학술논문

Double-Blind Concordance Study Of Breast Cancer Treatment Recommendations Between Multidisciplinary Tumour Board And An Artificial Intelligence Advisor-Watson For Oncology.
Document Type
Article
Source
Journal of Cancer Research & Therapeutics. 2017 Supplement, Vol. 13, pS100-S100. 1/5p.
Subject
*BREAST cancer
*CANCER treatment
*ARTIFICIAL intelligence
*ONCOLOGY
*CONCORDANCES
Language
ISSN
0973-1482
Abstract
Background: Breast cancer oncologists are challenged to personalize care with rapidly changing scientific evidence, drug approvals, and treatment guidelines. Cognitive clinical decision-support systems (CDSSs) have the potential to help address this challenge. We report here the results of examining the level of agreement (concordance) between treatment recommendations made by the cognitive CDSS Watson for Oncology (WFO) and a multidisciplinary tumor board for breast cancer. Patients and methods: Treatment recommendations were provided for 638 breast cancers between 2014-2016 at the Manipal Comprehensive Cancer Center, Bengaluru, India. WFO provided treatment recommendations for the identical cases in 2016. A blinded second review was performed by the center's tumor board in 2016 for all cases in which there was not agreement, to account for treatments and guidelines not available before 2016. Treatment recommendations were considered concordant if the tumor board recommendations were designated "recommended" or "for consideration" by WFO. Results: Treatment concordance between WFO and the multidisciplinary tumor board occurred in 93% of breast cancer cases. Subgroup analysis found that patients with stage I or IV disease were less likely to be concordant than patients with stage II or III disease. Increasing age was found to have a major impact on concordance. Concordance declined significantly (p?0.02; p. [ABSTRACT FROM AUTHOR]