Development of a nomogram for predicting pelvic lymph node metastasis in cervical squamous cell carcinoma.

Objective: To develop and validate a nomogram for predicting pelvic lymph node metastasis (LNM) in cervical squamous cell carcinoma (SCC). Methods: This was a retrospective study that included 715 patients with cervical SCC who underwent radical hysterectomy and bilateral pelvic lymphadenectomy between 2009 and 2018. Logistic regression analysis was used to identify independent risk factors for pelvic LNM. Based on these risk factors, a nomogram predicting LNM risk was constructed and internally validated using the bootstrapping resampling method. Results: The rate of LNM in FIGO (the International Federation of Gynecology & Obstetrics) Stage IA2–IIA2 cervical SCC was 24.2%. In multivariate analysis, FIGO Stage II, moderately differentiated or poorly differentiated histology, abnormally elevated serum SCC‐antigen, and triglyceride were identified as independent risk factors for LNM. Tumor size greater than 2 cm and parametrial involvement had borderline significance. Ultimately, the nomogram contained the six variables mentioned above, showing positive calibration and positive discrimination. The area under the receiver operating characteristic curvewas 0.827 and the bootstrap‐validated C‐index was 0.827. The Youden index of this paper was 0.540. Conclusions: We developed and validated a nomogram to predict pelvic LNM in SCC based on clinical data, which can help physicians develop an optimal treatment strategy. Synopsis: We developed and validated a nomogram to predict pelvic lymph node metastasis in cervical squamous cell carcinoma based on clinical data. [ABSTRACT FROM AUTHOR]