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Updated: Jan 30, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Nomogram for Predicting Individual Survival After Recurrence of Advanced-Stage, High-Grade Ovarian Carcinoma
Peter G Rose1, James J Java, Ritu Salani
1Cleveland Clinic Foundation and Case Western Reserve University, Cleveland, Ohio; NRG Oncology Statistics and Data Management Center, Roswell Park Cancer Institute, Buffalo, New York; The Ohio State University, Columbus, Ohio; the University of Minnesota, Minneapolis, Minnesota; Duke University Hospital; Durham, North Carolina; the University of California at Irvine, Orange, California; the University of Iowa Hospital, Iowa City, Iowa; Washington University in St. Louis School of Medicine, St. Louis, Missouri; ANZGOG, Australia-New Zealand Gynaecological Oncology Group, Sydney, Australia; the University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Community Health Network and Indiana University School of Medicine, Indianapolis, Indiana; Walter Reed Army Medical Center; Bethesda, Maryland; Tacoma General Hospital, Tacoma, Washington; Moffitt Cancer Center, Tampa, Florida; the University of Colorado School of Medicine at Denver, Aurora, Colorado; Cancer Treatment Centers of America, Philadelphia Pennsylvania; NYU Clinical Cancer Center, New York, New York; Johns Hopkins University/Sidney Kimmel Cancer Center, Baltimore, Maryland; US Oncology Research, Arizona Oncology, Tucson, Arizona; the University of Pennsylvania Medical Center, Philadelphia, Pennsylvania; and The Ohio State University Medical Center, Columbus, Ohio.
Objective:
To analyze clinical prognostic factors for survival after recurrence of high-grade, advanced-stage ovarian-peritoneal-tubal carcinoma and to develop a nomogram to predict individual survival after recurrence.
Methods:
We retrospectively analyzed patients treated in multicenter Gynecologic Oncology Group protocols for stage III and IV ovarian-peritoneal-tubal carcinoma who underwent primary debulking surgery, received chemotherapy with paclitaxel and a platinum compound, and subsequently developed recurrence. Prognostic factors affecting survival were identified and used to develop a nomogram, which was both internally and externally validated.
Results:
There were 4,739 patients included in this analysis, of whom, 84% had stage III and 16% had stage IV ovarian carcinoma. At a median follow-up of 88.8 months (95% CI 86.2-92.0 months), the vast majority of patients (89.4%) had died. The median survival after recurrence was 21.4 months (95% CI 20.5-21.9 months). Time to recurrence after initial chemotherapy, clear cell or mucinous histology, performance status, stage IV disease, and age were significant variables used to develop a nomogram for survival after recurrence, which had a concordance index of 0.67. The time to recurrence alone accounted for 85% of the prognostic information. Similar results were found for patients who underwent second look laparotomy and had a complete pathologic response or received intraperitoneal chemotherapy.
Conclusion:
For individuals with advanced-stage ovarian carcinoma who recur after standard first-line therapy, estimated survivals after recurrence are closely related to the time to recurrence after chemotherapy and prognostic variables can be used to predict subsequent survival.
Clinical Trial Registration:
ClinialTrials.gov, NCT00002568, NCT00837993, NCT00002717, NCT01074398, and NCT00011986.
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