On the use of the E-value for sensitivity analysis in epidemiologic studies

Abstract

This study illustrates the use of a recently developed sensitivity index, the E-value, helpful in strengthening causal inferences in observational epidemiological studies. The E-value aims to determine the minimum required strength of association between an unmeasured confounder and an exposure/outcome to explain the observed association as non-causal. Such parameter is defined as E - v a l u e = R R + R R R R - 1, where RR is the risk ratio between the exposure and the outcome. Our work illustrates the E-value using observational data from a recently published study on the relationship between indicators of prenatal care adequacy and the outcome low birthweight. The E-value ranged between 1.45 and 5.63 according to the category and prenatal care index evaluated, showing the highest value for the “no prenatal care” category of the GINDEX index and the minimum value for “intermediate prenatal care” of the APNCU index. For “inappropriate prenatal care” (all indexes), the E-value ranged between 2.76 (GINDEX) and 4.99 (APNCU). These findings indicate that only strong confounder/low birthweight associations (more than 400% increased risk) would be able to fully explain the prenatal care vs. low birthweight association observed. The E-value is a useful, intuitive sensitivity analysis tool that may help strengthening causal inferences in epidemiological observational studies.