Molecular Scores to Predict Ovarian Cancer Outcomes: A Worthy Goal, but Not Ready for Prime Time

Abstract

Ovarian carcinoma has the highest mortality of all gynecological cancers. The American Cancer Society estimates that in 2012, about 22 280 new cases of ovarian cancer will be diagnosed, and 15 500 women will die of ovarian cancer in the United States (1). Despite achieving high rates of remission following radical surgery and platinum-based chemotherapy, most women relapse and ultimately die of chemoresistant disease. Advances in chemotherapy lengthen survival for women with advanced-stage (stages III and IV) disease but have not changed the likelihood of cure. Biomarkers, such as the rate of decline of serum cancer antigen 125 (CA-125, also known as mucin-16) level or the absolute CA-125 nadir, can be predictors of progression-free and overall survivals (2–4); however, when faced with a slowly declining level of CA-125 during primary treatment, the oncologist has few effective alternatives. With almost 80% of primary ovarian cancers initially responding to platinum-based therapy, a prospective biomarker would need to be highly predictive of treatment failure because alternative treatments would be purely experimental.