Background Breast cancer oncologists are challenged to personalize care with rapidly changing scientific evidence, drug approvals, and treatment guidelines. Artificial intelligence (AI) 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 AI 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 and 2016 at the Manipal Comprehensive Cancer Center, Bengaluru, India. WFO provided treatment recommendations for the identical cases in 2016. A blinded second review was carried out 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 < 0.001) in all age groups compared with patients <45 years of age, except for the age group 55-64 years. Receptor status was not found to affect concordance. Conclusion Treatment recommendations made by WFO and the tumor board were highly concordant for breast cancer cases examined. Breast cancer stage and patient age had significant influence on concordance, while receptor status alone did not. This study demonstrates that the AI clinical decision-support system WFO may be a helpful tool for breast cancer treatment decision making, especially at centers where expert breast cancer resources are limited.

中文翻译：

---

沃森肿瘤学和乳腺癌治疗建议：与多学科肿瘤专家委员会达成协议。

背景技术乳腺癌肿瘤学家面临着通过快速变化的科学证据，药物批准和治疗指南来个性化护理的挑战。人工智能（AI）临床决策支持系统（CDSS）有潜力帮助应对这一挑战。我们在此报告检查AI CDSS沃森肿瘤学（WFO）和乳腺癌多学科肿瘤委员会之间提出的治疗建议之间的一致性（一致性）水平的结果。患者和方法在2014年至2016年之间，印度班加罗尔的Manipal综合癌症中心提供了638例乳腺癌的治疗建议。WFO在2016年为相同的病例提供了治疗建议。该中心的肿瘤委员会于2016年对所有未达成一致的病例进行了盲目第二次检查，考虑到2016年之前尚无可用的治疗方法和指南。如果WFO将肿瘤委员会的建议指定为“推荐”或“考虑”，则认为治疗建议是一致的。结果93％的乳腺癌患者发生了WFO与多学科肿瘤委员会之间的治疗一致性。亚组分析发现，患有I或IV期疾病的患者与患有II或III期疾病的患者相比，不太可能保持一致。人们发现，年龄的增长对和声有重大影响。与所有年龄组<45岁的患者相比，所有年龄组的一致性显着下降（P≤0.02; P <0.001），年龄在55-64岁之间的患者除外。未发现受体状态影响一致性。结论WFO和肿瘤委员会提出的治疗建议与所检查的乳腺癌病例高度一致。乳腺癌的分期和患者的年龄对一致性有重要影响，而单独的受体状态则没有。这项研究表明，AI临床决策支持系统WFO可能是乳腺癌治疗决策的有用工具，特别是在专家乳腺癌资源有限的中心。