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Artificial intelligence and lung cancer treatment decision: agreement with recommendation of multidisciplinary tumor board.
Kim, Min-Seok; Park, Ha-Young; Kho, Bo-Gun; Park, Cheol-Kyu; Oh, In-Jae; Kim, Young-Chul; Kim, Seok; Yun, Ju-Sik; Song, Sang-Yun; Na, Kook-Joo; Jeong, Jae-Uk; Yoon, Mee Sun; Ahn, Sung-Ja; Yoo, Su Woong; Kang, Sae-Ryung; Kwon, Seong Young; Bom, Hee-Seung; Jang, Woo-Youl; Kim, In-Young; Lee, Jong-Eun; Jeong, Won-Gi; Kim, Yun-Hyeon; Lee, Taebum; Choi, Yoo-Duk.
Afiliação
  • Kim MS; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Park HY; Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Kho BG; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Park CK; Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Oh IJ; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Kim YC; Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Kim S; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Yun JS; Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Song SY; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Na KJ; Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Jeong JU; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Yoon MS; Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Ahn SJ; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Yoo SW; Department of Thoracic Surgery, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Kang SR; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Kwon SY; Department of Thoracic Surgery, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Bom HS; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Jang WY; Department of Thoracic Surgery, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Kim IY; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Lee JE; Department of Thoracic Surgery, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Jeong WG; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Kim YH; Department of Radiation Oncology, Chonnam National University Medical School, Gwangju, Republic of Korea.
  • Lee T; Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
  • Choi YD; Department of Radiation Oncology, Chonnam National University Medical School, Gwangju, Republic of Korea.
Transl Lung Cancer Res ; 9(3): 507-514, 2020 Jun.
Article em En | MEDLINE | ID: mdl-32676314
ABSTRACT

BACKGROUND:

IBM Watson for Oncology (WFO) is a cognitive computing system helping physicians quickly identify key information in a patient's medical record, surface relevant evidence, and explore treatment options. This study assessed the possibility of using WFO for clinical treatment in lung cancer patients.

METHODS:

We evaluated the level of agreement between WFO and multidisciplinary team (MDT) for lung cancer. From January to December 2018, newly diagnosed lung cancer cases in Chonnam National University Hwasun Hospital were retrospectively examined using WFO version 18.4 according to four treatment categories (surgery, radiotherapy, chemoradiotherapy, and palliative care). Treatment recommendations were considered concordant if the MDT recommendations were designated 'recommended' by WFO. Concordance between MDT and WFO was analyzed by Cohen's kappa value.

RESULTS:

In total, 405 (male 340, female 65) cases with different histology (adenocarcinoma 157, squamous cell carcinoma 132, small cell carcinoma 94, others 22 cases) were enrolled. Concordance between MDT and WFO occurred in 92.4% (k=0.881, P<0.001) of all cases, and concordance differed according to clinical stages. The strength of agreement was very good in stage IV non-small cell lung carcinoma (NSCLC) (100%, k=1.000) and extensive disease small cell lung carcinoma (SCLC) (100%, k=1.000). In stage I NSCLC, the agreement strength was good (92.4%, k=0.855). The concordance was moderate in stage III NSCLC (80.8%, k=0.622) and relatively low in stage II NSCLC (83.3%, k=0.556) and limited disease SCLC (84.6%, k=0.435). There were discordant cases in surgery (7/57, 12.3%), radiotherapy (2/12, 16.7%), and chemoradiotherapy (15/129, 11.6%), but no discordance in metastatic disease patients.

CONCLUSIONS:

Treatment recommendations made by WFO and MDT were highly concordant for lung cancer cases especially in metastatic stage. However, WFO was just an assisting tool in stage I-III NSCLC and limited disease SCLC; so, patient-doctor relationship and shared decision making may be more important in this stage.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: Transl Lung Cancer Res Ano de publicação: 2020 Tipo de documento: Article País de publicação: CHINA / CN / REPUBLIC OF CHINA

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Idioma: En Revista: Transl Lung Cancer Res Ano de publicação: 2020 Tipo de documento: Article País de publicação: CHINA / CN / REPUBLIC OF CHINA