Identification of known potential confounders to design target trial emulation studies: a systematic assessment
Abstract
Background: We aimed to systematically identify and assess known potential confounders for the design of a target trial emulation on multiple sclerosis and to investigate its feasibility.
Methods: We used the comparison of two drugs for relapsing-remitting multiple sclerosis. We conducted a systematic literature analysis (date of last search November 2, 2023) of observational studies and randomized trials, qualitative interviews, and a quantitative survey with clinicians. All identified potential confounders were categorized and classified by clinical importance. We estimated the resource use per study step and per identified potential confounder.
Results: We assessed 53 observational studies and 27 randomized trials, surveyed 8 clinicians, and conducted 8 interviews with clinical experts. We identified a total of 160 individual potential confounders. While most of these were identified in the literature ( n = 125, 78%), interviews revealed an additional 35 (22%) factors. Of the 17 confounders rated by clinicians as very important for treatment decisions, 9 were identified by interviews (53%). All the potential confounders related to patient perspective were identified in interviews only. Across all data sources, the 5 most frequently considered factors were age ( n = 71), gender/sex ( n = 62), disability status ( n = 62), disease duration ( n = 53), and relapses ( n = 44); these were all considered in 16 (30%) of the observational studies. Sixty-two person-days were deemed necessary to identify the 160 potential confounders.
Conclusions: There was a substantial discrepancy between factors considered when making treatment decisions and the confounders considered in studies. Even with extensive efforts, it is likely that for observational studies assessing treatment effects their key assumption of no unmeasured confounding is currently not met, and they will have challenges to provide credible real-world evidence due to serious concerns of confounding bias.
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BibTeX
@article{hirt2026identification,
title = {{Identification of known potential confounders to design target trial emulation studies: a systematic assessment}},
author = {Julian Hirt and Tim Woelfle and Perrine Janiaud and Lars G. Hemkens},
journal = {BMC Medicine},
year = {2026},
month = oct,
doi = {10.1186/s12916-026-05328-3},
url = {https://link.springer.com/article/10.1186/s12916-026-05328-3},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Identification of known potential confounders to design target trial emulation studies: a systematic assessment
AU - Julian Hirt
AU - Tim Woelfle
AU - Perrine Janiaud
AU - Lars G. Hemkens
PY - 2026
DA - 2026/10/21
JO - BMC Medicine
DO - 10.1186/s12916-026-05328-3
UR - https://link.springer.com/article/10.1186/s12916-026-05328-3
AB - Background: We aimed to systematically identify and assess known potential confounders for the design of a target trial emulation on multiple sclerosis and to investigate its feasibility. Methods: We used the comparison of two drugs for relapsing-remitting multiple sclerosis. We conducted a systematic literature analysis (date of last search November 2, 2023) of observational studies and randomized trials, qualitative interviews, and a quantitative survey with clinicians. All identified potential confounders were categorized and classified by clinical importance. We estimated the resource use per study step and per identified potential confounder. Results: We assessed 53 observational studies and 27 randomized trials, surveyed 8 clinicians, and conducted 8 interviews with clinical experts. We identified a total of 160 individual potential confounders. While most of these were identified in the literature ( n = 125, 78%), interviews revealed an additional 35 (22%) factors. Of the 17 confounders rated by clinicians as very important for treatment decisions, 9 were identified by interviews (53%). All the potential confounders related to patient perspective were identified in interviews only. Across all data sources, the 5 most frequently considered factors were age ( n = 71), gender/sex ( n = 62), disability status ( n = 62), disease duration ( n = 53), and relapses ( n = 44); these were all considered in 16 (30%) of the observational studies. Sixty-two person-days were deemed necessary to identify the 160 potential confounders. Conclusions: There was a substantial discrepancy between factors considered when making treatment decisions and the confounders considered in studies. Even with extensive efforts, it is likely that for observational studies assessing treatment effects their key assumption of no unmeasured confounding is currently not met, and they will have challenges to provide credible real-world evidence due to serious concerns of confounding bias.
SN - 1741-7015
ER -