Editorial
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Methodol. Sep 26, 2015; 5(3): 122-126
Published online Sep 26, 2015. doi: 10.5662/wjm.v5.i3.122
Methodological challenges to control for immortal time bias in addressing drug effects in type 2 diabetes
Xi-Lin Yang, Xiao-Xu Huo, Juliana CN Chan
Xi-Lin Yang, Xiao-Xu Huo, Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin 300070, China
Juliana CN Chan, Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Hong Kong, China
Juliana CN Chan, Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
Author contributions: Yang XL conceived the idea and wrote this paper; Chan JCN conceived the idea and critically revised and edited this paper; Huo XX gave critical comments and revised this paper.
Conflict-of-interest statement: Chan JC is a board member of the Asia Diabetes Foundation. She is a consultant for AstraZeneca, Bayer, Merck Sharp and Dohme, Pfizer, Sanofi and Qualigenics. She has received honoraria, travel expenses, and/or payments from AstraZeneca, Bayer, Bristol-Myers Squibb, Daiichi-Sankyo, Eli Lilly, GlaxoSmithKline, Merck Serono, Merck Sharp and Dohme, Nestle Nutrition Institute, Novo Nordisk, Pfizer, Roche, Sanofi and Takeda for giving lectures. Her institution has received grants from these companies.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Dr. Xi-Lin Yang, Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, 22 Qixiangtai Road, Heping District, Tianjin 300070, China. yangxilin@tmu.edu.cn
Telephone: +86-22-83336617 Fax: +86-22-83336608
Received: April 13, 2015
Peer-review started: April 18, 2015
First decision: June 3, 2015
Revised: June 12, 2015
Accepted: August 13, 2015
Article in press: August 14, 2015
Published online: September 26, 2015
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.

Keywords: Pharmacoepidemiological analysis, Immortal time bias, Drug effects, Prevalent drug user bias, Drug indication bias, Type 2 diabetes

Core tip: There are multiple biases in using observational studies to examine treatment effects. These biases include those due to prevalent drug users, immortal time and drug indications that must be taken into consideration. In this regard, we used drugs with proven effects in randomized controlled trials and applied those proposed methods by other groups to estimate their effects in a prospective cohort of patients with type 2 diabetes. Our results highlighted the importance of validating adjustment methods for immortal time and drug use indications before applying them to addressing research questions, so to avoid making erroneous conclusions.