Editorial: Identifying the Perfect Predictor of Absence of Disease: A Shift Toward Necessary Condition Analysis in Evidence-Based Medicine?

Abstract

One of the challenges of evidence-based medicine is balancing population-level findings with individualized care. Average treatment effect studies, including cohort studies and randomized controlled trials, offer insights into factors affecting disease likelihood at group level or subgroup level (precision medicine), but are limited in predicting individual outcomes. This limitation arises because average treatment effect studies operate within a probabilistic causal framework, indicating how likely a disease is when a certain individual or contextual factor is present: if X, then probably Y.