The Journey of Cornfield's Inequalities and How They Shaped Modern Sensitivity Analysis

Cornfield et al.'s 1959 paper introduced a seminal framework for evaluating the impact of unmeasured confounding by quantifying the strength an unobserved factor would need to overturn an observed association. This commentary revisits Cornfield's original inequalities, clarifying their interpretation, and highlighting the reverse-reasoning principle that underlies modern sensitivity analysis. We summarize key methodological extensions developed by later researchers-ranging from conditional independence formulations and multiplicative bounds to the sharpened limits that led to the E-value, and illustrate how these refinements broadened the applicability of Cornfield's logic. Finally, we discuss the continued influence of Cornfield-type reasoning across epidemiology and related fields, where sensitivity analysis has become an essential component of study design and causal interpretation. More than six decades later, Cornfield's insight remains a foundational pillar of causal inference, guiding researchers in assessing the robustness of empirical findings to unmeasured confounding.