title: Methodological challenges to control for immortal time bias in addressing drug effects in type 2 diabetes.
abstract: There are multiple biases in using observational studies to examine treatment effects such as those from prevalent drug users, immortal time and drug indications. We used renin angiotensin system (RAS) inhibitors and statins as reference drugs with proven efficacies in randomized clinical trials (RCTs) and examined their effectiveness in the prospective Hong Kong Diabetes Registry using adjustment methods proposed in the literature. Using time-dependent exposures to drug treatments yielded greatly inflated hazard ratios (HR) regarding the treatment effects of these drugs for cardiovascular disease (CVD) in type 2 diabetes. These errors were probably due to changing indications to use these drugs during follow up periods, especially at the time of drug commencement making time-dependent analysis extremely problematic. Using time-fixed analysis with exclusion of immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of RAS inhibitors for CVD was comparable to that in RCT. The result supported the use of the Registry for performing pharmacoepidemiological analysis which revealed an attenuated low low-density lipoprotein cholesterol related cancer risk with RAS inhibitors. On the other hand, time-fixed analysis with including immortal time and adjustment for confounders at baseline and/or during follow-up periods, the HR of statins for CVD was similar to that in the RCT. Our results highlight the complexity and difficulty in removing these biases. We call for validations of the methods to cope with immortal time and drug use indications before applying them to particular research questions, so to avoid making erroneous conclusions.
authors.affiliation: Xi-Lin Yang, Xiao-Xu Huo, Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China.
authors.forename: Xi-Lin
authors.initials: XL
authors.lastname: Yang
authors.affiliation: Xi-Lin Yang, Xiao-Xu Huo, Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China.
authors.forename: Xiao-Xu
authors.initials: XX
authors.lastname: Huo
authors.affiliation: Xi-Lin Yang, Xiao-Xu Huo, Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China.
authors.forename: Juliana Cn
authors.initials: JC
authors.lastname: Chan
keywords: Drug effects; Drug indication bias; Immortal time bias; Pharmacoepidemiological analysis; Prevalent drug user bias; Type 2 diabetes