Objective: The aim of this study was to develop a nomogram for predicting the 5-year disease-free survival (DFS) after radical hysterectomy for early-stage cervical cancer.
Patients and methods: An institutional database of 275 consecutive patients treated at Seoul National University Hospital for stage I to stage IIA cervical cancer was used to develop a nomogram based on Cox proportional hazards regression model. The developed nomogram was internally validated with bootstrapping, and performance was assessed by concordance index and a calibration curve. External validation was also performed using an independent data set of patients from Asan Medical Center.
Results: From Cox regression analysis, disease stage, number of positive lymph nodes, parametrial involvement, and depth of invasion were identified as independent risk factors for disease recurrence (P < 0.05). The nomogram incorporating these factors appeared to be accurate and predicted the outcomes better than the International Federation of Gynecology and Obstetrics stage alone (concordance index, 0.858 compared with 0.719; P = 0.001). When applied to a separate validation set, the nomogram also showed similar predictive accuracy (concordance index, 0.879).
Conclusion: We have developed a nomogram that can predict the recurrence risk in patients with early-stage cervical cancer after surgery, which was internally and externally validated.