Assessment of published models and prognostic variables in epithelial ovarian cancer at Mayo Clinic

Andrea E Wahner Hendrickson, Kieran M. Hawthorne, Ellen L Goode, Kimberly R. Kalli, Krista M. Goergen, Jamie N Bakkum-Gamez, William Arthur Cliby, Gary Keeney, Daniel W Visscher, Yaman Tarabishy, Ann L Oberg, Lynn C. Hartmann, Matthew J. Maurer

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

Objectives: Epithelial ovarian cancer (EOC) is an aggressive disease in which first line therapy consists of a surgical staging/debulking procedure and platinum based chemotherapy. There is significant interest in clinically applicable, easy to use prognostic tools to estimate risk of recurrence and overall survival. In this study we used a large prospectively collected cohort of women with EOC to validate currently published models and assess prognostic variables. Methods: Women with invasive ovarian, peritoneal, or fallopian tube cancer diagnosed between 2000 and 2011 and prospectively enrolled into the Mayo Clinic Ovarian Cancer registry were identified. Demographics and known prognostic markers as well as epidemiologic exposure variables were abstracted from the medical record and collected via questionnaire. Six previously published models of overall and recurrence-free survival were assessed for external validity. In addition, predictors of outcome were assessed in our dataset. Results: Previously published models validated with a range of c-statistics (0.587-0.827), though application of models containing variables which are not part of routine practice were somewhat limited by missing data; utilization of all applicable models and comparison of results are suggested. Examination of prognostic variables identified only the presence of ascites and ASA score to be independent predictors of prognosis in our dataset, albeit with marginal gain in prognostic information, after accounting for stage and debulking. Conclusions: Existing prognostic models for newly diagnosed EOC showed acceptable calibration in our cohort for clinical application. However, modeling of prospective variables in our dataset reiterates that stage and debulking remains the most important predictors of prognosis in this setting.

Original languageEnglish (US)
JournalGynecologic Oncology
DOIs
StateAccepted/In press - Dec 2 2014

Keywords

  • Model
  • Nomogram
  • Ovarian
  • Prognostic
  • Validation

ASJC Scopus subject areas

  • Obstetrics and Gynecology
  • Oncology

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