval requirements for maintenance on survival craft falls? 150.503 Section 150.503 Navigation and Navigable Waters... maintenance on survival craft falls? (a) Each fall used in a launching device for survival craft or rescue...

  2. Progression-free survival/time to progression as a potential surrogate for overall survival in HR+, HER2– metastatic breast cancer

    Directory of Open Access Journals (Sweden)

    Forsythe A

    2018-05-01

    Full Text Available Anna Forsythe,1 David Chandiwana,2 Janina Barth,3 Marroon Thabane,4 Johan Baeck,2 Gabriel Tremblay1 1Purple Squirrel Economics, New York, NY, 2Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 3Novartis Pharma GmbH, Nuremberg, Germany; 4Novartis Pharmaceuticals Incorporated, Dorval, QC, Canada Background: Several recent randomized controlled trials (RCTs in hormone receptor-positive (HR+, human epidermal growth factor receptor 2-negative (HER2– metastatic breast cancer (MBC have demonstrated significant improvements in progression-free survival (PFS; however, few have reported improvement in overall survival (OS. The surrogacy of PFS or time to progression (TTP for OS has not been formally investigated in HR+, HER2– MBC.Methods: A systematic literature review of RCTs in HR+, HER2– MBC was conducted to identify studies that reported both median PFS/TTP and OS. The correlation between PFS/TTP and OS was evaluated using Pearson’s product–moment correlation and Spearman’s rank correlation. Subgroup analyses were performed to explore possible reasons for heterogeneity. Errors-in-variables weighted least squares regression (LSR was used to model incremental OS months as a function of incremental PFS/TTP months. An exploratory analysis investigated the impact of three covariates (chemotherapy vs hormonal/targeted therapy, PFS vs TTP, and first-line therapy vs second-line therapy or greater on OS prediction. The lower 95% prediction band was used to determine the minimum incremental PFS/TTP months required to predict OS benefit (surrogate threshold effect [STE].Results: Forty studies were identified. There was a statistically significant correlation between median PFS/TTP and OS (Pearson =0.741, P=0.000; Spearman =0.650, P=0.000. These results proved consistent for chemotherapy and hormonal/targeted therapy. Univariate LSR analysis yielded an R2 of 0.354 with 1 incremental PFS/TTP month corresponding to 1.13 incremental OS months

  3. A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic

    International Nuclear Information System (INIS)

    Chow, Edward; Fung, KinWah; Panzarella, Tony; Bezjak, Andrea; Danjoux, Cyril; Tannock, Ian

    2002-01-01

    Purpose: To develop a predictive model for survival from the time of presentation in an outpatient palliative radiotherapy clinic. Methods and Materials: Sixteen factors were analyzed prospectively in 395 patients seen in a dedicated palliative radiotherapy clinic in a large tertiary cancer center using Cox's proportional hazards regression model. Results: Six prognostic factors had a statistically significant impact on survival, as follows: primary cancer site, site of metastases, Karnofsky performance score (KPS), and fatigue, appetite, and shortness of breath scores from the modified Edmonton Symptom Assessment Scale. Risk group stratification was performed (1) by assigning weights to the prognostic factors based on their levels of significance, and (2) by the number of risk factors present. The weighting method provided a Survival Prediction Score (SPS), ranging from 0 to 32. The survival probability at 3, 6, and 12 months was 83%, 70%, and 51%, respectively, for patients with SPS ≤13 (n=133); 67%, 41%, and 20% for patients with SPS 14-19 (n=129); and 36%, 18%, and 4% for patients with SPS ≥20 (n=133) (p<0.0001). Corresponding survival probabilities based on number of risk factors were as follows: 85%, 72%, and 52% (≤3 risk factors) (n=98); 68%, 47%, and 24% (4 risk factors) (n=117); and 46%, 24%, and 11% (≥5 factors) (n=180) (p<0.0001). Conclusion: Clinical prognostic factors can be used to predict prognosis among patients attending a palliative radiotherapy clinic. If validated in an independent series of patients, the model can be used to guide clinical decisions, plan supportive services, and allocate resource use

  4. Impedance models in time domain

    NARCIS (Netherlands)

    Rienstra, S.W.

    2005-01-01

    Necessary conditions for an impedance function are derived. Methods available in the literature are discussed. A format with recipe is proposed for an exact impedance condition in time domain on a time grid, based on the Helmholtz resonator model. An explicit solution is given of a pulse reflecting

  5. Survival time and effect of selected predictor variables on survival in owned pet cats seropositive for feline immunodeficiency and leukemia virus attending a referral clinic in northern Italy.

    Science.gov (United States)

    Spada, Eva; Perego, Roberta; Sgamma, Elena Assunta; Proverbio, Daniela

    2018-02-01

    Feline immunodeficiency virus (FIV) and feline leukemia virus (FeLV) are among the most important feline infectious diseases worldwide. This retrospective study investigated survival times and effects of selected predictor factors on survival time in a population of owned pet cats in Northern Italy testing positive for the presence of FIV antibodies and FeLV antigen. One hundred and three retrovirus-seropositive cats, 53 FIV-seropositive cats, 40 FeLV-seropositive cats, and 10 FIV+FeLV-seropositive cats were included in the study. A population of 103 retrovirus-seronegative age and sex-matched cats was selected. Survival time was calculated and compared between retrovirus-seronegative, FIV, FeLV and FIV+FeLV-seropositive cats using Kaplan-Meier survival analysis. Cox proportional-hazards regression analysis was used to study the effect of selected predictor factors (male gender, peripheral blood cytopenia as reduced red blood cells - RBC- count, leukopenia, neutropenia and lymphopenia, hypercreatininemia and reduced albumin to globulin ratio) on survival time in retrovirus-seropositive populations. Median survival times for seronegative cats, FIV, FeLV and FIV+FeLV-seropositive cats were 3960, 2040, 714 and 77days, respectively. Compared to retrovirus-seronegative cats median survival time was significantly lower (P<0.000) in FeLV and FIV+FeLV-seropositive cats. Median survival time in FeLV and FIV+FeLV-seropositive cats was also significant lower (P<0.000) when compared to FIV-seropositive cats. Hazard ratio of death in FeLV and FIV+FeLV-seropositive cats being respectively 3.4 and 7.4 times higher, in comparison to seronegative cats and 2.3 and 4.8 times higher in FeLV and FIV+FeLV-seropositive cats as compared to FIV-seropositive cats. A Cox proportional-hazards regression analysis showed that FIV and FeLV-seropositive cats with reduced RBC counts at time of diagnosis of seropositivity had significantly shorter survival times when compared to FIV and Fe

  6. Clinical findings and survival time in dogs with advanced heart failure.

    Science.gov (United States)

    Beaumier, Amelie; Rush, John E; Yang, Vicky K; Freeman, Lisa M

    2018-04-10

    Dogs with advanced heart failure are a clinical challenge for veterinarians but there are no studies reporting clinical features and outcome of this population. To describe clinical findings and outcome of dogs with advanced heart failure caused by degenerative mitral valve disease (DMVD). Fifty-four dogs with advanced heart failure because of DMVD. For study purposes, advanced heart failure was defined as recurrence of congestive heart failure signs despite receiving the initially prescribed dose of pimobendan, angiotensin-converting-enzyme inhibitor (ACEI), and furosemide >4 mg/kg/day. Data were collected for the time of diagnosis of Stage C heart failure and time of diagnosis of advanced heart failure. Date of death was recorded. At the diagnosis of advanced heart failure, doses of pimobendan (n = 30), furosemide (n = 28), ACEI (n = 13), and spironolactone (n = 4) were increased, with ≥1 new medications added in most dogs. After initial diagnosis of advanced heart failure, 38 (70%) dogs had additional medications adjustments (median = 2 [range, 0-27]), with the final total medication number ranging from 2-10 (median = 5). Median survival time after diagnosis of advanced heart failure was 281 days (range, 3-885 days). Dogs receiving a furosemide dose >6.70 mg/kg/day had significantly longer median survival times (402 days [range, 3-885 days] versus 129 days [range 9-853 days]; P = .017). Dogs with advanced heart failure can have relatively long survival times. Higher furosemide dose and non-hospitalization were associated with longer survival. Copyright © 2018 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

  7. Evaluation of serum biochemical marker concentrations and survival time in dogs with protein-losing enteropathy.

    Science.gov (United States)

    Equilino, Mirjam; Théodoloz, Vincent; Gorgas, Daniela; Doherr, Marcus G; Heilmann, Romy M; Suchodolski, Jan S; Steiner, Jörg M; Burgener Dvm, Iwan A

    2015-01-01

    To evaluate serum concentrations of biochemical markers and survival time in dogs with protein-losing enteropathy (PLE). Prospective study. 29 dogs with PLE and 18 dogs with food-responsive diarrhea (FRD). Data regarding serum concentrations of various biochemical markers at the initial evaluation were available for 18 of the 29 dogs with PLE and compared with findings for dogs with FRD. Correlations between biochemical marker concentrations and survival time (interval between time of initial evaluation and death or euthanasia) for dogs with PLE were evaluated. Serum C-reactive protein concentration was high in 13 of 18 dogs with PLE and in 2 of 18 dogs with FRD. Serum concentration of canine pancreatic lipase immunoreactivity was high in 3 dogs with PLE but within the reference interval in all dogs with FRD. Serum α1-proteinase inhibitor concentration was less than the lower reference limit in 9 dogs with PLE and 1 dog with FRD. Compared with findings in dogs with FRD, values of those 3 variables in dogs with PLE were significantly different. Serum calprotectin (measured by radioimmunoassay and ELISA) and S100A12 concentrations were high but did not differ significantly between groups. Seventeen of the 29 dogs with PLE were euthanized owing to this disease; median survival time was 67 days (range, 2 to 2,551 days). Serum C-reactive protein, canine pancreatic lipase immunoreactivity, and α1-proteinase inhibitor concentrations differed significantly between dogs with PLE and FRD. Most initial biomarker concentrations were not predictive of survival time in dogs with PLE.

  8. Stochastic models for time series

    CERN Document Server

    Doukhan, Paul

    2018-01-01

    This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...

  9. Rigorous bounds on survival times in circular accelerators and efficient computation of fringe-field transfer maps

    International Nuclear Information System (INIS)

    Hoffstaetter, G.H.

    1994-12-01

    Analyzing stability of particle motion in storage rings contributes to the general field of stability analysis in weakly nonlinear motion. A method which we call pseudo invariant estimation (PIE) is used to compute lower bounds on the survival time in circular accelerators. The pseudeo invariants needed for this approach are computed via nonlinear perturbative normal form theory and the required global maxima of the highly complicated multivariate functions could only be rigorously bound with an extension of interval arithmetic. The bounds on the survival times are large enough to the relevant; the same is true for the lower bounds on dynamical aperatures, which can be computed. The PIE method can lead to novel design criteria with the objective of maximizing the survival time. A major effort in the direction of rigourous predictions only makes sense if accurate models of accelerators are available. Fringe fields often have a significant influence on optical properties, but the computation of fringe-field maps by DA based integration is slower by several orders of magnitude than DA evaluation of the propagator for main-field maps. A novel computation of fringe-field effects called symplectic scaling (SYSCA) is introduced. It exploits the advantages of Lie transformations, generating functions, and scaling properties and is extremely accurate. The computation of fringe-field maps is typically made nearly two orders of magnitude faster. (orig.)

  10. Survival times with and without tube feeding in patients with dementia or psychiatric diseases in Japan.

    Science.gov (United States)

    Takayama, Keiko; Hirayama, Keisuke; Hirao, Akihiko; Kondo, Keiko; Hayashi, Hideki; Kadota, Koichi; Asaba, Hiroyuki; Ishizu, Hideki; Nakata, Kenji; Kurisu, Kairi; Oshima, Etsuko; Yokota, Osamu; Yamada, Norihito; Terada, Seishi

    2017-11-01

    It is widely supposed that there has been no evidence of increased survival in patients with advanced dementia receiving enteral tube feeding. However, more than a few studies have reported no harmful outcome from tube feeding in dementia patients compared to in patients without dementia. This was a retrospective study. Nine psychiatric hospitals in Okayama Prefecture participated in this survey. All inpatients fulfilling the entry criteria were evaluated. All subjects suffered from difficulty with oral intake. Attending physicians thought that the patients could not live without long-term artificial nutrition. The physicians decided whether to make use of long-term artificial nutrition between January 2012 and December 2014. We evaluated 185 patients. Their mean age was 76.6 ± 11.4 years. Of all subjects, patients with probable Alzheimer's disease (n = 78) formed the biggest group, schizophrenia patients (n = 44) the second, and those with vascular dementia (n = 30) the third. The median survival times were 711 days for patients with tube feeding and 61 days for patients without tube feeding. In a comparison different types of tube feeding, median survival times were 611 days for patients with a nasogastric tube and more than 1000 days for those with a percutaneous endoscopic gastrostomy tube. Patients with tube feeding survived longer than those without tube feeding, even among dementia patients. This study suggests that enteral nutrition for patients with dementia prolongs survival. Additionally, percutaneous endoscopic gastrostomy tube feeding may be safer than nasogastric tube feeding among patients in psychiatric hospitals. © 2017 Japanese Psychogeriatric Society.

  11. Estimation of direct effects for survival data by using the Aalen additive hazards model

    DEFF Research Database (Denmark)

    Martinussen, Torben; Vansteelandt, Stijn; Gerster, Mette

    2011-01-01

    We extend the definition of the controlled direct effect of a point exposure on a survival outcome, other than through some given, time-fixed intermediate variable, to the additive hazard scale. We propose two-stage estimators for this effect when the exposure is dichotomous and randomly assigned...... Aalen's additive regression for the event time, given exposure, intermediate variable and confounders. The second stage involves applying Aalen's additive model, given the exposure alone, to a modified stochastic process (i.e. a modification of the observed counting process based on the first...

  12. Systematic review of survival time in experimental mouse stroke with impact on reliability of infarct estimation

    DEFF Research Database (Denmark)

    Klarskov, Carina Kirstine; Klarskov, Mikkel Buster; Hasseldam, Henrik

    2016-01-01

    infarcts with more substantial edema. Purpose: This paper will give an overview of previous studies of experimental mouse stroke, and correlate survival time to peak time of edema formation. Furthermore, investigations of whether the included studies corrected the infarct measurements for edema...... of reasons for the translational problems from mouse experimental stroke to clinical trials probably exists, including infarct size estimations around the peak time of edema formation. Furthermore, edema is a more prominent feature of stroke in mice than in humans, because of the tendency to produce larger...... of the investigated process. Our findings indicate a need for more research in this area, and establishment of common correction methodology....

  13. Evaluation of Survival Time of Tooth Color Dental Materials in Primary Anterior Teeth

    Directory of Open Access Journals (Sweden)

    Behjat-Al-Molook Ajami

    2013-01-01

    Full Text Available Introduction: In restorative dentistry, selecting the proper material is an important factor for clinical success. The objective of this study was clinical evaluation of survival time of three tooth color materials in primary anterior teeth. Methods: In this interventional clinical trial study, 94 deciduous anterior teeth (36 teeth in boys, 58 teeth in girls belonging to 3-5 year old children in Pediatric Department of Mashhad Faculty of Dentistry, Iran were selected. Selective dental materials included compoglass, glass-ionomer Fuji II LC, and composite resin. The data were analyzed with Kaplan–Meyer and Log rank test. Results: compoglass had the highest survival time in comparison with composite and glass-ionomer. Nine months retention rate for teeth restored with compoglass, composite resin and glass-ionomer were estimated: 95%, 21%, and 12.5%, respectively. Conclusion: Compoglass can be a suitable material for anterior primary teeth restoration

  14. Evaluation of Survival Time of Tooth Color Dental Materials in Primary Anterior Teeth

    Directory of Open Access Journals (Sweden)

    Taraneh Movahhed

    2012-09-01

    Full Text Available Introduction: In restorative dentistry, selecting the proper material is an important factor for clinical success. The objective of this study was clinical evaluation of survival time of three tooth color materials in primary anterior teeth. Methods: In this interventional clinical trial study, 94 deciduous anterior teeth (36 teeth in boys, 58 teeth in girls belonging to 3-5 year old children in Pediatric Department of Mashhad Faculty of Dentistry, Iran were selected. Selective dental materials included compoglass, glass-ionomer Fuji II LC, and composite resin. The data were analyzed with Kaplan–Meyer and Log rank test. Results: compoglass had the highest survival time in comparison with composite and glass-ionomer. Nine months retention rate for teeth restored with compoglass, composite resin and glass-ionomer were estimated: 95%, 21%, and 12.5%, respectively. Conclusion: Compoglass can be a suitable material for anterior primary teeth restoration.

  15. Survivable architectures for time and wavelength division multiplexed passive optical networks

    Science.gov (United States)

    Wong, Elaine

    2014-08-01

    The increased network reach and customer base of next-generation time and wavelength division multiplexed PON (TWDM-PONs) have necessitated rapid fault detection and subsequent restoration of services to its users. However, direct application of existing solutions for conventional PONs to TWDM-PONs is unsuitable as these schemes rely on the loss of signal (LOS) of upstream transmissions to trigger protection switching. As TWDM-PONs are required to potentially use sleep/doze mode optical network units (ONU), the loss of upstream transmission from a sleeping or dozing ONU could erroneously trigger protection switching. Further, TWDM-PONs require its monitoring modules for fiber/device fault detection to be more sensitive than those typically deployed in conventional PONs. To address the above issues, three survivable architectures that are compliant with TWDM-PON specifications are presented in this work. These architectures combine rapid detection and protection switching against multipoint failure, and most importantly do not rely on upstream transmissions for LOS activation. Survivability analyses as well as evaluations of the additional costs incurred to achieve survivability are performed and compared to the unprotected TWDM-PON. Network parameters that impact the maximum achievable network reach, maximum split ratio, connection availability, fault impact, and the incremental reliability costs for each proposed survivable architecture are highlighted.

  16. Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients.

    Science.gov (United States)

    Isik, Zerrin; Ercan, Muserref Ece

    2017-10-01

    Integration of several types of patient data in a computational framework can accelerate the identification of more reliable biomarkers, especially for prognostic purposes. This study aims to identify biomarkers that can successfully predict the potential survival time of a cancer patient by integrating the transcriptomic (RNA-Seq), proteomic (RPPA), and protein-protein interaction (PPI) data. The proposed method -RPBioNet- employs a random walk-based algorithm that works on a PPI network to identify a limited number of protein biomarkers. Later, the method uses gene expression measurements of the selected biomarkers to train a classifier for the survival time prediction of patients. RPBioNet was applied to classify kidney renal clear cell carcinoma (KIRC), glioblastoma multiforme (GBM), and lung squamous cell carcinoma (LUSC) patients based on their survival time classes (long- or short-term). The RPBioNet method correctly identified the survival time classes of patients with between 66% and 78% average accuracy for three data sets. RPBioNet operates with only 20 to 50 biomarkers and can achieve on average 6% higher accuracy compared to the closest alternative method, which uses only RNA-Seq data in the biomarker selection. Further analysis of the most predictive biomarkers highlighted genes that are common for both cancer types, as they may be driver proteins responsible for cancer progression. The novelty of this study is the integration of a PPI network with mRNA and protein expression data to identify more accurate prognostic biomarkers that can be used for clinical purposes in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Comparison of hypertabastic survival model with other unimodal hazard rate functions using a goodness-of-fit test.

    Science.gov (United States)

    Tahir, M Ramzan; Tran, Quang X; Nikulin, Mikhail S

    2017-05-30

    We studied the problem of testing a hypothesized distribution in survival regression models when the data is right censored and survival times are influenced by covariates. A modified chi-squared type test, known as Nikulin-Rao-Robson statistic, is applied for the comparison of accelerated failure time models. This statistic is used to test the goodness-of-fit for hypertabastic survival model and four other unimodal hazard rate functions. The results of simulation study showed that the hypertabastic distribution can be used as an alternative to log-logistic and log-normal distribution. In statistical modeling, because of its flexible shape of hazard functions, this distribution can also be used as a competitor of Birnbaum-Saunders and inverse Gaussian distributions. The results for the real data application are shown. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  18. A Multiscale Survival Process for Modeling Human Activity Patterns.

    Science.gov (United States)

    Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

    2016-01-01

    Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

  19. Association of the Timing of Pregnancy With Survival in Women With Breast Cancer

    Science.gov (United States)

    Iqbal, Javaid; Amir, Eitan; Rochon, Paula A.; Giannakeas, Vasily; Sun, Ping

    2017-01-01

    Importance Increasing numbers of women experience pregnancy around the time of, or after, a diagnosis of breast cancer. Understanding the effect of pregnancy on survival in women with breast cancer will help in the counseling and treatment of these women. Objective To compare the overall survival of women diagnosed with breast cancer during pregnancy or in the postpartum period with that of women who had breast cancer but did not become pregnant. Design, Setting, and Participants This population-based, retrospective cohort study linked health administrative databases in Ontario, Canada, comprising 7553 women aged 20 to 45 years at the time of diagnosis with invasive breast cancer, from January 1, 2003, to December 31, 2014. Exposures Any pregnancy in the period from 5 years before, until 5 years after, the index date of the diagnosis of breast cancer. Women were classified into the following 4 exposure groups: no pregnancy (the referent), pregnancy before breast cancer, pregnancy-associated breast cancer, and pregnancy following breast cancer. Main Outcomes and Measures Five-year actuarial survival rates for all exposure groups, age-adjusted and multivariable hazard ratios [HRs] of pregnancy for overall survival for all exposure groups, and time-dependent hazard ratios for women with pregnancy following breast cancer. Results Among the 7553 women in the study (mean age at diagnosis, 39.1 years; median, 40 years; range, 20-44 years) the 5-year actuarial survival rate was 87.5% (95% CI, 86.5%-88.4%) for women with no pregnancy, 85.3% (95% CI, 82.8%-87.8%) for women with pregnancy before breast cancer (age-adjusted hazard ratio, 1.03; 95% CI, 0.85-1.27; P = .73), and 82.1% (95% CI, 78.3%-85.9%) for women with pregnancy-associated breast cancer (age-adjusted hazard ratio, 1.18; 95% CI, 0.91-1.53; P = .20). The 5-year actuarial survival rate was 96.7% (95% CI, 94.1%-99.3%) for women who had pregnancy 6 months or more after diagnosis of breast cancer, vs 87

  20. A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

    Energy Technology Data Exchange (ETDEWEB)

    Oberije, Cary, E-mail: cary.oberije@maastro.nl [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); De Ruysscher, Dirk [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Universitaire Ziekenhuizen Leuven, KU Leuven (Belgium); Houben, Ruud [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Heuvel, Michel van de; Uyterlinde, Wilma [Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Deasy, Joseph O. [Memorial Sloan Kettering Cancer Center, New York (United States); Belderbos, Jose [Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Dingemans, Anne-Marie C. [Department of Pulmonology, University Hospital Maastricht, Research Institute GROW of Oncology, Maastricht (Netherlands); Rimner, Andreas; Din, Shaun [Memorial Sloan Kettering Cancer Center, New York (United States); Lambin, Philippe [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands)

    2015-07-15

    Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

  1. Timely disclosure of progress in long-term cancer survival: the boomerang method substantially improved estimates in a comparative study.

    Science.gov (United States)

    Brenner, Hermann; Jansen, Lina

    2016-02-01

    Monitoring cancer survival is a key task of cancer registries, but timely disclosure of progress in long-term survival remains a challenge. We introduce and evaluate a novel method, denoted "boomerang method," for deriving more up-to-date estimates of long-term survival. We applied three established methods (cohort, complete, and period analysis) and the boomerang method to derive up-to-date 10-year relative survival of patients diagnosed with common solid cancers and hematological malignancies in the United States. Using the Surveillance, Epidemiology and End Results 9 database, we compared the most up-to-date age-specific estimates that might have been obtained with the database including patients diagnosed up to 2001 with 10-year survival later observed for patients diagnosed in 1997-2001. For cancers with little or no increase in survival over time, the various estimates of 10-year relative survival potentially available by the end of 2001 were generally rather similar. For malignancies with strongly increasing survival over time, including breast and prostate cancer and all hematological malignancies, the boomerang method provided estimates that were closest to later observed 10-year relative survival in 23 of the 34 groups assessed. The boomerang method can substantially improve up-to-dateness of long-term cancer survival estimates in times of ongoing improvement in prognosis. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. The Impact of Radiation Treatment Time on Survival in Patients With Head and Neck Cancer

    International Nuclear Information System (INIS)

    Shaikh, Talha; Handorf, Elizabeth A.; Murphy, Colin T.; Mehra, Ranee; Ridge, John A.; Galloway, Thomas J.

    2016-01-01

    Purpose: To assess the impact of radiation treatment time (RTT) in head and neck cancers on overall survival (OS) in the era of chemoradiation. Methods and Materials: Patients with diagnoses of tongue, hypopharynx, larynx, oropharynx, or tonsil cancer were identified by use of the National Cancer Database. RTT was defined as date of first radiation treatment to date of last radiation treatment. In the definitive setting, prolonged RTT was defined as >56 days, accelerated RTT was defined as 49 days, accelerated RTT was defined as <40 days, and standard RTT was defined as 40 to 49 days. We used χ"2 tests to identify predictors of RTT. The Kaplan-Meier method was used to compare OS among groups. Cox proportional hazards model was used for OS analysis in patients with known comorbidity status. Results: 19,531 patients were included; 12,987 (67%) had a standard RTT, 4,369 (34%) had an accelerated RTT, and 2,165 (11%) had a prolonged RTT. On multivariable analysis, accelerated RTT (hazard ratio [HR] 0.84; 95% confidence interval [CI] 0.73-0.97) was associated with an improved OS, and prolonged RTT (HR 1.25; 95% CI 1.14-1.37) was associated with a worse OS relative to standard RTT. When the 9,200 (47%) patients receiving definitive concurrent chemoradiation were examined, prolonged RTT (HR 1.29; 95% CI 1.11-1.50) was associated with a worse OS relative to standard RTT, whereas there was no significant association between accelerated RTT and OS (HR 0.76; 95% CI 0.57-1.01). Conclusion: Prolonged RTT is associated with worse OS in patients receiving radiation therapy for head and neck cancer, even in the setting of chemoradiation. Expeditious completion of radiation should continue to be a quality metric for the management of head and neck malignancies.

  3. Expectation-maximization algorithms for learning a finite mixture of univariate survival time distributions from partially specified class values

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Youngrok [Iowa State Univ., Ames, IA (United States)

    2013-05-15

    Heterogeneity exists on a data set when samples from di erent classes are merged into the data set. Finite mixture models can be used to represent a survival time distribution on heterogeneous patient group by the proportions of each class and by the survival time distribution within each class as well. The heterogeneous data set cannot be explicitly decomposed to homogeneous subgroups unless all the samples are precisely labeled by their origin classes; such impossibility of decomposition is a barrier to overcome for estimating nite mixture models. The expectation-maximization (EM) algorithm has been used to obtain maximum likelihood estimates of nite mixture models by soft-decomposition of heterogeneous samples without labels for a subset or the entire set of data. In medical surveillance databases we can find partially labeled data, that is, while not completely unlabeled there is only imprecise information about class values. In this study we propose new EM algorithms that take advantages of using such partial labels, and thus incorporate more information than traditional EM algorithms. We particularly propose four variants of the EM algorithm named EM-OCML, EM-PCML, EM-HCML and EM-CPCML, each of which assumes a specific mechanism of missing class values. We conducted a simulation study on exponential survival trees with five classes and showed that the advantages of incorporating substantial amount of partially labeled data can be highly signi cant. We also showed model selection based on AIC values fairly works to select the best proposed algorithm on each specific data set. A case study on a real-world data set of gastric cancer provided by Surveillance, Epidemiology and End Results (SEER) program showed a superiority of EM-CPCML to not only the other proposed EM algorithms but also conventional supervised, unsupervised and semi-supervised learning algorithms.

  4. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    International Nuclear Information System (INIS)

    Taktak, Azzam F G; Fisher, Anthony C; Damato, Bertil E

    2004-01-01

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate

  5. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    Energy Technology Data Exchange (ETDEWEB)

    Taktak, Azzam F G [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Fisher, Anthony C [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Damato, Bertil E [Department of Ophthalmology, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom)

    2004-01-07

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate.

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

    Science.gov (United States)

    Shek, L L; Godolphin, W

    1988-10-01

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

  7. Modeling the survivability of brucella to exposure of Ultraviolet radiation and temperature

    Science.gov (United States)

    Howe, R.

    Accumulated summation of daily Ultra Violet-B (UV-B = 290? to 320 ? ) data? from The USDA Ultraviolet Radiation Monitoring Program show good correlation (R^2 = 77%) with daily temperature data during the five month period from February through June, 1998. Exposure of disease organisms, such as brucella to the effects of accumulated UV-B radiation, can be modeled for a 5 month period from February through June, 1998. Estimates of a lethal dosage for brucell of UV-B in the environment is dependent on minimum/maximum temperature and Solar Zenith Angle for the time period. The accumulated increase in temperature over this period also effects the decomposition of an aborted fetus containing brucella. Decomposition begins at some minimum daily temperature at 27 to 30 degrees C and peaks at 39 to 40C. It is useful to view the summation of temperature as a threshold for other bacteria growth, so that accumulated temperature greater than some value causes decomposition through competition with other bacteria and brucella die from the accumulated effects of UV-B, temperature and organism competition. Results of a study (Cook 1998) to determine survivability of brucellosis in the environment through exposure of aborted bovine fetuses show no one cause can be attributed to death of the disease agent. The combination of daily increase in temperature and accumulated UV-B radiation reveal an inverse correlation to survivability data and can be modeled as an indicator of brucella survivability in the environment in arid regions.

  8. [The survival prediction model of advanced gallbladder cancer based on Bayesian network: a multi-institutional study].

    Science.gov (United States)

    Tang, Z H; Geng, Z M; Chen, C; Si, S B; Cai, Z Q; Song, T Q; Gong, P; Jiang, L; Qiu, Y H; He, Y; Zhai, W L; Li, S P; Zhang, Y C; Yang, Y

    2018-05-01

    Objective: To investigate the clinical value of Bayesian network in predicting survival of patients with advanced gallbladder cancer(GBC)who underwent curative intent surgery. Methods: The clinical data of patients with advanced GBC who underwent curative intent surgery in 9 institutions from January 2010 to December 2015 were analyzed retrospectively.A median survival time model based on a tree augmented naïve Bayes algorithm was established by Bayesia Lab software.The survival time, number of metastatic lymph nodes(NMLN), T stage, pathological grade, margin, jaundice, liver invasion, age, sex and tumor morphology were included in this model.Confusion matrix, the receiver operating characteristic curve and area under the curve were used to evaluate the accuracy of the model.A priori statistical analysis of these 10 variables and a posterior analysis(survival time as the target variable, the remaining factors as the attribute variables)was performed.The importance rankings of each variable was calculated with the polymorphic Birnbaum importance calculation based on the posterior analysis results.The survival probability forecast table was constructed based on the top 4 prognosis factors. The survival curve was drawn by the Kaplan-Meier method, and differences in survival curves were compared using the Log-rank test. Results: A total of 316 patients were enrolled, including 109 males and 207 females.The ratio of male to female was 1.0∶1.9, the age was (62.0±10.8)years.There was 298 cases(94.3%) R0 resection and 18 cases(5.7%) R1 resection.T staging: 287 cases(90.8%) T3 and 29 cases(9.2%) T4.The median survival time(MST) was 23.77 months, and the 1, 3, 5-year survival rates were 67.4%, 40.8%, 32.0%, respectively.For the Bayesian model, the number of correctly predicted cases was 121(≤23.77 months) and 115(>23.77 months) respectively, leading to a 74.86% accuracy of this model.The prior probability of survival time was 0.503 2(≤23.77 months) and 0.496 8

  9. Estimation and model selection of semiparametric multivariate survival functions under general censorship.

    Science.gov (United States)

    Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

    2010-07-01

    We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root- n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

  10. An exploratory discrete-time multilevel analysis of the effect of social support on the survival of elderly people in China

    Science.gov (United States)

    Feng, Zhixin; Jones, Kelvyn; Wang, Wenfei Winnie

    2015-01-01

    This study undertakes a survival analysis of elderly persons in China using Chinese Longitudinal Healthy Longevity Survey 2002–2008. Employing discrete-time multilevel models, we explored the effect of social support on the survival of elderly people in China. This study focuses on objective (living arrangements and received support) and subjective activities (perceived support) of social support, finding that the effect of different activities of social support on the survival of elderly people varies according to the availability of different support resources. Specifically, living with a spouse, financial independence, perceiving care support from any resource is associated with higher survival rates for elderly people. Separate analysis focusing on urban elderly and rural elderly revealed broadly similar results. There is a larger difference between those perceiving care support from family or social service and not perceiving care support in urban areas comparing to those in rural areas. Those who cannot pay medical expenses are the least likely to survive. The higher level of economic development in province has no significant effect on the survival of elderly people for the whole sample model and the elderly people in urban areas; however, there is a negative influence on the survival of the rural elderly people. PMID:25703671

  11. Does prehospital time affect survival of major trauma patients where there is no prehospital care?

    Directory of Open Access Journals (Sweden)

    S B Dharap

    2017-01-01

    Full Text Available Background: Survival after major trauma is considered to be time dependent. Efficient prehospital care with rapid transport is the norm in developed countries, which is not available in many lower middle and low-income countries. The aim of this study was to assess the effect of prehospital time and primary treatment given on survival of major trauma patients in a setting without prehospital care. Materials and Methods: This prospective observational study was carried out in a university hospital in Mumbai, from January to December 2014. The hospital has a trauma service but no organized prehospital care or defined interhospital transfer protocols. All patients with life- and/or limb-threatening injuries were included in the study. Injury time and arrival time were noted and the interval was defined as “prehospital time” for the directly arriving patients and as “time to tertiary care” for those transferred. Primary outcome measure was in-hospital death (or discharge. Results: Of 1181 patients, 352 were admitted directly from the trauma scene and 829 were transferred from other hospitals. In-hospital mortality was associated with age, mechanism and mode of injury, shock, Glasgow Coma Score <9, Injury Severity Score ≥16, need for intubation, and ventilatory support on arrival; but neither with prehospital time nor with time to tertiary care. Transferred patients had a significantly higher mortality (odds ratio = 1.869, 95% confidence interval = 1.233–2.561, P = 0.005 despite fewer patients with severe injury. Two hundred and ninety-four (35% of these needed airway intervention while 108 (13% needed chest tube insertion on arrival to the trauma unit suggesting inadequate care at primary facility. Conclusion: Mortality is not associated with prehospital time but with transfers from primary care; probably due to deficient care. To improve survival after major trauma, enhancement of resources for resuscitation and capacity building of on

  12. A survival model for fractionated radiotherapy with an application to prostate cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zaider, Marco [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)]. E-mail: Zaiderm@mskcc.org; Zelefsky, Michael J.; Leibel, Steven A. [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Hanin, Leonid G. [Department of Mathematics, Idaho State University, Pocatello, ID (United States); Tsodikov, Alexander D.; Yakovlev, Andrei Y. [Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (United States)

    2001-10-01

    This paper explores the applicability of a mechanistic survival model, based on the distribution of clonogens surviving a course of fractionated radiation therapy, to clinical data on patients with prostate cancer. The study was carried out using data on 1100 patients with clinically localized prostate cancer who were treated with three-dimensional conformal radiation therapy. The patients were stratified by radiation dose (group 1: <67.5 Gy; group 2: 67.5-72.5 Gy; group 3: 72.5-77.5 Gy; group 4: 77.5-87.5 Gy) and prognosis category (favourable, intermediate and unfavourable as defined by pre-treatment PSA and Gleason score). A relapse was recorded when tumour recurrence was diagnosed or when three successive prostate specific antigen (PSA) elevations were observed from a post-treatment nadir PSA level. PSA relapse-free survival was used as the primary end point. The model, which is based on an iterated Yule process, is specified in terms of three parameters: the mean number of tumour clonogens that survive the treatment, the mean of the progression time of post-treatment tumour development and its standard deviation. The model parameters were estimated by the maximum likelihood method. The fact that the proposed model provides an excellent description both of the survivor function and of the hazard rate is prima facie evidence of the validity of the model because closeness of the two survivor functions (empirical and model-based) does not generally imply closeness of the corresponding hazard rates. The estimated cure probabilities for the favourable group are 0.80, 0.74 and 0.87 (for dose groups 1-3, respectively); for the intermediate group: 0.25, 0.51, 0.58 and 0.78 (for dose groups 1-4, respectively) and for the unfavourable group: 0.0, 0.27, 0.33 and 0.64 (for dose groups 1-4, respectively). The distribution of progression time to tumour relapse was found to be independent of prognosis group but dependent on dose. As the dose increases the mean progression

  13. Timing of adjuvant chemotherapy and its relation to survival among patients with stage III colon cancer.

    Science.gov (United States)

    Bos, A C R K; van Erning, F N; van Gestel, Y R B M; Creemers, G J M; Punt, C J A; van Oijen, M G H; Lemmens, V E P P

    2015-11-01

    Currently available data suggest that delaying the start of adjuvant chemotherapy in colon cancer patients has a detrimental effect on survival. We analysed which factors impact on the timing of adjuvant chemotherapy and evaluated the influence on overall survival (OS). Stage III colon cancer patients who underwent resection and received adjuvant chemotherapy between 2008 and 2013 were selected from the Netherlands Cancer Registry. Timing of adjuvant chemotherapy was subdivided into: ⩽ 4, 5-6, 7-8, 9-10, 11-12 and 13-16 weeks post-surgery. Multivariable regressions were performed to assess the influence of several factors on the probability of starting treatment within 8 weeks post-surgery and to evaluate the association of timing of adjuvant chemotherapy with 5-year OS. 6620 patients received adjuvant chemotherapy, 14% commenced after 8 weeks. Factors associated with starting treatment after 8 weeks were older age (Odds ratio (OR) 65-74 versus colon cancer patients within 8 weeks post-surgery. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Using Concurrent Cardiovascular Information to Augment Survival Time Data from Orthostatic Tilt Tests

    Science.gov (United States)

    Feiveson, Alan H.; Fiedler, James; Lee, Stuart M. M.; Westby, Christian M.; Stenger, Michael B.; Platts, Steven H.

    2014-01-01

    Orthostatic Intolerance (OI) is the propensity to develop symptoms of fainting during upright standing. OI is associated with changes in heart rate, blood pressure and other measures of cardiac function. Problem: NASA astronauts have shown increased susceptibility to OI on return from space missions. Current methods for counteracting OI in astronauts include fluid loading and the use of compression garments. Multivariate trajectory spread is greater as OI increases. Pairwise comparisons at the same time within subjects allows incorporation of pass/fail outcomes. Path length, convex hull area, and covariance matrix determinant do well as statistics to summarize this spread Missing data problems Time series analysis need many more time points per OTT session treatment of trend? how incorporate survival information?

  15. Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock

    Science.gov (United States)

    Loman, Zachary G.; Monroe, Adrian; Riffell, Samuel K.; Miller, Darren A.; Vilella, Francisco; Wheat, Bradley R.; Rush, Scott A.; Martin, James A.

    2018-01-01

    Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA.We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.Synthesis and applications. Community models represent a viable

  16. 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.

  17. Exposure to aged crumb rubber reduces survival time during a stress test in earthworms (Eisenia fetida).

    Science.gov (United States)

    Pochron, Sharon; Nikakis, Jacqueline; Illuzzi, Kyra; Baatz, Andrea; Demirciyan, Loriana; Dhillon, Amritjot; Gaylor, Thomas; Manganaro, Alexa; Maritato, Nicholas; Moawad, Michael; Singh, Rajwinder; Tucker, Clara; Vaughan, Daniel

    2018-04-01

    Solid waste management struggles with the sustainable disposal of used tires. One solution involves shredding used tires into crumb rubber and using the material as infill for artificial turf. However, crumb rubber contains hydrocarbons, organic compounds, and heavy metals, and it travels into the environment. Earthworms living in soil contaminated with virgin crumb rubber gained 14% less body weight than did earthworms living in uncontaminated soil, but the impact of aged crumb rubber on the earthworms is unknown. Since many athletic fields contain aged crumb rubber, we compared the body weight, survivorship, and longevity in heat and light stress for earthworms living in clean topsoil to those living in topsoil contaminated with aged crumb rubber. We also characterized levels of metals, nutrients, and micronutrients of both soil treatments and compared those to published values for soil contaminated with virgin crumb rubber. Consistent with earlier research, we found that contaminated soil did not inhibit microbial respiration rates. Aged crumb rubber, like new crumb rubber, had high levels of zinc. However, while exposure to aged crumb rubber did not reduce earthworm body weight as did exposure to new crumb rubber, exposure to aged crumb rubber reduced earthworm survival time during a stress test by a statistically significant 38 min (16.2%) relative to the survival time for worms that had lived in clean soil. Aged crumb rubber and new crumb rubber appear to pose similar toxic risks to earthworms. This study suggests an environmental cost associated with the current tire-recycling solution.

  18. The Impact of Radiation Treatment Time on Survival in Patients With Head and Neck Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Shaikh, Talha [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania (United States); Handorf, Elizabeth A. [Department of Biostatistics, Fox Chase Cancer Center, Philadelphia, Pennsylvania (United States); Murphy, Colin T. [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania (United States); Mehra, Ranee [Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania (United States); Ridge, John A. [Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania (United States); Galloway, Thomas J., E-mail: Thomas.Galloway@fccc.edu [Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania (United States)

    2016-12-01

    Purpose: To assess the impact of radiation treatment time (RTT) in head and neck cancers on overall survival (OS) in the era of chemoradiation. Methods and Materials: Patients with diagnoses of tongue, hypopharynx, larynx, oropharynx, or tonsil cancer were identified by use of the National Cancer Database. RTT was defined as date of first radiation treatment to date of last radiation treatment. In the definitive setting, prolonged RTT was defined as >56 days, accelerated RTT was defined as <47 days, and standard RTT was defined as 47 to 56 days. In the postoperative setting, prolonged RTT was defined as >49 days, accelerated RTT was defined as <40 days, and standard RTT was defined as 40 to 49 days. We used χ{sup 2} tests to identify predictors of RTT. The Kaplan-Meier method was used to compare OS among groups. Cox proportional hazards model was used for OS analysis in patients with known comorbidity status. Results: 19,531 patients were included; 12,987 (67%) had a standard RTT, 4,369 (34%) had an accelerated RTT, and 2,165 (11%) had a prolonged RTT. On multivariable analysis, accelerated RTT (hazard ratio [HR] 0.84; 95% confidence interval [CI] 0.73-0.97) was associated with an improved OS, and prolonged RTT (HR 1.25; 95% CI 1.14-1.37) was associated with a worse OS relative to standard RTT. When the 9,200 (47%) patients receiving definitive concurrent chemoradiation were examined, prolonged RTT (HR 1.29; 95% CI 1.11-1.50) was associated with a worse OS relative to standard RTT, whereas there was no significant association between accelerated RTT and OS (HR 0.76; 95% CI 0.57-1.01). Conclusion: Prolonged RTT is associated with worse OS in patients receiving radiation therapy for head and neck cancer, even in the setting of chemoradiation. Expeditious completion of radiation should continue to be a quality metric for the management of head and neck malignancies.

  19. Frozen in Time? Microbial strategies for survival and carbon metabolism over geologic time in a Pleistocene permafrost chronosequence

    Science.gov (United States)

    Mackelprang, R.; Douglas, T. A.; Waldrop, M. P.

    2014-12-01

    Permafrost soils have received tremendous interest due to their importance as a global carbon store with the potential to be thawed over the coming centuries. Instead of being 'frozen in time,' permafrost contains active microbes. Most metagenomic studies have focused on Holocene aged permafrost. Here, we target Pleistocene aged ice and carbon rich permafrost (Yedoma), which can differ in carbon content and stage of decay. Our aim was to understand how microbes in the permafrost transform organic matter over geologic time and to identify physiological and biochemical adaptations that enable long-term survival. We used next-generation sequencing to characterize microbial communities along a permafrost age gradient. Samples were collected from the Cold Regions Research and Engineering Laboratory (CRREL) Permafrost Tunnel near Fox, AK, which penetrates a hillside providing access to permafrost ranging in age from 12 to 40 kyr. DNA was extracted directly from unthawed samples. 16S rRNA amplicon (16S) and shotgun metagenome sequencing revealed significant age-driven differences. First, microbial diversity declines with permafrost age, likely due to long-term exposure to environmental stresses and a reduction in metabolic resources. Second, we observed taxonomic differences among ages, with an increasing abundance of Firmicutes (endospore-formers) in older samples, suggesting that dormancy is a common survival strategy in older permafrost. Ordination of 16S and metagenome data revealed age-based clustering. Genes differing significantly between age categories included those involved in lipopolysaccharide assembly, cold-response, and carbon processing. These data point to the physiological adaptations to long-term frozen conditions and to the metabolic processes utilized in ancient permafrost. In fact, a gene common in older samples is involved in cadaverine production, which could potentially explain the putrefied smell of Pleistocene aged permafrost. Coupled with soil

  20. Ensemble of cell survival experiments after ion irradiation for validation of RBE models

    Energy Technology Data Exchange (ETDEWEB)

    Friedrich, Thomas; Scholz, Uwe; Scholz, Michael [GSI Helmholtzzentrum fuer Schwerionenforschung, Darmstadt (Germany); Durante, Marco [GSI Helmholtzzentrum fuer Schwerionenforschung, Darmstadt (Germany); Institut fuer Festkoerperphysik, TU Darmstadt, Darmstadt (Germany)

    2012-07-01

    There is persistent interest in understanding the systematics of the relative biological effectiveness (RBE). Models such as the Local Effect Model (LEM) or the Microdosimetric Kinetic Model have the goal to predict the RBE. For the validation of these models a collection of many in-vitro cell survival experiments is most appropriate. The set-up of an ensemble of in-vitro cell survival data comprising about 850 survival experiments after both ion and photon irradiation is reported. The survival curves have been taken out from publications. The experiments encompass survival curves obtained in different labs, using different ion species from protons to uranium, varying irradiation modalities (shaped or monoenergetic beam), various energies and linear energy transfers, and a whole variety of cell types (human or rodent; normal, mutagenic or tumor; radioresistant or -sensitive). Each cell survival curve has been parameterized by the linear-quadratic model. The photon parameters have been added to the data base to allow to calculate the experimental RBE to any survival level. We report on experimental trends found within the data ensemble. The data will serve as a testing ground for RBE models such as the LEM. Finally, a roadmap for further validation and first model results using the data base in combination with the LEM are presented.

  1. Evaluating time to cancer recurrence as a surrogate marker for survival from an information theory perspective.

    Science.gov (United States)

    Alonso, Ariel; Molenberghs, Geert

    2008-10-01

    The last two decades have seen a lot of development in the area of surrogate marker validation. One of these approaches places the evaluation in a meta-analytic framework, leading to definitions in terms of trial- and individual-level association. A drawback of this methodology is that different settings have led to different measures at the individual level. Using information theory, Alonso et al. proposed a unified framework, leading to a new definition of surrogacy, which offers interpretational advantages and is applicable in a wide range of situations. In this work, we illustrate how this information-theoretic approach can be used to evaluate surrogacy when both endpoints are of a time-to-event type. Two meta-analyses, in early and advanced colon cancer, respectively, are then used to evaluate the performance of time to cancer recurrence as a surrogate for overall survival.

  2. Survival of viral pathogens in animal feed ingredients under transboundary shipping models

    Science.gov (United States)

    Bauermann, Fernando V.; Niederwerder, Megan C.; Singrey, Aaron; Clement, Travis; de Lima, Marcelo; Long, Craig; Patterson, Gilbert; Sheahan, Maureen A.; Stoian, Ana M. M.; Petrovan, Vlad; Jones, Cassandra K.; De Jong, Jon; Ji, Ju; Spronk, Gordon D.; Minion, Luke; Christopher-Hennings, Jane; Zimmerman, Jeff J.; Rowland, Raymond R. R.; Nelson, Eric; Sundberg, Paul; Diel, Diego G.

    2018-01-01

    The goal of this study was to evaluate survival of important viral pathogens of livestock in animal feed ingredients imported daily into the United States under simulated transboundary conditions. Eleven viruses were selected based on global significance and impact to the livestock industry, including Foot and Mouth Disease Virus (FMDV), Classical Swine Fever Virus (CSFV), African Swine Fever Virus (ASFV), Influenza A Virus of Swine (IAV-S), Pseudorabies virus (PRV), Nipah Virus (NiV), Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), Swine Vesicular Disease Virus (SVDV), Vesicular Stomatitis Virus (VSV), Porcine Circovirus Type 2 (PCV2) and Vesicular Exanthema of Swine Virus (VESV). Surrogate viruses with similar genetic and physical properties were used for 6 viruses. Surrogates belonged to the same virus families as target pathogens, and included Senecavirus A (SVA) for FMDV, Bovine Viral Diarrhea Virus (BVDV) for CSFV, Bovine Herpesvirus Type 1 (BHV-1) for PRV, Canine Distemper Virus (CDV) for NiV, Porcine Sapelovirus (PSV) for SVDV and Feline Calicivirus (FCV) for VESV. For the remaining target viruses, actual pathogens were used. Virus survival was evaluated using Trans-Pacific or Trans-Atlantic transboundary models involving representative feed ingredients, transport times and environmental conditions, with samples tested by PCR, VI and/or swine bioassay. SVA (representing FMDV), FCV (representing VESV), BHV-1 (representing PRV), PRRSV, PSV (representing SVDV), ASFV and PCV2 maintained infectivity during transport, while BVDV (representing CSFV), VSV, CDV (representing NiV) and IAV-S did not. Notably, more viruses survived in conventional soybean meal, lysine hydrochloride, choline chloride, vitamin D and pork sausage casings. These results support published data on transboundary risk of PEDV in feed, demonstrate survival of certain viruses in specific feed ingredients (“high-risk combinations”) under conditions simulating transport between

  3. Preoperative diffusion-weighted imaging of single brain metastases correlates with patient survival times.

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    Anna Sophie Berghoff

    Full Text Available BACKGROUND: MRI-based diffusion-weighted imaging (DWI visualizes the local differences in water diffusion in vivo. The prognostic value of DWI signal intensities on the source images and apparent diffusion coefficient (ADC maps respectively has not yet been studied in brain metastases (BM. METHODS: We included into this retrospective analysis all patients operated for single BM at our institution between 2002 and 2010, in whom presurgical DWI and BM tissue samples were available. We recorded relevant clinical data, assessed DWI signal intensity and apparent diffusion coefficient (ADC values and performed histopathological analysis of BM tissues. Statistical analyses including uni- and multivariate survival analyses were performed. RESULTS: 65 patients (34 female, 31 male with a median overall survival time (OS of 15 months (range 0-99 months were available for this study. 19 (29.2% patients presented with hyper-, 3 (4.6% with iso-, and 43 (66.2% with hypointense DWI. ADCmean values could be determined in 32 (49.2% patients, ranged from 456.4 to 1691.8*10⁻⁶ mm²/s (median 969.5 and showed a highly significant correlation with DWI signal intensity. DWI hyperintensity correlated significantly with high amount of interstitial reticulin deposition. In univariate analysis, patients with hyperintense DWI (5 months and low ADCmean values (7 months had significantly worse OS than patients with iso/hypointense DWI (16 months and high ADCmean values (30 months, respectively. In multivariate survival analysis, high ADCmean values retained independent statistical significance. CONCLUSIONS: Preoperative DWI findings strongly and independently correlate with OS in patients operated for single BM and are related to interstitial fibrosis. Inclusion of DWI parameters into established risk stratification scores for BM patients should be considered.

  4. The synthetic parasite-derived peptide GK1 increases survival in a preclinical mouse melanoma model.

    Science.gov (United States)

    Pérez-Torres, Armando; Vera-Aguilera, Jesús; Hernaiz-Leonardo, Juan Carlos; Moreno-Aguilera, Eduardo; Monteverde-Suarez, Diego; Vera-Aguilera, Carlos; Estrada-Bárcenas, Daniel

    2013-11-01

    The therapeutic efficacy of a synthetic parasite-derived peptide GK1, an immune response booster, was evaluated in a mouse melanoma model. This melanoma model correlates with human stage IIb melanoma, which is treated with wide surgical excision; a parallel study employing a surgical treatment was carried out as an instructive goal. C57BL/6 mice were injected subcutaneously in the flank with 2×10(5) B16-F10 murine melanoma cells. When the tumors reached 20 mm3, mice were separated into two different groups; the GK1 group, treated weekly with peritumoral injections of GK1 (10 μg/100 μL of sterile saline solution) and the control group, treated weekly with an antiseptic peritumoral injection of 100 μL of sterile saline solution without further intervention. All mice were monitored daily for clinical appearance, tumor size, and survival. Surgical treatment was performed in parallel when the tumor size was 20 mm3 (group A), 500 mm3 (group B), and >500 mm3 (group C). The GK1 peptide effectively increased the mean survival time by 9.05 days, corresponding to an increase of 42.58%, and significantly delayed tumor growth from day 3 to 12 of treatment. In addition, tumor necrosis was significantly increased (pcancers remains to be determined, and surgical removal remains a challenge for any new experimental treatment of melanoma in mouse models.

  5. Analyzing survival curves at a fixed point in time for paired and clustered right-censored data

    Science.gov (United States)

    Su, Pei-Fang; Chi, Yunchan; Lee, Chun-Yi; Shyr, Yu; Liao, Yi-De

    2018-01-01

    In clinical trials, information about certain time points may be of interest in making decisions about treatment effectiveness. Rather than comparing entire survival curves, researchers can focus on the comparison at fixed time points that may have a clinical utility for patients. For two independent samples of right-censored data, Klein et al. (2007) compared survival probabilities at a fixed time point by studying a number of tests based on some transformations of the Kaplan-Meier estimators of the survival function. However, to compare the survival probabilities at a fixed time point for paired right-censored data or clustered right-censored data, their approach would need to be modified. In this paper, we extend the statistics to accommodate the possible within-paired correlation and within-clustered correlation, respectively. We use simulation studies to present comparative results. Finally, we illustrate the implementation of these methods using two real data sets. PMID:29456280

  6. Impact of latency time on survival for adolescents and young adults with a second primary malignancy.

    Science.gov (United States)

    Goldfarb, Melanie; Rosenberg, Aaron S; Li, Qian; Keegan, Theresa H M

    2018-03-15

    The adverse impact of second primary malignancies (SPMs) on survival is substantial for adolescents and young adults (AYAs; ie, those 15-39 years old). No studies have evaluated whether the latency time between the first malignancy (the primary malignancy [PM]) and the SPM affects cancer-specific survival (CSS). A multivariate Cox proportional hazards regression with Surveillance, Epidemiology, and End Results data for 13 regions from 1992 to 2008 was used to ascertain whether the latency time (1-5 vs ≥ 6 years) to the development of an SPM affected the CSS and overall survival with respect to either the PM or SPM for AYAs with common SPMs. The majority of 1515 AYAs with an SPM had their PM diagnosed between the ages of 26 and 39 years (74.2%) and an SPM diagnosed within 1 to 5 years (72.9%) of the PM's diagnosis. Overall, AYAs that developed an SPM 1 to 5 years after the diagnosis (vs ≥ 6 years) had an increased risk of death from cancer (hazard ratio [HR], 2.52; 95% confidence interval [CI], 1.92-3.29) as well as any cause (HR, 2.60; 95% CI, 2.04-3.32). Specifically, for AYAs with an SPM that was leukemia or a colorectal, breast, or central nervous system malignancy, a shorter latency time (1-5 years) from their PM diagnosis was associated with an overall significantly increased risk of death (2.6-fold) from either their PM or that particular SPM. However, latency did not appear to affect the CSS with respect to either the PM or SPM for AYA patients with a lymphoma or sarcoma SPM. Most AYAs who develop an SPM do so within 1 to 5 years of their primary cancer diagnosis, and they have an increased risk of death from cancer in comparison with AYAs with an SPM developing after longer survivorship intervals. Cancer 2018;124:1260-8. © 2017 American Cancer Society. © 2017 American Cancer Society.

  7. Splenectomy increases the survival time of heart allograft via developing immune tolerance

    Science.gov (United States)

    2013-01-01

    Background The spleen is an active lymphoid organ. The effect of splenectomy on the immune response remains unclear. This study investigated whether splenectomy can induce immune tolerance and has a beneficial role in cardiac allograft. Methods Wistar rats were used for heart donors. The Sprague–Dawley (SD) rats designated as the recipients of heart transplantation (HT) were randomly assigned into four groups: sham, splenectomy, HT, splenectomy + HT. The survival of transplanted hearts was assessed by daily checking of abdominal palpation. At various time points after transplantation, the transplanted hearts were collected and histologically examined; the level of CD4+CD25+ T regulatory lymphocytes (Tregs) and rate of lymphocyte apoptosis (annexin-v+ PI+ cells) in the blood were analyzed by using flow cytometric method. Results 1) Splenectomy significantly prolonged the mean survival time of heart allografts (7 ± 1.1 days and 27 ± 1.5 days for HT and splenectomy + HT, respectively; n = 12-14/group, HT vs. splenectomy + HT, p Splenectomy delayed pathological changes (inflammatory cell infiltration, myocardial damage) of the transplanted hearts in splenectomy + HT rats; 3) The level of CD4+CD25+ Tregs in the blood of splenectomized rats was significantly increased within 7 days (2.4 ± 0.5%, 4.9 ± 1.3% and 5.3 ± 1.0% for sham, splenectomy and splenectomy + HT, respectively; n = 15/group, sham vs. splenectomy or splenectomy + HT, p splenectomy surgery and gradually decreased to baseline level; 4) Splenectomy increased the rate of lymphocyte apoptosis (day 7: 0.3 ± 0.05%, 3.9 ± 0.9% and 4.1 ± 0.9% for sham, splenectomy and splenectomy + HT, respectively; n = 15/group, sham vs. splenectomy or splenectomy + HT, p Splenectomy inhibits the development of pathology and prolongs the survival time of cardiac allograft. The responsible mechanism is associated with induction of immune

  8. Improving breast cancer survival analysis through competition-based multidimensional modeling.

    Directory of Open Access Journals (Sweden)

    Erhan Bilal

    Full Text Available Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

  9. A survivability model for ejection of green compacts in powder metallurgy technology

    Directory of Open Access Journals (Sweden)

    Payman Ahi

    2012-01-01

    Full Text Available Reliability and quality assurance have become major considerations in the design and manufacture of today’s parts and products. Survivability of green compact using powder metallurgy technology is considered as one of the major quality attributes in manufacturing systems today. During powder metallurgy (PM production, the compaction conditions and behavior of the metal powder dictate the stress and density distribution in the green compact prior to sintering. These parameters greatly influence the mechanical properties and overall strength of the final component. In order to improve these properties, higher compaction pressures are usually employed, which make unloading and ejection of green compacts more challenging, especially for the powder-compacted parts with relatively complicated shapes. This study looked at a mathematical survivability model concerning green compact characteristics in PM technology and the stress-strength failure model in reliability engineering. This model depicts the relationship between mechanical loads (stress during ejection, experimentally determined green strength and survivability of green compact. The resulting survivability is the probability that a green compact survives during and after ejection. This survivability model can be used as an efficient tool for selecting the appropriate parameters for the process planning stage in PM technology. A case study is presented here in order to demonstrate the application of the proposed survivability model.

  10. Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

    Science.gov (United States)

    Astuti Thamrin, Sri; Taufik, Irfan

    2018-03-01

    Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

  11. Hepatic retransplantation in New England--a regional experience and survival model.

    Science.gov (United States)

    Powelson, J A; Cosimi, A B; Lewis, W D; Rohrer, R J; Freeman, R B; Vacanti, J P; Jonas, M; Lorber, M I; Marks, W H; Bradley, J

    1993-04-01

    Hepatic retransplantation (reTx) offers the only alternative to death for patients who have failed primary hepatic transplantation (PTx). Assuming a finite number of donor organs, reTx also denies the chance of survival for some patients awaiting PTx. The impact of reTx on overall survival (i.e., the survival of all candidates for transplantation) must therefore be clarified. Between 1983 and 1991, 651 patients from the New England Organ Bank underwent liver transplantation, and 73 reTx were performed in 71 patients (11% reTx rate). The 1-year actuarial survival for reTx (48%) was significantly less than for PTx (70%, P 365 days, 83%). Patients on the regional waiting list had an 18% mortality rate while awaiting transplantation. These results were incorporated into a mathematical model describing survival as a function of reTx rate, assuming a limited supply of donor livers. ReTx improves the 1-year survival rate for patients undergoing PTx but decreases overall survival (survival of all candidates) for liver transplantation. In the current era of persistently insufficient donor numbers, strategies based on minimizing the use of reTx, especially in the case of patients in whom chances of success are minimal, will result in the best overall rate of patient survival.

  12. Modeling nest-survival data: a comparison of recently developed methods that can be implemented in MARK and SAS

    Directory of Open Access Journals (Sweden)

    Rotella, J. J.

    2004-06-01

    Full Text Available Estimating nest success and evaluating factors potentially related to the survival rates of nests are key aspects of many studies of avian populations. A strong interest in nest success has led to a rich literature detailing a variety of estimation methods for this vital rate. In recent years, modeling approaches have undergone especially rapid development. Despite these advances, most researchers still employ Mayfield’s ad-hoc method (Mayfield, 1961 or, in some cases, the maximum-likelihood estimator of Johnson (1979 and Bart & Robson (1982. Such methods permit analyses of stratified data but do not allow for more complex and realistic models of nest survival rate that include covariates that vary by individual, nest age, time, etc. and that may be continuous or categorical. Methods that allow researchers to rigorously assess the importance of a variety of biological factors that might affect nest survival rates can now be readily implemented in Program MARK and in SAS’s Proc GENMOD and Proc NLMIXED. Accordingly, use of Mayfield’s estimator without first evaluating the need for more complex models of nest survival rate cannot be justified. With the goal of increasing the use of more flexible methods, we first describe the likelihood used for these models and then consider the question of what the effective sample size is for computation of AICc. Next, we consider the advantages and disadvantages of these different programs in terms of ease of data input and model construction; utility/flexibility of generated estimates and predictions; ease of model selection; and ability to estimate variance components. An example data set is then analyzed using both MARK and SAS to demonstrate implementation of the methods with various models that contain nest-, group- (or block-, and time-specific covariates. Finally, we discuss improvements that would, if they became available, promote a better general understanding of nest survival rates.

  13. Survival time of bacteria on different plastics by application of ultraviolet rays and desinfectants

    International Nuclear Information System (INIS)

    Glueck, S.

    1975-01-01

    The survival times of four sorts of germs were studied (Staph. albus, Staph. aureus, E.coli and Clebsiella) on 28 different plastic surfaces under different ambient conditions, (darkness, daylight, UV-radiation) and after preceding disinfection of the surfaces. For these studies, a formaldehydecontaining, phenolic, and a surface-active preparation were used. No essential differences in the survival times of the 4 types of germs tested were found. Besides the chemical basic structure additional substances were found to play a substantial role for the autobactericides. The dark values which could help to obtain findings about auto-bactericides did not show significant correspondence within the groups of the plastics. Only for a few materials a safe auto-bactericide could be found (alkyd lake, phenol resin). In the case of some other substances (some preparations made of PVC, polystyrene, polyacetal) an effect on the germs could be seen which was, at least totally seen, unfavourable, if all test conditions (darkness, daylight, UV-radiation) are viewed as a total. As comparative values on glass had shown a lower lethal rate of the germs, a certain auto-bactericide is likely to exist in all plastics tested. A considerable antibacterial effect of daylight was found, even with low daylight quotients and clased windows. UV-rays also diminished the number of germs on the plastic surfaces considerably, even with only indirect irradiation. Delayed effects of desinfecting agents partially depend on the surface material. Thus the phenolic agent showed strong delayed effects on the acryl glas, polyethylene, phenol resin, polycarbonate, but less on PVC. Phormaldehyde showed a good long-term effect only on phenol resin. (orig.) [de

  14. Modeling the effect of temperature on survival rate of Listeria monocytogenes in yogurt.

    Science.gov (United States)

    Szczawiński, J; Szczawińska, M E; Łobacz, A; Jackowska-Tracz, A

    2016-01-01

    The aim of the study was to (i) evaluate the behavior of Listeria monocytogenes in a commercially produced yogurt, (ii) determine the survival/inactivation rates of L. monocytogenes during cold storage of yogurt and (iii) to generate primary and secondary mathematical models to predict the behavior of these bacteria during storage at different temperatures. The samples of yogurt were inoculated with the mixture of three L. monocytogenes strains and stored at 3, 6, 9, 12 and 15°C for 16 days. The number of listeriae was determined after 0, 1, 2, 3, 5, 7, 9, 12, 14 and 16 days of storage. From each sample a series of decimal dilutions were prepared and plated onto ALOA agar (agar for Listeria according to Ottaviani and Agosti). It was found that applied temperature and storage time significantly influenced the survival rate of listeriae (pbacteria was found in the samples stored at 6°C (D-10 value = 243.9 h), whereas the highest reduction in the number of the bacteria was observed in the samples stored at 15°C (D-10 value = 87.0 h). The number of L. monocytogenes was correlated with the pH value of the samples (pyogurt stored under temperature range from 3 to 15°C, however, the polynomial model gave a better fit to the experimental data.

  15. Bayesian Analysis for Dynamic Generalized Linear Latent Model with Application to Tree Survival Rate

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    Yu-sheng Cheng

    2014-01-01

    Full Text Available Logistic regression model is the most popular regression technique, available for modeling categorical data especially for dichotomous variables. Classic logistic regression model is typically used to interpret relationship between response variables and explanatory variables. However, in real applications, most data sets are collected in follow-up, which leads to the temporal correlation among the data. In order to characterize the different variables correlations, a new method about the latent variables is introduced in this study. At the same time, the latent variables about AR (1 model are used to depict time dependence. In the framework of Bayesian analysis, parameters estimates and statistical inferences are carried out via Gibbs sampler with Metropolis-Hastings (MH algorithm. Model comparison, based on the Bayes factor, and forecasting/smoothing of the survival rate of the tree are established. A simulation study is conducted to assess the performance of the proposed method and a pika data set is analyzed to illustrate the real application. Since Bayes factor approaches vary significantly, efficiency tests have been performed in order to decide which solution provides a better tool for the analysis of real relational data sets.

  16. Single nucleotide polymorphisms in the D-loop region of mitochondrial DNA is associated with the kidney survival time in chronic kidney disease patients.

    Science.gov (United States)

    Xu, Jinsheng; Guo, Zhanjun; Bai, Yaling; Zhang, Junxia; Cui, Liwen; Zhang, Huiran; Zhang, Shenglei; Ai, Xiaolu

    2015-02-01

    The mitochondrial displacement loop (D-loop) is known to accumulate mutations and SNPs at a higher frequency than other regions of mitochondrial DNA (mtDNA). We had identified chronic kidney disease (CKD) risk-associated SNPs in the D-loop of CKD patients previously. In this study, we investigated the association of SNPs in the D-loop of mtDNA with the kidney survival of CKD. The D-loop region of mtDNA was sequenced for 119 CKD patients from the inpatient of the Fourth Hospital of Hebei Medical University. The Kaplan-Meier method was used to identify disease outcome-associated SNPs in the D-loop of CKD patients. The Cox proportional hazards model was used to identify risk factors for the kidney survival of CKD. In the present study, we identified 20 SNPs with a frequency higher than 5% and assessed the relationship of these SNPs with kidney survival time in CKD patients, a SNP of 146 was identified by log-rank test for statistically significant prediction of the kidney survival time. In an overall multivariate analysis, allele 146 was identified as an independent predictor of kidney survival time in CKD patients. The survival time of kidney in the CKD patients with 146C was significantly shorter than that of kidney in CKD patients with 146T (relative risk, 2.336; 95% CI, 1.319-3.923; p = 0.001). SNPs in the D-loop can predict the kidney survival of CKD patients. Analysis of genetic polymorphisms in the mitochondrial D-loop can help to identify CKD patient subgroup at high risk of a poor disease outcome.

  17. Parametric and semiparametric models with applications to reliability, survival analysis, and quality of life

    CERN Document Server

    Nikulin, M; Mesbah, M; Limnios, N

    2004-01-01

    Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.

  18. Selective histone deacetylase 6 inhibition prolongs survival in a lethal two-hit model.

    Science.gov (United States)

    Cheng, Xin; Liu, Zhengcai; Liu, Baoling; Zhao, Ting; Li, Yongqing; Alam, Hasan B

    2015-07-01

    Hemorrhagic shock (HS) followed by a subsequent insult ("second hit") often initiates an exaggerated systemic inflammatory response and multiple organ failure. We have previously demonstrated that valproic acid, a pan histone deacetylase inhibitor, could improve survival in a rodent "two-hit" model. In the present study, our goal was to determine whether selective inhibition of histone deacetylase 6 with Tubastatin A (Tub-A) could prolong survival in a two-hit model where HS was followed by sepsis from cecal ligation and puncture (CLP). C57Bl/6J mice were subjected to sublethal HS (30% blood loss) and then randomly divided into two groups (n = 13 per group) such as Tub-A group (treatment) and vehicle (VEH) group (control). The Tub-A group was given an intraperitoneal injection of Tub-A (70 mg/kg) dissolved in dimethyl sulfoxide (DMSO). The VEH group was injected with DMSO (1 μl/g body weight). After 24 h, all mice were subjected CLP followed immediately by another dose of Tub-A or DMSO. Survival was monitored for 10 d. In a parallel study, peritoneal irrigation fluid and liver tissue from Tub-A- or DMSO-treated mice were collected 3 h after CLP. Enzyme-linked immunosorbent assay was performed to quantify activity of the myeloperoxidase and concentrations of tumor necrosis factor-alpha (TNF-α) and interleukin 6 (IL-6) in the peritoneal irrigation fluid. RNA was isolated from the liver tissue, and real-time polymerase chain reaction was performed to measure relative messenger RNA levels of TNF-α and IL-6. Treatment with Tub-A significantly improved survival compared with that of the control (69.2% versus 15.4%). In addition, Tub-A significantly suppressed myeloperoxidase activity (169.9 ± 8.4 ng/mL versus 70.4 ± 17.4 ng/mL; P hit model. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. The Impact of Timing and Graft Dysfunction on Survival and Cardiac Allograft Vasculopathy in Antibody Mediated Rejection

    Science.gov (United States)

    Clerkin, Kevin J.; Restaino, Susan W.; Zorn, Emmanuel; Vasilescu, Elena R.; Marboe, Charles C.; Mancini, Donna M.

    2017-01-01

    Background Antibody mediated rejection (AMR) has been associated with increased mortality and cardiac allograft vasculopathy (CAV). Early studies suggested that late AMR was rarely associated with graft dysfunction while recent reports have demonstrated an association with increased mortality. We sought to investigate the timing of AMR and its association with graft dysfunction, mortality, and CAV. Methods This retrospective cohort study identified all adult heart transplant recipients at Columbia University Medical Center from 2004–2013 (689 patients). There were 68 primary cases of AMR, which were stratified by early (1-year post-OHT) AMR. Kaplan-Meier survival analysis and modeling was performed with multivariable logistic regression and Cox proportional hazards regression. Results From January 1, 2004 through October 1, 2015 43 patients had early AMR (median 23 days post-OHT) and 25 had late AMR (median 1084 days post-OHT). Graft dysfunction was less common with early compared with late AMR (25.6% vs. 56%, p=0.01). Patients with late AMR had decreased post-AMR survival compared with early AMR (1-year 80% vs. 93%, 5-year 51% vs. 73%, p<0.05). When stratified by graft dysfunction, only those with late AMR and graft dysfunction had worse survival (30-day 79%, 1-year 64%, and 5-year 36%, p<0.006). The association remained irrespective of age, sex, DSA, LVAD use, reason for OHT, and recovery of graft function. Similarly, those with late AMR and graft dysfunction had accelerated development of de-novo CAV (50% at 1 year, HR 5.42, p=0.009), while all other groups were all similar to the general transplant population. Conclusion Late AMR is frequently associated with graft dysfunction. When graft dysfunction is present in late AMR there is an early and sustained increased risk of mortality and rapid development of de-novo CAV despite aggressive treatment. PMID:27423693

  20. Modeling the airborne survival of influenza virus in a residential setting: the impacts of home humidification

    Science.gov (United States)

    2010-01-01

    Background Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH) conditions. Further analysis has shown that absolute humidity (AH) may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. Methods A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US) using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. Results The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. Conclusion This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity indoors. PMID:20815876

  1. Modeling the airborne survival of influenza virus in a residential setting: the impacts of home humidification

    Directory of Open Access Journals (Sweden)

    Myatt Theodore A

    2010-09-01

    Full Text Available Abstract Background Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH conditions. Further analysis has shown that absolute humidity (AH may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. Methods A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. Results The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. Conclusion This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity

  2. A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

    Science.gov (United States)

    Chai, Hua; Li, Zi-Na; Meng, De-Yu; Xia, Liang-Yong; Liang, Yong

    2017-10-12

    Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such information in the censored data, a semi-supervised learning framework (Cox-AFT model) combined with Cox proportional hazard (Cox) and accelerated failure time (AFT) model was used in cancer research, which has better performance than the single Cox or AFT model. This method, however, is easily affected by noise. To alleviate this problem, in this paper we combine the Cox-AFT model with self-paced learning (SPL) method to more effectively employ the information in the censored data in a self-learning way. SPL is a kind of reliable and stable learning mechanism, which is recently proposed for simulating the human learning process to help the AFT model automatically identify and include samples of high confidence into training, minimizing interference from high noise. Utilizing the SPL method produces two direct advantages: (1) The utilization of censored data is further promoted; (2) the noise delivered to the model is greatly decreased. The experimental results demonstrate the effectiveness of the proposed model compared to the traditional Cox-AFT model.

  3. Growth and survival of larval and early juvenile lesser sandeel in patchy prey field in the North Sea: An examination using individual-based modelling

    DEFF Research Database (Denmark)

    Gürkan, Zeren; Christensen, Asbjørn; Deurs, Mikael van

    2012-01-01

    -stages in the North Sea. Simulations of patchiness related starvation mortality are able to explain observed patterns of variation in sandeel growth. Reduced prey densities within patches decrease growth and survival rate of larvae and match–mismatch affect growth and survival of larvae with different hatch time due...... by modeling copepod size spectra dynamics and patchiness based on particle count transects and Continuous Plankton Recorder time series data. The study analyzes the effects of larval hatching time, presence of zooplankton patchiness and within patch abundance on growth and survival of sandeel early life...

  4. Extensions in Joint Modeling of Survival and Longitudinal Outcomes

    NARCIS (Netherlands)

    M. Murawska (Magdalena)

    2014-01-01

    markdownabstract__abstract__ In many medical studies both longitudinal and event history data are collected for each patient. A well-known and broadly studied example is found in AIDS research, where CD4 cell counts taken at different time points are related to the time-to-death. Often such

  5. Modeling of pathogen survival during simulated gastric digestion.

    Science.gov (United States)

    Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

    2011-02-01

    The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens.

  6. Modeling of Pathogen Survival during Simulated Gastric Digestion ▿

    Science.gov (United States)

    Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

    2011-01-01

    The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens. PMID:21131530

  7. A hands-on approach for fitting long-term survival models under the GAMLSS framework.

    Science.gov (United States)

    de Castro, Mário; Cancho, Vicente G; Rodrigues, Josemar

    2010-02-01

    In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. In this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

  8. Modelling Tradescantia fluminensis to assess long term survival

    Directory of Open Access Journals (Sweden)

    Alex James

    2015-06-01

    Full Text Available We present a simple Poisson process model for the growth of Tradescantia fluminensis, an invasive plant species that inhibits the regeneration of native forest remnants in New Zealand. The model was parameterised with data derived from field experiments in New Zealand and then verified with independent data. The model gave good predictions which showed that its underlying assumptions are sound. However, this simple model had less predictive power for outputs based on variance suggesting that some assumptions were lacking. Therefore, we extended the model to include higher variability between plants thereby improving its predictions. This high variance model suggests that control measures that promote node death at the base of the plant or restrict the main stem growth rate will be more effective than those that reduce the number of branching events. The extended model forms a good basis for assessing the efficacy of various forms of control of this weed, including the recently-released leaf-feeding tradescantia leaf beetle (Neolema ogloblini.

  9. Generation of a convalescent model of virulent Francisella tularensis infection for assessment of host requirements for survival of tularemia.

    Directory of Open Access Journals (Sweden)

    Deborah D Crane

    Full Text Available Francisella tularensis is a facultative intracellular bacterium and the causative agent of tularemia. Development of novel vaccines and therapeutics for tularemia has been hampered by the lack of understanding of which immune components are required to survive infection. Defining these requirements for protection against virulent F. tularensis, such as strain SchuS4, has been difficult since experimentally infected animals typically die within 5 days after exposure to as few as 10 bacteria. Such a short mean time to death typically precludes development, and therefore assessment, of immune responses directed against virulent F. tularensis. To enable identification of the components of the immune system that are required for survival of virulent F. tularensis, we developed a convalescent model of tularemia in C57Bl/6 mice using low dose antibiotic therapy in which the host immune response is ultimately responsible for clearance of the bacterium. Using this model we demonstrate αβTCR(+ cells, γδTCR(+ cells, and B cells are necessary to survive primary SchuS4 infection. Analysis of mice deficient in specific soluble mediators shows that IL-12p40 and IL-12p35 are essential for survival of SchuS4 infection. We also show that IFN-γ is required for survival of SchuS4 infection since mice lacking IFN-γR succumb to disease during the course of antibiotic therapy. Finally, we found that both CD4(+ and CD8(+ cells are the primary producers of IFN-γand that γδTCR(+ cells and NK cells make a minimal contribution toward production of this cytokine throughout infection. Together these data provide a novel model that identifies key cells and cytokines required for survival or exacerbation of infection with virulent F. tularensis and provides evidence that this model will be a useful tool for better understanding the dynamics of tularemia infection.

  10. Timing of chemotherapy and survival in patients with resectable gastric adenocarcinoma

    Science.gov (United States)

    Arrington, Amanda K; Nelson, Rebecca; Patel, Supriya S; Luu, Carrie; Ko, Michelle; Garcia-Aguilar, Julio; Kim, Joseph

    2013-01-01

    AIM: To evaluate the timing of chemotherapy in gastric cancer by comparing survival outcomes in treatment groups. METHODS: Patients with surgically resected gastric adenocarcinoma from 1988 to 2006 were identified from the Los Angeles County Cancer Surveillance Program. To evaluate the population most likely to receive and/or benefit from adjunct chemotherapy, inclusion criteria consisted of Stage II or III gastric cancer patients > 18 years of age who underwent curative-intent surgical resection. Patients were categorized into three groups according to the receipt of chemotherapy: (1) no chemotherapy; (2) preoperative chemotherapy; or (3) postoperative chemotherapy. Clinical and pathologic characteristics were compared across the different treatment arms. RESULTS: Of 1518 patients with surgically resected gastric cancer, 327 (21.5%) received perioperative chemotherapy. The majority of these 327 patients were male (68%) with a mean age of 61.5 years; and they were significantly younger than non-chemotherapy patients (mean age, 70.7; P advanced gastric cancer. CONCLUSION: This study supports the implementation of a randomized trial comparing the timing of perioperative therapy in patients with locally advanced gastric cancer. PMID:24392183

  11. Revealing the equivalence of two clonal survival models by principal component analysis

    International Nuclear Information System (INIS)

    Lachet, Bernard; Dufour, Jacques

    1976-01-01

    The principal component analysis of 21 chlorella cell survival curves, adjusted by one-hit and two-hit target models, lead to quite similar projections on the principal plan: the homologous parameters of these models are linearly correlated; the reason for the statistical equivalence of these two models, in the present state of experimental inaccuracy, is revealed [fr

  12. Nutritional intra-amniotic therapy increases survival in a rabbit model of fetal growth restriction

    Science.gov (United States)

    Illa, Miriam; Pla, Laura; Zamora, Monica; Crispi, Fatima; Gratacos, Eduard

    2018-01-01

    Objective To evaluate the perinatal effects of a prenatal therapy based on intra-amniotic nutritional supplementation in a rabbit model of intrauterine growth restriction (IUGR). Methods IUGR was surgically induced in pregnant rabbits at gestational day 25 by ligating 40–50% of uteroplacental vessels of each gestational sac. At the same time, modified-parenteral nutrition solution (containing glucose, amino acids and electrolytes) was injected into the amniotic sac of nearly half of the IUGR fetuses (IUGR-T group n = 106), whereas sham injections were performed in the rest of fetuses (IUGR group n = 118). A control group without IUGR induction but sham injection was also included (n = 115). Five days after the ligation procedure, a cesarean section was performed to evaluate fetal cardiac function, survival and birth weight. Results Survival was significantly improved in the IUGR fetuses that were treated with intra-amniotic nutritional supplementation as compared to non-treated IUGR animals (survival rate: controls 71% vs. IUGR 44% p = 0.003 and IUGR-T 63% vs. IUGR 44% p = 0.02), whereas, birth weight (controls mean 43g ± SD 9 vs. IUGR 36g ± SD 9 vs. IUGR-T 35g ± SD 8, p = 0.001) and fetal cardiac function were similar among the IUGR groups. Conclusion Intra-amniotic injection of a modified-parenteral nutrient solution appears to be a promising therapy for reducing mortality among IUGR. These results provide an opportunity to develop new intra-amniotic nutritional strategies to reach the fetus by bypassing the placental insufficiency. PMID:29466434

  13. Regression models for interval censored survival data: Application to HIV infection in Danish homosexual men

    DEFF Research Database (Denmark)

    Carstensen, Bendix

    1996-01-01

    This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men.......This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men....

  14. Modeling the effect of temperature on survival rate of Salmonella Enteritidis in yogurt.

    Science.gov (United States)

    Szczawiński, J; Szczawińska, M E; Łobacz, A; Jackowska-Tracz, A

    2014-01-01

    The aim of the study was to determine the inactivation rates of Salmonella Enteritidis in commercially produced yogurt and to generate primary and secondary mathematical models to predict the behaviour of these bacteria during storage at different temperatures. The samples were inoculated with the mixture of three S. Enteritidis strains and stored at 5 degrees C, 10 degrees C, 15 degrees C, 20 degrees C and 25 degrees C for 24 h. The number of salmonellae was determined every two hours. It was found that the number of bacteria decreased linearly with storage time in all samples. Storage temperature and pH of yogurt significantly influenced survival rate of S. Enteritidis (p bacteria was the most dynamic. The natural logarithm of mean inactivation rates of Salmonella calculated from primary model was fitted to two secondary models: linear and polynomial. Equations obtained from both secondary models can be applied as a tool for prediction of inactivation rate of Salmonella in yogurt stored under temperature range from 5 to 25 degrees C; however, polynomial model gave the better fit to the experimental data.

  15. The Health Rationale for Family Planning: Timing of Births and Child Survival.

    Science.gov (United States)

    United Nations, New York, NY. Population Div.

    Among the most influential findings from the World Fertility Survey (WFS) were those linking fertility patterns to child survival, in particular the findings concerning the high infant and child mortality for children born after a short birth interval. This study examined the relations between fertility and child survival based on more recent data…

  16. Patients with type 2 diabetes benefit from primary care-based disease management: a propensity score matched survival time analysis.

    Science.gov (United States)

    Drabik, Anna; Büscher, Guido; Thomas, Karsten; Graf, Christian; Müller, Dirk; Stock, Stephanie

    2012-08-01

    This study aimed to assess the impact of a nationwide German diabetes mellitus disease management program (DMP) on survival time and costs in comparison to routine care. The authors conducted a retrospective observational cohort study using routine administration data from Germany's largest sickness fund to identify insured suffering from diabetes in 2002. A total of 95,443 insured with type 2 diabetes mellitus who were born before January 1, 1962 met the defined inclusion criteria, resulting in 19,888 pairs of DMP participants and nonparticipants matched for socioeconomic and health status using propensity score matching methods. This is the first time propensity score matching has been used to evaluate a survival benefit of DMPs. In the time frame analyzed (3 years), mean survival time for the DMP group was 1045 days vs. 985 days for the routine care group (Ptime. They also incurred lower costs compared to propensity score matched insured in routine care.

  17. Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

    Science.gov (United States)

    Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

    2016-03-01

    One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi

  18. Single-incision laparoscopic surgery in a survival animal model using a transabdominal magnetic anchoring system.

    Science.gov (United States)

    Cho, Yong Beom; Park, Chan Ho; Kim, Hee Cheol; Yun, Seong Hyeon; Lee, Woo Yong; Chun, Ho-Kyung

    2011-12-01

    Though single-incision laparoscopic surgery (SILS) can reduce operative scarring and facilitates postoperative recovery, it does have some limitations, such as reduction in instrument working, difficulty in triangulation, and collision of instruments. To overcome these limitations, development of new instruments is needed. The aim of this study is to evaluate the feasibility and safety of a magnetic anchoring system in performing SILS ileocecectomy. Experiments were performed in a living dog model. Five dogs (26.3-29.2 kg) underwent ileocecectomy using a multichannel single port (OCTO port; Darim, Seoul, Korea). The port was inserted at the umbilicus and maintained a CO(2) pneumoperitoneum. Two magnet-fixated vascular clips were attached to the colon using an endoclip applicator, and it was held together across the abdominal wall by using an external handheld magnet. The cecum was then retracted in an upward direction by moving the external handheld magnet, and the mesocolon was dissected with Ultracision(®). Extracorporeal functional end-to-end anastomosis was done using a linear stapler. All animals survived during the observational period of 2 weeks, and then re-exploration was performed under general anesthesia for evaluation of intra-abdominal healing and complications. Mean operation time was 70 min (range 55-100 min), with each subsequent case taking less time. The magnetic anchoring system was effective in achieving adequate exposure in all cases. All animals survived and convalesced normally without evidence of clinical complication during the observation period. At re-exploration, all anastomoses were completely healed and there were no complications such as abscess, bleeding or organ injury. SILS ileocecectomy using a magnetic anchoring system was safe and effective in a dog model. The development of magnetic anchoring systems may be beneficial for overcoming the limitations of SILS.

  19. Multiple Indicator Stationary Time Series Models.

    Science.gov (United States)

    Sivo, Stephen A.

    2001-01-01

    Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

  20. Survival Analysis of a Nonautonomous Logistic Model with Stochastic Perturbation

    Directory of Open Access Journals (Sweden)

    Chun Lu

    2012-01-01

    Full Text Available Taking white noise into account, a stochastic nonautonomous logistic model is proposed and investigated. Sufficient conditions for extinction, nonpersistence in the mean, weak persistence, stochastic permanence, and global asymptotic stability are established. Moreover, the threshold between weak persistence and extinction is obtained. Finally, we introduce some numerical simulink graphics to illustrate our main results.

  1. Surviving the present: Modeling tools for organizational change

    International Nuclear Information System (INIS)

    Pangaro, P.

    1992-01-01

    The nuclear industry, like the rest of modern American business, is beset by a confluence of economic, technological, competitive, regulatory, and political pressures. For better or worse, business schools and management consultants have leapt to the rescue, offering the most modern conveniences that they can purvey. Recent advances in the study of organizations have led to new tools for their analysis, revision, and repair. There are two complementary tools that do not impose values or injunctions in themselves. One, called the organization modeler, captures the hierarchy of purposes that organizations and their subparts carry out. Any deficiency or pathology is quickly illuminated, and requirements for repair are made clear. The second, called THOUGHTSTICKER, is used to capture the semantic content of the conversations that occur across the interactions of parts of an organization. The distinctions and vocabulary in the language of an organization, and the relations within that domain, are elicited from the participants so that all three are available for debate and refinement. The product of the applications of these modeling tools is not the resulting models but rather the enhancement of the organization as a consequence of the process of constructing them

  2. Abundance of early functional HIV-specific CD8+ T cells does not predict AIDS-free survival time.

    Directory of Open Access Journals (Sweden)

    Ingrid M M Schellens

    Full Text Available BACKGROUND: T-cell immunity is thought to play an important role in controlling HIV infection, and is a main target for HIV vaccine development. HIV-specific central memory CD8(+ and CD4(+ T cells producing IFNgamma and IL-2 have been associated with control of viremia and are therefore hypothesized to be truly protective and determine subsequent clinical outcome. However, the cause-effect relationship between HIV-specific cellular immunity and disease progression is unknown. We investigated in a large prospective cohort study involving 96 individuals of the Amsterdam Cohort Studies with a known date of seroconversion whether the presence of cytokine-producing HIV-specific CD8(+ T cells early in infection was associated with AIDS-free survival time. METHODS AND FINDINGS: The number and percentage of IFNgamma and IL-2 producing CD8(+ T cells was measured after in vitro stimulation with an overlapping Gag-peptide pool in T cells sampled approximately one year after seroconversion. Kaplan-Meier survival analysis and Cox proportional hazard models showed that frequencies of cytokine-producing Gag-specific CD8(+ T cells (IFNgamma, IL-2 or both shortly after seroconversion were neither associated with time to AIDS nor with the rate of CD4(+ T-cell decline. CONCLUSIONS: These data show that high numbers of functional HIV-specific CD8(+ T cells can be found early in HIV infection, irrespective of subsequent clinical outcome. The fact that both progressors and long-term non-progressors have abundant T cell immunity of the specificity associated with low viral load shortly after seroconversion suggests that the more rapid loss of T cell immunity observed in progressors may be a consequence rather than a cause of disease progression.

  3. Modelling of the process of micromycetus survival in fruit and berry syrups

    Directory of Open Access Journals (Sweden)

    L. Osipova

    2017-06-01

    Full Text Available In order to develop methods for preserving fruit and berry syrup, which exclude the use of high-temperature sterilization and preservatives, the survival of spores of micromycetes (B. nivea molds in model media with different concentration of food osmotically active substances (sucrose, ethyl alcohol, citric acid at a certain concentration of lethal effects on microorganisms. It has been established that model media (juice based syrups from blueberries with a mass content of 4 % and 6 % alcohol, 50 % sucrose, 1 % and 2 % titrated acids, have a lethal effect on spores of B. nivea molds. The regression equation is obtained expressing the dependence of the amount of spores of B. nivea molds on the concentration of sucrose, acid, alcohol and the storage time of syrups. The form of the dependence and direction of the connection between the variables is established – a negative linear regression, which is expressed in the uniform decrease of the function. The estimation of quality of the received regression model is defined. The deviations of the calculated data from the data of the initial set are calculated. The proposed model has sufficient reliability, since the regression function is defined, interpreted and justified, and the estimation of the accuracy of the regression analysis meets the requirements.

  4. End points for adjuvant therapy trials: has the time come to accept disease-free survival as a surrogate end point for overall survival?

    Science.gov (United States)

    Gill, Sharlene; Sargent, Daniel

    2006-06-01

    The intent of adjuvant therapy is to eradicate micro-metastatic residual disease following curative resection with the goal of preventing or delaying recurrence. The time-honored standard for demonstrating efficacy of new adjuvant therapies is an improvement in overall survival (OS). This typically requires phase III trials of large sample size with lengthy follow-up. With the intent of reducing the cost and time of completing such trials, there is considerable interest in developing alternative or surrogate end points. A surrogate end point may be employed as a substitute to directly assess the effects of an intervention on an already accepted clinical end point such as mortality. When used judiciously, surrogate end points can accelerate the evaluation of new therapies, resulting in the more timely dissemination of effective therapies to patients. The current review provides a perspective on the suitability and validity of disease-free survival (DFS) as an alternative end point for OS. Criteria for establishing surrogacy and the advantages and limitations associated with the use of DFS as a primary end point in adjuvant clinical trials and as the basis for approval of new adjuvant therapies are discussed.

  5. A Survival Model for Shortleaf Pine Tress Growing in Uneven-Aged Stands

    Science.gov (United States)

    Thomas B. Lynch; Lawrence R. Gering; Michael M. Huebschmann; Paul A. Murphy

    1999-01-01

    A survival model for shortleaf pine (Pinus echinata Mill.) trees growing in uneven-aged stands was developed using data from permanently established plots maintained by an industrial forestry company in western Arkansas. Parameters were fitted to a logistic regression model with a Bernoulli dependent variable in which "0" represented...

  6. Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

    Science.gov (United States)

    Nikbakht, Roya; Bahrampour, Abbas

    2017-01-01

    Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

  7. Effect of 153Sm-EDTMP on survival time in patients with nasopharyngeal carcinoma and multiple bone metastases

    International Nuclear Information System (INIS)

    Fan Wei; Zheng Zongyuan; Xu Guangpu

    2004-01-01

    Objective: To evaluate the effect on survival of Samarium-153-ethylene diamine tetramethylene phosphonate (153Sm-EDTMP) in patients with nasopharyngeal carcinoma (NPC) and multiple bone metastases. Methods: From 1993 to 1999, 160 patients (127 men, 33 women; median age 35 years) presented with NPC and multiple bone metastases. Of these, 40 patients had undergone chemotherapy, and 72 palliative radiotherapy. Patients were randomly divided into four groups: Group 1 (N = 20) received analgesics (control); Groups 2, 3 and 4 (N = 80, 40, and 20, respectively) received one, two or three courses, respectively, of 153Sm-EDTMP (77.7 MBq/kg/course; course interval, 4 wk). Results: Eight patients died of non-cancer-related causes, and 24 were lost to follow-up. The median survival time for Group 1 (7.8 months) was significantly less (p < 0.05) than that of Groups 2, 3 and 4 (11.6, 13.4 and 12.8 months, respectively). Patients given 153Sm-EDTMP who had had revious external radiation survived longer (p < 0.05) than those in the other treatment groups. Conclusions: Internal radiotherapy with 153Sm-EDTMP can extend survival time in patients with nasopharyngeal carcinoma and multiple bone metastases; when combined with external radiotherapy in appropriate patients, its effect on survival time is enhanced.. (authors)

  8. Quadratic Term Structure Models in Discrete Time

    OpenAIRE

    Marco Realdon

    2006-01-01

    This paper extends the results on quadratic term structure models in continuos time to the discrete time setting. The continuos time setting can be seen as a special case of the discrete time one. Recursive closed form solutions for zero coupon bonds are provided even in the presence of multiple correlated underlying factors. Pricing bond options requires simple integration. Model parameters may well be time dependent without scuppering such tractability. Model estimation does not require a r...

  9. Model Checking Real-Time Systems

    DEFF Research Database (Denmark)

    Bouyer, Patricia; Fahrenberg, Uli; Larsen, Kim Guldstrand

    2018-01-01

    This chapter surveys timed automata as a formalism for model checking real-time systems. We begin with introducing the model, as an extension of finite-state automata with real-valued variables for measuring time. We then present the main model-checking results in this framework, and give a hint...

  10. Joint modelling of longitudinal CEA tumour marker progression and survival data on breast cancer

    Science.gov (United States)

    Borges, Ana; Sousa, Inês; Castro, Luis

    2017-06-01

    This work proposes the use of Biostatistics methods to study breast cancer in patients of Braga's Hospital Senology Unit, located in Portugal. The primary motivation is to contribute to the understanding of the progression of breast cancer, within the Portuguese population, using a more complex statistical model assumptions than the traditional analysis that take into account a possible existence of a serial correlation structure within a same subject observations. We aim to infer which risk factors aect the survival of Braga's Hospital patients, diagnosed with breast tumour. Whilst analysing risk factors that aect a tumour markers used on the surveillance of disease progression the Carcinoembryonic antigen (CEA). As survival and longitudinal processes may be associated, it is important to model these two processes together. Hence, a joint modelling of these two processes to infer on the association of these was conducted. A data set of 540 patients, along with 50 variables, was collected from medical records of the Hospital. A joint model approach was used to analyse these data. Two dierent joint models were applied to the same data set, with dierent parameterizations which give dierent interpretations to model parameters. These were used by convenience as the ones implemented in R software. Results from the two models were compared. Results from joint models, showed that the longitudinal CEA values were signicantly associated with the survival probability of these patients. A comparison between parameter estimates obtained in this analysis and previous independent survival[4] and longitudinal analysis[5][6], lead us to conclude that independent analysis brings up bias parameter estimates. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary. Results indicate that the longitudinal progression of CEA is signicantly associated with the probability of survival of these patients. Hence, an assumption of

  11. Differences in compliance with Surviving Sepsis Campaign recommendations according to hospital entrance time: day versus night.

    Science.gov (United States)

    Almeida, Mónica; Ribeiro, Orquídea; Aragão, Irene; Costa-Pereira, Altamiro; Cardoso, Teresa

    2013-04-23

    Higher compliance with Surviving Sepsis Campaign (SSC) recommendations has been associated with lower mortality. The authors evaluate differences in compliance with SSC 6-hour bundle according to hospital entrance time (day versus night) and its impact on hospital mortality. Prospective cohort study of all patients with community-acquired severe sepsis admitted to the intensive care unit of a large university tertiary care hospital, over 3.5 years with a follow-up until hospital discharge. Time to compliance with each recommendation of the SSC 6-hour bundle was calculated according to hospital entrance period: day (08:30 to 20:30) versus night (20:30 to 08:30). For the same periods, clinical staff composition and the number of patients attending the emergency department (ED) was also recorded. In this period 300 consecutive patients were included. Compliance rate was (night vs. day): serum lactate measurement 57% vs. 49% (P = 0.171), blood cultures drawn 59% vs. 37% (P 8 mmHg 45% vs. 29% (P = 0.021), and central venous oxygen saturation (SvcO₂) >70%, 7% vs. 2% (P = 0.082); fluids were administered in all patients with hypotension in both periods and vasopressors were administered in patients with hypotension not responsive to fluids in 100% vs. 99%. Time to get specific actions done was also different (night vs. day): serum lactate measurement (4.5 vs. 7 h, P = 0.018), blood cultures drawn (4 vs. 8 h, P night with a higher proportion of less differentiated doctors. The number of patients attending the Emergency Department was lower overnight. Hospital mortality rate was 34% in patients entering in the night period vs. 40% in those entering during the day (P = 0.281). Compliance with SSC recommendations was higher at night. A possible explanation might be the increased nurse to patient ratio in that period. Adjustment of the clinical team composition to the patients' demand is needed to increase compliance and improve prognosis.

  12. Time lags in biological models

    CERN Document Server

    MacDonald, Norman

    1978-01-01

    In many biological models it is necessary to allow the rates of change of the variables to depend on the past history, rather than only the current values, of the variables. The models may require discrete lags, with the use of delay-differential equations, or distributed lags, with the use of integro-differential equations. In these lecture notes I discuss the reasons for including lags, especially distributed lags, in biological models. These reasons may be inherent in the system studied, or may be the result of simplifying assumptions made in the model used. I examine some of the techniques available for studying the solution of the equations. A large proportion of the material presented relates to a special method that can be applied to a particular class of distributed lags. This method uses an extended set of ordinary differential equations. I examine the local stability of equilibrium points, and the existence and frequency of periodic solutions. I discuss the qualitative effects of lags, and how these...

  13. Flow cytometric and radioisotopic determinations of platelet survival time in normal cats and feline leukemia virus-infected cats

    Energy Technology Data Exchange (ETDEWEB)

    Jacobs, R.M.; Boyce, J.T.; Kociba, G.J.

    1986-01-01

    This study demonstrates the potential usefulness of a flow cytometric technique to measure platelet survival time in cats utilizing autologous platelets labeled in vitro with fluorescein isothiocyanate (FITC). When compared with a 51Cr method, no significant differences in estimated survival times were found. Both the 51Cr and FITC-labeling procedures induced similar changes in platelet shape and collagen-induced aggregation. Platelets labeled with FITC had significantly greater volumes compared with those of glutaraldehyde-fixed platelets. These changes were primarily related to the platelet centrifugation and washing procedures rather than the labels themselves. This novel technique potentially has wide applicability to cell circulation time studies as flow cytometry equipment becomes more readily available. Problems with the technique are discussed. In a preliminary study of the platelet survival time in feline leukemia virus (FeLV)-infected cats, two of three cats had significantly reduced survival times using both flow cytometric and radioisotopic methods. These data suggest increased platelet turnover in FeLV-infected cats.

  14. Flow cytometric and radioisotopic determinations of platelet survival time in normal cats and feline leukemia virus-infected cats

    International Nuclear Information System (INIS)

    Jacobs, R.M.; Boyce, J.T.; Kociba, G.J.

    1986-01-01

    This study demonstrates the potential usefulness of a flow cytometric technique to measure platelet survival time in cats utilizing autologous platelets labeled in vitro with fluorescein isothiocyanate (FITC). When compared with a 51Cr method, no significant differences in estimated survival times were found. Both the 51Cr and FITC-labeling procedures induced similar changes in platelet shape and collagen-induced aggregation. Platelets labeled with FITC had significantly greater volumes compared with those of glutaraldehyde-fixed platelets. These changes were primarily related to the platelet centrifugation and washing procedures rather than the labels themselves. This novel technique potentially has wide applicability to cell circulation time studies as flow cytometry equipment becomes more readily available. Problems with the technique are discussed. In a preliminary study of the platelet survival time in feline leukemia virus (FeLV)-infected cats, two of three cats had significantly reduced survival times using both flow cytometric and radioisotopic methods. These data suggest increased platelet turnover in FeLV-infected cats

  15. The impact of chemotherapy and its timing on survival in malignant peritoneal mesothelioma treated with complete debulking.

    Science.gov (United States)

    Naffouje, Samer A; Tulla, Kiara A; Salti, George I

    2018-04-12

    The current standard of treatment for malignant peritoneal mesothelioma (MPM) is cytoreductive surgery when the disease distribution is favorable. The role of chemotherapy, as an adjunct to surgery, remains unclear. The national database of mesothelioma was used to identify MPM patients who were treated with curative intent. Patients were divided into treatment groups: (1) chemotherapy only, (2) surgery only, (3) neoadjuvant chemotherapy + surgery, and (4) surgery + adjuvant chemotherapy. A negative control group of patients who did not receive any treatment was added (group 0). Totally, 1740 patients were included. Mean age was 63.04 ± 14.58 and 60.7% were males. The patients' distribution into the treatment groups was 604, 684, 169, 55, and 228 patients in groups 0-4, respectively, with a median survival of 3.61 ± 0.37, 11.10 ± 0.73, 57.41 ± 11.91, 52.30 ± 7.20, and 55.00 ± 9.19 months. The addition of chemotherapy, in any setting, to surgery provided an improved survival at 1 year (p = 0.006). This survival benefit ceased at the 2-, 3-, and 5-year checkpoints. The multivariate analysis identified age, sarcomatoid/biphasic histologies, nodal and distant metastasis, and offering no treatment or chemotherapy only as poor prognostic factors for overall survival. No difference in overall survival was noted with the addition of chemotherapy to complete debulking regardless of the timing. Complete debulking remains the standard treatment for MPM. The addition of systemic chemotherapy provides a short-term survival improvement at 1 year only and was similar whether given in the neoadjuvant or adjuvant setting. Nevertheless, it did not add a survival benefit beyond the 1-year time point.

  16. Determine the Influence of Time Held in “Knockdown” Anesthesia on Survival and Stress of Surgically Implanted Juvenile Salmonids

    Energy Technology Data Exchange (ETDEWEB)

    Woodley, Christa M.; Wagner, Katie A.; Knox, Kasey M.

    2012-01-31

    The Juvenile Salmon Acoustic Telemetry System (JSATS) was developed for the U.S. Army Corp of Engineers Portland District (USACE) to address questions related to survival and performance measures of juvenile salmonids as they pass through the Federal Columbia River Power System (FCRPS). Researchers using JSATS acoustic transmitters (ATs) were tasked with standardizing the surgical implantation procedure to ensure that the stressors of handling and surgery on salmonids were consistent and less likely to cause effects of tagging in survival studies. Researchers questioned whether the exposure time in 'knockdown' anesthesia (or induction) to prepare fish for surgery could influence the survival of study fish (CBSPSC 2011). Currently, fish are held in knockdown anesthesia after they reach Stage 4 anesthesia until the completion of the surgical implantation of a transmitter, varies from 5 to 15 minutes for studies conducted in the Columbia Basin. The Columbia Basin Surgical Protocol Steering Committee (CBSPSC ) expressed concern that its currently recommended 10-minute maximum time limit during which fish are held in anesthetic - tricaine methanesulfonate (MS-222, 80 mg L-1 water) - could increase behavioral and physiological costs, and/or decrease survival of outmigrating juvenile salmonids. In addition, the variability in the time fish are held at Stage 4 could affect the data intended for direct comparison of fish within or among survival studies. Under the current recommended protocol, if fish exceed the 10-minute time limit, they are to be released without surgical implantation, thereby increasing the number of fish handled and endangered species 'take' at the bypass systems for FCRPS survival studies.

  17. Edaravone improves survival and neurological outcomes after CPR in a ventricular fibrillation model of rats.

    Science.gov (United States)

    Qin, Tao; Lei, Ling-Yan; Li, Nuo; Shi, Fangying Ruan; Chen, Meng-Hua; Xie, Lu

    2016-10-01

    Overproduction of free radicals is a main factor contributing to cerebral injury after cardiac arrest (CA)/cardiopulmonary resuscitation (CPR). We sought to evaluate the impact of edaravone on the survival and neurological outcomes after CA/CPR in rats. Rats were subjected to CA following CPR. For survival study, the rats with restoration of spontaneous circulation (ROSC) were randomly allocated to one of the two groups (edaravone and saline group, n=20/each group) to received Edaravone (3 mg/kg) or normal saline. Another 10 rats without experiencing CA and CPR served as the sham group. Survival was observed for 72 hours and the neurological deficit score (NDS) was calculated at 12, 24, 48, and 72 hours after ROSC. For the neurological biochemical analysis study, rats were subjected to the same experimental procedures. Then, edaravone group (n=24), saline group (n=24) and sham group (n=16) were further divided into 4 subgroups according to the different time intervals (12, 24, 48, and 72 hours following ROSC). Brain tissues were harvested at relative time intervals for evaluation of oxidative stress, TUNEL staining and apoptotic gene expression. Edaravone improved postresuscitative survival time and neurological deficit, decreased brain malonylaldehyde level, increased superoxide dismutase activities, decreased proapoptotic gene expression of capase-8, capase-3, and Bax, and increased antiapoptotic Bcl-2 expression at 12, 24, 48, and 72 hours after ROSC. Edaravone improves survival and neurological outcomes following CPR via antioxidative and antiapoptotic effects in rats. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Modeling nonstationarity in space and time.

    Science.gov (United States)

    Shand, Lyndsay; Li, Bo

    2017-09-01

    We propose to model a spatio-temporal random field that has nonstationary covariance structure in both space and time domains by applying the concept of the dimension expansion method in Bornn et al. (2012). Simulations are conducted for both separable and nonseparable space-time covariance models, and the model is also illustrated with a streamflow dataset. Both simulation and data analyses show that modeling nonstationarity in both space and time can improve the predictive performance over stationary covariance models or models that are nonstationary in space but stationary in time. © 2017, The International Biometric Society.

  19. The effect of timing and graft dysfunction on survival and cardiac allograft vasculopathy in antibody-mediated rejection.

    Science.gov (United States)

    Clerkin, Kevin J; Restaino, Susan W; Zorn, Emmanuel; Vasilescu, Elena R; Marboe, Charles C; Mancini, Donna M

    2016-09-01

    Antibody-mediated rejection (AMR) has been associated with increased death and cardiac allograft vasculopathy (CAV). Early studies suggested that late AMR was rarely associated with graft dysfunction, whereas recent reports have demonstrated an association with increased mortality. We investigated the timing of AMR and its association with graft dysfunction, death, and CAV. This retrospective cohort study identified all adult orthotopic heart transplant (OHT) recipients (N = 689) at Columbia University Medical Center from 2004 to 2013. There were 68 primary cases of AMR, which were stratified by early ( 1 year post-OHT) AMR. Kaplan-Meier survival analysis and modeling was performed with multivariable logistic regression and Cox proportional hazards regression. From January 1, 2004, through October 1, 2015, early AMR (median 23 days post-OHT) occurred in 43 patients and late AMR (median 1,084 days post-OHT) occurred in 25. Graft dysfunction was less common with early compared with late AMR (25.6% vs 56%, p = 0.01). Patients with late AMR had decreased post-AMR survival compared with early AMR (1 year: 80% vs 93%, 5 years: 51% vs 73%, p < 0.05). When stratified by graft dysfunction, only those with late AMR and graft dysfunction had worse survival (30 days: 79%, 1 year: 64%, 5 years: 36%; p < 0.006). The association remained irrespective of age, sex, donor-specific antibodies, left ventricular assist device use, reason for OHT, and recovery of graft function. Similarly, those with late AMR and graft dysfunction had accelerated development of de novo CAV (50% at 1 year; hazard ratio, 5.42; p = 0.009), whereas all other groups were all similar to the general transplant population. Late AMR is frequently associated with graft dysfunction. When graft dysfunction is present in late AMR, there is an early and sustained increased risk of death and rapid development of de novo CAV despite aggressive treatment. Copyright © 2016 International Society for Heart and Lung

  20. Time to Thrive, Not Just Survive: Accumulating Advantage for Women in Science

    Science.gov (United States)

    Rolison, Debra

    2005-04-01

    Our departments of science, technology, mathematics, and engineering (STEM) need more women as faculty, and not only to show their undergraduates that a career in academia is a viable path. Their absence warns us that an unhealthy environment exists: unhealthy to those scientists who want fulfilling lives beyond academe and unhealthy to those women, who once they demonstrate productivity, scholarship, and mentorship, still reap less respect, space, salary, funding, and awards than their male colleagues. The recalcitrance of too many of our research universities toward diversifying their faculty is a national disgrace in that these universities covet a diversified student body, but do not reflect that pool of talent onto their faculty. Similar difficulties are apparent among the staff of National and Federal laboratories. Self-reform is not getting it done, and is especially frustrating in light of the historic opportunity to change the demographics as scientists and engineers hired in the 1960s retire. Is it time to apply the logic of Title IX--the loss of Federal funds--for the entrenched inability to increase the number of women represented on STEM faculties? Such a threat may be the impetus necessary for university administrators to create departmental environments that women are willing to call home. The July 2004 release of the GAO report on Women's Participation in the Sciences (which also surveyed DOE facilities) reminded those Federal agencies that fund scientific research that Title IX is the law and that these agencies must begin Title IX assessments of compliance in the STEM departments and institutions they fund. It is past time that women thrive, not just survive in their career homes. Using the mechanistic philosophy of Title IX--denial of resources to recalacitrant departments and laboratories--may be the start of a truly inclusive scientific enterprise in the United States. We must accept this opportunity to redirect the nature of the research

  1. Survival times of patients with a first hip fracture with and without subsequent major long-bone fractures.

    Science.gov (United States)

    Angthong, Chayanin; Angthong, Wirana; Harnroongroj, Thos; Naito, Masatoshi; Harnroongroj, Thossart

    2013-01-01

    Survival rates are poorer after a second hip fracture than after a first hip fracture. Previous survival studies have included in-hospital mortality. Excluding in-hospital deaths from the analysis allows survival times to be evaluated in community-based patients. There is still a lack of data regarding the effects of subsequent fractures on survival times after hospital discharge following an initial hip fracture. This study compared the survival times of community-dwelling patients with hip fracture who had or did not have a subsequent major long-bone fracture. Hazard ratios and risk factors for subsequent fractures and mortality rates with and without subsequent fractures were calculated. Of 844 patients with hip fracture from 2000 through 2008, 71 had a subsequent major long-bone fracture and 773 did not. Patients who died of other causes, such as perioperative complications, during hospitalization were excluded. Such exclusion allowed us to determine the effect of subsequent fracture on the survival of community-dwelling individuals after hospital discharge or after the time of the fracture if they did not need hospitalization. Demographic data, causes of death, and mortality rates were recorded. Differences in mortality rates between the patient groups and hazard ratios were calculated. Mortality rates during the first year and from 1 to 5 years after the most recent fracture were 5.6% and 1.4%, respectively, in patients with subsequent fractures, and 4.7% and 1.4%, respectively, in patients without subsequent fractures. These rates did not differ significantly between the groups. Cox regression analysis and calculation of hazard ratios did not show significant differences between patients with subsequent fractures and those without. On univariate and multivariate analyses, age fracture. This study found that survival times did not differ significantly between patients with and without subsequent major long-bone fractures after hip fracture. Therefore, all

  2. Estimating survival of dental fillings on the basis of interval-censored data and multi-state models

    DEFF Research Database (Denmark)

    Joly, Pierre; Gerds, Thomas A; Qvist, Vibeke

    2012-01-01

    We aim to compare the life expectancy of a filling in a primary tooth between two types of treatments. We define the probabilities that a dental filling survives without complication until the permanent tooth erupts from beneath (exfoliation). We relate the time to exfoliation of the tooth...... with all these particularities, we propose to use a parametric four-state model with three random effects to take into account the hierarchical cluster structure. For inference, right and interval censoring as well as left truncation have to be dealt with. With the proposed approach, we can conclude...... that the estimated probability that a filling survives without complication until exfoliation is larger for one treatment than for the other, for all ages of the child at the time of treatment....

  3. On the analysis of clonogenic survival data: Statistical alternatives to the linear-quadratic model

    International Nuclear Information System (INIS)

    Unkel, Steffen; Belka, Claus; Lauber, Kirsten

    2016-01-01

    The most frequently used method to quantitatively describe the response to ionizing irradiation in terms of clonogenic survival is the linear-quadratic (LQ) model. In the LQ model, the logarithm of the surviving fraction is regressed linearly on the radiation dose by means of a second-degree polynomial. The ratio of the estimated parameters for the linear and quadratic term, respectively, represents the dose at which both terms have the same weight in the abrogation of clonogenic survival. This ratio is known as the α/β ratio. However, there are plausible scenarios in which the α/β ratio fails to sufficiently reflect differences between dose-response curves, for example when curves with similar α/β ratio but different overall steepness are being compared. In such situations, the interpretation of the LQ model is severely limited. Colony formation assays were performed in order to measure the clonogenic survival of nine human pancreatic cancer cell lines and immortalized human pancreatic ductal epithelial cells upon irradiation at 0-10 Gy. The resulting dataset was subjected to LQ regression and non-linear log-logistic regression. Dimensionality reduction of the data was performed by cluster analysis and principal component analysis. Both the LQ model and the non-linear log-logistic regression model resulted in accurate approximations of the observed dose-response relationships in the dataset of clonogenic survival. However, in contrast to the LQ model the non-linear regression model allowed the discrimination of curves with different overall steepness but similar α/β ratio and revealed an improved goodness-of-fit. Additionally, the estimated parameters in the non-linear model exhibit a more direct interpretation than the α/β ratio. Dimensionality reduction of clonogenic survival data by means of cluster analysis was shown to be a useful tool for classifying radioresistant and sensitive cell lines. More quantitatively, principal component analysis allowed

  4. Increased survival rate by local release of diclofenac in a murine model of recurrent oral carcinoma

    Directory of Open Access Journals (Sweden)

    Will OM

    2016-10-01

    determination of tumor recurrence. At the end of 7 weeks following tumor resection, 33% of mice with diclofenac-loaded scaffolds had a recurrent tumor, in comparison to 90%–100% of the mice in the other three groups. At this time point, mice with diclofenac-releasing scaffolds showed 89% survival rate, while the other groups showed survival rates of 10%–25%. Immunohistochemical staining of recurrent tumors revealed a near 10-fold decrease in the proliferation marker Ki-67 in the tumors derived from mice with diclofenac-releasing scaffolds. In summary, the local application of diclofenac in an orthotopic mouse tumor resection model of oral cancer reduced tumor recurrence with significant improvement in survival over a 7-week study period following tumor resection. Local drug release of anti-inflammatory agents should be investigated as a therapeutic option in the prevention of tumor recurrence in oral squamous carcinoma. Keywords: tumor recurrence, oral squamous cell carcinoma, head and neck cancer, NSAIDs, drug releasing polymers, mouse model 

  5. Flux balance modeling to predict bacterial survival during pulsed-activity events

    Science.gov (United States)

    Jose, Nicholas A.; Lau, Rebecca; Swenson, Tami L.; Klitgord, Niels; Garcia-Pichel, Ferran; Bowen, Benjamin P.; Baran, Richard; Northen, Trent R.

    2018-04-01

    Desert biological soil crusts (BSCs) are cyanobacteria-dominated surface soil microbial communities common to plant interspaces in arid environments. The capability to significantly dampen their metabolism allows them to exist for extended periods in a desiccated dormant state that is highly robust to environmental stresses. However, within minutes of wetting, metabolic functions reboot, maximizing activity during infrequent permissive periods. Microcoleus vaginatus, a primary producer within the crust ecosystem and an early colonizer, initiates crust formation by binding particles in the upper layer of soil via exopolysaccharides, making microbial dominated biological soil crusts highly dependent on the viability of this organism. Previous studies have suggested that biopolymers play a central role in the survival of this organism by powering resuscitation, rapidly forming compatible solutes, and fueling metabolic activity in dark, hydrated conditions. To elucidate the mechanism of this phenomenon and provide a basis for future modeling of BSCs, we developed a manually curated, genome-scale metabolic model of Microcoleus vaginatus (iNJ1153). To validate this model, gas chromatography-mass spectroscopy (GC-MS) and liquid chromatography-mass spectroscopy (LC-MS) were used to characterize the rate of biopolymer accumulation and depletion in in hydrated Microcoleus vaginatus under light and dark conditions. Constraint-based flux balance analysis showed agreement between model predictions and experimental reaction fluxes. A significant amount of consumed carbon and light energy is invested into storage molecules glycogen and polyphosphate, while β-polyhydroxybutyrate may function as a secondary resource. Pseudo-steady-state modeling suggests that glycogen, the primary carbon source with the fastest depletion rate, will be exhausted if M. vaginatus experiences dark wetting events 4 times longer than light wetting events.

  6. KMWin--a convenient tool for graphical presentation of results from Kaplan-Meier survival time analysis.

    Science.gov (United States)

    Gross, Arnd; Ziepert, Marita; Scholz, Markus

    2012-01-01

    Analysis of clinical studies often necessitates multiple graphical representations of the results. Many professional software packages are available for this purpose. Most packages are either only commercially available or hard to use especially if one aims to generate or customize a huge number of similar graphical outputs. We developed a new, freely available software tool called KMWin (Kaplan-Meier for Windows) facilitating Kaplan-Meier survival time analysis. KMWin is based on the statistical software environment R and provides an easy to use graphical interface. Survival time data can be supplied as SPSS (sav), SAS export (xpt) or text file (dat), which is also a common export format of other applications such as Excel. Figures can directly be exported in any graphical file format supported by R. On the basis of a working example, we demonstrate how to use KMWin and present its main functions. We show how to control the interface, customize the graphical output, and analyse survival time data. A number of comparisons are performed between KMWin and SPSS regarding graphical output, statistical output, data management and development. Although the general functionality of SPSS is larger, KMWin comprises a number of features useful for survival time analysis in clinical trials and other applications. These are for example number of cases and number of cases under risk within the figure or provision of a queue system for repetitive analyses of updated data sets. Moreover, major adjustments of graphical settings can be performed easily on a single window. We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. It can be used by non-statisticians and provides often used functions as well as functions which are not supplied by standard software packages. The software is routinely applied in several clinical study groups.

  7. KMWin – A Convenient Tool for Graphical Presentation of Results from Kaplan-Meier Survival Time Analysis

    Science.gov (United States)

    Gross, Arnd; Ziepert, Marita; Scholz, Markus

    2012-01-01

    Background Analysis of clinical studies often necessitates multiple graphical representations of the results. Many professional software packages are available for this purpose. Most packages are either only commercially available or hard to use especially if one aims to generate or customize a huge number of similar graphical outputs. We developed a new, freely available software tool called KMWin (Kaplan-Meier for Windows) facilitating Kaplan-Meier survival time analysis. KMWin is based on the statistical software environment R and provides an easy to use graphical interface. Survival time data can be supplied as SPSS (sav), SAS export (xpt) or text file (dat), which is also a common export format of other applications such as Excel. Figures can directly be exported in any graphical file format supported by R. Results On the basis of a working example, we demonstrate how to use KMWin and present its main functions. We show how to control the interface, customize the graphical output, and analyse survival time data. A number of comparisons are performed between KMWin and SPSS regarding graphical output, statistical output, data management and development. Although the general functionality of SPSS is larger, KMWin comprises a number of features useful for survival time analysis in clinical trials and other applications. These are for example number of cases and number of cases under risk within the figure or provision of a queue system for repetitive analyses of updated data sets. Moreover, major adjustments of graphical settings can be performed easily on a single window. Conclusions We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. It can be used by non-statisticians and provides often used functions as well as functions which are not supplied by standard software packages. The software is routinely applied in several clinical study groups. PMID:22723912

  8. Impact of Sodium Chloride and Heat on Survival Time of Linguatula Serrata Nymphs in vitro: An Experimental Study

    Directory of Open Access Journals (Sweden)

    B. Hajimohammadi

    2012-07-01

    Full Text Available Introduction: Linguatula serrata is a zoonotic parasite, belonging to the class Pentastomida. The major aim of this study was to evaluate the impact of sodium chloride (NaCl and heat on survival time of Linguatula serrata nymphs. Materials & Methods: Thirty nymphs (10 in triplicate were separately transferred to plastic tubes, containing different concentrations of NaCl solution (2%, 5% and 10%. Meanwhile, 30 nymphs in tubes containing Phosphate Buffer Saline (PBS were separately treated by +50°C, +60°C and +72°C. As control group, thirty nymphs were stored in PBS at +4°C. The effects of different conditions on survival time of the nymphs were evaluated by observing their motility in different periods of time. Results: The survival time of the nymphs stored in 10% NaCl solution was too short and all of them were dead after 3 hours. But the other ones maintained in 2% NaCl solution were significantly more resistant (p<0.05 and were survived for 2 days. All the nymphs pertaining to each +60°C and +72°C treatments were found dead after first 5-minute storage interval; the nymphs stored at +50°C died totally after 20 minutes. The nymphs maintained in PBS at +4°C (control group showed the longest survival time (p<0.05; all of them were alive until day 4 and the last ones died on day 34. Conclusion: It is concluded that salting and heating have significant parasiticidal effects on L. serrata nymphs and could be used as disinfecting methods in processing of meat products especially liver. However, refrigeration at +4°C increases the resistance of the nymphs in meat products and therefore might endanger the food safety.

  9. KMWin--a convenient tool for graphical presentation of results from Kaplan-Meier survival time analysis.

    Directory of Open Access Journals (Sweden)

    Arnd Gross

    Full Text Available BACKGROUND: Analysis of clinical studies often necessitates multiple graphical representations of the results. Many professional software packages are available for this purpose. Most packages are either only commercially available or hard to use especially if one aims to generate or customize a huge number of similar graphical outputs. We developed a new, freely available software tool called KMWin (Kaplan-Meier for Windows facilitating Kaplan-Meier survival time analysis. KMWin is based on the statistical software environment R and provides an easy to use graphical interface. Survival time data can be supplied as SPSS (sav, SAS export (xpt or text file (dat, which is also a common export format of other applications such as Excel. Figures can directly be exported in any graphical file format supported by R. RESULTS: On the basis of a working example, we demonstrate how to use KMWin and present its main functions. We show how to control the interface, customize the graphical output, and analyse survival time data. A number of comparisons are performed between KMWin and SPSS regarding graphical output, statistical output, data management and development. Although the general functionality of SPSS is larger, KMWin comprises a number of features useful for survival time analysis in clinical trials and other applications. These are for example number of cases and number of cases under risk within the figure or provision of a queue system for repetitive analyses of updated data sets. Moreover, major adjustments of graphical settings can be performed easily on a single window. CONCLUSIONS: We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. It can be used by non-statisticians and provides often used functions as well as functions which are not supplied by standard software packages. The software is routinely applied in several clinical study groups.

  10. Advanced age negatively impacts survival in an experimental brain tumor model.

    Science.gov (United States)

    Ladomersky, Erik; Zhai, Lijie; Gritsina, Galina; Genet, Matthew; Lauing, Kristen L; Wu, Meijing; James, C David; Wainwright, Derek A

    2016-09-06

    Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with an average age of 64 years at the time of diagnosis. To study GBM, a number of mouse brain tumor models have been utilized. In these animal models, subjects tend to range from 6 to 12 weeks of age, which is analogous to that of a human teenager. Here, we examined the impact of age on host immunity and the gene expression associated with immune evasion in immunocompetent mice engrafted with syngeneic intracranial GL261. The data indicate that, in mice with brain tumors, youth conveys an advantage to survival. While age did not affect the tumor-infiltrating T cell phenotype or quantity, we discovered that old mice express higher levels of the immunoevasion enzyme, IDO1, which was decreased by the presence of brain tumor. Interestingly, other genes associated with promoting immunosuppression including CTLA-4, PD-L1 and FoxP3, were unaffected by age. These data highlight the possibility that IDO1 contributes to faster GBM outgrowth with advanced age, providing rationale for future investigation into immunotherapeutic targeting in the future. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Bootstrapping a time series model

    International Nuclear Information System (INIS)

    Son, M.S.

    1984-01-01

    The bootstrap is a methodology for estimating standard errors. The idea is to use a Monte Carlo simulation experiment based on a nonparametric estimate of the error distribution. The main objective of this dissertation was to demonstrate the use of the bootstrap to attach standard errors to coefficient estimates and multi-period forecasts in a second-order autoregressive model fitted by least squares and maximum likelihood estimation. A secondary objective of this article was to present the bootstrap in the context of two econometric equations describing the unemployment rate and individual income tax in the state of Oklahoma. As it turns out, the conventional asymptotic formulae (both the least squares and maximum likelihood estimates) for estimating standard errors appear to overestimate the true standard errors. But there are two problems: 1) the first two observations y 1 and y 2 have been fixed, and 2) the residuals have not been inflated. After these two factors are considered in the trial and bootstrap experiment, both the conventional maximum likelihood and bootstrap estimates of the standard errors appear to be performing quite well. At present, there does not seem to be a good rule of thumb for deciding when the conventional asymptotic formulae will give acceptable results

  12. Correlation between the genetic diversity of nosocomial pathogens and their survival time in intensive care units.

    NARCIS (Netherlands)

    Gastmeier, P; Schwab, F; Bärwolff, S; Rüden, H; Grundmann, Hajo

    2006-01-01

    Bacteria differ in their ability to survive in the hospital environment outside the human host. Species remaining viable and infectious have a higher chance of being transmitted, giving them a fitness advantage in hospitals. This differential fitness could be expected to alter the genetic population

  13. Time-related survival effects of two gluconasturtiin hydrolysis products on the terrestrial isopod Porcellio scaber

    DEFF Research Database (Denmark)

    van Ommen Kloeke, A E Elaine; Jager, Tjalling; van Gestel, Cornelis A. M.

    2012-01-01

    Glucosinolates are compounds produced by commercial crops which can hydrolyse in a range of natural toxins that may exert detrimental effects on beneficial soil organisms. This study examined the effects of 2-phenylethyl isothiocyanate and 3-phenylpropionitrile on the survival and growth of the w...

  14. Predicting treatment effect from surrogate endpoints and historical trials: an extrapolation involving probabilities of a binary outcome or survival to a specific time.

    Science.gov (United States)

    Baker, Stuart G; Sargent, Daniel J; Buyse, Marc; Burzykowski, Tomasz

    2012-03-01

    Using multiple historical trials with surrogate and true endpoints, we consider various models to predict the effect of treatment on a true endpoint in a target trial in which only a surrogate endpoint is observed. This predicted result is computed using (1) a prediction model (mixture, linear, or principal stratification) estimated from historical trials and the surrogate endpoint of the target trial and (2) a random extrapolation error estimated from successively leaving out each trial among the historical trials. The method applies to either binary outcomes or survival to a particular time that is computed from censored survival data. We compute a 95% confidence interval for the predicted result and validate its coverage using simulation. To summarize the additional uncertainty from using a predicted instead of true result for the estimated treatment effect, we compute its multiplier of standard error. Software is available for download. © 2011, The International Biometric Society No claim to original US government works.

  15. Lag space estimation in time series modelling

    DEFF Research Database (Denmark)

    Goutte, Cyril

    1997-01-01

    The purpose of this article is to investigate some techniques for finding the relevant lag-space, i.e. input information, for time series modelling. This is an important aspect of time series modelling, as it conditions the design of the model through the regressor vector a.k.a. the input layer...

  16. Time-Weighted Balanced Stochastic Model Reduction

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat; Shaker, Hamid Reza

    2011-01-01

    A new relative error model reduction technique for linear time invariant (LTI) systems is proposed in this paper. Both continuous and discrete time systems can be reduced within this framework. The proposed model reduction method is mainly based upon time-weighted balanced truncation and a recently...

  17. Effects of temperature on development, survival and reproduction of insects: Experimental design, data analysis and modeling

    Science.gov (United States)

    Jacques Regniere; James Powell; Barbara Bentz; Vincent Nealis

    2012-01-01

    The developmental response of insects to temperature is important in understanding the ecology of insect life histories. Temperature-dependent phenology models permit examination of the impacts of temperature on the geographical distributions, population dynamics and management of insects. The measurement of insect developmental, survival and reproductive responses to...

  18. Exploring location influences on firm survival rates using parametric duration models

    NARCIS (Netherlands)

    Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.; Timmermans, H.J.P.; Vries, de B.

    2010-01-01

    Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and

  19. Exploring location influences on firm survival rates using parametric duration models

    NARCIS (Netherlands)

    Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.

    2011-01-01

    Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and

  20. Exploration of location influences on firm survival rates using parametric duration models

    NARCIS (Netherlands)

    Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.

    2011-01-01

    This study explored the influences of location on business firm survival rates with the use of parametric duration models applied to a data set. Of the variables included, those found to be the most significant were accessibility to infrastructure supply, regional effects, demographic and economic

  1. Inference for shared-frailty survival models with left-truncated data

    NARCIS (Netherlands)

    van den Berg, G.J.; Drepper, B.

    2016-01-01

    Shared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with left-truncated

  2. Long time to diagnosis of medulloblastoma in children is not associated with decreased survival or with worse neurological outcome.

    Directory of Open Access Journals (Sweden)

    Jean-Francois Brasme

    Full Text Available BACKGROUND: The long time to diagnosis of medulloblastoma, one of the most frequent brain tumors in children, is the source of painful remorse and sometimes lawsuits. We analyzed its consequences for tumor stage, survival, and sequelae. PATIENTS AND METHODS: This retrospective population-based cohort study included all cases of pediatric medulloblastoma from a region of France between 1990 and 2005. We collected the demographic, clinical, and tumor data and analyzed the relations between the interval from symptom onset until diagnosis, initial disease stage, survival, and neuropsychological and neurological outcome. RESULTS: The median interval from symptom onset until diagnosis for the 166 cases was 65 days (interquartile range 31-121, range 3-457. A long interval (defined as longer than the median was associated with a lower frequency of metastasis in the univariate and multivariate analyses and with a larger tumor volume, desmoplastic histology, and longer survival in the univariate analysis, but not after adjustment for confounding factors. The time to diagnosis was significantly associated with IQ score among survivors. No significant relation was found between the time to diagnosis and neurological disability. In the 62 patients with metastases, a long prediagnosis interval was associated with a higher T stage, infiltration of the fourth ventricle floor, and incomplete surgical resection; it nonetheless did not influence survival significantly in this subgroup. CONCLUSIONS: We found complex and often inverse relations between time to diagnosis of medulloblastoma in children and initial severity factors, survival, and neuropsychological and neurological outcome. This interval appears due more to the nature of the tumor and its progression than to parental or medical factors. These conclusions should be taken into account in the information provided to parents and in expert assessments produced for malpractice claims.

  3. Formal Modeling and Analysis of Timed Systems

    DEFF Research Database (Denmark)

    Larsen, Kim Guldstrand; Niebert, Peter

    This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Formal Modeling and Analysis of Timed Systems, FORMATS 2003, held in Marseille, France in September 2003. The 19 revised full papers presented together with an invited paper and the abstracts of ...... systems, discrete time systems, timed languages, and real-time operating systems....... of two invited talks were carefully selected from 36 submissions during two rounds of reviewing and improvement. All current aspects of formal method for modeling and analyzing timed systems are addressed; among the timed systems dealt with are timed automata, timed Petri nets, max-plus algebras, real-time......This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Formal Modeling and Analysis of Timed Systems, FORMATS 2003, held in Marseille, France in September 2003. The 19 revised full papers presented together with an invited paper and the abstracts...

  4. Learning Survival Models with On-Line Simulation Activities in the Actuarial Science Degree

    Directory of Open Access Journals (Sweden)

    Antonio Fernandez-Morales

    2011-03-01

    Full Text Available The aim of this paper is to describe an on-line survival laboratory designed to enhance teaching and learning in the Statistics courses of the Actuarial Science Degree of the Uni-versity of Málaga. The objective of the on-line survival lab is to help students through a guided program of simulation activities with the understanding of the most important statistical concepts of the stochastic modeling of human survival, from an Actuarial point of view. The graphical interactive simulator is implemented as Java applets for the web version, and as a Javascript animation for a lite iPhone/iPod touch version. Finally, the results of a survey carried out at the end of the course are discussed to have a preliminary assessment of the students’ satisfaction with the resources, and their perception about the usefulness for their learning process.

  5. Statistical modelling of survival data with random effects h-likelihood approach

    CERN Document Server

    Ha, Il Do; Lee, Youngjo

    2017-01-01

    This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to research...

  6. Genetic Determinants Associated With in Vivo Survival of Burkholderia cenocepacia in the Caenorhabditis elegans Model

    KAUST Repository

    Wong, Yee-Chin

    2018-05-29

    A Burkholderia cenocepacia infection usually leads to reduced survival and fatal cepacia syndrome in cystic fibrosis patients. The identification of B. cenocepacia essential genes for in vivo survival is key to designing new anti-infectives therapies. We used the Transposon-Directed Insertion Sequencing (TraDIS) approach to identify genes required for B. cenocepacia survival in the model infection host, Caenorhabditis elegans. A B. cenocepacia J2315 transposon pool of ∼500,000 mutants was used to infect C. elegans. We identified 178 genes as crucial for B. cenocepacia survival in the infected nematode. The majority of these genes code for proteins of unknown function, many of which are encoded by the genomic island BcenGI13, while other gene products are involved in nutrient acquisition, general stress responses and LPS O-antigen biosynthesis. Deletion of the glycosyltransferase gene wbxB and a histone-like nucleoid structuring (H-NS) protein-encoding gene (BCAL0154) reduced bacterial accumulation and attenuated virulence in C. elegans. Further analysis using quantitative RT-PCR indicated that BCAL0154 modulates B. cenocepacia pathogenesis via transcriptional regulation of motility-associated genes including fliC, fliG, flhD, and cheB1. This screen has successfully identified genes required for B. cenocepacia survival within the host-associated environment, many of which are potential targets for developing new antimicrobials.

  7. Genetic Determinants Associated With in Vivo Survival of Burkholderia cenocepacia in the Caenorhabditis elegans Model

    KAUST Repository

    Wong, Yee-Chin; Abd El Ghany, Moataz; Ghazzali, Raeece N. M.; Yap, Soon-Joo; Hoh, Chee-Choong; Pain, Arnab; Nathan, Sheila

    2018-01-01

    A Burkholderia cenocepacia infection usually leads to reduced survival and fatal cepacia syndrome in cystic fibrosis patients. The identification of B. cenocepacia essential genes for in vivo survival is key to designing new anti-infectives therapies. We used the Transposon-Directed Insertion Sequencing (TraDIS) approach to identify genes required for B. cenocepacia survival in the model infection host, Caenorhabditis elegans. A B. cenocepacia J2315 transposon pool of ∼500,000 mutants was used to infect C. elegans. We identified 178 genes as crucial for B. cenocepacia survival in the infected nematode. The majority of these genes code for proteins of unknown function, many of which are encoded by the genomic island BcenGI13, while other gene products are involved in nutrient acquisition, general stress responses and LPS O-antigen biosynthesis. Deletion of the glycosyltransferase gene wbxB and a histone-like nucleoid structuring (H-NS) protein-encoding gene (BCAL0154) reduced bacterial accumulation and attenuated virulence in C. elegans. Further analysis using quantitative RT-PCR indicated that BCAL0154 modulates B. cenocepacia pathogenesis via transcriptional regulation of motility-associated genes including fliC, fliG, flhD, and cheB1. This screen has successfully identified genes required for B. cenocepacia survival within the host-associated environment, many of which are potential targets for developing new antimicrobials.

  8. Time series modeling, computation, and inference

    CERN Document Server

    Prado, Raquel

    2010-01-01

    The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

  9. Applied survival analysis using R

    CERN Document Server

    Moore, Dirk F

    2016-01-01

    Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics...

  10. Hyperthermic survival of Chinese hamster ovary cells as a function of cellular population density at the time of plating

    International Nuclear Information System (INIS)

    Highfield, D.P.; Holahan, E.V.; Holahan, P.K.; Dewey, W.C.

    1984-01-01

    The survival of synchronous G 1 or asynchronous Chinese hamster ovary cells in vitro to heat treatment may depend on the cellular population density at the time of heating and/or as the cells are cultured after heating. The addition of lethally irradiated feeder cells may increase survival at 10 -3 by as much as 10- to 100-fold for a variety of conditions when cells are heated either in suspension culture or as monolayers with or without trypsinization. The protective effect associated with feeder cells appears to be associated with close cell-to-cell proximity. However, when cells are heated without trypsinization about 24 hr or later after plating, when adaptation to monolayer has occurred, the protective effect is reduced; i.e., addition of feeder cells enhances survival much less, for example, about 2- to 3-fold at 10 -2 -10 -3 survival. Also, the survival of a cell to heat is independent of whether the neighboring cell in a microcolony is destined to live or die. Finally, if protective effects associated with cell density do occur and are not controlled, serious artifacts can result as the interaction of heat and radiation is studied; for example, survival curves can be moved upward, and thus changed in shape as the number of cells plated is increased with an increase in the hyperthermic treatment or radiation dose following hyperthermia. Therefore, to understand mechanisms and to obtain information relevant to populations of cells in close proximity, such as those in vivo, these cellular population density effects should be considered and understood

  11. First off-time treatment prostate-specific antigen kinetics predicts survival in intermittent androgen deprivation for prostate cancer.

    Science.gov (United States)

    Sanchez-Salas, Rafael; Olivier, Fabien; Prapotnich, Dominique; Dancausa, José; Fhima, Mehdi; David, Stéphane; Secin, Fernando P; Ingels, Alexandre; Barret, Eric; Galiano, Marc; Rozet, François; Cathelineau, Xavier

    2016-01-01

    Prostate-specific antigen (PSA) doubling time is relying on an exponential kinetic pattern. This pattern has never been validated in the setting of intermittent androgen deprivation (IAD). Objective is to analyze the prognostic significance for PCa of recurrent patterns in PSA kinetics in patients undergoing IAD. A retrospective study was conducted on 377 patients treated with IAD. On-treatment period (ONTP) consisted of gonadotropin-releasing hormone agonist injections combined with oral androgen receptor antagonist. Off-treatment period (OFTP) began when PSA was lower than 4 ng/ml. ONTP resumed when PSA was higher than 20 ng/ml. PSA values of each OFTP were fitted with three basic patterns: exponential (PSA(t) = λ.e(αt)), linear (PSA(t) = a.t), and power law (PSA(t) = a.t(c)). Univariate and multivariate Cox regression model analyzed predictive factors for oncologic outcomes. Only 45% of the analyzed OFTPs were exponential. Linear and power law PSA kinetics represented 7.5% and 7.7%, respectively. Remaining fraction of analyzed OFTPs (40%) exhibited complex kinetics. Exponential PSA kinetics during the first OFTP was significantly associated with worse oncologic outcome. The estimated 10-year cancer-specific survival (CSS) was 46% for exponential versus 80% for nonexponential PSA kinetics patterns. The corresponding 10-year probability of castration-resistant prostate cancer (CRPC) was 69% and 31% for the two patterns, respectively. Limitations include retrospective design and mixed indications for IAD. PSA kinetic fitted with exponential pattern in approximately half of the OFTPs. First OFTP exponential PSA kinetic was associated with a shorter time to CRPC and worse CSS. © 2015 Wiley Periodicals, Inc.

  12. Discounting Models for Outcomes over Continuous Time

    DEFF Research Database (Denmark)

    Harvey, Charles M.; Østerdal, Lars Peter

    Events that occur over a period of time can be described either as sequences of outcomes at discrete times or as functions of outcomes in an interval of time. This paper presents discounting models for events of the latter type. Conditions on preferences are shown to be satisfied if and only if t...... if the preferences are represented by a function that is an integral of a discounting function times a scale defined on outcomes at instants of time....

  13. A sequential threshold cure model for genetic analysis of time-to-event data

    DEFF Research Database (Denmark)

    Ødegård, J; Madsen, Per; Labouriau, Rodrigo S.

    2011-01-01

    In analysis of time-to-event data, classical survival models ignore the presence of potential nonsusceptible (cured) individuals, which, if present, will invalidate the inference procedures. Existence of nonsusceptible individuals is particularly relevant under challenge testing with specific...... pathogens, which is a common procedure in aquaculture breeding schemes. A cure model is a survival model accounting for a fraction of nonsusceptible individuals in the population. This study proposes a mixed cure model for time-to-event data, measured as sequential binary records. In a simulation study...... survival data were generated through 2 underlying traits: susceptibility and endurance (risk of dying per time-unit), associated with 2 sets of underlying liabilities. Despite considerable phenotypic confounding, the proposed model was largely able to distinguish the 2 traits. Furthermore, if selection...

  14. Modeling the kinetics of survival of Staphylococcus aureus in regional yogurt from goat's milk.

    Science.gov (United States)

    Bednarko-Młynarczyk, E; Szteyn, J; Białobrzewski, I; Wiszniewska-Łaszczych, A; Liedtke, K

    2015-01-01

    The aim of this study was to determine the kinetics of the survival of the test strain of Staphylococcus aureus in the product investigated. Yogurt samples were contaminated with S. aure to an initial level of 10(3)-10(4) cfu/g. The samples were then stored at four temperatures: 4, 6, 20, 22°C. During storage, the number of S. aureus forming colonies in a gram of yogurt was determined every two hours. Based on the results of the analysis culture the curves of survival were plotted. Three primary models were selected to describe the kinetics of changes in the count of bacteria: Cole's model, a modified model of Gompertz and the model of Baranyi and Roberts. Analysis of the model fit carried out based on the average values of Pearson's correlation coefficient, between the modeled and measured values, showed that the Cole's model had the worst fit. The modified Gompertz model showed the count of S. aureus as a negative value. These drawbacks were not observed in the model of Baranyi and Roberts. For this reason, this model best reflects the kinetics of changes in the number of staphylococci in yogurt.

  15. Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models

    Science.gov (United States)

    Nilsaz-Dezfouli, Hamid; Abu-Bakar, Mohd Rizam; Arasan, Jayanthi; Adam, Mohd Bakri; Pourhoseingholi, Mohamad Amin

    2017-01-01

    In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve. PMID:28469384

  16. On discrete models of space-time

    International Nuclear Information System (INIS)

    Horzela, A.; Kempczynski, J.; Kapuscik, E.; Georgia Univ., Athens, GA; Uzes, Ch.

    1992-02-01

    Analyzing the Einstein radiolocation method we come to the conclusion that results of any measurement of space-time coordinates should be expressed in terms of rational numbers. We show that this property is Lorentz invariant and may be used in the construction of discrete models of space-time different from the models of the lattice type constructed in the process of discretization of continuous models. (author)

  17. Effect of intestinal microflora on the survival time of mice exposed to lethal whole-body. gamma. irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Onoue, M.; Uchida, K.; Yokokura, T.; Takahashi, T.; Mutai, M.

    1981-11-01

    The effect of intestinal microflora on the survival time of mice exposed to 2-kR whole-body ..gamma.. irradiation was studied using germfree, monoassociated, and conventionalized ICR mice. The germfree mice were monoassociated with 1 of 11 bacterial strains, which were isolated from the fresh feces of conventional mice, 2 weeks prior to irradiation. All mice died within 3 weeks after irradiation. Monoassociation with Fusobacterium sp., Streptococcus faecalis, Escherichia coli, or Pseudomonas sp. significantly reduced the mean survival time compared to that of germfree mice. In contrast, monoassociation with Clostridium sp., Bifidobacterium pseudolongum, or Lactobacillus acidophilus significantly prolonged the mean survival time compared to that of germfree mice. This suggests that the latter organisms may perform some activity to protect the mice from radiation injury. In this histopathological autopsy examination, the main lesions were hypocellularity in hematopoietic organs and hemorrhage in various organs. Neither karyorrhexis nor desquamation of intestinal mucosal cells was observed in any mice. From these observations, it is suggested that the death of these mice was related to hematopoietic damage. Bacterial invasion into various organs was observed in conventionalized and Pseudomonas-, E. coli-, or S. faecalis-monoassociated mice but not in Clostridium-, B. pseudolongum-, L. acidophilus-, or Fusobacterium-monoassociated mice.

  18. Effect of intestinal microflora on the survival time of mice exposed to lethal whole-body γ irradiation

    International Nuclear Information System (INIS)

    Onoue, M.; Uchida, K.; Yokokura, T.; Takahashi, T.; Mutai, M.

    1981-01-01

    The effect of intestinal microflora on the survival time of mice exposed to 2-kR whole-body γ irradiation was studied using germfree, monoassociated, and conventionalized ICR mice. The germfree mice were monoassociated with 1 of 11 bacterial strains, which were isolated from the fresh feces of conventional mice, 2 weeks prior to irradiation. All mice died within 3 weeks after irradiation. Monoassociation with Fusobacterium sp., Streptococcus faecalis, Escherichia coli, or Pseudomonas sp. significantly reduced the mean survival time compared to that of germfree mice. In contrast, monoassociation with Clostridium sp., Bifidobacterium pseudolongum, or Lactobacillus acidophilus significantly prolonged the mean survival time compared to that of germfree mice. This suggests that the latter organisms may perform some activity to protect the mice from radiation injury. In this histopathological autopsy examination, the main lesions were hypocellularity in hematopoietic organs and hemorrhage in various organs. Neither karyorrhexis nor desquamation of intestinal mucosal cells was observed in any mice. From these observations, it is suggested that the death of these mice was related to hematopoietic damage. Bacterial invasion into various organs was observed in conventionalized and Pseudomonas-, E. coli-, or S. faecalis-monoassociated mice but not in Clostridium-, B. pseudolongum-, L. acidophilus-, or Fusobacterium-monoassociated mice

  19. Assessing the effect of quantitative and qualitative predictors on gastric cancer individuals survival using hierarchical artificial neural network models.

    Science.gov (United States)

    Amiri, Zohreh; Mohammad, Kazem; Mahmoudi, Mahmood; Parsaeian, Mahbubeh; Zeraati, Hojjat

    2013-01-01

    There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models. This study was designed and conducted to examine the application of these models in order to determine the survival of gastric cancer patients, in comparison to the Cox proportional hazards model. We studied the postoperative survival of 330 gastric cancer patients who suffered surgery at a surgical unit of the Iran Cancer Institute over a five-year period. Covariates of age, gender, history of substance abuse, cancer site, type of pathology, presence of metastasis, stage, and number of complementary treatments were entered in the models, and survival probabilities were calculated at 6, 12, 18, 24, 36, 48, and 60 months using the Cox proportional hazards and neural network models. We estimated coefficients of the Cox model and the weights in the neural network (with 3, 5, and 7 nodes in the hidden layer) in the training group, and used them to derive predictions in the study group. Predictions with these two methods were compared with those of the Kaplan-Meier product limit estimator as the gold standard. Comparisons were performed with the Friedman and Kruskal-Wallis tests. Survival probabilities at different times were determined using the Cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the Kaplan-Meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between Cox and Kaplan-Meier (P neural network, and the neural network and the standard (Kaplan-Meier), as well as better accuracy for the neural network (with 3 nodes in the hidden layer

  20. Modeling seasonality in bimonthly time series

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    1992-01-01

    textabstractA recurring issue in modeling seasonal time series variables is the choice of the most adequate model for the seasonal movements. One selection method for quarterly data is proposed in Hylleberg et al. (1990). Market response models are often constructed for bimonthly variables, and

  1. Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

    Science.gov (United States)

    Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

    2017-10-01

    Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (PLearning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that

  2. Validation of a Predictive Model for Survival in Metastatic Cancer Patients Attending an Outpatient Palliative Radiotherapy Clinic

    International Nuclear Information System (INIS)

    Chow, Edward; Abdolell, Mohamed; Panzarella, Tony; Harris, Kristin; Bezjak, Andrea; Warde, Padraig; Tannock, Ian

    2009-01-01

    Purpose: To validate a predictive model for survival of patients attending a palliative radiotherapy clinic. Methods and Materials: We described previously a model that had good predictive value for survival of patients referred during 1999 (1). The six prognostic factors (primary cancer site, site of metastases, Karnofsky performance score, and the fatigue, appetite and shortness-of-breath items from the Edmonton Symptom Assessment Scale) identified in this training set were extracted from the prospective database for the year 2000. We generated a partial score whereby each prognostic factor was assigned a value proportional to its prognostic weight. The sum of the partial scores for each patient was used to construct a survival prediction score (SPS). Patients were also grouped according to the number of these risk factors (NRF) that they possessed. The probability of survival at 3, 6, and 12 months was generated. The models were evaluated for their ability to predict survival in this validation set with appropriate statistical tests. Results: The median survival and survival probabilities of the training and validation sets were similar when separated into three groups using both SPS and NRF methods. There was no statistical difference in the performance of the SPS and NRF methods in survival prediction. Conclusion: Both the SPS and NRF models for predicting survival in patients referred for palliative radiotherapy have been validated. The NRF model is preferred because it is simpler and avoids the need to remember the weightings among the prognostic factors

  3. Survival probability of Baltic larval cod in relation to spatial overlap patterns with their prey obtained from drift model studies

    DEFF Research Database (Denmark)

    Hinrichsen, H.H.; Schmidt, J.O.; Petereit, C.

    2005-01-01

    Temporal mismatch between the occurrence of larvae and their prey potentially affects the spatial overlap and thus the contact rates between predator and prey. This might have important consequences for growth and survival. We performed a case study investigating the influence of circulation......-prey overlap, dependent on the hatching time of cod larvae. By performing model runs for the years 1979-1998 investigated the intra- and interannual variability of potential spatial overlap between predator and prey. Assuming uniform prey distributions, we generally found the overlap to have decreased since...

  4. Survey of time preference, delay discounting models

    Directory of Open Access Journals (Sweden)

    John R. Doyle

    2013-03-01

    Full Text Available The paper surveys over twenty models of delay discounting (also known as temporal discounting, time preference, time discounting, that psychologists and economists have put forward to explain the way people actually trade off time and money. Using little more than the basic algebra of powers and logarithms, I show how the models are derived, what assumptions they are based upon, and how different models relate to each other. Rather than concentrate only on discount functions themselves, I show how discount functions may be manipulated to isolate rate parameters for each model. This approach, consistently applied, helps focus attention on the three main components in any discounting model: subjectively perceived money; subjectively perceived time; and how these elements are combined. We group models by the number of parameters that have to be estimated, which means our exposition follows a trajectory of increasing complexity to the models. However, as the story unfolds it becomes clear that most models fall into a smaller number of families. We also show how new models may be constructed by combining elements of different models. The surveyed models are: Exponential; Hyperbolic; Arithmetic; Hyperboloid (Green and Myerson, Rachlin; Loewenstein and Prelec Generalized Hyperboloid; quasi-Hyperbolic (also known as beta-delta discounting; Benhabib et al's fixed cost; Benhabib et al's Exponential / Hyperbolic / quasi-Hyperbolic; Read's discounting fractions; Roelofsma's exponential time; Scholten and Read's discounting-by-intervals (DBI; Ebert and Prelec's constant sensitivity (CS; Bleichrodt et al.'s constant absolute decreasing impatience (CADI; Bleichrodt et al.'s constant relative decreasing impatience (CRDI; Green, Myerson, and Macaux's hyperboloid over intervals models; Killeen's additive utility; size-sensitive additive utility; Yi, Landes, and Bickel's memory trace models; McClure et al.'s two exponentials; and Scholten and Read's trade

  5. Forecasting with nonlinear time series models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econo- metrics are presented and some of their properties discussed. This in- cludes two models based on universal approximators: the Kolmogorov- Gabor polynomial model...... applied to economic fore- casting problems, is briefly highlighted. A number of large published studies comparing macroeconomic forecasts obtained using different time series models are discussed, and the paper also contains a small simulation study comparing recursive and direct forecasts in a partic...... and two versions of a simple artificial neural network model. Techniques for generating multi-period forecasts from nonlinear models recursively are considered, and the direct (non-recursive) method for this purpose is mentioned as well. Forecasting with com- plex dynamic systems, albeit less frequently...

  6. Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening.

    Science.gov (United States)

    Han, Guangchun; Zhao, Wei; Song, Xiaofeng; Kwok-Shing Ng, Patrick; Karam, Jose A; Jonasch, Eric; Mills, Gordon B; Zhao, Zhongming; Ding, Zhiyong; Jia, Peilin

    2017-10-03

    In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC's prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA). With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data. Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients' survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These

  7. Bayesian Model Selection under Time Constraints

    Science.gov (United States)

    Hoege, M.; Nowak, W.; Illman, W. A.

    2017-12-01

    Bayesian model selection (BMS) provides a consistent framework for rating and comparing models in multi-model inference. In cases where models of vastly different complexity compete with each other, we also face vastly different computational runtimes of such models. For instance, time series of a quantity of interest can be simulated by an autoregressive process model that takes even less than a second for one run, or by a partial differential equations-based model with runtimes up to several hours or even days. The classical BMS is based on a quantity called Bayesian model evidence (BME). It determines the model weights in the selection process and resembles a trade-off between bias of a model and its complexity. However, in practice, the runtime of models is another weight relevant factor for model selection. Hence, we believe that it should be included, leading to an overall trade-off problem between bias, variance and computing effort. We approach this triple trade-off from the viewpoint of our ability to generate realizations of the models under a given computational budget. One way to obtain BME values is through sampling-based integration techniques. We argue with the fact that more expensive models can be sampled much less under time constraints than faster models (in straight proportion to their runtime). The computed evidence in favor of a more expensive model is statistically less significant than the evidence computed in favor of a faster model, since sampling-based strategies are always subject to statistical sampling error. We present a straightforward way to include this misbalance into the model weights that are the basis for model selection. Our approach follows directly from the idea of insufficient significance. It is based on a computationally cheap bootstrapping error estimate of model evidence and is easy to implement. The approach is illustrated in a small synthetic modeling study.

  8. Relationships among the cervical mucus urea and acetone, accuracy of insemination timing, and sperm survival in Holstein cows.

    Science.gov (United States)

    Beran, J; Stádník, L; Ducháček, J; Okrouhlá, M; Doležalová, M; Kadlecová, V; Ptáček, M

    2013-11-01

    The objectives of this study were to evaluate the relationships among urea and acetone content in cows' cervical mucus (CM), its crystallization type (CT) and sperm survival (SS) after timed AI. Samples of CM were collected from 192 Holstein cows treated by Ovsynch(®) protocol. Analysis of the urea and acetone content for identification of the metabolic status, the arborization test for evaluation of insemination timing and the short-term heat test of SS for assessment of its suitability as a biological matrix were performed. The data set was analyzed by the GLM procedure using SAS(®). The results documented the existence of substantial differences in individual response to the Ovsynch(®) protocol causing insemination of 55.2% cows at an inappropriate time. The urea content was found as a possible indicator of a cow's metabolism and/or of insemination timing, concentrations of less than 500 mg/L corresponded (Pacetone content on SS were determined. The greatest values of SS were detected in cows with an expected response to precisely timed oestrus documented by the corresponding CT. Greater values of urea (>260 mg/L) and acetone (>5mg/L) negatively affected SS as well (P<0.05-0.01). The results confirmed that the accuracy of insemination timing can be affected by the metabolism intensity, just as CM quality directly influences sperm survival. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. Conceptual Modeling of Time-Varying Information

    DEFF Research Database (Denmark)

    Gregersen, Heidi; Jensen, Christian S.

    2004-01-01

    A wide range of database applications manage information that varies over time. Many of the underlying database schemas of these were designed using the Entity-Relationship (ER) model. In the research community as well as in industry, it is common knowledge that the temporal aspects of the mini......-world are important, but difficult to capture using the ER model. Several enhancements to the ER model have been proposed in an attempt to support the modeling of temporal aspects of information. Common to the existing temporally extended ER models, few or no specific requirements to the models were given...

  10. Iterative Bayesian Model Averaging: a method for the application of survival analysis to high-dimensional microarray data

    Directory of Open Access Journals (Sweden)

    Raftery Adrian E

    2009-02-01

    Full Text Available Abstract Background Microarray technology is increasingly used to identify potential biomarkers for cancer prognostics and diagnostics. Previously, we have developed the iterative Bayesian Model Averaging (BMA algorithm for use in classification. Here, we extend the iterative BMA algorithm for application to survival analysis on high-dimensional microarray data. The main goal in applying survival analysis to microarray data is to determine a highly predictive model of patients' time to event (such as death, relapse, or metastasis using a small number of selected genes. Our multivariate procedure combines the effectiveness of multiple contending models by calculating the weighted average of their posterior probability distributions. Our results demonstrate that our iterative BMA algorithm for survival analysis achieves high prediction accuracy while consistently selecting a small and cost-effective number of predictor genes. Results We applied the iterative BMA algorithm to two cancer datasets: breast cancer and diffuse large B-cell lymphoma (DLBCL data. On the breast cancer data, the algorithm selected a total of 15 predictor genes across 84 contending models from the training data. The maximum likelihood estimates of the selected genes and the posterior probabilities of the selected models from the training data were used to divide patients in the test (or validation dataset into high- and low-risk categories. Using the genes and models determined from the training data, we assigned patients from the test data into highly distinct risk groups (as indicated by a p-value of 7.26e-05 from the log-rank test. Moreover, we achieved comparable results using only the 5 top selected genes with 100% posterior probabilities. On the DLBCL data, our iterative BMA procedure selected a total of 25 genes across 3 contending models from the training data. Once again, we assigned the patients in the validation set to significantly distinct risk groups (p

  11. Modeling of Volatility with Non-linear Time Series Model

    OpenAIRE

    Kim Song Yon; Kim Mun Chol

    2013-01-01

    In this paper, non-linear time series models are used to describe volatility in financial time series data. To describe volatility, two of the non-linear time series are combined into form TAR (Threshold Auto-Regressive Model) with AARCH (Asymmetric Auto-Regressive Conditional Heteroskedasticity) error term and its parameter estimation is studied.

  12. Disparities in breast cancer tumor characteristics, treatment, time to treatment, and survival probability among African American and white women.

    Science.gov (United States)

    Foy, Kevin Chu; Fisher, James L; Lustberg, Maryam B; Gray, Darrell M; DeGraffinreid, Cecilia R; Paskett, Electra D

    2018-01-01

    African American (AA) women have a 42% higher breast cancer death rate compared to white women despite recent advancements in management of the disease. We examined racial differences in clinical and tumor characteristics, treatment and survival in patients diagnosed with breast cancer between 2005 and 2014 at a single institution, the James Cancer Hospital, and who were included in the Arthur G. James Cancer Hospital and Richard J. Solove Research Institute Cancer Registry in Columbus OH. Statistical analyses included likelihood ratio chi-square tests for differences in proportions, as well as univariate and multivariate Cox proportional hazards regressions to examine associations between race and overall and progression-free survival probabilities. AA women made up 10.2% (469 of 4593) the sample. Average time to onset of treatment after diagnosis was almost two times longer in AA women compared to white women (62.0 days vs 35.5 days, p  triple negative and late stage breast cancer, and were less likely to receive surgery, especially mastectomy and reconstruction following mastectomy. After adjustment for confounding factors (age, grade, and surgery), overall survival probability was significantly associated with race (HR = 1.33; 95% CI 1.03-1.72). These findings highlight the need for efforts focused on screening and receipt of prompt treatment among AA women diagnosed with breast cancer.

  13. Nutrition management methods effective in increasing weight, survival time and functional status in ALS patients: a systematic review.

    Science.gov (United States)

    Kellogg, Jaylin; Bottman, Lindsey; Arra, Erin J; Selkirk, Stephen M; Kozlowski, Frances

    2018-02-01

    Poor prognosis and decreased survival time correlate with the nutritional status of patients with amyotrophic lateral sclerosis (ALS). Various studies were reviewed which assessed weight, body mass index (BMI), survival time and ALS functional rating scale revised (ALSFRS-R) in order to determine the best nutrition management methods for this patient population. A systematic review was conducted using CINAHL, Medline, and PubMed, and various search terms in order to determine the most recent clinical trials and observational studies that have been conducted concerning nutrition and ALS. Four articles met criteria to be included in the review. Data were extracted from these articles and were inputted into the Data Extraction Tool (DET) provided by the Academy of Nutrition and Dietetics (AND). Results showed that nutrition supplementation does promote weight stabilisation or weight gain in individuals with ALS. Given the low risk and low cost associated with intervention, early and aggressive nutrition intervention is recommended. This systematic review shows that there is a lack of high quality evidence regarding the efficacy of any dietary interventions for promoting survival in ALS or slowing disease progression; therefore more research is necessary related to effects of nutrition interventions.

  14. On avian influenza epidemic models with time delay.

    Science.gov (United States)

    Liu, Sanhong; Ruan, Shigui; Zhang, Xinan

    2015-12-01

    After the outbreak of the first avian influenza A virus (H5N1) in Hong Kong in 1997, another avian influenza A virus (H7N9) crossed the species barrier in mainland China in 2013 and 2014 and caused more than 400 human cases with a death rate of nearly 40%. In this paper, we take account of the incubation periods of avian influenza A virus and construct a bird-to-human transmission model with different time delays in the avian and human populations combining the survival probability of the infective avian and human populations at the latent time. By analyzing the dynamical behavior of the model, we obtain a threshold value for the prevalence of avian influenza and investigate local and global asymptotical stability of equilibria of the system.

  15. Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

    Science.gov (United States)

    Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

    2016-01-01

    Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

  16. Cell survival in carbon beams - comparison of amorphous track model predictions

    DEFF Research Database (Denmark)

    Grzanka, L.; Greilich, S.; Korcyl, M.

    Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under i....... Amorphous track modelling of luminescence detector efficiency in proton and carbon beams. 4.Tsuruoka C, Suzuki M, Kanai T, et al. LET and ion species dependence for cell killing in normal human skin fibroblasts. Radiat Res. 2005;163:494-500.......Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under ion....... [2] . In addition, a new approach based on microdosimetric distributions is presented and investigated [3] . Material and methods: A suitable software library embrasing the mentioned amorphous track models including numerous submodels with respect to delta-electron range models, radial dose...

  17. Constitutive model with time-dependent deformations

    DEFF Research Database (Denmark)

    Krogsbøll, Anette

    1998-01-01

    are common in time as well as size. This problem is adressed by means of a new constitutive model for soils. It is able to describe the behavior of soils at different deformation rates. The model defines time-dependent and stress-related deformations separately. They are related to each other and they occur...... was the difference in time scale between the geological process of deposition (millions of years) and the laboratory measurements of mechanical properties (minutes or hours). In addition, the time scale relevant to the production history of the oil field was interesting (days or years)....

  18. Building Chaotic Model From Incomplete Time Series

    Science.gov (United States)

    Siek, Michael; Solomatine, Dimitri

    2010-05-01

    This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual

  19. First recovery in anorexia nervosa patients in the long-term course: a discrete-time survival analysis.

    Science.gov (United States)

    Herzog, W; Schellberg, D; Deter, H C

    1997-02-01

    The results of a 12-year follow-up study of occurrence and timing of first recovery in 69 hospitalized patients with severe anorexia nervosa (AN) are presented. For the first time discrete-time survival analysis methods were used to determine the likelihood of recovery in AN patients. Furthermore, predictors gleaned from pretreatment-posttreatment studies of long-term outcome in AN could be evaluated as to their effect on a change in the time course structure of the likelihood of first recovery. Results show that AN condition did not improve until after 6 years after the first inpatient treatment in 50% of patients. However, a restricter-type AN and low serum creatinine levels were predictors for earlier recovery. One specific effect was that AN patients who show purging behavior in combination with additional social disturbances have a lower chance of recovering. The use of discrete-time survival analysis methodology in further prospective studies will contribute to the development of more tailored treatment of AN, which also takes the individual phase of illness and specific aspects of the symptomatology into account.

  20. Compiling models into real-time systems

    International Nuclear Information System (INIS)

    Dormoy, J.L.; Cherriaux, F.; Ancelin, J.

    1992-08-01

    This paper presents an architecture for building real-time systems from models, and model-compiling techniques. This has been applied for building a real-time model-based monitoring system for nuclear plants, called KSE, which is currently being used in two plants in France. We describe how we used various artificial intelligence techniques for building it: a model-based approach, a logical model of its operation, a declarative implementation of these models, and original knowledge-compiling techniques for automatically generating the real-time expert system from those models. Some of those techniques have just been borrowed from the literature, but we had to modify or invent other techniques which simply did not exist. We also discuss two important problems, which are often underestimated in the artificial intelligence literature: size, and errors. Our architecture, which could be used in other applications, combines the advantages of the model-based approach with the efficiency requirements of real-time applications, while in general model-based approaches present serious drawbacks on this point

  1. Compiling models into real-time systems

    International Nuclear Information System (INIS)

    Dormoy, J.L.; Cherriaux, F.; Ancelin, J.

    1992-08-01

    This paper presents an architecture for building real-time systems from models, and model-compiling techniques. This has been applied for building a real-time model-base monitoring system for nuclear plants, called KSE, which is currently being used in two plants in France. We describe how we used various artificial intelligence techniques for building it: a model-based approach, a logical model of its operation, a declarative implementation of these models, and original knowledge-compiling techniques for automatically generating the real-time expert system from those models. Some of those techniques have just been borrowed from the literature, but we had to modify or invent other techniques which simply did not exist. We also discuss two important problems, which are often underestimated in the artificial intelligence literature: size, and errors. Our architecture, which could be used in other applications, combines the advantages of the model-based approach with the efficiency requirements of real-time applications, while in general model-based approaches present serious drawbacks on this point

  2. Risk-adjusted survival for adults following in-hospital cardiac arrest by day of week and time of day: observational cohort study

    Science.gov (United States)

    Robinson, Emily J; Power, Geraldine S; Nolan, Jerry; Soar, Jasmeet; Spearpoint, Ken; Gwinnutt, Carl; Rowan, Kathryn M

    2016-01-01

    Background Internationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events. Objective To describe IHCA demographics during three day/time periods—weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)—and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care. Methods We performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals. Results Risk-adjusted outcomes (OR (95% CI)) were worse (p20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses. Conclusions IHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during

  3. Risk-adjusted survival for adults following in-hospital cardiac arrest by day of week and time of day: observational cohort study.

    Science.gov (United States)

    Robinson, Emily J; Smith, Gary B; Power, Geraldine S; Harrison, David A; Nolan, Jerry; Soar, Jasmeet; Spearpoint, Ken; Gwinnutt, Carl; Rowan, Kathryn M

    2016-11-01

    Internationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events. To describe IHCA demographics during three day/time periods-weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)-and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care. We performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals. Risk-adjusted outcomes (OR (95% CI)) were worse (p20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses. IHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during weekday daytimes. Organisational or care differences at

  4. Electricity price modeling with stochastic time change

    International Nuclear Information System (INIS)

    Borovkova, Svetlana; Schmeck, Maren Diane

    2017-01-01

    In this paper, we develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. This technique allows us to incorporate the characteristic features of electricity prices (such as seasonal volatility, time varying mean reversion and seasonally occurring price spikes) into the model in an elegant and economically justifiable way. The stochastic time change introduces stochastic as well as deterministic (e.g., seasonal) features in the price process' volatility and in the jump component. We specify the base process as a mean reverting jump diffusion and the time change as an absolutely continuous stochastic process with seasonal component. The activity rate of the stochastic time change can be related to the factors that influence supply and demand. Here we use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change, and show that this choice leads to realistic price paths. We derive properties of the resulting price process and develop the model calibration procedure. We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths by Monte Carlo simulations. We show that the simulated price process matches the distributional characteristics of the observed electricity prices in periods of both high and low demand. - Highlights: • We develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. • We incorporate the characteristic features of electricity prices, such as seasonal volatility and spikes into the model. • We use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change • We derive properties of the resulting price process and develop the model calibration procedure. • We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths.

  5. Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic.

    Science.gov (United States)

    Wang, Ming; Long, Qi

    2016-09-01

    Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c-statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy is assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations. © 2016, The International Biometric Society.

  6. Time series modeling in traffic safety research.

    Science.gov (United States)

    Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

    2018-08-01

    The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Exact results for survival probability in the multistate Landau-Zener model

    International Nuclear Information System (INIS)

    Volkov, M V; Ostrovsky, V N

    2004-01-01

    An exact formula is derived for survival probability in the multistate Landau-Zener model in the special case where the initially populated state corresponds to the extremal (maximum or minimum) slope of a linear diabatic potential curve. The formula was originally guessed by S Brundobler and V Elzer (1993 J. Phys. A: Math. Gen. 26 1211) based on numerical calculations. It is a simple generalization of the expression for the probability of diabatic passage in the famous two-state Landau-Zener model. Our result is obtained via analysis and summation of the entire perturbation theory series

  8. Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models.

    Science.gov (United States)

    Forutan, M; Ansari Mahyari, S; Sargolzaei, M

    2015-02-01

    Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49,583 female calves born during 1998 and 2009 were considered in five age periods as days 1-30, 31-180, 181-365, 366-760 and full period (day 1-760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd-year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82-0.95 and 0.61-0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31-180 and 181-365 (r(g) = 0.59), 31-180 and 366-760 (r(g) = 0.52), and 181-365 and 366-760 (r(g) = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection. © 2014 Blackwell Verlag GmbH.

  9. Discrete-time rewards model-checked

    NARCIS (Netherlands)

    Larsen, K.G.; Andova, S.; Niebert, Peter; Hermanns, H.; Katoen, Joost P.

    2003-01-01

    This paper presents a model-checking approach for analyzing discrete-time Markov reward models. For this purpose, the temporal logic probabilistic CTL is extended with reward constraints. This allows to formulate complex measures – involving expected as well as accumulated rewards – in a precise and

  10. Modeling vector nonlinear time series using POLYMARS

    NARCIS (Netherlands)

    de Gooijer, J.G.; Ray, B.K.

    2003-01-01

    A modified multivariate adaptive regression splines method for modeling vector nonlinear time series is investigated. The method results in models that can capture certain types of vector self-exciting threshold autoregressive behavior, as well as provide good predictions for more general vector

  11. Forecasting with periodic autoregressive time series models

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

    1999-01-01

    textabstractThis paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption

  12. Time versus frequency domain measurements: layered model ...

    African Journals Online (AJOL)

    ... their high frequency content while among TEM data sets with low frequency content, the averaging times for the FEM ellipticity were shorter than the TEM quality. Keywords: ellipticity, frequency domain, frequency electromagnetic method, model parameter, orientation error, time domain, transient electromagnetic method

  13. Modeling nonhomogeneous Markov processes via time transformation.

    Science.gov (United States)

    Hubbard, R A; Inoue, L Y T; Fann, J R

    2008-09-01

    Longitudinal studies are a powerful tool for characterizing the course of chronic disease. These studies are usually carried out with subjects observed at periodic visits giving rise to panel data. Under this observation scheme the exact times of disease state transitions and sequence of disease states visited are unknown and Markov process models are often used to describe disease progression. Most applications of Markov process models rely on the assumption of time homogeneity, that is, that the transition rates are constant over time. This assumption is not satisfied when transition rates depend on time from the process origin. However, limited statistical tools are available for dealing with nonhomogeneity. We propose models in which the time scale of a nonhomogeneous Markov process is transformed to an operational time scale on which the process is homogeneous. We develop a method for jointly estimating the time transformation and the transition intensity matrix for the time transformed homogeneous process. We assess maximum likelihood estimation using the Fisher scoring algorithm via simulation studies and compare performance of our method to homogeneous and piecewise homogeneous models. We apply our methodology to a study of delirium progression in a cohort of stem cell transplantation recipients and show that our method identifies temporal trends in delirium incidence and recovery.

  14. A linear-quadratic model of cell survival considering both sublethal and potentially lethal radiation damage

    International Nuclear Information System (INIS)

    Rutz, H.P.; Coucke, P.A.; Mirimanoff, R.O.

    1991-01-01

    The authors assessed the dose-dependence of repair of potentially lethal damage in Chinese hamster ovary cells x-irradiated in vitro. The recovery ratio (RR) by which survival (SF) of the irradiated cells was enhanced increased exponentially with a linear and a quadratic component namely ζ and ψ: RR=exp(ζD+ψD 2 ). Survival of irradiated cells can thus be expressed by a combined linear-quadratic model considering 4 variables, namely α and β for the capacity of the cells to accumulate sublethal damage, and ζ and ψ for their capacity to repair potentially lethal damage: SF=exp((ζ-α)D+ (ψ-β)D 2 ). author. 26 refs.; 1 fig.; 1 tab

  15. Discrete-time modelling of musical instruments

    International Nuclear Information System (INIS)

    Vaelimaeki, Vesa; Pakarinen, Jyri; Erkut, Cumhur; Karjalainen, Matti

    2006-01-01

    This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect to time, because the aim is to run the simulation using a computer. The physics-based modelling methods can be classified as mass-spring, modal, wave digital, finite difference, digital waveguide and source-filter models. We present the basic theory and a discussion on possible extensions for each modelling technique. For some methods, a simple model example is chosen from the existing literature demonstrating a typical use of the method. For instance, in the case of the digital waveguide modelling technique a vibrating string model is discussed, and in the case of the wave digital filter technique we present a classical piano hammer model. We tackle some nonlinear and time-varying models and include new results on the digital waveguide modelling of a nonlinear string. Current trends and future directions in physical modelling of musical instruments are discussed

  16. Living donor risk model for predicting kidney allograft and patient survival in an emerging economy.

    Science.gov (United States)

    Zafar, Mirza Naqi; Wong, Germaine; Aziz, Tahir; Abbas, Khawar; Adibul Hasan Rizvi, S

    2018-03-01

    Living donor kidney is the main source of donor organs in low to middle income countries. We aimed to develop a living donor risk model that predicts graft and patient survival in an emerging economy. We used data from the Sindh Institute of Urology and Transplantation (SIUT) database (n = 2283 recipients and n = 2283 living kidney donors, transplanted between 1993 and 2009) and conducted Cox proportional hazard analyses to develop a composite score that predicts graft and patient survivals. Donor factors age, creatinine clearance, nephron dose (estimated by donor/recipient body weight ratio) and human leukocyte antigen (HLA) match were included in the living donor risk model. The adjusted hazard ratios (HRs) for graft failures among those who received a kidney with living donor scores (reference to donor score of zero) of 1, 2, 3 and 4 were 1.14 (95%CI: 0.94-1.39), 1.24 (95%CI:1.03-1.49), 1.25 (95%CI:1.03-1.51) and 1.36 (95%CI:1.08-1.72) (P-value for trend =0.05). Similar findings were observed for patient survival. Similar to findings in high income countries, our study suggests that donor characteristics such as age, nephron dose, creatinine clearance and HLA match are important factors that determine the long-term patient and graft survival in low income countries. However, other crucial but undefined factors may play a role in determining the overall risk of graft failure and mortality in living kidney donor transplant recipients. © 2016 Asian Pacific Society of Nephrology.

  17. An Optic Nerve Crush Injury Murine Model to Study Retinal Ganglion Cell Survival

    Science.gov (United States)

    Tang, Zhongshu; Zhang, Shuihua; Lee, Chunsik; Kumar, Anil; Arjunan, Pachiappan; Li, Yang; Zhang, Fan; Li, Xuri

    2011-01-01

    Injury to the optic nerve can lead to axonal degeneration, followed by a gradual death of retinal ganglion cells (RGCs), which results in irreversible vision loss. Examples of such diseases in human include traumatic optic neuropathy and optic nerve degeneration in glaucoma. It is characterized by typical changes in the optic nerve head, progressive optic nerve degeneration, and loss of retinal ganglion cells, if uncontrolled, leading to vision loss and blindness. The optic nerve crush (ONC) injury mouse model is an important experimental disease model for traumatic optic neuropathy, glaucoma, etc. In this model, the crush injury to the optic nerve leads to gradual retinal ganglion cells apoptosis. This disease model can be used to study the general processes and mechanisms of neuronal death and survival, which is essential for the development of therapeutic measures. In addition, pharmacological and molecular approaches can be used in this model to identify and test potential therapeutic reagents to treat different types of optic neuropathy. Here, we provide a step by step demonstration of (I) Baseline retrograde labeling of retinal ganglion cells (RGCs) at day 1, (II) Optic nerve crush injury at day 4, (III) Harvest the retinae and analyze RGC survival at day 11, and (IV) Representative result. PMID:21540827

  18. Waiting Time from Diagnosis to Treatment has no Impact on Survival in Patients with Esophageal Cancer

    NARCIS (Netherlands)

    Visser, E.; Leeftink, Anne Greetje; van Rossum, P.S.N.; Siesling, Sabine; van Hillegersberg, R.; Ruurda, J.P.

    2016-01-01

    Background Waiting time from diagnosis to treatment has emerged as an important quality indicator in cancer care. This study was designed to determine the impact of waiting time on long-term outcome of patients with esophageal cancer who are treated with neoadjuvant therapy followed by surgery or

  19. Does the benefit on survival from leisure time physical activity depend on physical activity at work?

    DEFF Research Database (Denmark)

    Holtermann, Andreas; Marott, Jacob Louis; Gyntelberg, Finn

    2013-01-01

    To investigate if persons with high physical activity at work have the same benefits from leisure time physical activity as persons with sedentary work.......To investigate if persons with high physical activity at work have the same benefits from leisure time physical activity as persons with sedentary work....

  20. Vitamin D Depletion in Pregnancy Decreases Survival Time, Oxygen Saturation, Lung Weight and Body Weight in Preterm Rat Offspring.

    Directory of Open Access Journals (Sweden)

    Sine Lykkedegn

    Full Text Available Animal studies suggest a role of vitamin D in fetal lung development although not studied in preterm animals. We tested the hypothesis that vitamin D depletion aggravates respiratory insufficiency in preterm rat offspring. Furthermore, the effects of vitamin D depletion on growth and lung surfactant were investigated. Female Sprague-Dawley rats were randomly assigned low vitamin D (VDL or control diet before mating and followed with serum 25-hydroxyvitamin D (s-25(OHD determinations. After cesarean section at gestational day 19 (E19 or day 22 (E22, placental weight, birth weight, crown-rump-length (CRL, oxygenation (SaO2 at 30 min and survival time were recorded. The pup lungs were analyzed for phospholipid levels, surfactant protein A-D mRNA and the expression of the vitamin D receptor (VDR. S-25(OHD was significantly lower in the VDL group at cesarean section (12 vs. 30nmol/L, p<0.0001. Compared to the controls, E19 VDL pups had lower birth weight (2.13 vs. 2.29g, p<0.001, lung weight (0.09 vs. 0.10g, p = 0.002, SaO2 (54% vs. 69%, p = 0.002 as well as reduced survival time (0.50 vs. 1.25h, p<0.0001. At E22, the VDL-induced pulmonary differences were leveled out, but VDL pups had lower CRL (4.0 vs. 4.5cm, p<0.0001. The phospholipid levels and the surfactant protein mRNA expression did not differ between the dietary groups. In conclusion, Vitamin D depletion led to lower oxygenation and reduced survival time in the preterm offspring, associated with reduced lung weight and birth weight. Further studies of vitamin D depletion in respiratory insufficiency in preterm neonates are warranted.

  1. DNA-mediated adjuvant immunotherapy extends survival in two different mouse models of myeloid malignancies.

    Science.gov (United States)

    Le Pogam, Carole; Patel, Satyananda; Gorombei, Petra; Guerenne, Laura; Krief, Patricia; Omidvar, Nader; Tekin, Nilgun; Bernasconi, Elena; Sicre, Flore; Schlageter, Marie-Helene; Chopin, Martine; Noguera, Maria-Elena; West, Robert; Abu, Ansu; Mathews, Vikram; Pla, Marika; Fenaux, Pierre; Chomienne, Christine; Padua, Rose Ann

    2015-10-20

    We have previously shown that a specific promyelocytic leukemia-retinoic acid receptor alpha (PML-RARA) DNA vaccine combined with all-trans retinoic acid (ATRA) increases the number of long term survivors with enhanced immune responses in a mouse model of acute promyelocytic leukemia (APL). This study reports the efficacy of a non-specific DNA vaccine, pVAX14Flipper (pVAX14), in both APL and high risk myelodysplastic syndrome (HR-MDS) models. PVAX14 is comprised of novel immunogenic DNA sequences inserted into the pVAX1 therapeutic plasmid. APL mice treated with pVAX14 combined with ATRA had increased survival comparable to that obtained with a specific PML-RARA vaccine. Moreover, the survival advantage correlated with decreased PML-RARA transcript levels and increase in anti-RARA antibody production. In HR-MDS mice, pVAX14 significantly improved survival and reduced biomarkers of leukemic transformation such as phosphorylated mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK) 1. In both preclinical models, pVAX14 vaccine significantly increased interferon gamma (IFNγ) production, memory T-cells (memT), reduced the number of colony forming units (CFU) and increased expression of the adapter molecule signalling to NF-κB, MyD88. These results demonstrate the adjuvant properties of pVAX14 providing thus new approaches to improve clinical outcome in two different models of myeloid malignancies, which may have potential for a broader applicability in other cancers.

  2. Impact of sentinel lymphadenectomy on survival in a murine model of melanoma.

    Science.gov (United States)

    Rebhun, Robert B; Lazar, Alexander J F; Fidler, Isaiah J; Gershenwald, Jeffrey E

    2008-01-01

    Lymphatic mapping and sentinel lymph node biopsy-also termed sentinel lymphadenectomy (SL)-has become a standard of care for patients with primary invasive cutaneous melanoma. This technique has been shown to provide accurate information about the disease status of the regional lymph node basins at risk for metastasis, provide prognostic information, and provide durable regional lymph node control. The potential survival benefit afforded to patients undergoing SL is controversial. Central to this controversy is whether metastasis to regional lymph nodes occurs independent of or prior to widespread hematogenous dissemination. A related area of uncertainty is whether tumor cells residing within regional lymph nodes have increased metastatic potential. We have used a murine model of primary invasive cutaneous melanoma based on injection of B16-BL6 melanoma cells into the pinna to address two questions: (1) does SL plus wide excision of the primary tumor result in a survival advantage over wide excision alone; and (2) do melanoma cells growing within lymph nodes produce a higher incidence of hematogenous metastases than do cells growing at the primary tumor site? We found that SL significantly improved the survival of mice with small primary tumors. We found no difference in the incidence of lung metastases produced by B16-BL6 melanoma cells growing exclusively within regional lymph nodes and cells growing within the pinna.

  3. Development of a likelihood of survival scoring system for hospitalized equine neonates using generalized boosted regression modeling.

    Directory of Open Access Journals (Sweden)

    Katarzyna A Dembek

    Full Text Available BACKGROUND: Medical management of critically ill equine neonates (foals can be expensive and labor intensive. Predicting the odds of foal survival using clinical information could facilitate the decision-making process for owners and clinicians. Numerous prognostic indicators and mathematical models to predict outcome in foals have been published; however, a validated scoring method to predict survival in sick foals has not been reported. The goal of this study was to develop and validate a scoring system that can be used by clinicians to predict likelihood of survival of equine neonates based on clinical data obtained on admission. METHODS AND RESULTS: Data from 339 hospitalized foals of less than four days of age admitted to three equine hospitals were included to develop the model. Thirty seven variables including historical information, physical examination and laboratory findings were analyzed by generalized boosted regression modeling (GBM to determine which ones would be included in the survival score. Of these, six variables were retained in the final model. The weight for each variable was calculated using a generalized linear model and the probability of survival for each total score was determined. The highest (7 and the lowest (0 scores represented 97% and 3% probability of survival, respectively. Accuracy of this survival score was validated in a prospective study on data from 283 hospitalized foals from the same three hospitals. Sensitivity, specificity, positive and negative predictive values for the survival score in the prospective population were 96%, 71%, 91%, and 85%, respectively. CONCLUSIONS: The survival score developed in our study was validated in a large number of foals with a wide range of diseases and can be easily implemented using data available in most equine hospitals. GBM was a useful tool to develop the survival score. Further evaluations of this scoring system in field conditions are needed.

  4. Time-dependent perturbation theory for nonequilibrium lattice models

    International Nuclear Information System (INIS)

    Jensen, I.; Dickman, R.

    1993-01-01

    The authors develop a time-dependent perturbation theory for nonequilibrium interacting particle systems. They focus on models such as the contact process which evolve via destruction and autocatalytic creation of particles. At a critical value of the destruction rate there is a continuous phase transition between an active steady state and the vacuum state, which is absorbing. They present several methods for deriving series for the evolution starting from a single seed particle, including expansions for the ultimate survival probability in the super- and subcritical regions, expansions for the average number of particles in the subcritical region, and short-time expansions. Algorithms for computer generation of the various expansions are presented. Rather long series (24 terms or more) and precise estimates of critical parameters are presented. 45 refs., 4 figs., 9 tabs

  5. Modeling biological pathway dynamics with timed automata.

    Science.gov (United States)

    Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

    2014-05-01

    Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

  6. Markov chains and semi-Markov models in time-to-event analysis.

    Science.gov (United States)

    Abner, Erin L; Charnigo, Richard J; Kryscio, Richard J

    2013-10-25

    A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.

  7. STI571 (Gleevec) improves tumor growth delay and survival in irradiated mouse models of glioblastoma

    International Nuclear Information System (INIS)

    Geng Ling; Shinohara, Eric T.; Kim, Dong; Tan Jiahuai; Osusky, Kate; Shyr, Yu; Hallahan, Dennis E.

    2006-01-01

    Purpose: Glioblastoma multiforme (GBM) is a devastating brain neoplasm that is essentially incurable. Although radiation therapy prolongs survival, GBMs progress within areas of irradiation. Recent studies in invertebrates have shown that STI571 (Gleevec; Novartis, East Hanover, NJ) enhances the cytotoxicity of ionizing radiation. In the present study, the effectiveness of STI571 in combination with radiation was studied in mouse models of GBM. Methods and Materials: Murine GL261 and human D54 GBM cell lines formed tumors in brains and hind limbs of C57BL6 and nude mice, respectively. GL261 and D54 cells were treated with 5 μmol/L of STI571 for 1 h and/or irradiated with 3 Gy. Protein was analyzed by Western immunoblots probed with antibodies to caspase 3, cleaved caspase 3, phospho-Akt, Akt, and platelet-derived growth factor receptor (PDGFR) α and β. Tumor volumes were assessed in mice bearing GL261 or D54 tumors treated with 21 Gy administered in seven fractionated doses. Histologic sections from STI571-treated mice were stained with phospho-Akt and phospho-PDGFR β antibodies. Kaplan-Meier survival curves were used to study the response of mice bearing intracranial implants of GL261. Results: STI571 penetrated the blood-brain barrier, which resulted in a reduction in phospho-PDGFR in GBM. STI571-induced apoptosis in GBM was significantly enhanced by irradiation. STI571 combined with irradiation induced caspase 3 cleavage in GBM cells. Glioblastoma multiforme response to therapy correlated with an increase in tumor growth delay and survival when STI571 was administered in conjunction with daily irradiation. Conclusion: These findings suggest that STI571 has the potential to augment radiotherapy and thereby improve median survival

  8. Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

    Science.gov (United States)

    Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

    2015-02-01

    We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

  9. New Insights to Compare and Choose TKTD Models for Survival Based on an Interlaboratory Study for Lymnaea stagnalis Exposed to Cd.

    Science.gov (United States)

    Baudrot, Virgile; Preux, Sara; Ducrot, Virginie; Pave, Alain; Charles, Sandrine

    2018-02-06

    Toxicokinetic-toxicodynamic (TKTD) models, as the General Unified Threshold model of Survival (GUTS), provide a consistent process-based framework compared to classical dose-response models to analyze both time and concentration-dependent data sets. However, the extent to which GUTS models (Stochastic Death (SD) and Individual Tolerance (IT)) lead to a better fitting than classical dose-response model at a given target time (TT) has poorly been investigated. Our paper highlights that GUTS estimates are generally more conservative and have a reduced uncertainty through smaller credible intervals for the studied data sets than classical TT approaches. Also, GUTS models enable estimating any x% lethal concentration at any time (LC x,t ), and provide biological information on the internal processes occurring during the experiments. While both GUTS-SD and GUTS-IT models outcompete classical TT approaches, choosing one preferentially to the other is still challenging. Indeed, the estimates of survival rate over time and LC x,t are very close between both models, but our study also points out that the joint posterior distributions of SD model parameters are sometimes bimodal, while two parameters of the IT model seems strongly correlated. Therefore, the selection between these two models has to be supported by the experimental design and the biological objectives, and this paper provides some insights to drive this choice.

  10. From discrete-time models to continuous-time, asynchronous modeling of financial markets

    NARCIS (Netherlands)

    Boer, Katalin; Kaymak, Uzay; Spiering, Jaap

    2007-01-01

    Most agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modeling of financial markets. We study the behavior of a learning market maker in a market with information

  11. From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets

    NARCIS (Netherlands)

    K. Boer-Sorban (Katalin); U. Kaymak (Uzay); J. Spiering (Jaap)

    2006-01-01

    textabstractMost agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modelling of financial markets. We study the behaviour of a learning market maker in a market with

  12. A chip-level modeling approach for rail span collapse and survivability analyses

    International Nuclear Information System (INIS)

    Marvis, D.G.; Alexander, D.R.; Dinger, G.L.

    1989-01-01

    A general semiautomated analysis technique has been developed for analyzing rail span collapse and survivability of VLSI microcircuits in high ionizing dose rate radiation environments. Hierarchical macrocell modeling permits analyses at the chip level and interactive graphical postprocessing provides a rapid visualization of voltage, current and power distributions over an entire VLSIC. The technique is demonstrated for a 16k C MOS/SOI SRAM and a CMOS/SOS 8-bit multiplier. The authors also present an efficient method to treat memory arrays as well as a three-dimensional integration technique to compute sapphire photoconduction from the design layout

  13. Modeling of the time sharing for lecturers

    Directory of Open Access Journals (Sweden)

    E. Yu. Shakhova

    2017-01-01

    Full Text Available In the context of modernization of the Russian system of higher education, it is necessary to analyze the working time of the university lecturers, taking into account both basic job functions as the university lecturer, and others.The mathematical problem is presented for the optimal working time planning for the university lecturers. The review of the documents, native and foreign works on the study is made. Simulation conditions, based on analysis of the subject area, are defined. Models of optimal working time sharing of the university lecturers («the second half of the day» are developed and implemented in the system MathCAD. Optimal solutions have been obtained.Three problems have been solved:1 to find the optimal time sharing for «the second half of the day» in a certain position of the university lecturer;2 to find the optimal time sharing for «the second half of the day» for all positions of the university lecturers in view of the established model of the academic load differentiation;3 to find the volume value of the non-standardized part of time work in the department for the academic year, taking into account: the established model of an academic load differentiation, distribution of the Faculty number for the positions and the optimal time sharing «the second half of the day» for the university lecturers of the department.Examples are given of the analysis results. The practical application of the research: the developed models can be used when planning the working time of an individual professor in the preparation of the work plan of the university department for the academic year, as well as to conduct a comprehensive analysis of the administrative decisions in the development of local university regulations.

  14. Human umbilical-cord-blood mononucleated cells enhance the survival of lethally irradiated mice. Dosage and the window of time

    International Nuclear Information System (INIS)

    Kovalenko, Olga A.; Ende, Norman; Azzam, Edouard I.

    2013-01-01

    The purpose of this study was to evaluate the window of time and dose of human umbilical-cord-blood (HUCB) mononucleated cells necessary for successful treatment of radiation injury in mice. Female A/J mice (27-30 weeks old) were exposed to an absorbed dose of 9-10 Gy of 137 Cs γ-rays delivered acutely to the whole body. They were treated either with 1 × 10 8 or 2 × 10 8 HUCB mononucleated cells at 24-52 h after the irradiation. The antibiotic Levaquin was applied 4 h postirradiation. The increased dose of cord-blood cells resulted in enhanced survival. The enhancement of survival in animals that received 2 × 10 8 HUCB mononucleated cells relative to irradiated but untreated animals was highly significant (P < 0.01). Compared with earlier studies, the increased dose of HUCB mononucleated cells, coupled with early use of an antibiotic, extended the window of time for effective treatment of severe radiation injury from 4 to 24-52 h after exposure. (author)

  15. Survival of Lactobacillus plantarumU40 on the in vitro rumen fermentation quantified with real-time PCR

    Directory of Open Access Journals (Sweden)

    W.D. Astuti

    2018-05-01

    Full Text Available The objective of this study was to evaluate the survival of L. plantarumU40 quantified with real-time PCR during in vitro rumen fermentation. The experiment was arranged in a randomized block design with 3 treatments and 4 replications. Treatments were control, rumen fermentation inoculated with L. plantarumU40and L. plantarumU40 + glucose solution. Population of L. plantarum U40 was higher at inoculation treatment. After 8 hours incubation, glucose addition tended to decrease L. plantarum U40 population. Control treatment showed lowest population of L. plantarum U40 along in vitro fermentation compared with other treatment. Inoculation of L. plantarumU40 significantly (p<0.05 increased population of LAB until 12 hours incubation compared with control. Control treatment had highest pH at all incubation time. Glucose addition significantly (P<0.05 decreased final rumen pH (24 hours (6.30, compared with control treatment (6.85. Inoculation of L. plantarum U40 with glucose addition significantly (P<0.05increased propionic acid, decreased acetic acid and A/P ratio compared with other treatments. Lactobacillus plantarum U40 without glucose addition did not affect propionic acid production significantly. As conclusion, Lactobacillus plantarum U40 can survive in rumen fluid and changes rumen fermentation when glucose is added as carbon source.

  16. Slow Freezing or Vitrification of Oocytes: Their Effects on Survival and Meiotic Spindles, and the Time Schedule for Clinical Practice

    Directory of Open Access Journals (Sweden)

    Shee-Uan Chen

    2009-03-01

    Full Text Available Both the slow-freezing method with increased sucrose concentration and new vitrification techniques significantly improve the results of cryopreservation of human oocytes. The recent perfection for vitrification includes the concepts of increase of cooling and warming rates using minimum volume methods, and decrease of toxicity by reducing the concentration of cryoprotectants. In the recent literature, the survival of cryopreserved oocytes ranged from 74% to 90% using the slow-freezing method and from 84% to 99% by vitrification. Overall, the survival rate of oocytes from vitrification (95%, 899/948 appeared higher than that of the slow-freezing method (75%, 1,275/1,683. The microtubules of meiotic spindles are vulnerable to the thermal changes and will depolymerize. After incubation, the microtubules repolymerize. Spindle recovery is faster after vitrification than slow freezing. Even so, after 3 hours of incubation, spindle recuperation is similar between vitrification and slow freezing. Considering both aspects of spindle recovery and oocyte aging, the time schedule for oocyte cryopreservation program makes fertilization in the optimal time. Intracytoplasmic sperm injection is performed for oocytes at 3 hours of post-thaw incubation from the slow-freezing method and 2 hours from vitrification, with restoration of meiotic spindles. The pregnancy potential of cryopreserved oocytes is comparable to that of fresh oocytes or frozen embryos. Cryopreservation of oocytes would importantly contribute to oocyte donation and preservation of fertility for cancer patients.

  17. Modelling survival and connectivity of Mnemiopsis leidyi in the south-western North Sea and Scheldt estuaries

    DEFF Research Database (Denmark)

    van der Molen, J.; van Beek, J.; Augustine, Starrlight

    2015-01-01

    Three different models were applied to study the reproduction, survival and dispersal of Mnemiopsis leidyi in the Scheldt estuaries and the southern North Sea: a high-resolution particle tracking model with passive particles, a low-resolution particle tracking model with a reproduction model coup...

  18. Estimating High-Dimensional Time Series Models

    DEFF Research Database (Denmark)

    Medeiros, Marcelo C.; Mendes, Eduardo F.

    We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...

  19. Real-time modeling of heat distributions

    Science.gov (United States)

    Hamann, Hendrik F.; Li, Hongfei; Yarlanki, Srinivas

    2018-01-02

    Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.

  20. The M1 form of tumor-associated macrophages in non-small cell lung cancer is positively associated with survival time

    International Nuclear Information System (INIS)

    Ma, Junliang; Liu, Lunxu; Che, Guowei; Yu, Nanbin; Dai, Fuqiang; You, Zongbing

    2010-01-01

    Tumor-associated macrophages (TAMs) play an important role in growth, progression and metastasis of tumors. In non-small cell lung cancer (NSCLC), TAMs' anti-tumor or pro-tumor role is not determined. Macrophages are polarized into M1 (with anti-tumor function) and M2 (with pro-tumor function) forms. This study was conducted to determine whether the M1 and M2 macrophage densities in NSCLC are associated with patient's survival time. Fifty patients with an average of 1-year survival (short survival group) and 50 patients with an average of 5-year survival (long survival group) were included in this retrospective study. Paraffin-embedded NSCLC specimens and their clinicopathological data including up to 8-year follow-up information were used. Immunohistochemical double-staining of CD68/HLA-DR (markers for M1 macrophages) and CD68/CD163 (markers for M2 macrophages) was performed and evaluated in a blinded fashion. The M1 and M2 macrophage densities in the tumor islets, stroma, or islets and stroma were determined using computer-aided microscopy. Correlation of the macrophage densities and patient's survival time was analyzed using the Statistical Package for the Social Sciences. Approximately 70% of TAMs were M2 macrophages and the remaining 30% were M1 macrophages in NSCLC. The M2 macrophage densities (approximately 78 to 113 per mm 2 ) in the tumor islets, stroma, or islets and stroma were not significantly different between the long survival and short survival groups. The M1 macrophage densities in the tumor islets (approximately 70/mm 2 ) and stroma (approximately 34/mm 2 ) of the long survival group were significantly higher than the M1 macrophage densities in the tumor islets (approximately 7/mm 2 ) and stroma (13/mm 2 ) of the short survival group (P < 0.001 and P < 0.05, respectively). The M2 macrophage densities were not associated with patient's survival time. The M1 macrophage densities in the tumor islets, stroma, or islets and stroma

  1. Novel bifunctional anthracycline and nitrosourea chemotherapy for human bladder cancer: analysis in a preclinical survival model.

    Science.gov (United States)

    Glaves, D; Murray, M K; Raghavan, D

    1996-08-01

    A hybrid drug [N-2-chloroethylnitrosoureidodaunorubicin (AD312)] that combines structural and functional features of both anthracyclines and nitrosoureas was evaluated in a preclinical survival model of human bladder cancer. To measure the therapeutic activity of AD312, UCRU-BL13 transitional cell carcinoma cells were grown as xenografts in nude mice, and tumor growth rates were compared after i.v. administration of the drug at three dose levels. AD312 treatment at 45 and 60 mg/kg achieved 7-10-fold inhibition of tumor growth and increased host survival by 156 and 249%, respectively. Doses of 60 mg/kg showed optimal therapeutic efficacy, with sustained tumor growth inhibition, an over 2-fold increase in life span, and 40% of mice tumor free ("cured") at 120 days. Tumors were unresponsive to maximum tolerated doses of doxorubicin, a standard anthracycline used as a single agent and in combination therapies for bladder cancer. 1,3-Bis-[2-chloroethyl]-1-nitrosourea was used as a control for the apparently enhanced response of human tumors in murine hosts to nitrosoureas. 1, 3-Bis-[2-chloroethyl]-1-nitrosourea administered in three injections of 20 mg/kg did not cure mice but temporarily inhibited tumor growth by 70% and prolonged survival by 55%; its activity in this model suggests that it may be included in the repertoire of alkylating agents currently used for treatment of bladder cancers. AD312 showed increased antitumor activity with less toxicity than doxorubicin, and its bifunctional properties provide the opportunity for simultaneous treatment of individual cancer cells with two cytotoxic modalities as well as treatment of heterogeneous populations typical of bladder cancers. This novel cytotoxic drug cured doxorubicin-refractory disease and should be investigated for the clinical management of bladder cancer.

  2. Conditionally replicating adenovirus expressing TIMP2 increases survival in a mouse model of disseminated ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Sherry W Yang

    Full Text Available Ovarian cancer remains difficult to treat mainly due to presentation of the disease at an advanced stage. Conditionally-replicating adenoviruses (CRAds are promising anti-cancer agents that selectively kill the tumor cells. The present study evaluated the efficacy of a novel CRAd (Ad5/3-CXCR4-TIMP2 containing the CXCR4 promoter for selective viral replication in cancer cells together with TIMP2 as a therapeutic transgene, targeting the matrix metalloproteases (MMPs in a murine orthotopic model of disseminated ovarian cancer. An orthotopic model of ovarian cancer was established in athymic nude mice by intraperitonal injection of the human ovarian cancer cell line, SKOV3-Luc, expressing luciferase. Upon confirmation of peritoneal dissemination of the cells by non-invasive imaging, mice were randomly divided into four treatment groups: PBS, Ad-ΔE1-TIMP2, Ad5/3-CXCR4, and Ad5/3-CXCR4-TIMP2. All mice were imaged weekly to monitor tumor growth and were sacrificed upon reaching any of the predefined endpoints, including high tumor burden and significant weight loss along with clinical evidence of pain and distress. Survival analysis was performed using the Log-rank test. The median survival for the PBS cohort was 33 days; for Ad-ΔE1-TIMP2, 39 days; for Ad5/3-CXCR4, 52.5 days; and for Ad5/3-CXCR4-TIMP2, 63 days. The TIMP2-armed CRAd delayed tumor growth and significantly increased survival when compared to the unarmed CRAd. This therapeutic effect was confirmed to be mediated through inhibition of MMP9. Results of the in vivo study support the translational potential of Ad5/3-CXCR4-TIMP2 for treatment of human patients with advanced ovarian cancer.

  3. Space-time modeling of timber prices

    Science.gov (United States)

    Mo Zhou; Joseph Buongriorno

    2006-01-01

    A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...

  4. On modeling panels of time series

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    2002-01-01

    textabstractThis paper reviews research issues in modeling panels of time series. Examples of this type of data are annually observed macroeconomic indicators for all countries in the world, daily returns on the individual stocks listed in the S&P500, and the sales records of all items in a

  5. Time Series Modelling using Proc Varmax

    DEFF Research Database (Denmark)

    Milhøj, Anders

    2007-01-01

    In this paper it will be demonstrated how various time series problems could be met using Proc Varmax. The procedure is rather new and hence new features like cointegration, testing for Granger causality are included, but it also means that more traditional ARIMA modelling as outlined by Box...

  6. Theory of Time beyond the standard model

    International Nuclear Information System (INIS)

    Poliakov, Eugene S.

    2008-01-01

    A frame of non-uniform time is discussed. A concept of 'flow of time' is presented. The principle of time relativity in analogy with Galilean principle of relativity is set. Equivalence principle is set to state that the outcome of non-uniform time in an inertial frame of reference is equivalent to the outcome of a fictitious gravity force external to the frame of reference. Thus it is flow of time that causes gravity rather than mass. The latter is compared to experimental data achieving precision of up to 0.0003%. It is shown that the law of energy conservation is inapplicable to the frames of non-uniform time. A theoretical model of a physical entity (point mass, photon) travelling in the field of non-uniform time is considered. A generalized law that allows the flow of time to replace classical energy conservation is introduced on the basis of the experiment of Pound and Rebka. It is shown that linear dependence of flow of time on spatial coordinate conforms the inverse square law of universal gravitation and Keplerian mechanics. Momentum is shown to still be conserved

  7. Swedish National Registry of Urinary Bladder Cancer: No difference in relative survival over time despite more aggressive treatment.

    Science.gov (United States)

    Jahnson, Staffan; Hosseini Aliabad, Abolfazl; Holmäng, Sten; Jancke, Georg; Liedberg, Fredrik; Ljungberg, Börje; Malmström, Per-Uno; Rosell, Johan

    2016-01-01

    The aim of this study was to use the Swedish National Registry of Urinary Bladder Cancer (SNRUBC) to investigate changes in patient and tumour characteristics, management and survival in bladder cancer cases over a period of 15 years. All patients with newly detected bladder cancer reported to the SNRUBC during 1997-2011 were included in the study. The cohort was divided into three groups, each representing 5 years of the 15 year study period. The study included 31,266 patients (74% men, 26% women) with a mean age of 72 years. Mean age was 71.7 years in the first subperiod (1997-2001) and 72.5 years in the last subperiod (2007-2011). Clinical T categorization changed from the first to the last subperiod: Ta from 45% to 48%, T1 from 21.6% to 22.4%, and T2-T4 from 27% to 25%. Also from the first to the last subperiod, intravesical treatment after transurethral resection for T1G2 and T1G3 tumours increased from 15% to 40% and from 30% to 50%, respectively, and cystectomy for T2-T4 tumours increased from 30% to 40%. No differences between the analysed subperiods were found regarding relative survival in patients with T1 or T2-T4 tumours, or in the whole cohort. This investigation based on a national bladder cancer registry showed that the age of the patients at diagnosis increased, and the proportion of muscle-invasive tumours decreased. The treatment of all tumour stages became more aggressive but relative survival showed no statistically significant change over time.

  8. Physical models on discrete space and time

    International Nuclear Information System (INIS)

    Lorente, M.

    1986-01-01

    The idea of space and time quantum operators with a discrete spectrum has been proposed frequently since the discovery that some physical quantities exhibit measured values that are multiples of fundamental units. This paper first reviews a number of these physical models. They are: the method of finite elements proposed by Bender et al; the quantum field theory model on discrete space-time proposed by Yamamoto; the finite dimensional quantum mechanics approach proposed by Santhanam et al; the idea of space-time as lattices of n-simplices proposed by Kaplunovsky et al; and the theory of elementary processes proposed by Weizsaecker and his colleagues. The paper then presents a model proposed by the authors and based on the (n+1)-dimensional space-time lattice where fundamental entities interact among themselves 1 to 2n in order to build up a n-dimensional cubic lattice as a ground field where the physical interactions take place. The space-time coordinates are nothing more than the labelling of the ground field and take only discrete values. 11 references

  9. Rethinking plant functional types in Earth System Models: pan-tropical analysis of tree survival across environmental gradients

    Science.gov (United States)

    Johnson, D. J.; Needham, J.; Xu, C.; Davies, S. J.; Bunyavejchewin, S.; Giardina, C. P.; Condit, R.; Cordell, S.; Litton, C. M.; Hubbell, S.; Kassim, A. R. B.; Shawn, L. K. Y.; Nasardin, M. B.; Ong, P.; Ostertag, R.; Sack, L.; Tan, S. K. S.; Yap, S.; McDowell, N. G.; McMahon, S.

    2016-12-01

    Terrestrial carbon cycling is a function of the growth and survival of trees. Current model representations of tree growth and survival at a global scale rely on coarse plant functional traits that are parameterized very generally. In view of the large biodiversity in the tropical forests, it is important that we account for the functional diversity in order to better predict tropical forest responses to future climate changes. Several next generation Earth System Models are moving towards a size-structured, trait-based approach to modelling vegetation globally, but the challenge of which and how many traits are necessary to capture forest complexity remains. Additionally, the challenge of collecting sufficient trait data to describe the vast species richness of tropical forests is enormous. We propose a more fundamental approach to these problems by characterizing forests by their patterns of survival. We expect our approach to distill real-world tree survival into a reasonable number of functional types. Using 10 large-area tropical forest plots that span geographic, edaphic and climatic gradients, we model tree survival as a function of tree size for hundreds of species. We found surprisingly few categories of size-survival functions emerge. This indicates some fundamental strategies at play across diverse forests to constrain the range of possible size-survival functions. Initial cluster analysis indicates that four to eight functional forms are necessary to describe variation in size-survival relations. Temporal variation in size-survival functions can be related to local environmental variation, allowing us to parameterize how demographically similar groups of species respond to perturbations in the ecosystem. We believe this methodology will yield a synthetic approach to classifying forest systems that will greatly reduce uncertainty and complexity in global vegetation models.

  10. Evidence for a time-dependent association between FOLR1 expression and survival from ovarian carcinoma

    DEFF Research Database (Denmark)

    Köbel, M; Madore, J; Ramus, S J

    2014-01-01

    BACKGROUND: Folate receptor 1 (FOLR1) is expressed in the majority of ovarian carcinomas (OvCa), making it an attractive target for therapy. However, clinical trials testing anti-FOLR1 therapies in OvCa show mixed results and require better understanding of the prognostic relevance of FOLR1...... stage I/II tumours, patients with FOLR1-positive HGSC showed increased OS during the first 2 years only (hazard ratio=0.44, 95% confidence interval=0.20-0.96) and patients with FOLR1-positive clear cell carcinomas (CCC) showed decreased PFS independent of follow-up time (HR=1.89, 95% CI=1.10-3.25, N=259...

  11. NanOx, a new model to predict cell survival in the context of particle therapy

    Science.gov (United States)

    Cunha, M.; Monini, C.; Testa, E.; Beuve, M.

    2017-02-01

    Particle therapy is increasingly attractive for the treatment of tumors and the number of facilities offering it is rising worldwide. Due to the well-known enhanced effectiveness of ions, it is of utmost importance to plan treatments with great care to ensure tumor killing and healthy tissues sparing. Hence, the accurate quantification of the relative biological effectiveness (RBE) of ions, used in the calculation of the biological dose, is critical. Nevertheless, the RBE is a complex function of many parameters and its determination requires modeling. The approaches currently used have allowed particle therapy to thrive, but still show some shortcomings. We present herein a short description of a new theoretical framework, NanOx, to calculate cell survival in the context of particle therapy. It gathers principles from existing approaches, while addressing some of their weaknesses. NanOx is a multiscale model that takes the stochastic nature of radiation at nanometric and micrometric scales fully into account, integrating also the chemical aspects of radiation-matter interaction. The latter are included in the model by means of a chemical specific energy, determined from the production of reactive chemical species induced by irradiation. Such a production represents the accumulation of oxidative stress and sublethal damage in the cell, potentially generating non-local lethal events in NanOx. The complementary local lethal events occur in a very localized region and can, alone, lead to cell death. Both these classes of events contribute to cell death. The comparison between experimental data and model predictions for the V79 cell line show a good agreement. In particular, the dependence of the typical shoulders of cell survival curves on linear energy transfer are well described, but also the effectiveness of different ions, including the overkill effect. These results required the adjustment of a number of parameters compatible with the application of the model in

  12. Challenges in economic modeling of anticancer therapies: an example of modeling the survival benefit of olaparib maintenance therapy for patients with BRCA-mutated platinum-sensitive relapsed ovarian cancer.

    Science.gov (United States)

    Hettle, Robert; Posnett, John; Borrill, John

    2015-01-01

    The aim of this paper is to describe a four health-state, semi-Markov model structure with health states defined by initiation of subsequent treatment, designed to make best possible use of the data available from a phase 2 clinical trial. The approach is illustrated using data from a sub-group of patients enrolled in a phase 2 clinical trial of olaparib maintenance therapy in patients with platinum-sensitive relapsed ovarian cancer and a BRCA mutation (NCT00753545). A semi-Markov model was developed with four health states: progression-free survival (PFS), first subsequent treatment (FST), second subsequent treatment (SST), and death. Transition probabilities were estimated by fitting survival curves to trial data for time from randomization to FST, time from FST to SST, and time from SST to death. Survival projections generated by the model are broadly consistent with the outcomes observed in the clinical trial. However, limitations of the trial data (small sample size, immaturity of the PFS and overall survival [OS] end-points, and treatment switching) create uncertainty in estimates of survival. The model framework offers a promising approach to evaluating cost-effectiveness of a maintenance therapy for patients with cancer, which may be generalizable to other chronic diseases.

  13. A flexible and coherent test/estimation procedure based on restricted mean survival times for censored time-to-event data in randomized clinical trials.

    Science.gov (United States)

    Horiguchi, Miki; Cronin, Angel M; Takeuchi, Masahiro; Uno, Hajime

    2018-04-22

    In randomized clinical trials where time-to-event is the primary outcome, almost routinely, the logrank test is prespecified as the primary test and the hazard ratio is used to quantify treatment effect. If the ratio of 2 hazard functions is not constant, the logrank test is not optimal and the interpretation of hazard ratio is not obvious. When such a nonproportional hazards case is expected at the design stage, the conventional practice is to prespecify another member of weighted logrank tests, eg, Peto-Prentice-Wilcoxon test. Alternatively, one may specify a robust test as the primary test, which can capture various patterns of difference between 2 event time distributions. However, most of those tests do not have companion procedures to quantify the treatment difference, and investigators have fallen back on reporting treatment effect estimates not associated with the primary test. Such incoherence in the "test/estimation" procedure may potentially mislead clinicians/patients who have to balance risk-benefit for treatment decision. To address this, we propose a flexible and coherent test/estimation procedure based on restricted mean survival time, where the truncation time τ is selected data dependently. The proposed procedure is composed of a prespecified test and an estimation of corresponding robust and interpretable quantitative treatment effect. The utility of the new procedure is demonstrated by numerical studies based on 2 randomized cancer clinical trials; the test is dramatically more powerful than the logrank, Wilcoxon tests, and the restricted mean survival time-based test with a fixed τ, for the patterns of difference seen in these cancer clinical trials. Copyright © 2018 John Wiley & Sons, Ltd.

  14. Users' guide to system dynamics model describing Coho salmon survival in Olema Creek, Point Reyes National Seashore, Marin County, California

    Science.gov (United States)

    Woodward, Andrea; Torregrosa, Alicia; Madej, Mary Ann; Reichmuth, Michael; Fong, Darren

    2014-01-01

    The system dynamics model described in this report is the result of a collaboration between U.S. Geological Survey (USGS) scientists and National Park Service (NPS) San Francisco Bay Area Network (SFAN) staff, whose goal was to develop a methodology to integrate inventory and monitoring data to better understand ecosystem dynamics and trends using salmon in Olema Creek, Marin County, California, as an example case. The SFAN began monitoring multiple life stages of coho salmon (Oncorhynchus kisutch) in Olema Creek during 2003 (Carlisle and others, 2013), building on previous monitoring of spawning fish and redds. They initiated water-quality and habitat monitoring, and had access to flow and weather data from other sources. This system dynamics model of the freshwater portion of the coho salmon life cycle in Olema Creek integrated 8 years of existing monitoring data, literature values, and expert opinion to investigate potential factors limiting survival and production, identify data gaps, and improve monitoring and restoration prescriptions. A system dynamics model is particularly effective when (1) data are insufficient in time series length and/or measured parameters for a statistical or mechanistic model, and (2) the model must be easily accessible by users who are not modelers. These characteristics helped us meet the following overarching goals for this model: Summarize and synthesize NPS monitoring data with data and information from other sources to describe factors and processes affecting freshwater survival of coho salmon in Olema Creek. Provide a model that can be easily manipulated to experiment with alternative values of model parameters and novel scenarios of environmental drivers. Although the model describes the ecological dynamics of Olema Creek, these dynamics are structurally similar to numerous other coastal streams along the California coast that also contain anadromous fish populations. The model developed for Olema can be used, at least as a

  15. Dimethylaminoparthenolide and gemcitabine: a survival study using a genetically engineered mouse model of pancreatic cancer

    International Nuclear Information System (INIS)

    Yip-Schneider, Michele T; Wu, Huangbing; Stantz, Keith; Agaram, Narasimhan; Crooks, Peter A; Schmidt, C Max

    2013-01-01

    Pancreatic cancer remains one of the deadliest cancers due to lack of early detection and absence of effective treatments. Gemcitabine, the current standard-of-care chemotherapy for pancreatic cancer, has limited clinical benefit. Treatment of pancreatic cancer cells with gemcitabine has been shown to induce the activity of the transcription factor nuclear factor-kappaB (NF-κB) which regulates the expression of genes involved in the inflammatory response and tumorigenesis. It has therefore been proposed that gemcitabine-induced NF-κB activation may result in chemoresistance. We hypothesize that NF-κB suppression by the novel inhibitor dimethylaminoparthenolide (DMAPT) may enhance the effect of gemcitabine in pancreatic cancer. The efficacy of DMAPT and gemcitabine was evaluated in a chemoprevention trial using the mutant Kras and p53-expressing LSL-Kras G12D/+ ; LSL-Trp53 R172H ; Pdx-1-Cre mouse model of pancreatic cancer. Mice were randomized to treatment groups (placebo, DMAPT [40 mg/kg/day], gemcitabine [50 mg/kg twice weekly], and the combination DMAPT/gemcitabine). Treatment was continued until mice showed signs of ill health at which time they were sacrificed. Plasma cytokine levels were determined using a Bio-Plex immunoassay. Statistical tests used included log-rank test, ANOVA with Dunnett’s post-test, Student’s t-test, and Fisher exact test. Gemcitabine or the combination DMAPT/gemcitabine significantly increased median survival and decreased the incidence and multiplicity of pancreatic adenocarcinomas. The DMAPT/gemcitabine combination also significantly decreased tumor size and the incidence of metastasis to the liver. No significant differences in the percentages of normal pancreatic ducts or premalignant pancreatic lesions were observed between the treatment groups. Pancreata in which no tumors formed were analyzed to determine the extent of pre-neoplasia; mostly normal ducts or low grade pancreatic lesions were observed, suggesting prevention

  16. Effect of Migration Pathway on Travel Time and Survival of Acoustic-Tagged Juvenile Salmonids in the Columbia River Estuary

    Energy Technology Data Exchange (ETDEWEB)

    Harnish, Ryan A.; Johnson, Gary E.; McMichael, Geoffrey A.; Hughes, Michael S.; Ebberts, Blaine D.

    2012-02-01

    Off-channel areas (side channels, tidal flats, sand bars, and shallow-water bays) may serve as important migration corridors through estuarine environments for salmon and steelhead smolts. Relatively large percentages (21-33%) of acoustic-tagged yearling and subyearling Chinook salmon and steelhead smolts were detected migrating through off-channel areas of the Columbia River estuary in 2008. The probability of survival for off-channel migrants (0.78-0.94) was similar to or greater than the survival probability of main channel migrants (0.67-0.93). Median travel times were similar for all species or run types and migration pathways we examined, ranging from 1-2 d. The route used by smolts to migrate through the estuary may affect their vulnerability to predation. Acoustic-tagged steelhead that migrated nearest to avian predator nesting colonies experienced higher predation rates (24%) than those that migrated farthest from the colonies (10%). The use of multiple migration pathways may be advantageous to out-migrating smolts because it helps to buffer against high rates of mortality, which may occur in localized areas, and helps to minimize inter- and intraspecific competition.

  17. ENTREPRENEURSHIP IN TIMES OF ECONOMIC AND FINANCIAL CRISES, METHODS OF ADAPTATION AND SURVIVAL.

    Directory of Open Access Journals (Sweden)

    Radu Oprea

    2011-12-01

    Full Text Available This paper shows the main results of a research activity conducted in the South – East region of Romania during November 2009, over 117 small and medium-sized enterprises. The results help to better explain some of the social problems that have been generated in the region as a snow ball effect, due to the economic and financial crisis. The research has revealed the following:The majority of the employees of the companies that were interviewed do not participate in training courses related to project management and personal development. However, company administrators consider that such courses are useful to increase competitiveness in times of economic and financial crises. Personnel under 40 years of age suffer from a lack of professional training and dedication to job requirements. Companies have expressed an interest in accessing European Union funding. However, they do not have complete information that would allow them to start a project and finalize it. This lack of information is mainly due to lack of access to specialists who would write the projects and submit them. The majority of entrepreneurs consider they cannot write the projects themselves but on the other hand they do not have access to consulting companies or other organizations that could help them. Their main information source is the mass-media.As a result, companies have adjusted to the effects of the economic crisis, diminishing their activity and laying off people, decreasing the running expenses and stopping investing in their development.

  18. Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim (University of Texas at Austin, Austin, TX); Gilbert, Bob (University of Texas at Austin, Austin, TX); Lake, Larry W. (University of Texas at Austin, Austin, TX); Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett (University of Texas at Austin, Austin, TX); Thomas, Sunil G. (University of Texas at Austin, Austin, TX); Rightley, Michael J.; Rodriguez, Adolfo (University of Texas at Austin, Austin, TX); Klie, Hector (University of Texas at Austin, Austin, TX); Banchs, Rafael (University of Texas at Austin, Austin, TX); Nunez, Emilio J. (University of Texas at Austin, Austin, TX); Jablonowski, Chris (University of Texas at Austin, Austin, TX)

    2006-11-01

    The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensor packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging

  19. A comparative study of two food model systems to test the survival of Campylobacter jejuni at -18 degrees C

    DEFF Research Database (Denmark)

    Birk, Tina; Rosenquist, Hanne; Brondsted, L.

    2006-01-01

    The survival of Campylobacter jejuni NCTC 11168 was tested at freezing conditions (-18 degrees C) over a period of 32 days in two food models that simulated either (i) the chicken skin surface (skin model) or (ii) the chicken juice in and around a broiler carcass (liquid model). In the skin model...... NCTC 11168 cells was slower when suspended in chicken juice than in BHIB. After freezing for 32 days, the reductions in the cell counts were 1.5 log CFU/ml in chicken juice and 3.5 log CFU/ml in BHIB. After the same time of freezing but when inoculated onto chicken skin, C. jejuni NCTC 11168...... was reduced by 2.2 log units when inoculated in chicken juice and 3.2 log units when inoculated into BHIB. For both models, the major decrease occurred within the first 24 h of freezing. The results obtained in the liquid model with chicken juice were comparable to the reductions of Campylobacter observed...

  20. Thresholds and timing of pre-operative thrombocytosis and ovarian cancer survival: analysis of laboratory measures from electronic medical records

    International Nuclear Information System (INIS)

    Cozzi, Gabriella D.; Samuel, Jacob M.; Fromal, Jason T.; Keene, Spencer; Crispens, Marta A.; Khabele, Dineo; Beeghly-Fadiel, Alicia

    2016-01-01

    Thrombocytosis has been associated with poor ovarian cancer prognosis. However, comparisons of thresholds to define thrombocytosis and evaluation of relevant timing of platelet measurement has not been previously conducted. We selected Tumor Registry confirmed ovarian, primary peritoneal, and fallopian tube cancer cases diagnosed between 1995–2013 from the Vanderbilt University Medical Center. Laboratory measured platelet values from electronic medical records (EMR) were used to determine thrombocytosis at three thresholds: a platelet count greater than 350, 400, or 450 × 10 9 /liter. Timing was evaluated with 5 intervals: on the date of diagnosis, and up to 1, 2, 4, and 8 weeks prior to the date of diagnosis. Cox regression was used to calculate hazard ratios (HR) and confidence intervals (CI) for association with overall survival; adjustment included age, stage, grade, and histologic subtype of disease. Pre-diagnosis platelet measures were available for 136, 241, 280, 297, and 304 cases in the five intervals. The prevalence of thrombocytosis decreased with increasing thresholds and was generally consistent across the five time intervals, ranging from 44.8–53.2 %, 31.6–39.4 %, and 19.9–26.1 % across the three thresholds. Associations with higher grade and stage of disease gained significance as the threshold increased. With the exception of the lowest threshold on the date of diagnosis (HR 350 : 1.55, 95 % CI: 0.97–2.47), all other survival associations were significant, with the highest reaching twice the risk of death for thrombocytosis on the date of diagnosis (HR 400 : 2.01, 95 % CI: 1.25–3.23). Our EMR approach yielded associations comparable to published findings from medical record abstraction approaches. In addition, our results indicate that lower thrombocytosis thresholds and platelet measures up to 8 weeks before diagnosis may inform ovarian cancer characteristics and prognosis

  1. Does the benefit on survival from leisure time physical activity depend on physical activity at work? A prospective cohort study.

    Directory of Open Access Journals (Sweden)

    Andreas Holtermann

    Full Text Available PURPOSE: To investigate if persons with high physical activity at work have the same benefits from leisure time physical activity as persons with sedentary work. METHODS: In the Copenhagen City Heart Study, a prospective cohort of 7,411 males and 8,916 females aged 25-66 years without known cardiovascular disease at entry in 1976-78, 1981-83, 1991-94, or 2001-03, the authors analyzed with sex-stratified multivariate Cox proportional hazards regression the association between leisure time physical activity and cardiovascular and all-cause mortality among individuals with different levels of occupational physical activity. RESULTS: During a median follow-up of 22.4 years, 4,003 individuals died from cardiovascular disease and 8,935 from all-causes. Irrespective of level of occupational physical activity, a consistently lower risk with increasing leisure time physical activity was found for both cardiovascular and all-cause mortality among both men and women. Compared to low leisure time physical activity, the survival benefit ranged from 1.5-3.6 years for moderate and 2.6-4.7 years for high leisure time physical activity among the different levels of occupational physical activity. CONCLUSION: Public campaigns and initiatives for increasing physical activity in the working population should target everybody, irrespective of physical activity at work.

  2. Does the benefit on survival from leisure time physical activity depend on physical activity at work? A prospective cohort study.

    Science.gov (United States)

    Holtermann, Andreas; Marott, Jacob Louis; Gyntelberg, Finn; Søgaard, Karen; Suadicani, Poul; Mortensen, Ole Steen; Prescott, Eva; Schnohr, Peter

    2013-01-01

    To investigate if persons with high physical activity at work have the same benefits from leisure time physical activity as persons with sedentary work. In the Copenhagen City Heart Study, a prospective cohort of 7,411 males and 8,916 females aged 25-66 years without known cardiovascular disease at entry in 1976-78, 1981-83, 1991-94, or 2001-03, the authors analyzed with sex-stratified multivariate Cox proportional hazards regression the association between leisure time physical activity and cardiovascular and all-cause mortality among individuals with different levels of occupational physical activity. During a median follow-up of 22.4 years, 4,003 individuals died from cardiovascular disease and 8,935 from all-causes. Irrespective of level of occupational physical activity, a consistently lower risk with increasing leisure time physical activity was found for both cardiovascular and all-cause mortality among both men and women. Compared to low leisure time physical activity, the survival benefit ranged from 1.5-3.6 years for moderate and 2.6-4.7 years for high leisure time physical activity among the different levels of occupational physical activity. Public campaigns and initiatives for increasing physical activity in the working population should target everybody, irrespective of physical activity at work.

  3. Sodium caseinate induces increased survival in leukaemic mouse J774 model.

    Science.gov (United States)

    Córdova-Galaviz, Yolanda; Ledesma-Martínez, Edgar; Aguíñiga-Sánchez, Itzen; Soldevila-Melgarejo, Gloria; Soto-Cruz, Isabel; Weiss-Steider, Benny; Santiago-Osorio, Edelmiro

    2014-01-01

    Acute myeloid leukaemia is a neoplastic disease of haematopoietic stem cells. Although there have been recent advances regarding its treatment, mortality remains high. Consequently, therapeutic alternatives continue to be explored. In the present report, we present evidence that sodium caseinate (CasNa), a salt of the principal protein in milk, may possess important anti-leukaemic properties. J774 leukaemia macrophage-like cells were cultured with CasNa and proliferation, viability and differentiation were evaluated. These cells were also inoculated into BALB/c mice as a model of leukemia. We demonstrated that CasNa inhibits the in vitro proliferation and reduces viability of J774 cells, and leads to increased survival in vivo in a leukaemic mouse model. These data indicate that CasNa may be useful in leukaemia therapy. Copyright © 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  4. Bronchiolitis obliterans syndrome after single-lung transplantation: impact of time to onset on functional pattern and survival.

    Science.gov (United States)

    Brugière, Olivier; Pessione, Fabienne; Thabut, Gabriel; Mal, Hervé; Jebrak, Gilles; Lesèche, Guy; Fournier, Michel

    2002-06-01

    Among risk factors for the progression of bronchiolitis obliterans syndrome (BOS) after lung transplantation (LT), the influence of time to BOS onset is not known. The aim of the study was to assess if BOS occurring earlier after LT is associated with worse functional prognosis and worse graft survival. We retrospectively compared functional outcome and survival of all single-LT (SLT) recipients who had BOS develop during follow-up in our center according to time to onset of BOS ( or = 3 years after transplantation). Among the 29 SLT recipients with BOS identified during the study period, 20 patients had early-onset BOS and 9 patients had late-onset BOS. The mean decline of FEV(1) over time during the first 9 months in patients with early-onset BOS was significantly greater than in patients with of late-onset BOS (p = 0.04). At last follow-up, patients with early-onset BOS had a lower mean FEV(1) value (25% vs 39% of predicted, p = 0.004), a lower mean PaO(2) value (54 mm Hg vs 73 mm Hg, p = 0.0005), a lower 6-min walk test distance (241 m vs 414 m, p = 0.001), a higher Medical Research Council index value (3.6 vs 1.6, p = 0.0001), and a higher percentage of oxygen dependency (90% vs 11%, p = 0.001) compared with patients with late-onset BOS. In addition, graft survival of patients with early-onset BOS was significantly lower than that of patients with late-onset BOS (log-rank test, p = 0.04). There were 18 of 20 graft failures (90%) in the early-onset BOS group, directly attributable to BOS in all cases (deaths [n = 10] or retransplantation [n = 8]). In the late-onset BOS group, graft failure occurred in four of nine patients due to death from extrapulmonary causes in three of four cases. The median duration of follow-up after occurrence of BOS was not statistically different between patients with early-onset BOS and patients with late-onset BOS (31 +/- 28 months and 37 +/- 26 months, respectively; p = not significant). The subgroup of patients who had BOS develop

  5. Optimal time points sampling in pathway modelling.

    Science.gov (United States)

    Hu, Shiyan

    2004-01-01

    Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

  6. Design and Analysis of Salmonid Tagging Studies in the Columbia Basin : Evaluating Wetland Restoration Projects in the Columbia River Estuary using Hydroacoustic Telemetry Arrays to Estimate Movement, Survival, and Residence Times of Juvenile Salmonids, Volume XXII (22).

    Energy Technology Data Exchange (ETDEWEB)

    Perry, Russell W.; Skalski, John R.

    2008-08-01

    Wetlands in the Columbia River estuary are actively being restored by reconnecting these habitats to the estuary, making more wetland habitats available to rearing and migrating juvenile salmon. Concurrently, thousands of acoustically tagged juvenile salmonids are released into the Columbia River to estimate their survival as they migrate through the estuary. Here, we develop a release-recapture model that makes use of these tagged fish to measure the success of wetland restoration projects in terms of their contribution to populations of juvenile salmon. Specifically, our model estimates the fraction of the population that enter the wetland, survival within the wetland, and the mean residence time of fish within the wetland. Furthermore, survival in mainstem Columbia River downstream of the wetland can be compared between fish that remained the mainstem and entered the wetland. These conditional survival estimates provide a means of testing whether the wetland improves the subsequent survival of juvenile salmon by fostering growth or improving their condition. Implementing such a study requires little additional cost because it takes advantage of fish already released to estimate survival through the estuary. Thus, such a study extracts the maximum information at minimum cost from research projects that typically cost millions of dollars annually.

  7. A mathematical model resolving normal human blood lymphocyte population X-ray survival curves into six components: radiosensitivity, death rate and size of two responding sub-populations

    International Nuclear Information System (INIS)

    Thomson, A.E.R.; Vaughan-Smith, S.; Peel, W.E.

    1982-01-01

    The analysis was based on observations of survival decrease as a function of dose (range 0-5 Gy (= 500 rad)) and time after irradiation in vitro. Since lymphocyte survival is also sensitive to culture conditions the effects of radiation were examined daily up to 3 days only, while survival of control cells remained ca. 90 per cent. The time-dependent changes were resolved as the death rates (first-order governed) of lethally-hit cells (apparent survivors), so rendering these distinguishable from the morphologically identical, true (ultimate) survivors. For 12 blood donors the estimated dose permitting 37 per cent ultimate survival (D 37 value) averaged 0.72 +- 0.18 (SD) Gy for the more radiosensitive lymphocyte fraction and 2.50 +- 0.67 Gy for the less radiosensitive, each fraction proving homogeneously radiosensitive and the latter identifying substantially in kind with T-type (E-rosetting lymphocytes). The half-life of lethally-hit members of either fraction varied widely among the donors (ranges, 25-104 hours and 11-40 hours, respectively). Survival curves reconstructed by summating the numerical estimates of the six parameters according to the theoretical model closely matched those observed experimentally (ranged in multiple correlation coefficient, 0.9709-0.9994) for all donors). This signified the absence of any additional, totally radioresistant cell fraction. (author)

  8. Free Base Lysine Increases Survival and Reduces Metastasis in Prostate Cancer Model.

    Science.gov (United States)

    Ibrahim-Hashim, Arig; Wojtkowiak, Jonathan W; de Lourdes Coelho Ribeiro, Maria; Estrella, Veronica; Bailey, Kate M; Cornnell, Heather H; Gatenby, Robert A; Gillies, Robert J

    2011-11-19

    Malignant tumor cells typically metabolize glucose anaerobically to lactic acid even under normal oxygen tension, a phenomenon called aerobic glycolysis or the Warburg effect. This results in increased acid production and the acidification of the extracellular microenvironment in solid tumors. H + ions tend to flow along concentration gradients into peritumoral normal tissue causing extracellular matrix degradation and increased tumor cell motility thus promoting invasion and metastasis. We have shown that reducing this acidity with sodium bicarbonate buffer decreases the metastatic fitness of circulating tumor cells in prostate cancer and other cancer models. Mathematical models of the tumor-host dynamics predicted that buffers with a pka around 7 will be more effective in reducing intra- and peri-tumoral acidosis and, thus, and possibly more effective in inhibiting tumor metastasis than sodium bicarbonate which has a pKa around 6. Here we test this prediction the efficacy of free base lysine; a non-bicarbonate/non-volatile buffer with a higher pKa (~10), on prostate tumor metastases model. Oxygen consumption and acid production rate of PC3M prostate cancer cells and normal prostate cells were determined using the Seahorse Extracellular Flux (XF-96) analyzer. In vivo effect of 200 mM lysine started four days prior to inoculation on inhibition of metastasis was examined in PC3M-LUC-C6 prostate cancer model using SCID mice. Metastases were followed by bioluminescence imaging. PC3M prostate cancer cells are highly acidic in comparison to a normal prostate cell line indicating that reduction of intra- and perit-tumoral acidosis should inhibit metastases formation. In vivo administration of 200 mM free base lysine increased survival and reduced metastasis. PC3M prostate cancer cells are highly glycolytic and produce large amounts of acid when compared to normal prostate cells. Administration of non-volatile buffer decreased growth of metastases and improved survival

  9. Monte Carlo model to simulate the effects of DNA damage resulting from accumulation of 125I decays during development of colonies and clonogenic survival assays

    International Nuclear Information System (INIS)

    Lobachevsky, P.; Karagiannis, T.; Martin, R.F.

    1998-01-01

    Full text: Exposure of cultured cells to an internal source of ionising radiation, such as a radioactive isotope, differs substantially from external irradiation in the determination of delivered dose. In some cases, the radioactive isotope cannot be quickly and completely removed from cells before plating for clonogenic survival assay. This provides an additional dose of irradiation which is not easy to calculate. The contribution of this phenomenon to the cell survival is especially important if a radioactive isotope is incorporated into DNA, or a DNA-binding ligand is labelled with the isotope. The correction of the cell survival due to additional dose cannot be calculated using a simple analytical expression, since the isotope is present in the cells during colony growth. We have developed a Monte Carlo model which simulates the process of the colony growth, and takes into account the extent of damage from isotope decays accumulated between consequent cell divisions. The model considers such factors as cell cycle time, radiosensitivity, colony growth inhibition, isotope specific (per cell) activity, partition of isotope in daughter cells, isotope half-life time, isotope efflux. The model allows estimation of the impact of the irradiation during colony formation on the distribution of colony size, and on the calculation of the survival correction factor, which depends mainly on the isotope cell-specific activity. We applied the model to interpret the difference in survival of K652 cells exposed to 125 I decays with various cell-specific activities: 0.45, 3.21 and 7.42 decays/cell/hour. The cells were treated with 125 I - labelled Hoechst 33258 which binds to DNA in cell nucleus. After accumulation of 125 I decays under non-growth conditions, cells were plated for clonogenic survival assay. The survival correction factors calculated from the model for the given values of 125 I cell-specific activity are in good correlation with differences between experimental

  10. Fisher information framework for time series modeling

    Science.gov (United States)

    Venkatesan, R. C.; Plastino, A.

    2017-08-01

    A robust prediction model invoking the Takens embedding theorem, whose working hypothesis is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the working hypothesis satisfy a time independent Schrödinger-like equation in a vector setting. The inference of (i) the probability density function of the coefficients of the working hypothesis and (ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defines the working hypothesis, solely in terms of the observed data. Cases for prediction employing time series' obtained from the: (i) the Mackey-Glass delay-differential equation, (ii) one ECG signal from the MIT-Beth Israel Deaconess Hospital (MIT-BIH) cardiac arrhythmia database, and (iii) one ECG signal from the Creighton University ventricular tachyarrhythmia database. The ECG samples were obtained from the Physionet online repository. These examples demonstrate the efficiency of the prediction model. Numerical examples for exemplary cases are provided.

  11. SURVIVAL OF MICROORGANISMS FROM MODERN PROBIOTICS IN MODEL CONDITIONS OF THE INTESTINE

    Directory of Open Access Journals (Sweden)

    Kabluchko TV

    2017-03-01

    Full Text Available Introduction. The staye of intestinal microflora affects the work of the whole organism. When composition of normal ibtestine microflora changes, its restoration is required. In our days a wide variety of probiotic drugs are available on the market which can be used to solve this problem. Most bacteria having probiotic properties represent the families Lactobacillus and Bifidobacterium, which have poor resistance to acidic content of the stomach and toxic effects of bile salts. Various studies have clearly shown that in a person with normal acidic and bile secretion, the lactobacilli and bifidobacteria are not detected after the passage through the duodenum, i.e., they perish before reaching the small intestines. In this study we compared the survival of different microorganisms which are contained in 9 probiotic drugs in a model of gastric and intestinal environments. Material and methods. In the laboratory of SI: “Mechnikov Institute Microbiology and Immunology, National Ukrainian Academy Medical Sciences" the in vitro experiments have been evaluated to test the ability of different probiotic bacteria which were contained in 9 probiotic drugs to survive the impact of the model environment of the stomach and duodenum. Bacillus coagulans persistence was evaluated under impact of simulated environment of the stomach and duodenum, it also was assessed by the quantity of CFU by incubation on culture medium. The following were studied: Lactobacillus acidophilus, Lactobacillus rhamnosus, Lactobacillus reuteri, Lactobacillus casei, Lactobacillus plantarum, Lactobacillus bulgaricus, Bifidobacterium bifidum, Bifidobacterium longum , Bifidobacterium breve, Bifidobacterium infantis, Bifidobacterium animalis subsp. Lactis BB-12, Saccharomyces boulardii, Bacillus coagulans, Bacillus clausii, Enterococcus faecium. Microorganisms were incubated for 3 hours in a model environment of the stomach (pepsin 3 g / l, hydrochloric acid of 160 mmol / l, pH 2

  12. Modeling and Understanding Time-Evolving Scenarios

    Directory of Open Access Journals (Sweden)

    Riccardo Melen

    2015-08-01

    Full Text Available In this paper, we consider the problem of modeling application scenarios characterized by variability over time and involving heterogeneous kinds of knowledge. The evolution of distributed technologies creates new and challenging possibilities of integrating different kinds of problem solving methods, obtaining many benefits from the user point of view. In particular, we propose here a multilayer modeling system and adopt the Knowledge Artifact concept to tie together statistical and Artificial Intelligence rule-based methods to tackle problems in ubiquitous and distributed scenarios.

  13. Discrete time modelization of human pilot behavior

    Science.gov (United States)

    Cavalli, D.; Soulatges, D.

    1975-01-01

    This modelization starts from the following hypotheses: pilot's behavior is a time discrete process, he can perform only one task at a time and his operating mode depends on the considered flight subphase. Pilot's behavior was observed using an electro oculometer and a simulator cockpit. A FORTRAN program has been elaborated using two strategies. The first one is a Markovian process in which the successive instrument readings are governed by a matrix of conditional probabilities. In the second one, strategy is an heuristic process and the concepts of mental load and performance are described. The results of the two aspects have been compared with simulation data.

  14. Linear Parametric Model Checking of Timed Automata

    DEFF Research Database (Denmark)

    Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle

    2001-01-01

    We present an extension of the model checker Uppaal capable of synthesize linear parameter constraints for the correctness of parametric timed automata. The symbolic representation of the (parametric) state-space is shown to be correct. A second contribution of this paper is the identication...... of a subclass of parametric timed automata (L/U automata), for which the emptiness problem is decidable, contrary to the full class where it is know to be undecidable. Also we present a number of lemmas enabling the verication eort to be reduced for L/U automata in some cases. We illustrate our approach...

  15. The Design and Analysis of Salmonid Tagging Studies in the Columbia Basin : Volume XVII : Effects of Ocean Covariates and Release Timing on First Ocean-Year Survival of Fall Chinook Salmon from Oregon and Washington Coastal Hatcheries.

    Energy Technology Data Exchange (ETDEWEB)

    Burgess, Caitlin; Skalski, John R.

    2001-05-01

    Effects of oceanographic conditions, as well as effects of release-timing and release-size, on first ocean-year survival of subyearling fall chinook salmon were investigated by analyzing CWT release and recovery data from Oregon and Washington coastal hatcheries. Age-class strength was estimated using a multinomial probability likelihood which estimated first-year survival as a proportional hazards regression against ocean and release covariates. Weight-at-release and release-month were found to significantly effect first year survival (p < 0.05) and ocean effects were therefore estimated after adjusting for weight-at-release. Negative survival trend was modeled for sea surface temperature (SST) during 11 months of the year over the study period (1970-1992). Statistically significant negative survival trends (p < 0.05) were found for SST during April, June, November and December. Strong pairwise correlations (r > 0.6) between SST in April/June, April/November and April/December suggest the significant relationships were due to one underlying process. At higher latitudes (45{sup o} and 48{sup o}N), summer upwelling (June-August) showed positive survival trend with survival and fall (September-November) downwelling showed positive trend with survival, indicating early fall transition improved survival. At 45{sup o} and 48{sup o}, during spring, alternating survival trends with upwelling were observed between March and May, with negative trend occurring in March and May, and positive trend with survival occurring in April. In January, two distinct scenarios of improved survival were linked to upwelling conditions, indicated by (1) a significant linear model effect (p < 0.05) showing improved survival with increasing upwelling, and (2) significant bowl-shaped curvature (p < 0.05) of survival with upwelling. The interpretation of the effects is that there was (1) significantly improved survival when downwelling conditions shifted to upwelling conditions in January (i

  16. Identification of subgroups by risk of graft failure after paediatric renal transplantation: application of survival tree models on the ESPN/ERA-EDTA Registry.

    Science.gov (United States)

    Lofaro, Danilo; Jager, Kitty J; Abu-Hanna, Ameen; Groothoff, Jaap W; Arikoski, Pekka; Hoecker, Britta; Roussey-Kesler, Gwenaelle; Spasojević, Brankica; Verrina, Enrico; Schaefer, Franz; van Stralen, Karlijn J

    2016-02-01

    Identification of patient groups by risk of renal graft loss might be helpful for accurate patient counselling and clinical decision-making. Survival tree models are an alternative statistical approach to identify subgroups, offering cut-off points for covariates and an easy-to-interpret representation. Within the European Society of Pediatric Nephrology/European Renal Association-European Dialysis and Transplant Association (ESPN/ERA-EDTA) Registry data we identified paediatric patient groups with specific profiles for 5-year renal graft survival. Two analyses were performed, including (i) parameters known at time of transplantation and (ii) additional clinical measurements obtained early after transplantation. The identified subgroups were added as covariates in two survival models. The prognostic performance of the models was tested and compared with conventional Cox regression analyses. The first analysis included 5275 paediatric renal transplants. The best 5-year graft survival (90.4%) was found among patients who received a renal graft as a pre-emptive transplantation or after short-term dialysis (2.2 years). The Cox model including both pre-transplant factors and tree subgroups had a significantly better predictive performance than conventional Cox regression (P 30 mL/min/1.73 m(2) and dialysis 20 months). Also in this case combining tree findings and clinical factors improved the predictive performance as compared with conventional Cox model models (P tree model to be an accurate and attractive tool to predict graft failure for patients with specific characteristics. This may aid the evaluation of individual graft prognosis and thereby the design of measures to improve graft survival in the poor prognosis groups. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  17. Omnibus risk assessment via accelerated failure time kernel machine modeling.

    Science.gov (United States)

    Sinnott, Jennifer A; Cai, Tianxi

    2013-12-01

    Integrating genomic information with traditional clinical risk factors to improve the prediction of disease outcomes could profoundly change the practice of medicine. However, the large number of potential markers and possible complexity of the relationship between markers and disease make it difficult to construct accurate risk prediction models. Standard approaches for identifying important markers often rely on marginal associations or linearity assumptions and may not capture non-linear or interactive effects. In recent years, much work has been done to group genes into pathways and networks. Integrating such biological knowledge into statistical learning could potentially improve model interpretability and reliability. One effective approach is to employ a kernel machine (KM) framework, which can capture nonlinear effects if nonlinear kernels are used (Scholkopf and Smola, 2002; Liu et al., 2007, 2008). For survival outcomes, KM regression modeling and testing procedures have been derived under a proportional hazards (PH) assumption (Li and Luan, 2003; Cai, Tonini, and Lin, 2011). In this article, we derive testing and prediction methods for KM regression under the accelerated failure time (AFT) model, a useful alternative to the PH model. We approximate the null distribution of our test statistic using resampling procedures. When multiple kernels are of potential interest, it may be unclear in advance which kernel to use for testing and estimation. We propose a robust Omnibus Test that combines information across kernels, and an approach for selecting the best kernel for estimation. The methods are illustrated with an application in breast cancer. © 2013, The International Biometric Society.

  18. Vitamin D Depletion in Pregnancy Decreases Survival Time, Oxygen Saturation, Lung Weight and Body Weight in Preterm Rat Offspring

    DEFF Research Database (Denmark)

    Lykkedegn, Sine; Sorensen, Grith Lykke; Beck-Nielsen, Signe Sparre

    2016-01-01

    Animal studies suggest a role of vitamin D in fetal lung development although not studied in preterm animals. We tested the hypothesis that vitamin D depletion aggravates respiratory insufficiency in preterm rat offspring. Furthermore, the effects of vitamin D depletion on growth and lung...... surfactant were investigated. Female Sprague-Dawley rats were randomly assigned low vitamin D (VDL) or control diet before mating and followed with serum 25-hydroxyvitamin D (s-25(OH)D) determinations. After cesarean section at gestational day 19 (E19) or day 22 (E22), placental weight, birth weight, crown......-rump-length (CRL), oxygenation (SaO2) at 30 min and survival time were recorded. The pup lungs were analyzed for phospholipid levels, surfactant protein A-D mRNA and the expression of the vitamin D receptor (VDR). S-25(OH)D was significantly lower in the VDL group at cesarean section (12 vs. 30nmol/L, p

  19. Modelling of Patterns in Space and Time

    CERN Document Server

    Murray, James

    1984-01-01

    This volume contains a selection of papers presented at the work­ shop "Modelling of Patterns in Space and Time", organized by the 80nderforschungsbereich 123, "8tochastische Mathematische Modelle", in Heidelberg, July 4-8, 1983. The main aim of this workshop was to bring together physicists, chemists, biologists and mathematicians for an exchange of ideas and results in modelling patterns. Since the mathe­ matical problems arising depend only partially on the particular field of applications the interdisciplinary cooperation proved very useful. The workshop mainly treated phenomena showing spatial structures. The special areas covered were morphogenesis, growth in cell cultures, competition systems, structured populations, chemotaxis, chemical precipitation, space-time oscillations in chemical reactors, patterns in flames and fluids and mathematical methods. The discussions between experimentalists and theoreticians were especially interesting and effective. The editors hope that these proceedings reflect ...

  20. Model structure of the stream salmonid simulator (S3)—A dynamic model for simulating growth, movement, and survival of juvenile salmonids

    Science.gov (United States)

    Perry, Russell W.; Plumb, John M.; Jones, Edward C.; Som, Nicholas A.; Hetrick, Nicholas J.; Hardy, Thomas B.

    2018-04-06

    Fisheries and water managers often use population models to aid in understanding the effect of alternative water management or restoration actions on anadromous fish populations. We developed the Stream Salmonid Simulator (S3) to help resource managers evaluate the effect of management alternatives on juvenile salmonid populations. S3 is a deterministic stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and usable habitat area or carrying capacity. The physical characteristics of each habitat unit and the number of fish occupying each unit, in turn, drive survival and growth within each habitat unit and movement of fish among habitat units.The purpose of this report is to outline the underlying general structure of the S3 model that is common among different applications of the model. We have developed applications of the S3 model for juvenile fall Chinook salmon (Oncorhynchus tshawytscha) in the lower Klamath River. Thus, this report is a companion to current application of the S3 model to the Trinity River (in review). The general S3 model structure provides a biological and physical framework for the salmonid freshwater life cycle. This framework captures important demographics of juvenile salmonids aimed at translating management alternatives into simulated population responses. Although the S3 model is built on this common framework, the model has been constructed to allow much flexibility in application of the model to specific river systems. The ability for practitioners to include system-specific information for the

  1. Cisplatin Resistant Spheroids Model Clinically Relevant Survival Mechanisms in Ovarian Tumors.

    Directory of Open Access Journals (Sweden)

    Winyoo Chowanadisai

    Full Text Available The majority of ovarian tumors eventually recur in a drug resistant form. Using cisplatin sensitive and resistant cell lines assembled into 3D spheroids we profiled gene expression and identified candidate mechanisms and biological pathways associated with cisplatin resistance. OVCAR-8 human ovarian carcinoma cells were exposed to sub-lethal concentrations of cisplatin to create a matched cisplatin-resistant cell line, OVCAR-8R. Genome-wide gene expression profiling of sensitive and resistant ovarian cancer spheroids identified 3,331 significantly differentially expressed probesets coding for 3,139 distinct protein-coding genes (Fc >2, FDR < 0.05 (S2 Table. Despite significant expression changes in some transporters including MDR1, cisplatin resistance was not associated with differences in intracellular cisplatin concentration. Cisplatin resistant cells were significantly enriched for a mesenchymal gene expression signature. OVCAR-8R resistance derived gene sets were significantly more biased to patients with shorter survival. From the most differentially expressed genes, we derived a 17-gene expression signature that identifies ovarian cancer patients with shorter overall survival in three independent datasets. We propose that the use of cisplatin resistant cell lines in 3D spheroid models is a viable approach to gain insight into resistance mechanisms relevant to ovarian tumors in patients. Our data support the emerging concept that ovarian cancers can acquire drug resistance through an epithelial-to-mesenchymal transition.

  2. Neuron-specific antioxidant OXR1 extends survival of a mouse model of amyotrophic lateral sclerosis.

    Science.gov (United States)

    Liu, Kevin X; Edwards, Benjamin; Lee, Sheena; Finelli, Mattéa J; Davies, Ben; Davies, Kay E; Oliver, Peter L

    2015-05-01

    Amyotrophic lateral sclerosis is a devastating neurodegenerative disorder characterized by the progressive loss of spinal motor neurons. While the aetiological mechanisms underlying the disease remain poorly understood, oxidative stress is a central component of amyotrophic lateral sclerosis and contributes to motor neuron injury. Recently, oxidation resistance 1 (OXR1) has emerged as a critical regulator of neuronal survival in response to oxidative stress, and is upregulated in the spinal cord of patients with amyotrophic lateral sclerosis. Here, we tested the hypothesis that OXR1 is a key neuroprotective factor during amyotrophic lateral sclerosis pathogenesis by crossing a new transgenic mouse line that overexpresses OXR1 in neurons with the SOD1(G93A) mouse model of amyotrophic lateral sclerosis. Interestingly, we report that overexpression of OXR1 significantly extends survival, improves motor deficits, and delays pathology in the spinal cord and in muscles of SOD1(G93A) mice. Furthermore, we find that overexpression of OXR1 in neurons significantly delays non-cell-autonomous neuroinflammatory response, classic complement system activation, and STAT3 activation through transcriptomic analysis of spinal cords of SOD1(G93A) mice. Taken together, these data identify OXR1 as the first neuron-specific antioxidant modulator of pathogenesis and disease progression in SOD1-mediated amyotrophic lateral sclerosis, and suggest that OXR1 may serve as a novel target for future therapeutic strategies. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

  3. Method for widespread microRNA-155 inhibition prolongs survival in ALS-model mice

    Science.gov (United States)

    Koval, Erica D.; Shaner, Carey; Zhang, Peter; du Maine, Xavier; Fischer, Kimberlee; Tay, Jia; Chau, B. Nelson; Wu, Gregory F.; Miller, Timothy M.

    2013-01-01

    microRNAs (miRNAs) are dysregulated in a variety of disease states, suggesting that this newly discovered class of gene expression repressors may be viable therapeutic targets. A microarray of miRNA changes in ALS-model superoxide dismutase 1 (SOD1)G93A rodents identified 12 miRNAs as significantly changed. Six miRNAs tested in human ALS tissues were confirmed increased. Specifically, miR-155 was increased 5-fold in mice and 2-fold in human spinal cords. To test miRNA inhibition in the central nervous system (CNS) as a potential novel therapeutic, we developed oligonucleotide-based miRNA inhibitors (anti-miRs) that could inhibit miRNAs throughout the CNS and in the periphery. Anti-miR-155 caused global derepression of targets in peritoneal macrophages and, following intraventricular delivery, demonstrated widespread functional distribution in the brain and spinal cord. After treating SOD1G93A mice with anti-miR-155, we significantly extended survival by 10 days and disease duration by 15 days (38%) while a scrambled control anti-miR did not significantly improve survival or disease duration. Therefore, antisense oligonucleotides may be used to successfully inhibit miRNAs throughout the brain and spinal cord, and miR-155 is a promising new therapeutic target for human ALS. PMID:23740943

  4. Space-time modeling of soil moisture

    Science.gov (United States)

    Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

    2017-11-01

    A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

  5. Time series modeling for syndromic surveillance

    Directory of Open Access Journals (Sweden)

    Mandl Kenneth D

    2003-01-01

    Full Text Available Abstract Background Emergency department (ED based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Methods Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Results Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Conclusions Time series methods applied to historical ED utilization data are an important tool

  6. Outlier Detection in Structural Time Series Models

    DEFF Research Database (Denmark)

    Marczak, Martyna; Proietti, Tommaso

    investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality......Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general......–to–specific approach to the detection of structural change, currently implemented in Autometrics via indicator saturation, has proven to be both practical and effective in the context of stationary dynamic regression models and unit–root autoregressions. By focusing on impulse– and step–indicator saturation, we...

  7. Modelling tourists arrival using time varying parameter

    Science.gov (United States)

    Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

    2017-06-01

    The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.

  8. Regression modeling strategies with applications to linear models, logistic and ordinal regression, and survival analysis

    CERN Document Server

    Harrell , Jr , Frank E

    2015-01-01

    This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for fitting nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap.  The reader will gain a keen understanding of predictive accuracy, and the harm of categorizing continuous predictors or outcomes.  This text realistically...

  9. Studying DDT Susceptibility at Discriminating Time Intervals Focusing on Maximum Limit of Exposure Time Survived by DDT Resistant Phlebotomus argentipes (Diptera: Psychodidae): an Investigative Report.

    Science.gov (United States)

    Rama, Aarti; Kesari, Shreekant; Das, Pradeep; Kumar, Vijay

    2017-07-24

    Extensive application of routine insecticide i.e., dichlorodiphenyltrichloroethane (DDT) to control Phlebotomus argentipes (Diptera: Psychodidae), the proven vector of visceral leishmaniasis in India, had evoked the problem of resistance/tolerance against DDT, eventually nullifying the DDT dependent strategies to control this vector. Because tolerating an hour-long exposure to DDT is not challenging enough for the resistant P. argentipes, estimating susceptibility by exposing sand flies to insecticide for just an hour becomes a trivial and futile task.Therefore, this bioassay study was carried out to investigate the maximum limit of exposure time to which DDT resistant P. argentipes can endure the effect of DDT for their survival. The mortality rate of laboratory-reared DDT resistant strain P. argentipes exposed to DDT was studied at discriminating time intervals of 60 min and it was concluded that highly resistant sand flies could withstand up to 420 min of exposure to this insecticide. Additionally, the lethal time for female P. argentipes was observed to be higher than for males suggesting that they are highly resistant to DDT's toxicity. Our results support the monitoring of tolerance limit with respect to time and hence points towards an urgent need to change the World Health Organization's protocol for susceptibility identification in resistant P. argentipes.

  10. Trends and timing of cigarette smoking uptake among US young adults: survival analysis using annual national cohorts from 1976 to 2005.

    Science.gov (United States)

    Terry-McElrath, Yvonne M; O'Malley, Patrick M

    2015-07-01

    To measure changes over time in cigarette smoking uptake prevalence and timing during young adulthood (ages 19-26 years), and associations between time-invariant/-varying characteristics and uptake prevalence/timing. Discrete-time survival modeling of data collected from United States high school seniors (modal age 17/18) enrolled in successive graduating classes from 1976 to 2005 and participating in four follow-up surveys (to modal age 25/26). The longitudinal component of the Monitoring the Future study. A total of 10 758 individuals reporting no life-time smoking when first surveyed as high school seniors. Smoking uptake (any, experimental, occasional and regular); socio-demographic variables; marital, college and work status; time spent socializing. The percentage of young adults moving from non-smoker to experimental smoking [slope estimate 0.11, standard error (SE) = 0.04, P = 0.005] or occasional smoking (slope estimate 0.17, SE = 0.03, P age 19/20, but uptake prevalence at older ages increased over time [e.g. cohort year predicting occasional uptake at modal age 25/26 adjusted hazard odds ratio (AHOR) = 1.05, P = 0.002]. Time-invariant/-varying characteristics had unique associations with the timing of various forms of smoking uptake (e.g. at modal age 21/22, currently attending college increased occasional uptake risk (AHOR = 2.11, P age 19/20, but prevalence of uptake at older ages increased. © 2015 Society for the Study of Addiction.

  11. Post mortem Survival of Gallibacterium anatis in a Laying Hen Experimental Infection Model.

    Science.gov (United States)

    Wang, Chong; Pors, Susanne Elisabeth; Bojesen, Anders Miki

    2018-06-01

    To assess the survival of Gallibacterium anatis in dead laying hens, 21-wk-old laying hens were injected intraperitoneally with 0.5 ml brain hearth infusion broth containing 10 8 colony-forming units (CFU) of G. anatis 12656-12 liver ( n = 16), Escherichia coli ST141 ( n = 16), or a mix of G. anatis 12656-12 liver and E. coli ST141 ( n = 16), respectively. Birds were euthanatized 24 hr post injection. From each group eight dead birds were kept at 4 C and eight at room temperature. Swab samples were taken at different time points post euthanatization and streaked on blood agar plates. From the birds kept at 4 C, G. anatis was reisolated from the G. anatis and the G. anatis- E. coli co-injected groups at least 12 days post euthanization. From birds kept at room temperature, G. anatis was reisolated up to 2 days post euthanatization. When using the gyrB-based G. anatis-specific quantitative PCR (qPCR), G. anatis was detected within at least 5 days, and up to 5 days post euthanatization, from birds kept at room temperature and 4 C, respectively. Escherichia coli was reisolated from all the time points independent of how the birds were kept. No difference was observed between the reisolation rates for G. anatis or E. coli when comparing similar detection methods. For birds kept at 4 C, bacterial cultivation was a more sensitive method for detecting G. anatis ( P < 0.05), whereas for birds kept at room temperature, the G. anatis-specific qPCR outperformed bacterial culture ( P < 0.05). In conclusion, we demonstrated that G. anatis has a poorer survival rate than does E. coli in dead chickens kept at room temperature. That finding may affect the overall diagnostic sensitivity and lead to underdiagnosis of G. anatis in a normal production setting.

  12. The manifold model for space-time

    International Nuclear Information System (INIS)

    Heller, M.

    1981-01-01

    Physical processes happen on a space-time arena. It turns out that all contemporary macroscopic physical theories presuppose a common mathematical model for this arena, the so-called manifold model of space-time. The first part of study is an heuristic introduction to the concept of a smooth manifold, starting with the intuitively more clear concepts of a curve and a surface in the Euclidean space. In the second part the definitions of the Csub(infinity) manifold and of certain structures, which arise in a natural way from the manifold concept, are given. The role of the enveloping Euclidean space (i.e. of the Euclidean space appearing in the manifold definition) in these definitions is stressed. The Euclidean character of the enveloping space induces to the manifold local Euclidean (topological and differential) properties. A suggestion is made that replacing the enveloping Euclidean space by a discrete non-Euclidean space would be a correct way towards the quantization of space-time. (author)

  13. RTMOD: Real-Time MODel evaluation

    International Nuclear Information System (INIS)

    Graziani, G; Galmarini, S.; Mikkelsen, T.

    2000-01-01

    The 1998 - 1999 RTMOD project is a system based on an automated statistical evaluation for the inter-comparison of real-time forecasts produced by long-range atmospheric dispersion models for national nuclear emergency predictions of cross-boundary consequences. The background of RTMOD was the 1994 ETEX project that involved about 50 models run in several Institutes around the world to simulate two real tracer releases involving a large part of the European territory. In the preliminary phase of ETEX, three dry runs (i.e. simulations in real-time of fictitious releases) were carried out. At that time, the World Wide Web was not available to all the exercise participants, and plume predictions were therefore submitted to JRC-Ispra by fax and regular mail for subsequent processing. The rapid development of the World Wide Web in the second half of the nineties, together with the experience gained during the ETEX exercises suggested the development of this project. RTMOD featured a web-based user-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis of the forecasts. RTMOD has focussed on model intercomparison of concentration predictions at the nodes of a regular grid with 0.5 degrees of resolution both in latitude and in longitude, the domain grid extending from 5W to 40E and 40N to 65N. Hypothetical releases were notified around the world to the 28 model forecasters via the web on a one-day warning in advance. They then accessed the RTMOD web page for detailed information on the actual release, and as soon as possible they then uploaded their predictions to the RTMOD server and could soon after start their inter-comparison analysis with other modelers. When additional forecast data arrived, already existing statistical results would be recalculated to include the influence by all available predictions. The new web-based RTMOD concept has proven useful as a practical decision-making tool for realtime

  14. Is Leptospira able to survive in raw milk? Study on the inactivation at different storage times and temperatures.

    Science.gov (United States)

    Fratini, Filippo; Turchi, Barbara; Ferrone, Martina; Galiero, Alessia; Nuvoloni, Roberta; Torracca, Beatrice; Cerri, Domenico

    2016-09-01

    The consumption of raw milk is currently increasing due to several beneficial aspects, such as nutritional qualities, taste, and health benefits. However, some authors highlight the potential risk associated with raw milk consumption. In Italy, while the absence of some pathogen microorganisms is set by the regional regulation DGR 381/2007, for other microorganisms, such as Leptospira, no recommendations are provided. Leptospira is not ascribed among classical milk pathogens; however, it can potentially be present in raw milk. The aim of this study was to evaluate the survival in raw milk of six serovars of Leptospira after storage at different temperatures (4 °C ± 2 °C, 20 °C ± 2 °C, and 30 °C ± 2 °C) for different incubation times (20 min, 45 min, 1 h, and 1 h and 30 min), in order to determine the potential risk for consumers. Moreover, the immediate effect of bovine, goat, and donkey raw milk on tested Leptospira serovars was visually evaluated. After incubation, all samples were subcultured in EMJH and incubated aerobically at 30 °C for 3 months. All inoculated media were weekly examined by dark-field microscope in order to assess Leptospira survival. Extemporary observation of strains' behavior in milk allowed to detect an almost immediate motility loss, and no leptospires were detected by microscopic observations carried out weekly during the trial period. According to our results, it could be possible to exclude raw milk as a source of Leptospira infection for consumers.

  15. Metabolic therapy with Deanna Protocol supplementation delays disease progression and extends survival in amyotrophic lateral sclerosis (ALS mouse model.

    Directory of Open Access Journals (Sweden)

    Csilla Ari

    Full Text Available Amyotrophic Lateral Sclerosis (ALS, also known as Lou Gehrig's disease, is a neurodegenerative disorder of motor neurons causing progressive muscle weakness, paralysis, and eventual death from respiratory failure. There is currently no cure or effective treatment for ALS. Besides motor neuron degeneration, ALS is associated with impaired energy metabolism, which is pathophysiologically linked to mitochondrial dysfunction and glutamate excitotoxicity. The Deanna Protocol (DP is a metabolic therapy that has been reported to alleviate symptoms in patients with ALS. In this study we hypothesized that alternative fuels in the form of TCA cycle intermediates, specifically arginine-alpha-ketoglutarate (AAKG, the main ingredient of the DP, and the ketogenic diet (KD, would increase motor function and survival in a mouse model of ALS (SOD1-G93A. ALS mice were fed standard rodent diet (SD, KD, or either diets containing a metabolic therapy of the primary ingredients of the DP consisting of AAKG, gamma-aminobutyric acid, Coenzyme Q10, and medium chain triglyceride high in caprylic triglyceride. Assessment of ALS-like pathology was performed using a pre-defined criteria for neurological score, accelerated rotarod test, paw grip endurance test, and grip strength test. Blood glucose, blood beta-hydroxybutyrate, and body weight were also monitored. SD+DP-fed mice exhibited improved neurological score from age 116 to 136 days compared to control mice. KD-fed mice exhibited better motor performance on all motor function tests at 15 and 16 weeks of age compared to controls. SD+DP and KD+DP therapies significantly extended survival time of SOD1-G93A mice by 7.5% (p = 0.001 and 4.2% (p = 0.006, respectively. Sixty-three percent of mice in the KD+DP and 72.7% of the SD+DP group lived past 125 days, while only 9% of the control animals survived past that point. Targeting energy metabolism with metabolic therapy produces a therapeutic effect in ALS mice which

  16. Metabolic therapy with Deanna Protocol supplementation delays disease progression and extends survival in amyotrophic lateral sclerosis (ALS) mouse model.

    Science.gov (United States)

    Ari, Csilla; Poff, Angela M; Held, Heather E; Landon, Carol S; Goldhagen, Craig R; Mavromates, Nicholas; D'Agostino, Dominic P

    2014-01-01

    Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig's disease, is a neurodegenerative disorder of motor neurons causing progressive muscle weakness, paralysis, and eventual death from respiratory failure. There is currently no cure or effective treatment for ALS. Besides motor neuron degeneration, ALS is associated with impaired energy metabolism, which is pathophysiologically linked to mitochondrial dysfunction and glutamate excitotoxicity. The Deanna Protocol (DP) is a metabolic therapy that has been reported to alleviate symptoms in patients with ALS. In this study we hypothesized that alternative fuels in the form of TCA cycle intermediates, specifically arginine-alpha-ketoglutarate (AAKG), the main ingredient of the DP, and the ketogenic diet (KD), would increase motor function and survival in a mouse model of ALS (SOD1-G93A). ALS mice were fed standard rodent diet (SD), KD, or either diets containing a metabolic therapy of the primary ingredients of the DP consisting of AAKG, gamma-aminobutyric acid, Coenzyme Q10, and medium chain triglyceride high in caprylic triglyceride. Assessment of ALS-like pathology was performed using a pre-defined criteria for neurological score, accelerated rotarod test, paw grip endurance test, and grip strength test. Blood glucose, blood beta-hydroxybutyrate, and body weight were also monitored. SD+DP-fed mice exhibited improved neurological score from age 116 to 136 days compared to control mice. KD-fed mice exhibited better motor performance on all motor function tests at 15 and 16 weeks of age compared to controls. SD+DP and KD+DP therapies significantly extended survival time of SOD1-G93A mice by 7.5% (p = 0.001) and 4.2% (p = 0.006), respectively. Sixty-three percent of mice in the KD+DP and 72.7% of the SD+DP group lived past 125 days, while only 9% of the control animals survived past that point. Targeting energy metabolism with metabolic therapy produces a therapeutic effect in ALS mice which may prolong

  17. Joint modelling of repeated measurement and time-to-event data: an introductory tutorial.

    Science.gov (United States)

    Asar, Özgür; Ritchie, James; Kalra, Philip A; Diggle, Peter J

    2015-02-01

    The term 'joint modelling' is used in the statistical literature to refer to methods for simultaneously analysing longitudinal measurement outcomes, also called repeated measurement data, and time-to-event outcomes, also called survival data. A typical example from nephrology is a study in which the data from each participant consist of repeated estimated glomerular filtration rate (eGFR) measurements and time to initiation of renal replacement therapy (RRT). Joint models typically combine linear mixed effects models for repeated measurements and Cox models for censored survival outcomes. Our aim in this paper is to present an introductory tutorial on joint modelling methods, with a case study in nephrology. We describe the development of the joint modelling framework and compare the results with those obtained by the more widely used approaches of conducting separate analyses of the repeated measurements and survival times based on a linear mixed effects model and a Cox model, respectively. Our case study concerns a data set from the Chronic Renal Insufficiency Standards Implementation Study (CRISIS). We also provide details of our open-source software implementation to allow others to replicate and/or modify our analysis. The results for the conventional linear mixed effects model and the longitudinal component of the joint models were found to be similar. However, there were considerable differences between the results for the Cox model with time-varying covariate and the time-to-event component of the joint model. For example, the relationship between kidney function as measured by eGFR and the hazard for initiation of RRT was significantly underestimated by the Cox model that treats eGFR as a time-varying covariate, because the Cox model does not take measurement error in eGFR into account. Joint models should be preferred for simultaneous analyses of repeated measurement and survival data, especially when the former is measured with error and the association

  18. The application of cure models in the presence of competing risks: a tool for improved risk communication in population-based cancer patient survival.

    Science.gov (United States)

    Eloranta, Sandra; Lambert, Paul C; Andersson, Therese M-L; Björkholm, Magnus; Dickman, Paul W

    2014-09-01

    Quantifying cancer patient survival from the perspective of cure is clinically relevant. However, most cure models estimate cure assuming no competing causes of death. We use a relative survival framework to demonstrate how flexible parametric cure models can be used in combination with competing-risks theory to incorporate noncancer deaths. Under a model that incorporates statistical cure, we present the probabilities that cancer patients (1) have died from their cancer, (2) have died from other causes, (3) will eventually die from their cancer, or (4) will eventually die from other causes, all as a function of time since diagnosis. We further demonstrate how conditional probabilities can be used to update the prognosis among survivors (eg, at 1 or 5 years after diagnosis) by summarizing the proportion of patients who will not die from their cancer. The proposed method is applied to Swedish population-based data for persons diagnosed with melanoma, colon cancer, or acute myeloid leukemia between 1973 and 2007.

  19. RTMOD: Real-Time MODel evaluation

    DEFF Research Database (Denmark)

    Graziani, G.; Galmarini, S.; Mikkelsen, Torben

    2000-01-01

    the RTMOD web page for detailed information on the actual release, and as soon as possible they then uploaded their predictions to the RTMOD server and could soon after start their inter-comparison analysis with other modellers. When additionalforecast data arrived, already existing statistical results....... At that time, the World Wide Web was not available to all the exercise participants, and plume predictions were therefore submitted to JRC-Ispra by fax andregular mail for subsequent processing. The rapid development of the World Wide Web in the second half of the nineties, together with the experience gained...... during the ETEX exercises suggested the development of this project. RTMOD featured a web-baseduser-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis of the forecasts. RTMOD has focussed on model intercomparison of concentration...

  20. Time Modeling: Salvatore Sciarrino, Windows and Beclouding

    Directory of Open Access Journals (Sweden)

    Acácio Tadeu de Camargo Piedade

    2017-08-01

    Full Text Available In this article I intend to discuss one of the figures created by the Italian composer Salvatore Sciarrino: the windowed form. After the composer's explanation of this figure, I argue that windows in composition can open inwards and outwards the musical discourse. On one side, they point to the composition's inner ambiences and constitute an internal remission. On the other, they instigate the audience to comprehend the external reference, thereby constructing intertextuality. After the outward window form, I will consider some techniques of distortion, particularly one that I call beclouding. To conclude, I will comment the question of memory and of compostition as time modeling.

  1. Suspected survivor bias in case-control studies: stratify on survival time and use a negative control.

    Science.gov (United States)

    van Rein, Nienke; Cannegieter, Suzanne C; Rosendaal, Frits R; Reitsma, Pieter H; Lijfering, Willem M

    2014-02-01

    Selection bias in case-control studies occurs when control selection is inappropriate. However, selection bias due to improper case sampling is less well recognized. We describe how to recognize survivor bias (i.e., selection on exposed cases) and illustrate this with an example study. A case-control study was used to analyze the effect of statins on major bleedings during treatment with vitamin K antagonists. A total of 110 patients who experienced such bleedings were included 18-1,018 days after the bleeding complication and matched to 220 controls. A protective association of major bleeding for exposure to statins (odds ratio [OR]: 0.56; 95% confidence interval: 0.29-1.08) was found, which did not become stronger after adjustment for confounding factors. These observations lead us to suspect survivor bias. To identify this bias, results were stratified on time between bleeding event and inclusion, and repeated for a negative control (an exposure not related to survival): blood group non-O. The ORs for exposure to statins increased gradually to 1.37 with shorter time between outcome and inclusion, whereas ORs for the negative control remained constant, confirming our hypothesis. We recommend the presented method to check for overoptimistic results, that is, survivor bias in case-control studies. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

    NARCIS (Netherlands)

    Petersen, Japke F.; Stuiver, Martijn M.; Timmermans, Adriana J.; Chen, Amy; Zhang, Hongzhen; O'Neill, James P.; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T.; Koch, Wayne; van den Brekel, Michiel W. M.

    2017-01-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442

  3. Review and evaluation of performance measures for survival prediction models in external validation settings

    Directory of Open Access Journals (Sweden)

    M. Shafiqur Rahman

    2017-04-01

    Full Text Available Abstract Background When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. Methods An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Results Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell’s concordance measure which tended to increase as censoring increased. Conclusions We recommend that Uno’s concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller’s measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston’s D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive

  4. Growth, survival, and peptidolytic activity of Lactobacillus plantarum I91 in a hard-cheese model.

    Science.gov (United States)

    Bergamini, C V; Peralta, G H; Milesi, M M; Hynes, E R

    2013-09-01

    In this work, we studied the growth, survival, and peptidolytic activity of Lactobacillus plantarum I91 in a hard-cheese model consisting of a sterile extract of Reggianito cheese. To assess the influence of the primary starter and initial proteolysis level on these parameters, we prepared the extracts with cheeses that were produced using 2 different starter strains of Lactobacillus helveticus 138 or 209 (Lh138 or Lh209) at 3 ripening times: 3, 90, and 180 d. The experimental extracts were inoculated with Lb. plantarum I91; the control extracts were not inoculated and the blank extracts were heat-treated to inactivate enzymes and were not inoculated. All extracts were incubated at 34°C for 21 d, and then the pH, microbiological counts, and proteolysis profiles were determined. The basal proteolysis profiles in the extracts of young cheeses made with either strain tested were similar, but many differences between the proteolysis profiles of the extracts of the Lh138 and Lh209 cheeses were found when riper cheeses were used. The pH values in the blank and control extracts did not change, and no microbial growth was detected. In contrast, the pH value in experimental extracts decreased, and this decrease was more pronounced in extracts obtained from either of the young cheeses and from the Lh209 cheese at any stage of ripening. Lactobacillus plantarum I91 grew up to 8 log during the first days of incubation in all of the extracts, but then the number of viable cells decreased, the extent of which depended on the starter strain and the age of the cheese used for the extract. The decrease in the counts of Lb. plantarum I91 was observed mainly in the extracts in which the pH had diminished the most. In addition, the extracts that best supported the viability of Lb. plantarum I91 during incubation had the highest free amino acids content. The effect of Lb. plantarum I91 on the proteolysis profile of the extracts was marginal. Significant changes in the content of free

  5. Analysis of time to event outcomes in randomized controlled trials by generalized additive models.

    Directory of Open Access Journals (Sweden)

    Christos Argyropoulos

    Full Text Available Randomized Controlled Trials almost invariably utilize the hazard ratio calculated with a Cox proportional hazard model as a treatment efficacy measure. Despite the widespread adoption of HRs, these provide a limited understanding of the treatment effect and may even provide a biased estimate when the assumption of proportional hazards in the Cox model is not verified by the trial data. Additional treatment effect measures on the survival probability or the time scale may be used to supplement HRs but a framework for the simultaneous generation of these measures is lacking.By splitting follow-up time at the nodes of a Gauss Lobatto numerical quadrature rule, techniques for Poisson Generalized Additive Models (PGAM can be adopted for flexible hazard modeling. Straightforward simulation post-estimation transforms PGAM estimates for the log hazard into estimates of the survival function. These in turn were used to calculate relative and absolute risks or even differences in restricted mean survival time between treatment arms. We illustrate our approach with extensive simulations and in two trials: IPASS (in which the proportionality of hazards was violated and HEMO a long duration study conducted under evolving standards of care on a heterogeneous patient population.PGAM can generate estimates of the survival function and the hazard ratio that are essentially identical to those obtained by Kaplan Meier curve analysis and the Cox model. PGAMs can simultaneously provide multiple measures of treatment efficacy after a single data pass. Furthermore, supported unadjusted (overall treatment effect but also subgroup and adjusted analyses, while incorporating multiple time scales and accounting for non-proportional hazards in survival data.By augmenting the HR conventionally reported, PGAMs have the potential to support the inferential goals of multiple stakeholders involved in the evaluation and appraisal of clinical trial results under proportional and

  6. Flexible parametric survival models built on age-specific antimüllerian hormone percentiles are better predictors of menopause.

    Science.gov (United States)

    Ramezani Tehrani, Fahimeh; Mansournia, Mohammad Ali; Solaymani-Dodaran, Masoud; Steyerberg, Ewout; Azizi, Fereidoun

    2016-06-01

    This study aimed to improve existing prediction models for age at menopause. We identified all reproductive aged women with regular menstrual cycles who met our eligibility criteria (n = 1,015) in the Tehran Lipid and Glucose Study-an ongoing population-based cohort study initiated in 1998. Participants were examined every 3 years and their reproductive histories were recorded. Blood levels of antimüllerian hormone (AMH) were measured at the time of recruitment. Age at menopause was estimated based on serum concentrations of AMH using flexible parametric survival models. The optimum model was selected according to Akaike Information Criteria and the realness of the range of predicted median menopause age. We followed study participants for a median of 9.8 years during which 277 women reached menopause and found that a spline-based proportional odds model including age-specific AMH percentiles as the covariate performed well in terms of statistical criteria and provided the most clinically relevant and realistic predictions. The range of predicted median age at menopause for this model was 47.1 to 55.9 years. For those who reached menopause, the median of the absolute mean difference between actual and predicted age at menopause was 1.9 years (interquartile range 2.9). The model including the age-specific AMH percentiles as the covariate and using proportional odds as its covariate metrics meets all the statistical criteria for the best model and provides the most clinically relevant and realistic predictions for age at menopause for reproductive-aged women.

  7. Plants modify biological processes to ensure survival following carbon depletion: a Lolium perenne model.

    Directory of Open Access Journals (Sweden)

    Julia M Lee

    Full Text Available BACKGROUND: Plants, due to their immobility, have evolved mechanisms allowing them to adapt to multiple environmental and management conditions. Short-term undesirable conditions (e.g. moisture deficit, cold temperatures generally reduce photosynthetic carbon supply while increasing soluble carbohydrate accumulation. It is not known, however, what strategies plants may use in the long-term to adapt to situations resulting in net carbon depletion (i.e. reduced photosynthetic carbon supply and carbohydrate accumulation. In addition, many transcriptomic experiments have typically been undertaken under laboratory conditions; therefore, long-term acclimation strategies that plants use in natural environments are not well understood. METHODOLOGY/PRINCIPAL FINDINGS: Perennial ryegrass (Lolium perenne L. was used as a model plant to define whether plants adapt to repetitive carbon depletion and to further elucidate their long-term acclimation mechanisms. Transcriptome changes in both lamina and stubble tissues of field-grown plants with depleted carbon reserves were characterised using reverse transcription-quantitative polymerase chain reaction (RT-qPCR. The RT-qPCR data for select key genes indicated that plants reduced fructan degradation, and increased photosynthesis and fructan synthesis capacities following carbon depletion. This acclimatory response was not sufficient to prevent a reduction (P<0.001 in net biomass accumulation, but ensured that the plant survived. CONCLUSIONS: Adaptations of plants with depleted carbon reserves resulted in reduced post-defoliation carbon mobilization and earlier replenishment of carbon reserves, thereby ensuring survival and continued growth. These findings will help pave the way to improve plant biomass production, for either grazing livestock or biofuel purposes.

  8. The number and microlocalization of tumor-associated immune cells are associated with patient's survival time in non-small cell lung cancer

    International Nuclear Information System (INIS)

    Dai, Fuqiang; Liu, Lunxu; Che, Guowei; Yu, Nanbin; Pu, Qiang; Zhang, Shangfu; Ma, Junliang; Ma, Lin; You, Zongbing

    2010-01-01

    Tumor microenvironment is composed of tumor cells, fibroblasts, endothelial cells, and infiltrating immune cells. Tumor-associated immune cells may inhibit or promote tumor growth and progression. This study was conducted to determine whether the number and microlocalization of macrophages, mature dendritic cells and cytotoxic T cells in non-small cell lung cancer are associated with patient's survival time. Ninety-nine patients with non-small cell lung cancer (NSCLC) were included in this retrospective study. Paraffin-embedded NSCLC specimens and their clinicopathological data including up to 8-year follow-up information were used. Immunohistochemical staining for CD68 (marker for macrophages), CD83 (marker for mature dendritic cells), and CD8 (marker for cytotoxic T cells) was performed and evaluated in a blinded fashion. The numbers of immune cells in tumor islets and stroma, tumor islets, or tumor stroma were counted under a microscope. Correlation of the cell numbers and patient's survival time was analyzed using the Statistical Package for the Social Sciences (version 13.0). The numbers of macrophages, mature dendritic cells and cytotoxic T cells were significantly more in the tumor stroma than in the tumor islets. The number of macrophages in the tumor islets was positively associated with patient's survival time, whereas the number of macrophages in the tumor stroma was negatively associated with patient's survival time in both univariate and multivariate analyses. The number of mature dendritic cells in the tumor islets and stroma, tumor islets only, or tumor stroma only was positively associated with patient's survival time in a univariate analysis but not in a multivariate analysis. The number of cytotoxic T cells in the tumor islets and stroma was positively associated with patient's survival time in a univariate analysis but not in a multivariate analysis. The number of cytotoxic T cells in the tumor islets only or stroma

  9. A novel survival model of cardioplegic arrest and cardiopulmonary bypass in rats: a methodology paper

    Directory of Open Access Journals (Sweden)

    Podgoreanu Mihai V

    2008-08-01

    Full Text Available Abstract Background Given the growing population of cardiac surgery patients with impaired preoperative cardiac function and rapidly expanding surgical techniques, continued efforts to improve myocardial protection strategies are warranted. Prior research is mostly limited to either large animal models or ex vivo preparations. We developed a new in vivo survival model that combines administration of antegrade cardioplegia with endoaortic crossclamping during cardiopulmonary bypass (CPB in the rat. Methods Sprague-Dawley rats were cannulated for CPB (n = 10. With ultrasound guidance, a 3.5 mm balloon angioplasty catheter was positioned via the right common carotid artery with its tip proximal to the aortic valve. To initiate cardioplegic arrest, the balloon was inflated and cardioplegia solution injected. After 30 min of cardioplegic arrest, the balloon was deflated, ventilation resumed, and rats were weaned from CPB and recovered. To rule out any evidence of cerebral ischemia due to right carotid artery ligation, animals were neurologically tested on postoperative day 14, and their brains histologically assessed. Results Thirty minutes of cardioplegic arrest was successfully established in all animals. Functional assessment revealed no neurologic deficits, and histology demonstrated no gross neuronal damage. Conclusion This novel small animal CPB model with cardioplegic arrest allows for both the study of myocardial ischemia-reperfusion injury as well as new cardioprotective strategies. Major advantages of this model include its overall feasibility and cost effectiveness. In future experiments long-term echocardiographic outcomes as well as enzymatic, genetic, and histologic characterization of myocardial injury can be assessed. In the field of myocardial protection, rodent models will be an important avenue of research.

  10. Economic evaluation of nivolumab for the treatment of second-line advanced squamous NSCLC in Canada: a comparison of modeling approaches to estimate and extrapolate survival outcomes.

    Science.gov (United States)

    Goeree, Ron; Villeneuve, Julie; Goeree, Jeff; Penrod, John R; Orsini, Lucinda; Tahami Monfared, Amir Abbas

    2016-06-01

    Background Lung cancer is the most common type of cancer in the world and is associated with significant mortality. Nivolumab demonstrated statistically significant improvements in progression-free survival (PFS) and overall survival (OS) for patients with advanced squamous non-small cell lung cancer (NSCLC) who were previously treated. The cost-effectiveness of nivolumab has not been assessed in Canada. A contentious component of projecting long-term cost and outcomes in cancer relates to the modeling approach adopted, with the two most common approaches being partitioned survival (PS) and Markov models. The objectives of this analysis were to estimate the cost-utility of nivolumab and to compare the results using these alternative modeling approaches. Methods Both PS and Markov models were developed using docetaxel and erlotinib as comparators. A three-health state model was used consisting of progression-free, progressed disease, and death. Disease progression and time to progression were estimated by identifying best-fitting survival curves from the clinical trial data for PFS and OS. Expected costs and health outcomes were calculated by combining health-state occupancy with medical resource use and quality-of-life assigned to each of the three health states. The health outcomes included in the model were survival and quality-adjusted-life-years (QALYs). Results Nivolumab was found to have the highest expected per-patient cost, but also improved per-patient life years (LYs) and QALYs. Nivolumab cost an additional $151,560 and $140,601 per QALY gained compared to docetaxel and erlotinib, respectively, using a PS model approach. The cost-utility estimates using a Markov model were very similar ($152,229 and $141,838, respectively, per QALY gained). Conclusions Nivolumab was found to involve a trade-off between improved patient survival and QALYs, and increased cost. It was found that the use of a PS or Markov model produced very similar estimates of expected cost

  11. Results of surgical excision and evaluation of factors associated with survival time in dogs with lingual neoplasia: 97 cases (1995-2008).

    Science.gov (United States)

    Culp, William T N; Ehrhart, Nicole; Withrow, Stephen J; Rebhun, Robert B; Boston, Sarah; Buracco, Paolo; Reiter, Alexander M; Schallberger, Sandra P; Aldridge, Charles F; Kent, Michael S; Mayhew, Philipp D; Brown, Dorothy C

    2013-05-15

    To describe the clinical characteristics, treatments, outcomes, and factors associated with survival time in a cohort of dogs with lingual neoplasia that underwent surgical excision. Retrospective case series. Animals-97 client-owned dogs. Medical records of dogs with a lingual tumor examined between 1995 and 2008 were reviewed. Records were included if a lingual tumor was confirmed by histologic examination and surgical excision of the mass was attempted. Data were recorded and analyzed to identify prognostic factors. Clinical signs were mostly related to the oral cavity. For 93 dogs, marginal excision, subtotal glossectomy, and near-total glossectomy were performed in 35 (38%), 55 (59%), and 3 (3%), respectively. Surgery-related complications were rare, but 27 (28%) dogs had tumor recurrence. The most common histopathologic diagnoses for the 97 dogs were squamous cell carcinoma (31 [32%]) and malignant melanoma (29 [30%]). Eighteen (19%) dogs developed metastatic disease, and the overall median survival time was 483 days. Median survival time was 216 days for dogs with squamous cell carcinoma and 241 days for dogs with malignant melanoma. Dogs with lingual tumors ≥ 2 cm in diameter at diagnosis had a significantly shorter survival time than did dogs with tumors melanoma predominate. A thorough physical examination to identify lingual tumors at an early stage and surgical treatment after tumor identification are recommended because tumor size significantly affected survival time.

  12. System reliability time-dependent models

    International Nuclear Information System (INIS)

    Debernardo, H.D.

    1991-06-01

    A probabilistic methodology for safety system technical specification evaluation was developed. The method for Surveillance Test Interval (S.T.I.) evaluation basically means an optimization of S.T.I. of most important system's periodically tested components. For Allowed Outage Time (A.O.T.) calculations, the method uses system reliability time-dependent models (A computer code called FRANTIC III). A new approximation, which was called Independent Minimal Cut Sets (A.C.I.), to compute system unavailability was also developed. This approximation is better than Rare Event Approximation (A.E.R.) and the extra computing cost is neglectible. A.C.I. was joined to FRANTIC III to replace A.E.R. on future applications. The case study evaluations verified that this methodology provides a useful probabilistic assessment of surveillance test intervals and allowed outage times for many plant components. The studied system is a typical configuration of nuclear power plant safety systems (two of three logic). Because of the good results, these procedures will be used by the Argentine nuclear regulatory authorities in evaluation of technical specification of Atucha I and Embalse nuclear power plant safety systems. (Author) [es

  13. Foundations for Survivable System Development: Service Traces, Intrusion Traces, and Evaluation Models

    National Research Council Canada - National Science Library

    Linger, Richard

    2001-01-01

    .... On the system side, survivability specifications can be defined by essential-service traces that map essential-service workflows, derived from user requirements, into system component dependencies...

  14. Simvastatin Treatment Improves Survival in a Murine Model of Burn Sepsis

    Science.gov (United States)

    Beffa, David C; Fischman, Alan J.; Fagan, Shawn P.; Hamrahi, Victoria F.; Kaneki, Masao; Yu, Yong-Ming; Tompkins, Ronald G.; Carter, Edward A.

    2014-01-01

    Infection is the most common and most serious complication of a major burn injury related to burn size. Despite improvements in antimicrobial therapies sepsis still accounts for 50–60% of deaths in burn patients. Given the acute onset and unpredictable nature of sepsis, primary prevention was rarely attempted in its management. However, recent studies have demonstrated that statin treatment can decrease mortality is a murine model of sepsis by preservation of cardiac function and reversal of inflammatory alterations. In addition, it has been shown that treatment with statins is associated with reduced incidence of sepsis in human patients. In the current study groups of CD1 male mice (n=12) were anesthetized and subjected to a dorsal 30% TBSA scald burn injury. Starting 2 hours post burn, the animals were divided into a treatment group receiving 0.2 µ/g simvastatin or a sham group receiving placebo. Simvastatin and placebo were administered by intraperitoneal injection with two dosing regimens; once daily and every 12 hours. On Post burn day 7 cecal ligation and puncture with a 21-gauge needle was performed under ketamine/xylazine anesthesia and the two different dosing schedules were continued. A simvastatin dose dependant improvement in survival was observed in the burn sepsis model. PMID:21145172

  15. Irreversible electroporation of the pancreas is feasible and safe in a porcine survival model.

    Science.gov (United States)

    Fritz, Stefan; Sommer, Christof M; Vollherbst, Dominik; Wachter, Miguel F; Longerich, Thomas; Sachsenmeier, Milena; Knapp, Jürgen; Radeleff, Boris A; Werner, Jens

    2015-07-01

    Use of thermal tumor ablation in the pancreatic parenchyma is limited because of the risk of pancreatitis, pancreatic fistula, or hemorrhage. This study aimed to evaluate the feasibility and safety of irreversible electroporation (IRE) in a porcine model. Ten pigs were divided into 2 study groups. In the first group, animals received IRE of the pancreatic tail and were killed after 60 minutes. In the second group, animals received IRE at the head of the pancreas and were followed up for 7 days. Clinical parameters, computed tomography imaging, laboratory results, and histology were obtained. All animals survived IRE ablation, and no cardiac adverse effects were noted. Sixty minutes after IRE, a hypodense lesion on computed tomography imaging indicated the ablation zone. None of the animals developed clinical signs of acute pancreatitis. Only small amounts of ascites fluid, with a transient increase in amylase and lipase levels, were observed, indicating that no pancreatic fistula occurred. This porcine model shows that IRE is feasible and safe in the pancreatic parenchyma. Computed tomography imaging reveals significant changes at 60 minutes after IRE and therefore might serve as an early indicator of therapeutic success. Clinical studies are needed to evaluate the efficacy of IRE in pancreatic cancer.

  16. Preliminary study of the effects of smectite granules (WoundStat) on vascular repair and wound healing in a swine survival model.

    Science.gov (United States)

    Gerlach, Travis; Grayson, J Kevin; Pichakron, Kullada O; Sena, Matthew J; DeMartini, Steven D; Clark, Beth Z; Estep, J Scot; Zierold, Dustin

    2010-11-01

    WoundStat (WS) (TraumaCure, Bethesda, MD) is a topical hemostatic agent that effectively stops severe hemorrhage in animal models. To the best of our knowledge, no survival study has been conducted to ensure long-term product safety. We evaluated vascular patency and tissue responses to WS in a swine femoral artery injury model with survival up to 5 weeks. Anesthetized swine received a standardized femoral artery injury with free hemorrhage for 45 seconds followed by WS application. One hour after application, the WS was removed, the wound copiously irrigated, and the artery repaired using a vein patch. Six groups of three animals received WS and were killed either immediately after surgery or at weekly intervals up to 5 weeks. Three control animals were treated with gauze packing and direct pressure followed by identical vascular repair and survival for 1 week. At the time of killing, angiograms were performed, and tissue was collected for histopathology. Hemostasis was complete in all WS animals. All animals survived the procedure, and there were no clinically evident postoperative complications. Vascular repairs were angiographically patent in 15 of 18 animals (83%) receiving WS. Histopathologic examination of WS animals revealed severe diffuse fibrogranulomatous inflammation, early endothelial degeneration with subsequent intimal hyperplasia, moderate myocyte necrosis, and fibrogranulomatous nerve entrapment with axonal degeneration. Although an effective hemostatic agent, WS use was associated with a substantial local inflammatory response and neurovascular changes up to 5 weeks postinjury.

  17. Conceptualizing strategic business model innovation leadership for business survival and business model innovation excellence

    DEFF Research Database (Denmark)

    Lindgren, Peter; Abdullah, Maizura Ailin

    2013-01-01

    Too many businesses are being marginalized by blind "business model innovations (BMIs)" and simple "BMIs". As documented in previous research (Markides 2008, Lindgren 2012), most businesses perform BMIs at a reactive level i.e. perceiving what the market, customers and network partners might want...... rather than what they actually demand. Few businesses have the ability to proactively lead BMIs and on a strategic level lead BMIs to something that fits the business’s long term perspective (Hamel 2011). Apple, Ryanair, Facebook, Zappo are some businesses that have shown BMI Leadership (BMIL......) in a proactive way - and more importantly, as some examples of first level BMIL. The overall aim of the BMIL is to prevent businesses from being marginalized by the BMI and thereby to optimize the business’s total BMI investment. The literature research and case research we studied gave us some important...

  18. Opioid withdrawal, craving, and use during and after outpatient buprenorphine stabilization and taper: a discrete survival and growth mixture model.

    Science.gov (United States)

    Northrup, Thomas F; Stotts, Angela L; Green, Charles; Potter, Jennifer S; Marino, Elise N; Walker, Robrina; Weiss, Roger D; Trivedi, Madhukar

    2015-02-01

    Most patients relapse to opioids within one month of opioid agonist detoxification, making the antecedents and parallel processes of first use critical for investigation. Craving and withdrawal are often studied in relationship to opioid outcomes, and a novel analytic strategy applied to these two phenomena may indicate targeted intervention strategies. Specifically, this secondary data analysis of the Prescription Opioid Addiction Treatment Study used a discrete-time mixture analysis with time-to-first opioid use (survival) simultaneously predicted by craving and withdrawal growth trajectories. This analysis characterized heterogeneity among prescription opioid-dependent individuals (N=653) into latent classes (i.e., latent class analysis [LCA]) during and after buprenorphine/naloxone stabilization and taper. A 4-latent class solution was selected for overall model fit and clinical parsimony. In order of shortest to longest time-to-first use, the 4 classes were characterized as 1) high craving and withdrawal, 2) intermediate craving and withdrawal, 3) high initial craving with low craving and withdrawal trajectories and 4) a low initial craving with low craving and withdrawal trajectories. Odds ratio calculations showed statistically significant differences in time-to-first use across classes. Generally, participants with lower baseline levels and greater decreases in craving and withdrawal during stabilization combined with slower craving and withdrawal rebound during buprenorphine taper remained opioid-free longer. This exploratory work expanded on the importance of monitoring craving and withdrawal during buprenorphine induction, stabilization, and taper. Future research may allow individually tailored and timely interventions to be developed to extend time-to-first opioid use. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Efficacy of Re-188-labelled sulphur colloid on prolongation of survival time in melanoma-bearing animals

    International Nuclear Information System (INIS)

    Chen, F.D.; Hsieh, B.T.; Wang, H.E.; Ou, Y.H.; Yang, W.K.; Whang-Peng, J.; Liu, R.S.; Knapp, F.F.; Ting, G.; Yen, S.H.

    2001-01-01

    In this study, the effectiveness of a 188 Re labeled sulfur colloid with two particle size ranges was used to evaluate the effectiveness of this agent on melanoma tumors in mice in terms of animal lifespan. Methods: Two separate group of animals were used for investigating biodistribution and survival time. A total of 188 B16F10-melanoma-bearing BDF 1 mice were injected intraperitoneally with 3.7 MBq (0.1mCi)/2mL of radiolabeled sulfur colloid ten days after intraperitoneal inoculation of 5x10 5 B16F10 melanoma cells/2ml. For group 1, 30 mice were sacrificed at 1, 4, 24, 48 and 72 hours for biodistribution studies. In group 2, 158 mice were divided into 9 groups (n=16∼18/groups)each receiving respectively tumor alone, tumor with normal saline, cold colloid or hot colloid with 16, 23, 31, 46, 62, or 124 MBq activity. Each of these colloid groups was further divided into two groups, one receiving smaller particle sizes ( 188 Re-sulfur colloid is an effective agent in controlling tumor cells in the abdominal cavity in animals

  20. Evaluation of the Weibull and log normal distribution functions as survival models of Escherichia coli under isothermal and non isothermal conditions.

    Science.gov (United States)

    Aragao, Glaucia M F; Corradini, Maria G; Normand, Mark D; Peleg, Micha

    2007-11-01

    Published survival curves of Escherichia coli in two growth media, with and without the presence of salt, at various temperatures and in a Greek eggplant salad having various levels of essential oil, all had a characteristic downward concavity when plotted on semi logarithmic coordinates. Some also exhibited what appeared as a 'shoulder' of considerable length. Regardless of whether a shoulder was noticed, the survival pattern could be considered as a manifestation of an underlying unimodal distribution of the cells' death times. Mathematically, the data could be described equally well by the Weibull and log normal distribution functions, which had similar modes, means, standard deviations and coefficients of skewness. When plotted in their probability density function (PDF) form, the curves also appeared very similar visually. This enabled us to quantify and compare the effect of temperature or essential oil concentration on the organism's survival in terms of these temporal distributions' characteristics. Increased lethality was generally expressed in a shorter mean and mode, a smaller standard deviation and increased overall symmetry as judged by the distributions' degree of skewness. The 'shoulder', as expected, simply indicated that the distribution's standard deviation was much smaller than its mode. Rate models based on the two distribution functions could be used to predict non isothermal survival patterns. They were derived on the assumption that the momentary inactivation rate is the isothermal rate at the momentary temperature at a time that corresponds to the momentary survival ratio. In this application, however, the Weibullian model with a fixed power was not only simpler and more convenient mathematically than the one based on the log normal distribution, but it also provided more accurate estimates of the dynamic inactivation patterns.

  1. Expression of S1P metabolizing enzymes and receptors correlate with survival time and regulate cell migration in glioblastoma multiforme.

    Science.gov (United States)

    Bien-Möller, Sandra; Lange, Sandra; Holm, Tobias; Böhm, Andreas; Paland, Heiko; Küpper, Johannes; Herzog, Susann; Weitmann, Kerstin; Havemann, Christoph; Vogelgesang, Silke; Marx, Sascha; Hoffmann, Wolfgang; Schroeder, Henry W S; Rauch, Bernhard H

    2016-03-15

    A signaling molecule which is involved in proliferation and migration of malignant cells is the lipid mediator sphingosine-1-phosphate (S1P). There are hints for a potential role of S1P signaling in malignant brain tumors such as glioblastoma multiforme (GBM) which is characterized by a poor prognosis. Therefore, a comprehensive expression analysis of S1P receptors (S1P1-S1P5) and S1P metabolizing enzymes in human GBM (n = 117) compared to healthy brain (n = 10) was performed to evaluate their role for patient´s survival. Furthermore, influence of S1P receptor inhibition on proliferation and migration were studied in LN18 GBM cells. Compared to control brain, mRNA levels of S1P1, S1P2, S1P3 and S1P generating sphingosine kinase-1 were elevated in GBM. Kaplan-Meier analyses demonstrated an association between S1P1 and S1P2 with patient´s survival times. In vitro, an inhibitory effect of the SphK inhibitor SKI-II on viability of LN18 cells was shown. S1P itself had no effect on viability but stimulated LN18 migration which was blocked by inhibition of S1P1 and S1P2. The participation of S1P1 and S1P2 in LN18 migration was further supported by siRNA-mediated silencing of these receptors. Immunoblots and inhibition experiments suggest an involvement of the PI3-kinase/AKT1 pathway in the chemotactic effect of S1P in LN18 cells.In summary, our data argue for a role of S1P signaling in proliferation and migration of GBM cells. Individual components of the S1P pathway represent prognostic factors for patients with GBM. Perspectively, a selective modulation of S1P receptor subtypes could represent a therapeutic approach for GBM patients and requires further evaluation.

  2. Clinical variables serve as prognostic factors in a model for survival from glioblastoma multiforme

    DEFF Research Database (Denmark)

    Michaelsen, Signe Regner; Christensen, Ib Jarle; Grunnet, Kirsten

    2013-01-01

    Although implementation of temozolomide (TMZ) as a part of primary therapy for glioblastoma multiforme (GBM) has resulted in improved patient survival, the disease is still incurable. Previous studies have correlated various parameters to survival, although no single parameter has yet been...

  3. Continuous Time Dynamic Contraflow Models and Algorithms

    Directory of Open Access Journals (Sweden)

    Urmila Pyakurel

    2016-01-01

    Full Text Available The research on evacuation planning problem is promoted by the very challenging emergency issues due to large scale natural or man-created disasters. It is the process of shifting the maximum number of evacuees from the disastrous areas to the safe destinations as quickly and efficiently as possible. Contraflow is a widely accepted model for good solution of evacuation planning problem. It increases the outbound road capacity by reversing the direction of roads towards the safe destination. The continuous dynamic contraflow problem sends the maximum number of flow as a flow rate from the source to the sink in every moment of time unit. We propose the mathematical model for the continuous dynamic contraflow problem. We present efficient algorithms to solve the maximum continuous dynamic contraflow and quickest continuous contraflow problems on single source single sink arbitrary networks and continuous earliest arrival contraflow problem on single source single sink series-parallel networks with undefined supply and demand. We also introduce an approximation solution for continuous earliest arrival contraflow problem on two-terminal arbitrary networks.

  4. Statistical study of clone survival curves after irradiation in one or two stages. Comparison and generalization of different models

    International Nuclear Information System (INIS)

    Lachet, Bernard.

    1975-01-01

    A statistical study was carried out on 208 survival curves for chlorella subjected to γ or particle radiations. The computing programmes used were written in Fortran. The different experimental causes contributing to the variance of a survival rate are analyzed and consequently the experiments can be planned. Each curve was fitted to four models by the weighted least squares method applied to non-linear functions. The validity of the fits obtained can be checked by the F test. It was possible to define the confidence and prediction zones around an adjusted curve by weighting of the residual variance, in spite of error on the doses delivered; the confidence limits can them be fixed for a dose estimated from an exact or measured survival. The four models adopted were compared for the precision of their fit (by a non-parametric simultaneous comparison test) and the scattering of their adjusted parameters: Wideroe's model gives a very good fit with the experimental points in return for a scattering of its parameters, which robs them of their presumed meaning. The principal component analysis showed the statistical equivalence of the 1 and 2 hit target models. Division of the irradiation into two doses, the first fixed by the investigator, leads to families of curves for which the equation was established from that of any basic model expressing the dose survival relationship in one-stage irradiation [fr

  5. VEGF as a Survival Factor in Ex Vivo Models of Early Diabetic Retinopathy.

    Science.gov (United States)

    Amato, Rosario; Biagioni, Martina; Cammalleri, Maurizio; Dal Monte, Massimo; Casini, Giovanni

    2016-06-01

    Growing evidence indicates neuroprotection as a therapeutic target in diabetic retinopathy (DR). We tested the hypothesis that VEGF is released and acts as a survival factor in the retina in early DR. Ex vivo mouse retinal explants were exposed to stressors similar to those characterizing DR, that is, high glucose (HG), oxidative stress (OS), or advanced glycation end-products (AGE). Neuroprotection was provided using octreotide (OCT), a somatostatin analog, and pituitary adenylate cyclase activating peptide (PACAP), two well-documented neuroprotectants. Data were obtained with real-time RT-PCR, Western blot, ELISA, and immunohistochemistry. Apoptosis was induced in the retinal explants by HG, OS, or AGE treatments. At the same time, explants also showed increased VEGF expression and release. The data revealed that VEGF is released shortly after exposure of the explants to stressors and before the level of cell death reaches its maximum. Retinal cell apoptosis was inhibited by OCT and PACAP. At the same time, OCT and PACAP also reduced VEGF expression and release. Vascular endothelial growth factor turned out to be a protective factor for the stressed retinal explants, because inhibiting VEGF with a VEGF trap further increased cell death. These data show that protecting retinal neurons from diabetic stress also reduces VEGF expression and release, while inhibiting VEGF leads to exacerbation of apoptosis. These observations suggest that the retina in early DR releases VEGF as a prosurvival factor. Neuroprotective agents may decrease the need of VEGF production by the retina, therefore limiting the risk, in the long term, of pathologic angiogenesis.

  6. Maximizing time from the constraining European Working Time Directive (EWTD): The Heidelberg New Working Time Model.

    Science.gov (United States)

    Schimmack, Simon; Hinz, Ulf; Wagner, Andreas; Schmidt, Thomas; Strothmann, Hendrik; Büchler, Markus W; Schmitz-Winnenthal, Hubertus

    2014-01-01

    The introduction of the European Working Time Directive (EWTD) has greatly reduced training hours of surgical residents, which translates into 30% less surgical and clinical experience. Such a dramatic drop in attendance has serious implications such compromised quality of medical care. As the surgical department of the University of Heidelberg, our goal was to establish a model that was compliant with the EWTD while avoiding reduction in quality of patient care and surgical training. We first performed workload analyses and performance statistics for all working areas of our department (operation theater, emergency room, specialized consultations, surgical wards and on-call duties) using personal interviews, time cards, medical documentation software as well as data of the financial- and personnel-controlling sector of our administration. Using that information, we specifically designed an EWTD-compatible work model and implemented it. Surgical wards and operating rooms (ORs) were not compliant with the EWTD. Between 5 pm and 8 pm, three ORs were still operating two-thirds of the time. By creating an extended work shift (7:30 am-7:30 pm), we effectively reduced the workload to less than 49% from 4 pm and 8 am, allowing the combination of an eight-hour working day with a 16-hour on call duty; thus, maximizing surgical resident training and ensuring patient continuity of care while maintaining EDTW guidelines. A precise workload analysis is the key to success. The Heidelberg New Working Time Model provides a legal model, which, by avoiding rotating work shifts, assures quality of patient care and surgical training.

  7. Computer Aided Continuous Time Stochastic Process Modelling

    DEFF Research Database (Denmark)

    Kristensen, N.R.; Madsen, Henrik; Jørgensen, Sten Bay

    2001-01-01

    A grey-box approach to process modelling that combines deterministic and stochastic modelling is advocated for identification of models for model-based control of batch and semi-batch processes. A computer-aided tool designed for supporting decision-making within the corresponding modelling cycle...

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

    Science.gov (United States)

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

    2017-12-01

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

  9. Effect of time interval between capecitabine intake and radiotherapy on local recurrence-free survival in preoperative chemoradiation for locally advanced rectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yeon Joo; Kim, Jong Hoon; Yu, Chang Sik; Kim, Tae Won; Jang, Se Jin; Choi, Eun Kyung; Kim, Jin Cheon [Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Choi, Won Sik [University of Ulsan College of Medicine, Gangneung (Korea, Republic of)

    2017-06-15

    The concentration of capecitabine peaks at 1–2 hours after administration. We therefore assumed that proper timing of capecitabine administration and radiotherapy would maximize radiosensitization and influence survival among patients with locally advanced rectal cancer. We retrospectively reviewed 223 patients with locally advanced rectal cancer who underwent preoperative chemoradiation, followed by surgery from January 2002 to May 2006. All patients underwent pelvic radiotherapy (50 Gy/25 fractions) and received capecitabine twice daily at 12-hour intervals (1,650 mg/m2/day). Patients were divided into two groups according to the time interval between capecitabine intake and radiotherapy. Patients who took capecitabine 1 hour before radiotherapy were classified as Group A (n = 109); all others were classified as Group B (n = 114). The median follow-up period was 72 months (range, 7 to 149 months). Although Group A had a significantly higher rate of good responses (44% vs. 25%; p = 0.005), the 5-year local recurrence-free survival rates of 93% in Group A and 97% in Group B did not differ significantly (p = 0.519). The 5-year disease-free survival and overall survival rates were also comparable between the groups. Despite the better pathological response in Group A, the time interval between capecitabine and radiotherapy administration did not have a significant effect on survivals. Further evaluations are needed to clarify the interaction of these treatment modalities.

  10. Consequences of cold-ischemia time on primary nonfunction and patient and graft survival in liver transplantation: a meta-analysis.

    Directory of Open Access Journals (Sweden)

    James E Stahl

    2008-06-01

    Full Text Available The ability to preserve organs prior to transplant is essential to the organ allocation process.The purpose of this study is to describe the functional relationship between cold-ischemia time (CIT and primary nonfunction (PNF, patient and graft survival in liver transplant.To identify relevant articles Medline, EMBASE and the Cochrane database, including the non-English literature identified in these databases, was searched from 1966 to April 2008. Two independent reviewers screened and extracted the data. CIT was analyzed both as a continuous variable and stratified by clinically relevant intervals. Nondichotomous variables were weighted by sample size. Percent variables were weighted by the inverse of the binomial variance.Twenty-six studies met criteria. Functionally, PNF% = -6.678281+0.9134701*CIT Mean+0.1250879*(CIT Mean-9.895352-0.0067663*(CIT Mean-9.895353, r2 = .625, , p<.0001. Mean patient survival: 93% (1 month, 88% (3 months, 83% (6 months and 83% (12 months. Mean graft survival: 85.9% (1 month, 80.5% (3 months, 78.1% (6 months and 76.8% (12 months. Maximum patient and graft survival occurred with CITs between 7.5-12.5 hrs at each survival interval. PNF was also significantly correlated with ICU time, % first time grafts and % immunologic mismatches.The results of this work imply that CIT may be the most important pre-transplant information needed in the decision to accept an organ.

  11. Obiltoxaximab Prevents Disseminated Bacillus anthracis Infection and Improves Survival during Pre- and Postexposure Prophylaxis in Animal Models of Inhalational Anthrax

    Science.gov (United States)

    Yamamoto, Brent J.; Shadiack, Annette M.; Carpenter, Sarah; Sanford, Daniel; Henning, Lisa N.; Gonzales, Nestor; O'Connor, Edward; Casey, Leslie S.

    2016-01-01

    The Centers for Disease Control and Prevention recommend adjunctive antitoxins when systemic anthrax is suspected. Obiltoxaximab, a monoclonal antibody against protective antigen (PA), is approved for treatment of inhalational anthrax in combination with antibiotics and for prophylaxis when alternative therapies are not available. The impact of toxin neutralization with obiltoxaximab during pre- and postexposure prophylaxis was explored, and efficacy results that supported the prophylaxis indication are presented here. New Zealand White rabbits and cynomolgus macaques received obiltoxaximab as a single intramuscular or intravenous dose of 2 to 16 mg/kg of body weight at various times relative to Bacillus anthracis aerosol spore challenge. The primary endpoint was survival, and effect of treatment timing was explored. In rabbits, obiltoxaximab administration 9 h postchallenge singly or combined with a 5-day levofloxacin regimen protected 89% to 100% of animals compared to 33% with levofloxacin monotherapy. In cynomolgus macaques, a single intramuscular dose of 16 mg/kg obiltoxaximab led to 100% survival when given 1 to 3 days preexposure and 83% to 100% survival when given 18 to 24 h postexposure and prior to systemic bacteremia onset. Obiltoxaximab administration after bacteremia onset resulted in lower (25% to 50%) survival rates reflective of treatment setting. Prophylactic administration of obiltoxaximab before spore challenge or to spore-challenged animals before systemic bacterial dissemination is efficacious in promoting survival, ameliorating toxemia, and inhibiting bacterial spread to the periphery. PMID:27431219

  12. The mass effect model of the survival rate's dose effect of organism irradiated with low energy ion beam

    International Nuclear Information System (INIS)

    Shao Chunlin; Gui Qifu; Yu Zengliang

    1995-01-01

    The main characteristic of the low energy ions mutation is its mass deposition effect. Basing on the theory of 'double strand breaking' and the 'mass deposition effect', the authors suggests that the mass deposition products can repair or further damage the double strand breaking of DNA. According to this consideration the dose effect model of the survival rate of organism irradiated by low energy of N + ion beam is deduced as: S exp{-p[αφ + βφ 2 -Rφ 2 exp(-kφ)-Lφ 3 exp(-kφ)]}, which can be called 'mass effect model'. In the low energy ion beam mutation, the dose effects of many survival rates that can not be imitated by previous models are successfully imitated by this model. The suitable application fields of the model are also discussed

  13. Methodology to predict long-term cancer survival from short-term data using Tobacco Cancer Risk and Absolute Cancer Cure models

    International Nuclear Information System (INIS)

    Mould, R F; Lederman, M; Tai, P; Wong, J K M

    2002-01-01

    Three parametric statistical models have been fully validated for cancer of the larynx for the prediction of long-term 15, 20 and 25 year cancer-specific survival fractions when short-term follow-up data was available for just 1-2 years after the end of treatment of the last patient. In all groups of cases the treatment period was only 5 years. Three disease stage groups were studied, T1N0, T2N0 and T3N0. The models are the Standard Lognormal (SLN) first proposed by Boag (1949 J. R. Stat. Soc. Series B 11 15-53) but only ever fully validated for cancer of the cervix, Mould and Boag (1975 Br. J. Cancer 32 529-50), and two new models which have been termed Tobacco Cancer Risk (TCR) and Absolute Cancer Cure (ACC). In each, the frequency distribution of survival times of defined groups of cancer deaths is lognormally distributed: larynx only (SLN), larynx and lung (TCR) and all cancers (ACC). All models each have three unknown parameters but it was possible to estimate a value for the lognormal parameter S a priori. By reduction to two unknown parameters the model stability has been improved. The material used to validate the methodology consisted of case histories of 965 patients, all treated during the period 1944-1968 by Dr Manuel Lederman of the Royal Marsden Hospital, London, with follow-up to 1988. This provided a follow-up range of 20- 44 years and enabled predicted long-term survival fractions to be compared with the actual survival fractions, calculated by the Kaplan and Meier (1958 J. Am. Stat. Assoc. 53 457-82) method. The TCR and ACC models are better than the SLN model and for a maximum short-term follow-up of 6 years, the 20 and 25 year survival fractions could be predicted. Therefore the numbers of follow-up years saved are respectively 14 years and 19 years. Clinical trial results using the TCR and ACC models can thus be analysed much earlier than currently possible. Absolute cure from cancer was also studied, using not only the prediction models which

  14. Analyzing multivariate survival data using composite likelihood and flexible parametric modeling of the hazard functions

    DEFF Research Database (Denmark)

    Nielsen, Jan; Parner, Erik

    2010-01-01

    In this paper, we model multivariate time-to-event data by composite likelihood of pairwise frailty likelihoods and marginal hazards using natural cubic splines. Both right- and interval-censored data are considered. The suggested approach is applied on two types of family studies using the gamma...

  15. Clustered survival data with left-truncation

    DEFF Research Database (Denmark)

    Eriksson, Frank; Martinussen, Torben; Scheike, Thomas H.

    2015-01-01

    Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry....... Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific