Nomogram for survival after primary surgery for bulky stage IIIC ovarian carcinoma. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: 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, only one prediction model has been reported for patients with epithelial ovarian carcinoma (EOC). The objective of this study was to develop a more accurate survival nomogram for patients with bulky stage IIIC EOC. PATIENTS AND METHODS: Nomogram predictor variables included age, tumor grade, histologic type, preoperative platelet count, ascites, and residual disease after primary cytoreduction. Disease-specific survival was estimated by the Kaplan-Meier method. Cox proportional hazards regression was used for multivariate analysis, which was the basis for the nomogram. The concordance index was used as an accuracy measure with bootstrapping to correct for optimistic bias. RESULTS: A total of 424 evaluable patients with bulky stage IIIC EOC underwent primary surgery at our institution during the study period of 1/89 to 12/03. All patients received postoperative platinum-based systemic chemotherapy. EOC-specific survival at 5 years was 51%. Using the six predictor variables, a nomogram was constructed and internally validated using bootstrapping. It was shown to have excellent calibration with a bootstrap corrected concordance index of 0.67, which was more accurate in predicting survival at this stage than the previously published model (concordance index=0.53). CONCLUSION: Utilizing six readily accessible predictor variables, our nomogram more accurately predicted 5-year disease-specific survival for bulky stage IIIC EOC than the previously published model. This tool may be useful for patient counseling, determination of clinical trial eligibility, and postoperative management.

publication date

  • October 24, 2007

Research

keywords

  • Nomograms
  • Ovarian Neoplasms

Identity

Scopus Document Identifier

  • 37349005470

PubMed ID

  • 17950784

Additional Document Info

volume

  • 108

issue

  • 1