Results 51 to 60 of about 414,671 (320)

Survival analysis of irish amyotrophic lateral sclerosis patients diagnosed from 1995-2010. [PDF]

PLoS ONE, 2013
IntroductionThe Irish ALS register is a valuable resource for examining survival factors in Irish ALS patients. Cox regression has become the default tool for survival analysis, but recently new classes of flexible parametric survival analysis tools ...
James Rooney, Susan Byrne, Mark Heverin, Bernie Corr, Marwa Elamin, Anthony Staines, Ben Goldacre, Orla Hardiman   +7 more
doaj   +1 more source

Estimation of treatment effects in weighted log-rank tests

Contemporary Clinical Trials Communications, 2017
Non-proportional hazards have been observed in clinical trials. The log-rank test loses power and the standard Cox model generally produces biased estimates under such conditions.
Ray S. Lin, Larry F. León
doaj   +1 more source

An Online Updating Approach for Testing the Proportional Hazards Assumption with Streams of Big Survival Data

, 2018
The Cox model, which remains as the first choice in analyzing time-to-event data even for large datasets, relies on the proportional hazards assumption. When the data size exceeds the computer memory, the standard statistics for testing the proportional ...
Schifano, Elizabeth D., Wang, HaiYing, Xue, Yishu, Yan, Jun   +3 more
core   +1 more source

On the use of Fractional Polynomials in Dynamic Cox Models [PDF]

, 2000
Despite a sophisticated research on modelling of survival data in the last years, the most popular model used in practice is still the proportional hazards regression model proposed by Cox (1972).
Berger, Ursula, Gerein, Pia, Schäfer, Juliane, Ulm, Kurt   +3 more
core   +1 more source

Multiple imputation in Cox regression when there are time-varying effects of covariates. [PDF]

, 2017
In Cox regression, it is important to test the proportional hazards assumption and sometimes of interest in itself to study time-varying effects (TVEs) of covariates. TVEs can be investigated with log hazard ratios modelled as a function of time. Missing
Abrahamowicz, Abrahamowicz, Bartlett, Bartlett, Bartlett, Berger, Binquet, Borgan, Breslow, Buchholz, Carpenter, Collett, Collins, Cox, Cox, Cummins, Durrleman, Ford, Gerds, Gore, Grambsch, Gray, Hastie, Heinzl, Hess, Kooperberg, Li, Liu, Meng, Moreau, Morris, Ng'andu, Quantin, Royston, Royston, Rubin, Sauerbrei, Sauerbrei, Scheike, Schemper, Schoenfeld, Seaman, Stone, Therneau, Tian, Van Buuren, Van Buuren, Verweij, White, White, Winnett, Wood, Wynant, Yan, Zucker   +54 more
core   +3 more sources

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Estimation in Cox proportional hazards model with heteroscedastic errors in covariates

Modern Stochastics: Theory and Applications
Consistent estimators of the baseline hazard rate and the regression parameter are constructed in the Cox proportional hazards model with heteroscedastic measurement errors, assuming that the baseline hazard function belongs to a certain class of ...
Oksana Chernova
doaj   +1 more source

A Resampling Method to Improve the Prognostic Model of End-Stage Kidney Disease: A Better Strategy for Imbalanced Data

Frontiers in Medicine, 2022
BackgroundPrognostic models can help to identify patients at risk for end-stage kidney disease (ESKD) at an earlier stage to provide preventive medical interventions. Previous studies mostly applied the Cox proportional hazards model.
Xi Shi, Xi Shi, Tingyu Qu, Gijs Van Pottelbergh, Marjan van den Akker, Marjan van den Akker, Bart De Moor   +6 more
doaj   +1 more source

joineR: Joint modelling of repeated measurements and time-to-event data [PDF]

, 2012
The joineR package implements methods for analysing data from longitudinal studies in which the response from each subject consists of a time-sequence of repeated measurements and a possibly censored time-toevent outcome.
Diggle, Peter, Henderson, Robin, Kolamunnage-Dona, Ruwanthi, Philipson, Pete, Sousa, Ines, Williamson, Paula   +5 more
core  

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Molecular Oncology, EarlyView.
This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu, Katherine Eason, Suet‐Feung Chin, Paul A. W. Edwards, Raquel Manzano Garcia, Richard Moulange, Jia Wern Pan, Soo Hwang Teo, Sach Mukherjee, Maurizio Callari, Carlos Caldas, Stephen‐John Sammut, Oscar M. Rueda   +12 more
wiley   +1 more source