ArticleInternational journal of women's health2025
High Grade Squamous Intraepithelial Lesion (HSIL) Positive Disease Risk Nomogram Model: A Single Centre Retrospective Analysis.
Article in International journal of women's health, 2025. 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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Abstract
Purpose: To develop and validate a nomogram for predicting high-grade squamous intraepithelial lesions or worse (HSIL+), incorporating results from ThinPrep cytologic test (TCT) and Aptima HPV E6/E7 mRNA (AHPV) testing. Patients and Methods: This diagnostic study consecutively enrolled 3,202 patients referred for colposcopy due to abnormal cervical screening results. All participants underwent colposcopy with biopsy (targeted and/or endocervical) to obtain a definitive histopathological result, which served as the reference standard. The cohort was randomly split into training (70%) and validation (30%) sets. A binary logistic regression model was developed, and a nomogram was constructed. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results: The final multivariate model was defined by the equation: Logit(P) = -4.014 + 1.677 × OHR + 2.917 × HPV16 + 1.938 × HPV18/45 + 2.343 × HPV(16+18/45) + 0.326 × ASC-US + 1.676 × ASC-H + 1.161 × LSIL + 1.593 × AGC + 4.939 × ≥HSIL. A nomogram was developed using the R rms package. The model demonstrated excellent discrimination in internal validation, with areas under the ROC curves (AUCs) of 0.843 (95% CI: 0.824-0.863) in the training set and 0.833 (95% CI: 0.813-0.873) in the validation set, along with good calibration. DCA confirmed its clinical utility across a risk threshold of 2%-50%. Conclusion: The developed logistic-nomogram provides an accurate and practical tool for predicting HSIL+, potentially aiding in individualized clinical management.
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