AUC (Area Under the ROC Curve) measures how well a biomarker distinguishes between two groups (e.g., disease vs. healthy). AUC ranges from 0.5 (no discrimination, equivalent to random guessing) to 1.0 (perfect discrimination). General guidelines:
- 0.5-0.6 = fail
- 0.6-0.7 = poor
- 0.7-0.8 = fair
- 0.8-0.9 = good
- 0.9-1.0 = excellent
However, be cautious of overfitting: cross-validated AUC above 0.9 in small cohorts may not replicate in external validation. A relatively larger sample size is required for biomarker analysis.