Conditional survival in ovarian cancer: Results from the SEER dataset 1988-2001

Mehee Choi, Clifton D. Fuller, Charles R. Thomas, Samuel J. Wang

Research output: Contribution to journalArticlepeer-review

103 Scopus citations

Abstract

Objectives: Survival statistics for patients with ovarian cancer are typically reported in terms of survival from time of diagnosis. For patients who have survived a period of time since diagnosis, however, conditional survival (CS) is a more clinically relevant measure, as it accounts for the changes in risk over time. The purpose of this study was to estimate CS for ovarian cancer patients through analysis of large-scale cancer registry data. Methods: Ovarian cancer cases were extracted from the Surveillance, Epidemiology, and End Results (SEER 17) database from the National Cancer Institute (NCI) for patients diagnosed between 1988-2001. Five-year relative CS calculations were performed with stratification by age, race, stage, histology, and grade for patients who had already survived up to 5 years from diagnosis. Results: The 5-year overall relative CS improved over time for up to 5 years after diagnosis for ovarian cancer patients. The largest gains in CS over time were seen for patients with advanced stage disease, poor grade, and serous and undifferentiated epithelioid histologies. For patients with stage IV disease, 5-year CS more than tripled over the first 5 years of surveillance (17%-56%). Among histological types, patients with undifferentiated epithelioid histology saw 5-year CS rise from 29% at diagnosis to 84% after 5 years. Conclusions: Prognosis improves over time for almost all groups of ovarian cancer patients. For ovarian cancer survivors, CS provides a more relevant measure of prognosis than conventional survival estimates that are made at the time of diagnosis.

Original languageEnglish (US)
Pages (from-to)203-209
Number of pages7
JournalGynecologic oncology
Volume109
Issue number2
DOIs
StatePublished - May 2008

Keywords

  • Epidemiologic methods
  • Ovarian cancer
  • Prognosis
  • Survival analysis

ASJC Scopus subject areas

  • Oncology
  • Obstetrics and Gynecology

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