A preoperative prediction of lymph node metastasis in early cervical squamous cell cancer with hematologica - based model

Abstract

Background: This study aimed to construct a preoperative model predicting lymph node metastasis (LNM) in IB1-IIA2 stage cervical squamous cell cancer (CSCC) based on hematological indexes. Merhods: Between February 2011 and February 2022, 463 patients with IB1-IIA2 stage CSCC underwent radical resection. Patients were allocated to either a model-development cohort (n=337) or a validation cohort (n=126). The final model was determined by comparing different methods of variable selection, and then its discrimination and calibration metrics were evaluated. A predicted probability of LNM < 5% was defined as low risk. ROC curves were used to define high risk. Results: Age, lactate dehydrogenase level, FIGO stage, squamous cell carcinoma antigen, cancer antigen 125, and cancer antigen 199 were identified as critical factors for the construction of the model. The model demonstrated good discrimination and calibration (concordance index, 0.761; 95% confidence interval, 0.666-0.884). In the validation cohort the discrimination accuracy was 0.821 (95% confidence interval, 0.714 - 0.927). In the model-development cohort, 11.9% were classified as low risk with a negative predictive value of 95.0%, and 24.9% were classified as high risk with a positive predictive value of 39.3%. Conclusion: A predictive model was developed and validated for LNM in IB1-IIA2 stage CSCC. The model will assist physicians in appraising the risk of LNM in preoperative patients and could aid in patient counseling and individualized clinical decision-making.