Artificial intelligence and lung cancer treatment decision: agreement with recommendation of multidisciplinary tumor board

Min-Seok Kim; Ha-Young Park; Bo-Gun Kho; Cheol-Kyu Park; In-Jae Oh; Young-Chul Kim; Seok Kim; Ju-Sik Yun; Sang-Yun Song; Kook-Joo Na; Jae-Uk Jeong; Mee Sun Yoon; Sung-Ja Ahn; Su Woong Yoo; Sae-Ryung Kang; Seong Young Kwon; Hee-Seung Bom; Woo-Youl Jang; In-Young Kim; Jong-Eun Lee; Won-Gi Jeong; Yun-Hyeon Kim; Taebum Lee; Yoo-Duk Choi

doi:10.21037/tlcr.2020.04.11

Artificial intelligence and lung cancer treatment decision: agreement with recommendation of multidisciplinary tumor board

Transl Lung Cancer Res. 2020 Jun;9(3):507-514. doi: 10.21037/tlcr.2020.04.11.

Authors

Min-Seok Kim^{1

2}, Ha-Young Park^{1

2}, Bo-Gun Kho^{1

2}, Cheol-Kyu Park^{1

2}, In-Jae Oh^{1

2}, Young-Chul Kim^{1

2}, Seok Kim^{1

3}, Ju-Sik Yun^{1

3}, Sang-Yun Song^{1

3}, Kook-Joo Na^{1

3}, Jae-Uk Jeong^{1

4}, Mee Sun Yoon^{1

4}, Sung-Ja Ahn^{1

4}, Su Woong Yoo^{1

5}, Sae-Ryung Kang^{1

5}, Seong Young Kwon^{1

5}, Hee-Seung Bom^{1

5}, Woo-Youl Jang^{1

6}, In-Young Kim^{1

6}, Jong-Eun Lee⁷, Won-Gi Jeong^{1

7}, Yun-Hyeon Kim⁷, Taebum Lee⁸, Yoo-Duk Choi^{1

8}

Affiliations

¹ Lung and Esophageal Cancer Clinic, Chonnam National University, Hwasun Hospital, Hwasun, Republic of Korea.
² Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
³ Department of Thoracic Surgery, Chonnam National University Medical School, Gwangju, Republic of Korea.
⁴ Department of Radiation Oncology, Chonnam National University Medical School, Gwangju, Republic of Korea.
⁵ Department of Nuclear Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
⁶ Department of Neurosurgery, Chonnam National University Medical School, Gwangju, Republic of Korea.
⁷ Department of Radiology, Chonnam National University Medical School, Gwangju, Republic of Korea.
⁸ Department of Pathology, Chonnam National University Medical School, Gwangju, Republic of Korea.

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.

Keywords: Watson for Oncology (WFO); lung cancer; multidisciplinary tumor board.