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Updated: Aug 19, 2026
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Predicting poor prognosis recurrence in women with endometrial cancer: a nomogram developed by the FRANCOGYN study
Lobna Ouldamer1,2, Sofiane Bendifallah3,4, Gilles Body1,2
1Department of Gynecology, Centre Hospitalier Universitaire de Tours, Tours, France.
Background:
The purpose of this study was to develop a nomogram to predict 'poor prognosis recurrence' (PPR) in women treated for endometrial cancer (EC).
Methods:
The data of 861 women who received primary surgical treatment between January 2001 and December 2013 were abstracted from a prospective multicenter database. Data were randomly split into two sets: training and validation with a predefined 2/3 ratio. A Cox proportional hazards multivariate model of selected prognostic features was performed in the training cohort (n=574) to develop a nomogram predicting PPRs. The nomogram was validated in the validation cohort of 287 patients.
Results:
In the training cohort, 82 (14.3%) developed subsequent PPR. Age, histologic type and grade, lymphovascular space invasion status, FIGO stage, and nodal staging (SLN±pelvic and/or para-aortic lymphadenectomy) were independently associated with subsequent PPR. The nomogram showed an area under the receiver operating characteristic curve (AUC) of 0.82 (95% confidence interval (CI), 0.73-0.89) in the training set. The validation set showed a good discrimination with an AUC of 0.75 (95% CI, 0.65-0.83).
Conclusions:
We have developed a robust tool that is able to predict subsequent PPRs in women with FIGO I-III EC.
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