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沃森肿瘤学决策系统在乳腺癌治疗一致性研究中的应用。

Watson for oncology decision system for treatment consistency study in breast cancer.

机构信息

Department of Surgical Oncology, General Hospital of Ningxia Medical University, Yinchuan, 750004, Ningxia, People's Republic of China.

Breast Disease Diagnosis and Treatment Center of Affiliated Hospital of Qinghai University, Affiliated Cancer Hospital of Qinghai University, Xining, 810000, People's Republic of China.

出版信息

Clin Exp Med. 2023 Sep;23(5):1649-1657. doi: 10.1007/s10238-022-00896-z. Epub 2022 Sep 22.

DOI:10.1007/s10238-022-00896-z
PMID:36138331
Abstract

The Watson for Oncology (WFO) decision system has been rolled out in many cancers. However, the consistency of treatment for breast cancer is still unclear in relatively economically disadvantaged areas. Patients with postoperative adjuvant stage (January 2017 to December 2017) and advanced-stage breast cancer (January 2014 to December 2018) in northwest of China were included in this study. Patient information was imported to make treatment decisions using Watson version 19.20 analysis and subsequently compared with clinician decisions and analyzed for influencing factors. A total of 263 patients with postoperative adjuvant breast cancer and 200 with advanced breast cancer were included in this study. The overall treatment modality for WFO was in 80.2% and 50.5% agreement with clinicians in the adjuvant and advanced-stage population, respectively. In adjuvant treatment after breast cancer surgery, menopausal status (odds ratio (OR) = 2.89, P = 0.012, 95% CI, 1.260-6.630), histological grade (OR = 0.22, P = 0.019, 95% CI, 0.061-0.781) and tumor stage (OR = 0.22, P = 0.042, 95% CI, 0.050-0.943) were independent factors affecting the concordance between the two stages. In the first-line treatment of advanced breast cancer, hormone receptor status was a factor influencing the consistency of treatment (χ = 14.728, P < 0.001). There was good agreement between the WFOs and clinicians' treatment decisions in postoperative adjuvant breast cancer, but poor agreement was observed in patients with advanced breast cancer.

摘要

沃森肿瘤学决策系统(WFO)已在多种癌症中得到推广。然而,在相对经济落后的地区,乳腺癌的治疗一致性仍不清楚。本研究纳入了中国西北地区术后辅助期(2017 年 1 月至 2017 年 12 月)和晚期乳腺癌(2014 年 1 月至 2018 年 12 月)的患者。将患者信息输入 Watson 版本 19.20 进行分析,随后与临床医生的决策进行比较,并分析影响因素。本研究共纳入 263 例术后辅助乳腺癌患者和 200 例晚期乳腺癌患者。WFO 的总体治疗方式与辅助期和晚期人群中临床医生的治疗方式一致,分别为 80.2%和 50.5%。在乳腺癌手术后的辅助治疗中,绝经状态(比值比(OR)=2.89,P=0.012,95%置信区间,1.260-6.630)、组织学分级(OR=0.22,P=0.019,95%置信区间,0.061-0.781)和肿瘤分期(OR=0.22,P=0.042,95%置信区间,0.050-0.943)是影响两者一致性的独立因素。在晚期乳腺癌的一线治疗中,激素受体状态是影响治疗一致性的因素(χ²=14.728,P<0.001)。WFO 与临床医生在术后辅助乳腺癌的治疗决策上有较好的一致性,但在晚期乳腺癌患者中则不一致。

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Real world study for the concordance between IBM Watson for Oncology and clinical practice in advanced non-small cell lung cancer patients at a lung cancer center in China.中国肺癌中心一项针对 IBM Watson 肿瘤与晚期非小细胞肺癌临床实践一致性的真实世界研究。
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