Department of Breast Cancer, Academy of Military Medical Sciences, Beijing, People's Republic of China.
IBM Research, Yorktown Heights, NY.
JCO Clin Cancer Inform. 2020 Sep;4:824-838. doi: 10.1200/CCI.20.00018.
To examine the impact of a clinical decision support system (CDSS) on breast cancer treatment decisions and adherence to National Comprehensive Cancer Center (NCCN) guidelines.
A cross-sectional observational study was conducted involving 1,977 patients at high risk for recurrent or metastatic breast cancer from the Chinese Society of Clinical Oncology. Ten oncologists provided blinded treatment recommendations for an average of 198 patients before and after viewing therapeutic options offered by the CDSS. Univariable and bivariable analyses of treatment changes were performed, and multivariable logistic regressions were estimated to examine the effects of physician experience (years), patient age, and receptor subtype/TNM stage.
Treatment decisions changed in 105 (5%) of 1,977 patients and were concentrated in those with hormone receptor (HR)-positive disease or stage IV disease in the first-line therapy setting (73% and 58%, respectively). Logistic regressions showed that decision changes were more likely in those with HR-positive cancer (odds ratio [OR], 1.58; < .05) and less likely in those with stage IIA (OR, 0.29; < .05) or IIIA cancer (OR, 0.08; < .01). Reasons cited for changes included consideration of the CDSS therapeutic options (63% of patients), patient factors highlighted by the tool (23%), and the decision logic of the tool (13%). Patient age and oncologist experience were not associated with decision changes. Adherence to NCCN treatment guidelines increased slightly after using the CDSS (0.5%; = .003).
Use of an artificial intelligence-based CDSS had a significant impact on treatment decisions and NCCN guideline adherence in HR-positive breast cancers. Although cases of stage IV disease in the first-line therapy setting were also more likely to be changed, the effect was not statistically significant ( = .22). Additional research on decision impact, patient-physician communication, learning, and clinical outcomes is needed to establish the overall value of the technology.
研究临床决策支持系统（CDSS）对乳腺癌治疗决策和遵循国家综合癌症网络（NCCN）指南的影响。
本研究是在中国临床肿瘤学会（CSCO）的参与下，对 1977 例高危复发性或转移性乳腺癌患者进行的一项横断面观察性研究。10 位肿瘤学家在查看 CDSS 提供的治疗方案之前和之后，为平均 198 例患者提供了盲法治疗建议。对治疗方案的改变进行了单变量和双变量分析，并进行了多变量逻辑回归分析，以检查医生经验（年）、患者年龄和受体亚型/TNM 分期的影响。
1977 例患者中有 105 例（5%）的治疗决策发生了变化，主要集中在一线治疗中激素受体（HR）阳性疾病或 IV 期疾病的患者（分别为 73%和 58%）。逻辑回归显示，HR 阳性癌症患者的决策变化更有可能（优势比[OR]，1.58；<.05），而 IIA 期（OR，0.29；<.05）或 IIIA 期癌症患者的决策变化可能性更小（OR，0.08；<.01）。变化的原因包括考虑 CDSS 的治疗选择（63%的患者）、工具突出的患者因素（23%）和工具的决策逻辑（13%）。患者年龄和肿瘤医生的经验与决策变化无关。使用 CDSS 后，NCCN 治疗指南的遵循率略有提高（0.5%；<.003）。
使用基于人工智能的 CDSS 对 HR 阳性乳腺癌的治疗决策和 NCCN 指南的遵循有显著影响。虽然一线治疗中 IV 期疾病的病例更有可能发生变化，但差异无统计学意义（=0.22）。需要进一步研究决策的影响、医患沟通、学习和临床结果，以确定该技术的整体价值。
