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10.1016/j.conctc.2017.09.004 http://scihub22266oqcxt.onion/10.1016/j.conctc.2017.09.004 C5898500!5898500!29696204     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Contemp+Clin+Trials+Commun 2017 ; 8 (ä): 147-55 Nephropedia Template TP {{tp|p=29696204|t=2017. Estimation of treatment effects in weighted log-rank tests |pdf=|usr=}}{{29696204}} gab.com Text Estimation of treatment effects in weighted log-rank tests JO: Contemp Clin Trials Commun http://www.kidney.de/pget.php?&tw=1&pmid=29696204 #FOAvip 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. Weighted log-rank tests have been utilized to increase the test power; however, it is not intuitive how to interpret the test result in terms of the clinical effect. We propose a Cox-model based time-varying treatment effect estimate to complement the weighted log-rank test.The score test from the proposed model is equivalent to the weighted log-rank test, and a time-profile of the treatment effect can be obtained by fitting a time-varying covariate Cox model. Simulation results show that the proposed model preserves type-I error and achieve higher power than log-rank tests under non-proportional hazards scenarios. Whereas the standard Cox model produces biased effect estimates, the proposed model produces unbiased estimates if the weight function is correctly specified. It also achieves a better model fit and an enhanced flexibility to accommodate non-proportional hazards compared to the standard Cox model.The proposed approach makes the assumptions of the weighted log-rank test explicit and the validity of assumptions can be assessed based on prior knowledge or model goodness-of-fit. It also helps to translate the weighted log-rank test results into quantitative estimates of the treatment effect with intuitive interpretation. The proposed method can be routinely conducted to complement weighted log-rank tests, especially in the setting where non-proportional hazards are expected. Twit Text FOAVip Estimation of treatment effects in weighted log-rank tests ????Contemp Clin Trials Commun http://www.kidney.de/pget.php?&tw=1&pmid=29696204 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29696204 #FOAvip English Wikipedia <ref>{{Cite pmid|29696204}}</ref> Estimation of treatment effects in weighted log-rank tests #MMPMID29696204 Lin RS; León LF Contemp Clin Trials Commun 2017[Dec]; 8 (ä): 147-55 PMID29696204show ga 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. Weighted log-rank tests have been utilized to increase the test power; however, it is not intuitive how to interpret the test result in terms of the clinical effect. We propose a Cox-model based time-varying treatment effect estimate to complement the weighted log-rank test.The score test from the proposed model is equivalent to the weighted log-rank test, and a time-profile of the treatment effect can be obtained by fitting a time-varying covariate Cox model. Simulation results show that the proposed model preserves type-I error and achieve higher power than log-rank tests under non-proportional hazards scenarios. Whereas the standard Cox model produces biased effect estimates, the proposed model produces unbiased estimates if the weight function is correctly specified. It also achieves a better model fit and an enhanced flexibility to accommodate non-proportional hazards compared to the standard Cox model.The proposed approach makes the assumptions of the weighted log-rank test explicit and the validity of assumptions can be assessed based on prior knowledge or model goodness-of-fit. It also helps to translate the weighted log-rank test results into quantitative estimates of the treatment effect with intuitive interpretation. The proposed method can be routinely conducted to complement weighted log-rank tests, especially in the setting where non-proportional hazards are expected. äEstimation of treatment effects in weighted log-rank tests (epmc).pdf DeepDyve Pubget Overpricing