An E-value analysis of potential unmeasured or residual confounding in systematic reviews of post-tuberculosis mortality, respiratory disease, and cardiovascular disease.

Unmeasured confounding poses a serious threat to observational studies of post-TB health outcomes. E-values have been recently proposed as a method to assess the magnitude of unmeasured confounding necessary to nullify, or to render non-significant, relative effect estimates from observational studies. We calculated E-values for both the risk ratio (RR) point estimates and their lower 95% confidence limits (LCL) from studies of post-TB mortality, respiratory disease, and cardiovascular disease (CVD) included in published systematic reviews within and across post-TB outcome domains. We also employed a meta-analytic E-value approach to estimate the proportion of unconfounded study RRs greater than 1.1 at different levels of unmeasured confounding. Across post-TB health outcome domains, we observed a median E-value of 5.59 (IQR = 3.19-7.35) for RRs, and 2.95 (IQR = 1.71-4.61) for LCLs. Post-TB mortality studies had higher median E-values (E-value Unmeasured confounding with an association of 2.95 or greater with both the exposure (TB) and outcome, on the risk ratio scale, could render most post-TB health studies' findings statistically non-significant. Post-TB mortality and respiratory disease studies had higher E-values than TB-CVD studies, indicating that either (a) TB-CVD studies may be more susceptible to unmeasured confounding bias, or (b) the true effect of TB on CVD is lower.

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Déclaration de conflit d'intérêts

Declaration of Competing Interest CAB declares no conflicts or competing interests. MEK has received consulting fees from Biogen, Inc., unrelated to this manuscript.