J Biopharm Stat. 2022 Jun 8:1-18. doi: 10.1080/10543406.2022.2080696. Online ahead of print.
ABSTRACT
In clinical studies that utilize real-world data, time-to-event outcomes are often germane to scientific questions of interest. Two main obstacles are the presence of non-proportional hazards and confounding bias. Existing methods that could adjust for NPH or confounding bias, but no previous work delineated the complexity of simultaneous adjustments for both. In this paper, a propensity score stratified MaxCombo and weighted Cox model is proposed. This model can adjust for confounding bias and NPH and can be pre-specified when NPH pattern is unknown in advance. The method has robust performance as demonstrated in simulation studies and in a case study.
PMID:35675418 | DOI:10.1080/10543406.2022.2080696
