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

Area of Science:

• Clinical research methodology
• Biostatistics
• Anesthesiology

Background:

• Continuous variables are frequently categorized in clinical studies for simplicity.
• Improperly chosen cut-off points can reduce statistical power and lead to erroneous conclusions.
• This practice is common in anesthesia and perioperative research.

Purpose of the Study:

• To review common methods for determining cut-off points for continuous variables.
• To discuss the implications of different cut-off selection strategies.
• To provide recommendations for appropriate cut-off usage in anesthesia research.

Main Methods:

• Review of established methods for variable categorization.
• Description of guideline-based thresholds, median/quantile splits.
• Explanation of statistically derived methods like Receiver Operating Characteristic (ROC) curve analysis (e.g., Youden Index).

Main Results:

• Arbitrary cut-offs can significantly impact study outcomes and interpretations.
• Statistically derived methods, such as ROC analysis, offer more objective approaches.
• The choice of cut-off significantly influences statistical power and conclusion validity.

Conclusions:

• Careful consideration and justification are crucial when dichotomizing continuous variables.
• Transparent reporting of cut-off selection methods is essential for research integrity.
• Adopting evidence-based strategies for cut-off determination enhances the reliability of anesthesia and perioperative research findings.