Journal Article

Risk of bias in observational studies using routinely collected data of comparative effectiveness research: a meta-research study

Davison, Mauricia, Cochrane France, Porcher, Raphael, Ravaud, Philippe, Stanford University, Hôpital Hôtel-Dieu [Paris] ; Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Boutron, Isabelle, Engleton, Mishelle, Nguyen, Van, Thu, Centre for Research in Epidemiology and Statistics | Centre de Recherche Épidémiologie et Statistiques (CRESS (U1153 / UMR_A 1125)) ; Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

2021

Overview

Background: To assess the completeness of reporting, research transparency practices, and risk of selection and immortal bias in observational studies using routinely collected data for comparative effectiveness research. Method: We performed a meta-research study by searching PubMed for comparative effectiveness observational studies evaluating therapeutic interventions using routinely collected data published in high impact factor journals from 01/06/2018 to 30/06/2020. We assessed the reporting of the study design (i.e., eligibility, treatment assignment, and the start of follow-up). The risk of selection bias and immortal time bias was determined by assessing if the time of eligibility, the treatment assignment, and the start of follow-up were synchronized to mimic the randomization following the target trial emulation framework. Result: Seventy-seven articles were identified. Most studies evaluated pharmacological treatments (69%) with a median sample size of 24,000 individuals. In total, 20% of articles inadequately reported essential information of the study design. One-third of the articles (n = 25, 33%) raised some concerns because of unclear reporting (n = 6, 8%) or were at high risk of selection bias and/or immortal time bias (n = 19, 25%). Only five articles (25%) described a solution to mitigate these biases. Six articles (31%) discussed these biases in the limitations section. Conclusion: Reporting of essential information of study design in observational studies remained suboptimal. Selection bias and immortal time bias were common methodological issues that researchers and physicians should be aware of when interpreting the results of observational studies using routinely collected data.

• Publisher: CCSD,BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Analysis / Bias / Bias (Statistics) / Biomedicine / Clinical trials / Comparative Effectiveness Research / Contraindications / Data collection / Design / Diabetes / Drug therapy / Emulated trial / Endocrinology / Epidemiologic Studies / Evaluation / Funding / Humans / Impact factors / Information sharing / Intervention / Life Sciences / Medical research / Medicine / Medicine & Public Health / Medicine, Experimental / Meta-research / Observational studies / Physicians / Research Article / Research Design / Risk / Risk of bias / Routinely collected data / Routinely Collected Health Data / Statistics / Therapeutic applications