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Critical Review of Oncology Clinical Trial Design Under Non-proportional Hazards.
Critical Reviews in Oncology/Hematology, 2021In trials of novel immuno-oncology drugs, the proportional hazards (PH) assumption often does not hold for the primary time-to-event (TTE) efficacy endpoint, likely due to the unique mechanism of action of these drugs. In practice, when it is anticipated that PH may not hold for the TTE endpoint with respect to treatment, the sample size is often still
R. Ananthakrishnan +5 more
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Sequential tests for non-proportional hazards data
Lifetime Data Analysis, 2017In clinical trials survival endpoints are usually compared using the log-rank test. Sequential methods for the log-rank test and the Cox proportional hazards model are largely reported in the statistical literature. When the proportional hazards assumption is violated the hazard ratio is ill-defined and the power of the log-rank test depends on the ...
Matthias Brückner, W. Brannath
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Pharmaceutical statistics, 2022
Non‐proportional hazards have been observed in many studies especially in immuno‐oncology clinical trials. Traditional analysis using the combined approach with log‐rank test as the significance test and Cox model for treatment effect estimation becomes ...
Xiaodong Luo, Yuan Sun, Zhixing Xu
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Non‐proportional hazards have been observed in many studies especially in immuno‐oncology clinical trials. Traditional analysis using the combined approach with log‐rank test as the significance test and Cox model for treatment effect estimation becomes ...
Xiaodong Luo, Yuan Sun, Zhixing Xu
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Reduced‐rank hazard regression for modelling non‐proportional hazards
Statistics in Medicine, 2006The Cox proportional hazards model is the most common method to analyse survival data. However, the proportional hazards assumption might not hold. The natural extension of the Cox model is to introduce time-varying effects of the covariates. For some covariates such as (surgical)treatment non-proportionality could be expected beforehand.
A. Perperoglou +2 more
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Sample Size Determination Under Non-proportional Hazards
Springer Proceedings in Mathematics & statistics, 2016The proportional hazards assumption rarely holds in clinical trials of cancer immunotherapy. Specifically, delayed separation of the Kaplan-Meier survival curves and long-term survival have been observed. Routine practice in designing a randomized controlled two-arm clinical trial with a time-to-event endpoint assumes proportional hazards.
Miao Yang, Zhaowei Hua, S. Vardhanabhuti
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Non-proportional hazards models in survival analysis
, 2000Cox’ proportional hazard model is usually the model of choice in survival analysis. It is shown that this model can be embedded in a GLMmodel by proper discretization of the time axis. That approach easily allows non-proportional hazard models, that are special cases of time-varying coefficients models.
H. V. Houwelingen, P. Eilers
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On a non-proportional hazards regression model for repeated medical random counts.
Statistics in Medicine, 1997A wholly parametric non-proportional hazards survival model is introduced. The model retains Cox's constant of proportionality as the leading term in the relative risk but permits additional flexibility by modelling the relative risk as a function of time.
Gilbert MacKenzie
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Statistical Methods in Medical Research, 2019
The semiparametric Cox regression model is often fitted in the modeling of survival data. One of its main advantages is the ease of interpretation, as long as the hazards rates for two individuals do not vary over time.
V. Calsavara +3 more
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The semiparametric Cox regression model is often fitted in the modeling of survival data. One of its main advantages is the ease of interpretation, as long as the hazards rates for two individuals do not vary over time.
V. Calsavara +3 more
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A Non‐Proportional Hazards Model with Hazard Ratio Functions Free from Covariate Values
International Statistical Review, 2020SummaryA brief survey on methods to handle non‐proportional hazards in survival analysis is given with emphasis on short‐term and long‐term hazard ratio modelling. A drawback of the existing model of this nature is that except at time zero or infinity, the hazard ratio for a unit increase in the value of a covariate depends on the starting value.
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Estimation of Main Effect When Covariates Have Non-Proportional Hazards
Communications in Statistics - Simulation and Computation, 2014The Cox proportional hazards (PH) regression model has been widely used to analyze survival data in clinical trials and observational studies. In addition to estimating the main treatment or exposure group effect, it is common to adjust for additional covariates using the Cox model.
Erika Strandberg, Xinyi Lin, R. Xu
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