Construction and validation of prognostic models for young cervical cancer patients: age stratification based on restricted cubic splines.

Cervical cancer (CC) ranks as the second highest cause of morbidity and mortality among young women; however, there are currently no age-specific definitions for young cervical cancer or prognostic models tailored to this demographic. Data on CC diagnosed between 2000 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Age stratification is based on the relationship between age and cancer-specific mortality, as demonstrated by restricted cubic spline analyses (RCS). Cox proportional hazards regression analyses were employed to identify independent prognostic factors in the young CC group. Two novel nomograms for this population were developed and validated using an external validation cohort obtained from a local hospital database, evaluated with concordance index (C-index) and calibration plots. Receiver operating characteristic (ROC) curves were utilized to compare the accuracy of the established models against the International Federation of Gynaecology and Obstetrics (FIGO) staging system (2018). A total of 27,658 patients from the SEER database were classified into three age groups (<36 years, 36-60 years, >60 years) based on RCS analyses, with 4,990, 16,922, and 5,746 patients in each group, respectively. The independent prognostic factors identified for young CC included stage, tumour size, grade, histologic type, and surgical intervention. The results of the C-index and calibration in both the training and validation sets confirmed that the two nomograms can accurately predict the occurrence and prognosis of young CC patients. The area under the curve (AUC) values indicated that these models demonstrated higher efficacy in predicting overall survival (OS) compared to the FIGO staging system (2018). These models could potentially serve as effective tools for clinicians to estimate the prognosis of young CC patients.