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Individual 5-Year Lung Cancer Risk Prediction Model in Korea Using a Nationwide Representative Database

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Department of Family Medicine & Supportive Care Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
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Department of Preventive Medicine, Seoul National University College of Medicine, Seoul 03080, Korea
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Department of Clinical Research Design & Evaluation, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Korea
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Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Korea
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Department of Statistics and Actuarial Science, Soongsil University, Seoul 06978, Korea
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Department of Medical Statistics, College of Medicine, Catholic University of Korea, Seoul 06591, Korea
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Department of Family Medicine, CHA Gumi Medical Center, Gumi 39295, Korea
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Bucheon Geriatric Medical Center, Bucheon 14478, Korea
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Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
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Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, National Medical Center, Seoul 04564, Korea
*
Authors to whom correspondence should be addressed.
Academic Editor: Triantafillos Liloglou
Cancers 2021, 13(14), 3496; https://doi.org/10.3390/cancers13143496
Received: 12 May 2021 / Revised: 29 June 2021 / Accepted: 6 July 2021 / Published: 13 July 2021
(This article belongs to the Section Cancer Epidemiology and Prevention)
From the representative data in Korea, we developed individual lung cancer risk prediction model of Korean adults. Our model would serve as a tool to screen high-risk individuals who would benefit from participating in lung cancer screening in a clinical setting applicable to health examinees or the general adult population. We believe that interactive approaches between healthcare providers and examinees using an easily accessible and visualized risk score can be used for the development of health policies for lung cancer prevention.
Early detection of lung cancer by screening has contributed to reduce lung cancer mortality. Identifying high risk subjects for lung cancer is necessary to maximize the benefits and minimize the harms followed by lung cancer screening. In the present study, individual lung cancer risk in Korea was presented using a risk prediction model. Participants who completed health examinations in 2009 based on the Korean National Health Insurance (KNHI) database (DB) were eligible for the present study. Risk scores were assigned based on the adjusted hazard ratio (HR), and the standardized points for each risk factor were calculated to be proportional to the b coefficients. Model discrimination was assessed using the concordance statistic (c-statistic), and calibration ability assessed by plotting the mean predicted probability against the mean observed probability of lung cancer. Among candidate predictors, age, sex, smoking intensity, body mass index (BMI), presence of chronic obstructive pulmonary disease (COPD), pulmonary tuberculosis (TB), and type 2 diabetes mellitus (DM) were finally included. Our risk prediction model showed good discrimination (c-statistic, 0.810; 95% CI: 0.801–0.819). The relationship between model-predicted and actual lung cancer development correlated well in the calibration plot. When using easily accessible and modifiable risk factors, this model can help individuals make decisions regarding lung cancer screening or lifestyle modification, including smoking cessation. View Full-Text
Keywords: lung cancer; prediction; personalized risk; decision aids lung cancer; prediction; personalized risk; decision aids
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MDPI and ACS Style

Yeo, Y.; Shin, D.W.; Han, K.; Park, S.H.; Jeon, K.-H.; Lee, J.; Kim, J.; Shin, A. Individual 5-Year Lung Cancer Risk Prediction Model in Korea Using a Nationwide Representative Database. Cancers 2021, 13, 3496. https://doi.org/10.3390/cancers13143496

AMA Style

Yeo Y, Shin DW, Han K, Park SH, Jeon K-H, Lee J, Kim J, Shin A. Individual 5-Year Lung Cancer Risk Prediction Model in Korea Using a Nationwide Representative Database. Cancers. 2021; 13(14):3496. https://doi.org/10.3390/cancers13143496

Chicago/Turabian Style

Yeo, Yohwan, Dong W. Shin, Kyungdo Han, Sang H. Park, Keun-Hye Jeon, Jungkwon Lee, Junghyun Kim, and Aesun Shin. 2021. "Individual 5-Year Lung Cancer Risk Prediction Model in Korea Using a Nationwide Representative Database" Cancers 13, no. 14: 3496. https://doi.org/10.3390/cancers13143496

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