Determining a Meaningful R-squared Value in Clinical Medicine

Abstract

Introduction In clinical medicine, determining a meaningful R2 value requires careful consideration of various factors. The R-squared (R2) value is a statistical measure used to assess the extent to which independent variables explain the dependent variable in regression models. Its interpretation in clinical medicine is very context-dependent and lacks a definitive threshold. While a higher R2 suggests a stronger relationship between variables, smaller R-squared values will still hold relevance, especially for multifactorial clinical outcomes. Due to clinical medicine’s genetic, environmental, and behavioral factors, high R2 values may not be realistic or expected in this context. Methods This study is a narrative review encompassing expert opinions, results from randomized controlled trials (RCTs), and observational studies relating to the use and interpretation of the coefficient of variance (R2) in clinical medicine. Results 30 studies spanning literature across various disciplines within clinical medicine were evaluated and synthesized to provide a contextualized, nuanced approach to interpreting the R2 in medical literature. Conclusions A nuanced understanding of the significance of R2 values in clinical medicine requires considering the research question, clinical context, complexity of the phenomenon, and contextual comparisons. Integrating statistical rigor and clinical judgment helps derive meaningful insights from clinical data. This paper highlights key considerations for evaluating a “good” R2 value in clinical medicine and concludes that an R2 of >15% is a generally a meaningful value in clinical research.