Objective: The aim of this study was to construct a prognostic index that predicts risk of
relapse in women who have completed first-line treatment for ovarian cancer (OC).
Methods: A database of OC cases from 2000 to 2010 was interrogated for International
Federation of Gynecology and Obstetrics stage, grade and histological subtype of cancer,
preoperative and posttreatment CA-125 level, presence or absence of residual disease after
cytoreductive surgery and on postchemotherapy computed tomography scan, and time to
progression and death. The strongest predictors of relapse were included into an algorithm,
the Risk of Ovarian Cancer Relapse (ROVAR) score.
Results: Three hundred fifty-four cases of OC were analyzed to generate the ROVAR
score. Factors selected were preoperative serum CA-125, International Federation of
Gynecology and Obstetrics stage and grade of cancer, and presence of residual disease at
posttreatment computed tomography scan. In the validation data set, the ROVAR score had a
sensitivity and specificity of 94% and 61%, respectively. The concordance index for the
validation data set was 0.91 (95% confidence interval, 0.85-0.96). The score allows patient
stratification into low (G0.33), intermediate (0.34Y0.67), and high (90.67) probability of
relapse.
Conclusions: The ROVAR score stratifies patients according to their risk of relapse
following first-line treatment for OC. This can broadly facilitate the appropriate tailoring of
posttreatment care and support.