Nomogram for survival after primary surgery for bulky stage IIIC ovarian carcinoma

Abstract

5058 Background: Nomograms have been developed for numerous malignancies to predict a specific individual’s probability of long-term survival based on known prognostic factors. To date, no prediction model has been developed for patients with ovarian cancer. The objective of this study was to develop a nomogram to predict the probability of 4-year survival after primary cytoreductive surgery for bulky stage IIIC ovarian carcinoma. Methods: Nomogram predictor variables included age, tumor grade, histologic type, preoperative platelet count, the presence or absence of ascites, and residual disease status after primary cytoreduction. Disease-specific survival was estimated using the Kaplan-Meier method. Cox proportional hazards regression was used for multivariable analysis. The Cox model was the basis for the nomogram. The concordance index was used as an accuracy measure, with bootstrapping to correct for optimistic bias. Calibration plots were constructed. Results: A total of 462patients with bulky stage IIIC ovarian carcinoma underwent primary cytoreductive surgery at our institution during the study period of 1/89 to 12/03, of whom 397 were evaluable for inclusion in the study. The median age of the study population was 60 years (range 22–87). The primary surgeon in all cases was an attending gynecologic oncologist. Postoperatively, all patients received platinum-based systemic chemotherapy. Ovarian cancer-specific survival at 4 years was 51%. A nomogram was constructed on the basis of a Cox regression model and the 6 predictor variables. This nomogram was internally validated using bootstrapping and shown to have excellent calibration with a bootstrap-corrected concordance index of 0.67. Conclusions: A nomogram was developed to predict 4-year disease-specific survival after primary cytoreductive surgery for bulky stage IIIC ovarian carcinoma. The nomogram utilizes 6 predictor variables that are readily accessible, assigns a point value to each variable, and then predicts the probability of 4-year survival based on the total point value for an individual patient. This tool should be useful for patient counseling, clinical trial eligibility determination, postoperative management, and follow-up. No significant financial relationships to disclose.