Evidence map›Paper›PMID 42237140›Full record

ArticleBMC cancer2026

External validation of predictive models for high-grade cervical lesions in Thai women undergoing colposcopy: a retrospective external validation study.

Atikom Eidbur, Thiti Atjimakul

Abstract readValidation Study
In one paragraph

Article in BMC cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Atikom EidburDepartment of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand.
Thiti AtjimakulDepartment of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand. thitiatjimakul@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPredictive 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.

methodsThis 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 any 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 decision curve analysis.

resultsA 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 good performance in the Thai population. The Xue model demonstrated good discrimination, with an AUROC of 0.82 (95% CI: 0.77-0.86), whereas the Sheng model demonstrated good discrimination, with an AUROC of 0.80 (95% CI: 0.77-0.85). Both models showed acceptable calibration. The Xue model had a calibration-in-the-large of 0.03 (95% CI: -0.22 to 0.28) and a calibration slope of 0.77 (95% CI: 0.64-0.91), indicating mild overfitting that may benefit from recalibration. The Sheng model showed good calibration, with a slope of 0.88 (95% CI: 0.68-1.08) and a calibration-in-the-large of 0.17 (95% CI: -0.05 to 0.38). Brier scores were 0.148 and 0.163, respectively. Decision curve analysis demonstrated a positive net clinical benefit across clinically relevant threshold probabilities. At the original model-specific predefined probability thresholds, the Xue model achieved a sensitivity of 56.5% and specificity of 93.7%, whereas the Sheng model achieved a sensitivity of 93.5% and specificity of 34.3%, demonstrating a marked trade-off that highlights the importance of threshold selection.

conclusionsBoth predictive models showed good external validity and clinical utility in Thai patients undergoing colposcopy. These findings support individualized risk stratification in women with abnormal screening results to guide clinical decisions.

Indexed as

ColposcopyUterine Cervical DysplasiaUterine Cervical NeoplasmsAdultFemaleHuman Papillomavirus VirusesHumansMiddle AgedPapillomavirus InfectionsRetrospective StudiesROC CurveThailandCervical Intraepithelial NeoplasiaColposcopyHuman PapillomavirusPredictive Value of TestsRisk AssessmentValidation Studies as Topic

Identifiers

PMID42237140
PMCPMC13455249

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.