Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Department of Thoracic surgery, Yulin City First Hospital Yulin Branch, Yulin, Shaanxi, China.
Jpn J Clin Oncol. 2020 Aug 4;50(8):852-858. doi: 10.1093/jjco/hyaa051.
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.
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.
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.
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.
Watson for Oncology（WFO）是 IBM 公司开发的人工智能，能够通过分析患者的疾病特征提供治疗方案。本研究旨在检验 WFO 提出的治疗建议与本中心多学科肿瘤委员会之间的一致性，探索在中国使用 WFO 治疗乳腺癌病例的可行性，并确定使 WFO 更适合中国乳腺癌患者的方法。
检索并回顾性分析了 2016 年 10 月至 2018 年 2 月西安交通大学第二附属医院收治的 302 例乳腺癌患者的数据。根据 WFO 建议将患者分为“推荐”“考虑”和“不推荐”三组。当 WFO 将肿瘤学家的建议归类为“推荐”或“考虑”时，结果被认为是一致的。
200 例接受术后辅助治疗患者的一致性率为 77%。然而，102 例转移性疾病患者（接受一线或无治疗）的一致性率仅为 27.5%。进一步分析表明，不一致主要是由于化疗方案的选择不同。亚组研究表明，肿瘤分期、受体状态和年龄也对一致性率有影响。
本研究结果表明，WFO 是治疗乳腺癌的一种很有前途的人工智能系统。这些发现还可以为中国正在进行的医疗改革中纳入人工智能提供参考框架。
