Incorporating uncertainty in the baseline risk: An R Shiny tool and an empirical study

Abstract

The common practice in meta-analysis and clinical practice guidelines is to derive the absolute treatment effect (also called risk difference, RD) from a combination of a pooled relative risk (RR) that resulted from a meta-analysis, and a user-provided baseline risk (BR). However, this method does not address the uncertainty in BR. We developed a web-based R Shiny tool to perform simple microsimulation and incorporate uncertainty in BR into the precision of RD. We empirically evaluated this approach by estimating the impact of incorporating this uncertainty when BR is derived from the control group rates in 3,128 meta-analyses curated from the Cochrane Library (26,964 individual studies). When BR was derived from the largest study in each meta-analysis, the median width of the CI of BR was 11.6% (interquartile range (IQR), 6.30%–18.5%). Incorporating this uncertainty in BR led to expansion of the RD CI by a median of 8 per 1,000 persons (IQR 2–24). This expansion increased in a linear fashion with BR imprecision and was more prominent in meta-analyses with low BR. This study provides a web-based tool to perform simple microsimulation and incorporate uncertainty in BR into the CI of RD.