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Ovarian Cancer Screening: Development of the Risk of Ovarian Cancer Algorithm (ROCA) and ROCA Screening Trials
  1. Steven J. Skates, PhD
  1. Massachusetts General Hospital and Harvard Medical School, Boston, MA.
  1. Address correspondence and reprint requests to Steven J. Skates, PhD, Massachusetts General Hospital and Harvard Medical School, Suite 560, 50 Staniford St, Boston, MA 02114. E-mail: sskates@gmail.com.

Abstract

Abstract Ovarian cancer is most often detected in late stage when prognosis is poor; in contrast, prognosis is excellent when detection occurs in early stage. Early detection with regular biomarker tests may reduce disease-specific mortality. Two screening trials with annual CA125 greater than 35 U/mL demonstrated promise. Before undertaking larger trials, statistical analyses of serial CA125 levels showed each woman has her own baseline level; and in ovarian cancer cases, CA125 rose rapidly from her baseline after a change point. Improved early detection of ovarian cancer may result if each woman were tested for the presence of a change-point CA125 profile. Using the serial CA125 from the completed trials, a statistical method was developed to measure the probability a change-point had occurred. Subsequent screening trials implemented the risk of ovarian cancer algorithm (ROCA) in which screening decisions are made based on the risk of having a change point. Development of ROCA is described, and ROCA trials are listed.

  • Longitudinal CA125
  • ROCA
  • Early detection
  • Ovarian cancer

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Footnotes

  • Dr. Skates was supported by NCI’s Early Detection Research Network grant U01-CA152990, USPTO patent, and by the Julie Fund at the Massachusetts General Hospital.

  • The authors declare that there are no conflicts of interest.

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