External Validation of Predictive Models for High-Grade Cervical Lesions in Thai Women Undergoing Colposcopy

Background Predictive models for high-grade cervical lesions (CIN2+/HSIL) have been developed in various populations; however, their generalizability across different healthcare settings is uncertain. External validation in specific populations is required before clinical implementation. Methods This retrospective external validation study included Thai women who underwent colposcopy between 2022 and 2024 at a tertiary referral center. The primary outcome was histologically confirmed CIN2+/HSIL. Two previously published predictive models were applied without modifications. Model performance was evaluated in terms of discrimination using the area under the receiver operating characteristic curve (AUROC), calibration using calibration plots, calibration metrics, Brier scores, and clinical utility using a decision curve analysis. Results A total of 536 women were included, of whom 28.7% were diagnosed with CIN2+/HSIL. Despite differences in demographic characteristics, HPV genotype distribution, cytological findings, and colposcopic features compared to the original development cohorts, both models demonstrated robust performance in the Thai population. The Xue model showed excellent discrimination, with an AUROC of 0.85 (95% CI: 0.81–0.89), whereas the Sheng model demonstrated good discrimination, with an AUROC of 0.80 (95% CI: 0.77–0.85). At the optimal thresholds, the Xue model achieved a sensitivity of 77% and specificity of 82%, whereas the Sheng model achieved a sensitivity of 63% and specificity of 84%. Both models showed good calibration, with calibration slopes of 1.00, calibration-in-the-large of 0.00, and Brier scores of 0.127 and 0.147. Decision curve analysis demonstrated a positive net clinical benefit across the clinically relevant threshold probabilities. Conclusion Both predictive models showed good external validity and clinical utility in Thai colposcopy patients. These findings support individualized risk stratification in women with abnormal screening results for guiding clinical decisions.