How to choose cut-off points: statistical and clinical perspectives.

Abstract

Continuous variables are often dichotomized or categorized in clinical research to improve interpretability or to align with clinical thresholds. However, arbitrary or poorly justified cut-off points can cause substantial information loss, reduced statistical power, and potentially misleading conclusions. In this article, we describe commonly used approaches for determining cut-off points, including guideline-based thresholds, median, or quantile splits, and statistically derived methods, such as receiver operating characteristic (ROC) curve-based approaches (e.g., Youden Index and related criteria). We also discuss the clinical and methodological implications of these approaches using illustrative examples and offer practical recommendations to support the transparent and appropriate use of cut-offs in anesthesia and perioperative research.