High Grade Squamous Intraepithelial Lesion (HSIL) Positive Disease Risk Nomogram Model: A Single Centre Retrospective Analysis.

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.