Construction of a nomogram model for predicting residual or recurrent cervical intraepithelial neoplasia after the
Yuehong Tong, Lili Xu1, Yiqun Sun1
1Department of Gynecology, Jinhua Maternal and Child Health Care Hospital, Jinhua, Zhejiang, China.
Objective:
To investigate the predictive value of the neutrophil-to-high-density lipoprotein ratio (NHR) for residual or recurrent cervical intraepithelial neoplasia (CIN) after a loop electrosurgical excision procedure (LEEP) and to develop a nomogram model with multiple variables for identifying high-risk patients.
Methods:
A retrospective cohort of 282 patients with CIN treated by LEEP was analyzed. Clinical, laboratory, and follow-up data were collected. Univariate and multivariate logistic regression were used to find independent risk factors, and a nomogram model was constructed. The model's discrimination, calibration, and clinical utility were evaluated by the receiver operating characteristic curve, Hosmer-Lemeshow test, calibration curve, and decision curve analysis.
Results:
Among 282 patients, 44 (15.6%) had residual or recurrent CIN. Multivariate analysis found CIN grade 3, positive surgical margins, elevated fibrinogen levels, and increased NHR as independent risk factors. The NHR had good sensitivity and specificity in predicting post-LEEP residual or recurrent CIN. The nomogram model had an area under the curve of 0.858. Calibration plots and the Hosmer-Lemeshow test showed good fit, and decision curve analysis suggested net clinical benefit and applicability.
Conclusions:
The NHR, combined with fibrinogen, CIN grading, and margin status, can predict residual or recurrent CIN after LEEP. The nomogram model can guide high-risk patients' postoperative management. Prospective validation in large cohorts is needed.
