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Research Article: Analysis of prognostic factors in patients with locally advanced cervical squamous cell carcinoma and development of a nomogram prediction model

Date Published: 2026-09-10

Abstract:
To develop and validate a predictive model integrating patient demographics and clinical data for estimating 3-, 4-, and 5-year overall survival in patients with locally advanced cervical squamous cell carcinoma (LACSC). Clinical data from 670 LACSC patients at Shanxi Cancer Hospital were collected and then randomly assigned to a training cohort and an internal validation cohort at a 6:4 ratio by stratified sampling. Independent prognostic factors were identified using LASSO regression and multivariate Cox regression analysis, with which a predictive model was constructed. Model performance was assessed using the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration curves. Clinical utility was evaluated via decision curve analysis (DCA). A robust prognostic model was developed and visualized as a nomogram comprising six variables: NEUT, MONO, CA125, SII, lymph node metastasis status, and treatment modality. Patients were stratified into high- and low-risk groups based on the median risk score in the training cohort. The high-risk group exhibited significantly poorer overall survival (OS) in both cohorts ( P < 0.05). A clinical predictive model was established to estimate 3-, 4-, and 5-year survival rates for LACSC patients.

Introduction:
Cervical cancer is the fourth most common cancer among women worldwide, posing a major threat to women’s health ( 1 ). A major breakthrough in past research was the identification of persistent HPV infection as the etiological cause of the disease. A synthesis of virological, molecular, and clinical epidemiological studies provides clear evidence that cervical cancer arises from long-term, unresolved infection with specific HPV genotypes ( 2 ). Histologically, cervical cancer is classified into squamous cell…

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