Modified panel-based genetic counseling for ovarian cancer susceptibility: A randomized non-inferiority study

Objective. Genetic testing identifies cancer patients who may benefit from targeted treatment and allows for enhanced cancer screening and risk-reduction in their at-risk relatives. Traditional models of genetic counseling (GC) cannot meet the increasing demand and urgency for genetic testing. The objective of this study was to evaluate a new model of service delivery to improve the efficiency of pre-test GC for panel-based genetic testing. Methods. A parallel, two-armed, randomized non-inferiority study compared traditional and modified pretest GC models (1:2) prior to panel-based genetic testing. Participants were adult females, whose first-degree relative died of serous ovarian cancer. In the modified group, participants were emailed a 20-minute presentation prior to a scheduled pre-test GC telephone call. Psychosocial and knowledge questionnaires were provided at baseline (P1) and one week after pre-test GC (P2). Results. 382 women completed pre-test GC (256 modified, 126 traditional). There were no differences in marital status, education level or household income. Pre-test GC time was shorter in the modified group (average 19 vs. 46 min, p < 0.001), with no difference in post-test GC time (average 16 min each, p = 0.78). The modified pretest GC model was found to be non-inferior to traditional GC on measures of cancer-specific distress, depression, anxiety, decisional conflict, ovarian cancer knowledge and satisfaction. Perceived lifetime risk for ovarian cancer decreased to a lesser extent from baseline in women who received modified pre-test GC. Conclusions. A 20-minute presentation prior to pre-test telephone GC is non-inferior to traditional in-person GC on all variables tested, except for perceived ovarian cancer risk. This modified model improved GC efficiency without negatively affecting psychosocial outcomes, providing an alternative strategy to meet the growing demand for genetic testing. (C) 2019 Elsevier Inc. All rights reserved.