The New Scoring System for Predicting Positive Surgical Margins of High-grade Cervical Intraepithelial Neoplasia after Loop Electrosurgical Excision Procedure
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Abstract
Objectives: To develop prediction score for positive surgical margins after loop electrosurgical excision procedure (LEEP) in women with high-grade cervical intraepithelial neoplasia.
Materials and Methods: A diagnostic predictive model study was conducted during January 2025 to December 2026. Medical records of women with histologically confirmed cervical intraepithelial neoplasia 2/3 who underwent primary LEEP at HRH Princess Maha Chakri Sirindhorn Medical Center were reviewed between January 2017 and December 2023. Independent predictors identified by multivariable logistic regression were converted into a risk score based on regression coefficients. Model performance was assessed using area under the curve (AUC), calibration belt, and bootstrap internal validation.
Results: A total of 207 women were included. Four independent predictors were incorporated into the final model: endocervical gland involvement, transformation zone type, high-grade cytology, and cone depth. The total score ranged from 0 to 7. At a cutoff score of ≥ 4, the model yielded a sensitivity of 83.18%, specificity of 58%, positive predictive value of 67.9%, and negative predictive value of 76.3%. The model showed acceptable discrimination with AUC of 0.739 (95% confidence interval 0.672-0.807), with satisfactory calibration and good internal validity following bootstrap validation.
Conclusion: The prediction model can assist clinicians in estimating positive margin risk and optimizing surgical planning.
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