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

Area of Science:

• Gynecology
• Oncology
• Diagnostic Pathology

Background:

• Cervical cancer screening relies on cytology and HPV testing to detect precancerous lesions.
• Accurate prediction of high-grade squamous intraepithelial lesions or worse (HSIL+) is crucial for timely intervention.
• Existing prediction models may not fully integrate combined cytologic and HPV mRNA test results.

Purpose of the Study:

• To develop and validate a nomogram for predicting HSIL+.
• To incorporate ThinPrep cytologic test (TCT) and Aptima HPV E6/E7 mRNA (AHPV) testing results into the predictive model.
• To provide a practical tool for clinicians managing patients with abnormal cervical screening results.

Main Methods:

• A diagnostic study enrolled 3,202 patients referred for colposcopy.
• A binary logistic regression model was developed and a nomogram constructed using training (70%) and validation (30%) sets.
• Model performance was assessed using ROC curves, calibration plots, and decision curve analysis (DCA).

Main Results:

• The final multivariate model included various cytologic results and HPV types.
• The nomogram demonstrated excellent discrimination with AUCs of 0.843 (training) and 0.833 (validation).
• Good calibration and clinical utility across a wide risk threshold (2%-50%) were confirmed by DCA.

Conclusions:

• The developed logistic-nomogram is an accurate and practical tool for predicting HSIL+.
• This nomogram can aid in the individualized clinical management of patients with abnormal cervical screening.
• Integration of TCT and AHPV testing enhances predictive accuracy for cervical precancerous lesions.