Concordance between treatment recommendations provided by IBM Watson for Oncology and a multidisciplinary tumor board for breast cancer in China. (18th May 2020)

• Record Type: Journal Article
• Authors: Zhao, Xiaoyao; Zhang, Yinbin; Ma, Xingcong; Chen, Yinxi; Xi, Junfeng; Yin, Xiaoran; Kang, Huafeng; Guan, Haitao; Dai, Zijun; Liu, Di; Zhao, Fang; Sun, Chu; Li, Zongfang; Zhang, Shuqun
• Is Part Of: Japanese journal of clinical oncology. Volume 50:Number 8(2020)
• Page Start: 852
• Page End: 858
• Publication Date: 2020-05-18
• Subjects: breast cancer -- Watson for Oncology -- artificial intelligence -- multidisciplinary tumor board -- treatment recommendation; Oncology -- Periodicals; Cancer -- Periodicals; 616.994005
• DOI: 10.1093/jjco/hyaa051
• Languages: English
• ISSNs: 0368-2811

Abstract

Abstract: Objective: Watson for Oncology (WFO), an artificial intelligence from IBM Corporation, can provide a treatment plan by analyzing patient's disease characteristics. The present study was performed to examine the concordance between treatment recommendations proposed by WFO and the multidisciplinary tumor board at our center. The aim was to explore the feasibility of using WFO for breast cancer cases in China and to ascertain the ways to make WFO more suitable for Chinese patients with breast cancer. Methods: Data from 302 breast cancer patients treated at the Second Affiliated Hospital of Xi'an Jiaotong University between October 2016 and February 2018 was retrieved and retrospectively analyzed by WFO. The recommendations were divided into 'recommended', 'considered' and 'not recommended' groups. Results were considered concordant when oncologists' recommendations were categorized as 'recommended' or 'for consideration' by WFO. Results: The concordance rate of 200 subjects with postoperative adjuvant therapy was 77%. However, the rate was 27.5% in the remaining 102 cases with metastatic disease receiving either first-line or no treatment. Further analysis demonstrated that inconsistencies were mainly due to different choices of chemotherapy regimens. Subgroup study indicates that tumor stage, receptor status and age also had influences at the concordance rate. Conclusion: The results of this study suggest that WFO is a promising artificial intelligence system for the treatment of breast cancer. These findings can also serve as a reference framework for the inclusion of artificial intelligence in the ongoing medical reform in China. Abstract : We examine the concordance between treatment recommendations for breast cancer by Watson for Oncology (WFO, artificial intelligence) and oncologists. WFO is a promising system for the treatment of breast cancer.