Recurrence prediction is a cornerstone of patient management for borderline ovarian tumors. This study aimed to develop a nomogram predicting the recurrence probability in individual patients who had received primary surgical treatment.

This retrospective multicenter study included 186 patients with borderline ovarian tumor diagnosed from January 1980 through December 2008. A multivariate logistic regression analysis of selected prognostic features was performed and a nomogram to predict recurrence was constructed. The nomogram was internally validated.

The overall recurrence rate was 34.4% (64/186), with noninvasive and invasive forms in 29% (54/186) and 5.4% (10/186) of cases, respectively. International Federation of Gynecology and Obstetrics stage, age at diagnosis, histologic subtype, completeness of surgery, and type of surgery (radical vs fertility sparing) were associated with an increased risk of recurrence and were included in the nomogram. The predictive model had a concordance index of 0.78 (95% confidence interval, 0.76–0.80) and 0.77 (95% confidence interval, 0.75–0.79) before and after the 200 repetitions of bootstrap sample corrections, respectively, and showed good calibration.

Our results support the use of the present nomogram based on 5 clinical and pathological characteristics to predict recurrence probability with a high concordance, hence to inform patients on surgical management. External validation is required to recommend this nomogram in routine practice.