3762 - Clinical Characteristics and Prognostic Nomogram for Different Metastatic Patterns in Cervical Cancer
Presenter(s)
W. Chen, C. Liu, and S. Li; Department of Radiotherapy, Gynecology, Clinical Oncology School of Fujian Medical University, FujianCancer Hospital, Fuzhou, China, Fuzhou, China, China
Purpose/Objective(s): Metastatic cervical cancer (metastatic CC) exhibits high heterogeneity. This study aims to characterize clinical features across different metastatic patterns, assess their impact on overall survival (OS), and construct a clinicopathological-based nomogram to facilitate risk stratification and individualized treatment.
Materials/Methods: A retrospective cohort study was conducted on metastatic CC patients in our hospital from 2013 to 2021. Patients were categorized into four patterns: distant lymph node metastasis only (DLN-only), visceral metastasis only (Visceral-only), combined distant lymph node and visceral metastasis (Both), and regional bulk invasion only (RB-only). OS was the primary endpoint. Survival curves were analyzed using the Kaplan–Meier method and log-rank tests. Independent prognostic factors were identified via univariate and multivariate Cox proportional hazards models. A nomogram was developed to predict 1-, 2-, and 3-year OS. Model performance was validated using the C-index, time-dependent ROC curves (AUC), calibration curves, and decision curve analysis (DCA).
Results: A total of 207 patients were included with a median follow-up of 68 months (95% CI: 62–91). OS differed significantly across metastatic patterns (P < 0.05), with the "Both" group (DLN + Visceral) exhibiting the worst prognosis. Multivariate Cox analysis identified metastatic pattern, tumor size, histological type, and treatment modality as independent prognostic factors (all P < 0.05). The constructed nomogram demonstrated robust predictive power with a C-index of 0.728. The AUC values for 1-, 2-, and 3-year OS were 0.794, 0.763, and 0.811, respectively. Calibration curves showed high consistency between predicted and observed outcomes, and DCA confirmed the model's clinical utility.
Conclusion: Metastatic patterns are critical prognostic indicators for metastatic CC. The developed nomogram provides an accurate tool for survival prediction, supporting risk-stratified management and personalized therapeutic decisions in clinical practice.