A review of gynecological cancers studies of concordance with individual clinicians or multidisciplinary tumor boards for an artificial intelligence-based clinical decision-support system.

Abstract

e14070 Background: Watson for Oncology (WfO) is an artificial intelligence-based clinical decision-support system that offers potential therapeutic options to cancer-treating physicians. We reviewed studies of concordance between therapeutic options offered by WfO and treatment decisions made by individual clinicians (IC) and multidisciplinary tumor boards (MTB) in practice in gynecological cancers. Methods: We searched PubMed and an internal database to identify peer-reviewed WfO concordance studies of gynecological cancers published between 01/01/2015 and 06/30/2019. Concordance was defined as agreement between therapeutic options recommended or offered for consideration by WfO and treatment decisions made by IC or MTB. Mean concordance was calculated as a weighted average based on the number of patients per study. Statistical significance was evaluated by z-test of two proportions. Results: Our search identified 5 retrospective studies with 635 patients with cervical and ovarian cancers in China and Thailand; 4 compared WfO to MTB and 1 to IC. Overall WfO concordance with MTB and IC for both cancers was 77.2% (SD 11.6%). The concordance between MTB and WfO in cervical and ovarian cancers was 80.5% and 86.2%, respectively ( P = .21); IC concordance with WfO in cervical and ovarian cancers was 65.2% and 73.2%, respectively ( P = .18). MTB concordance with WfO for both cancers combined was 81.5%, significantly higher than the 67.9% IC concordance with WfO for both cancers ( P = .01). Conclusions: Studies of cervical and ovarian cancers demonstrated a statistically significantly higher concordance of MTB and WfO than IC and WFO, suggesting a role for WfO in supporting treatment-decision making in gynecological cancers that aligns with decisions made by MTB. Larger prospective studies are needed to evaluate the technical performance, usability, workflow integration, and clinical impact of WfO in gynecological cancers.[Table: see text]