Development of a longitudinal two-biomarker algorithm for early detection of ovarian cancer in women with BRCA mutations

Objective. To develop a longitudinal algorithm combining two biomarkers, CA125 and HE4, for early detection of ovarian cancer in women with BRCA mutations. Methods. Women with BRCA mutations and intact ovaries were invited to participate in a novel ovarian cancer early detection prospective study. The Risk of Ovarian Cancer Algorithm (ROCA) identifying significant increases above each woman's baseline in serum CA125 and HE4 was performed every four months; abnormal risks triggered a subsequent ultrasound. The study first used a risk algorithm for only CA125, a second algorithm was developed for HE4 and finally a risk algorithm combining the two biomarkers was implemented. The ROCA strategy was compared to Standard of Care (SOC) surveillance strategy. Results. A total of 149 women enrolled in the ROCA arm while 43 women enrolled in the SOC arm. Abnormal scores were found in 24% of ROCA CA125 tests, 16% if ROCA CA125 or the novel ROCA HE4 were used independently and reduced to 8% using the new two-marker ROCA, significantly lower than the 15% of abnormal tests seen in the SOC arm (p = 0.042). The average false positive rate among women without ovarian cancer for two-marker ROCA for referral to ultrasound was 6.6% (specificity 93.4%), and for the two-marker ROCA plus ultrasound for referral to surgical consultation was 1.7% (specificity 98.3%). Conclusion. A newly developed two-marker ROCA administered every 4 months had lower call-back rates than SOC surveillance. Having established high specificity, the two-marker ROCA score deserves further evaluation for sensitivity in a larger trial. (C) 2020 Elsevier Inc. All rights reserved.