Risk-stratified Approach for Never- and Ever-Smokers in Lung Cancer Screening: A Prospective Cohort Study in China

Wang, Fei; Tan, Fengwei; Shen, Sipeng; Wu, Zheng; Cao, Wei; Yu, Yiwen; Dong, Xuesi; Xia, Changfa; Tang, Wei; Xu, Yongjie; Qin, Chao; Zhu, Meng; Li, Jibin; Yang, Zhuoyu; Zheng, Yadi; Luo, Zilin; Zhao, Liang; Li, Jiang; Ren, Jiansong; Shi, Jufang; Huang, Yao; Wu, Ning; Shen, Hongbing; Chen, Wanqing; Li, Ni; He, Jie

doi:10.1164/rccm.202204-0727oc

Cited by 18 publications

(18 citation statements)

References 39 publications

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“…Our model for ever smokers included cigarettes per day, smoking years, quit years, and smoke inhalation to the lungs. The relative risks between cigarettes per day, smoking years, and lung cancer risk were weaker in our model than in the previous European or North American risk models [22, 32, 35], but were consistent with those in other Chinese models [36, 37]. For cigarettes per day, smoking years, and quit years, the associations with lung cancer risk were nonlinear in our study, which was also observed in European populations [28, 38‐40].…”

Section: Discussionsupporting

confidence: 85%

“…Besides, the morbidity and mortality rates of cancer in the CKB cohort are consistent with those from the Cancer Registration System of China, which indicates good representativeness of the participants in this study [56]. Moreover, the number of lung cancer cases in this study was the largest ( n = 4,395) compared to previous studies [7, 9, 21, 32, 36, 38].…”

Section: Discussionsupporting

confidence: 84%

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Lung cancer risk score for ever and never smokers in China

Zhu

et al. 2023

Cancer Communications

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Background Most lung cancer risk prediction models were developed in European and North‐American cohorts of smokers aged ≥ 55 years, while less is known about risk profiles in Asia, especially for never smokers or individuals aged < 50 years. Hence, we aimed to develop and validate a lung cancer risk estimate tool for ever and never smokers across a wide age range. Methods Based on the China Kadoorie Biobank cohort, we first systematically selected the predictors and explored the nonlinear association of predictors with lung cancer risk using restricted cubic splines. Then, we separately developed risk prediction models to construct a lung cancer risk score (LCRS) in 159,715 ever smokers and 336,526 never smokers. The LCRS was further validated in an independent cohort over a median follow‐up of 13.6 years, consisting of 14,153 never smokers and 5,890 ever smokers. Results A total of 13 and 9 routinely available predictors were identified for ever and never smokers, respectively. Of these predictors, cigarettes per day and quit years showed nonlinear associations with lung cancer risk (Pnon‐linear < 0.001). The curve of lung cancer incidence increased rapidly above 20 cigarettes per day and then was relatively flat until approximately 30 cigarettes per day. We also observed that lung cancer risk declined sharply within the first 5 years of quitting, and then continued to decrease but at a slower rate in the subsequent years. The 6‐year area under the receiver operating curve for the ever and never smokers’ models were respectively 0.778 and 0.733 in the derivation cohort, and 0.774 and 0.759 in the validation cohort. In the validation cohort, the 10‐year cumulative incidence of lung cancer was 0.39% and 2.57% for ever smokers with low (< 166.2) and intermediate‐high LCRS (≥ 166.2), respectively. Never smokers with a high LCRS (≥ 21.2) had a higher 10‐year cumulative incidence rate than those with a low LCRS (< 21.2; 1.05% vs. 0.22%). An online risk evaluation tool (LCKEY; http://ccra.njmu.edu.cn/lckey/web) was developed to facilitate the use of LCRS. Conclusions The LCRS can be an effective risk assessment tool designed for ever and never smokers aged 30 to 80 years.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionsupporting

confidence: 84%

Lung cancer risk score for ever and never smokers in China

Zhu

et al. 2023

Cancer Communications

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“…Our previous research has confirmed that simultaneous screening for smokers and nonsmokers based on the same risk of lung cancer is currently the most effective screening strategy in the Chinese population 24 . The study, however, did not take into account the difference in FPR and ensuing management challenges in positive screening results.…”

Section: Discussionmentioning

confidence: 93%

A strategy to reduce the false‐positive rate after low‐dose computed tomography in lung cancer screening: A multicenter prospective cohort study

Tan

Xie

et al. 2023

Cancer Medicine

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Background The ability of lung cancer screening to manage pulmonary nodules was limited because of the high false‐positive rate in the current mainstream screening method, low‐dose computed tomography (LDCT). We aimed to reduce overdiagnosis in Chinese population. Methods Lung cancer risk prediction models were constructed using data from a population‐based cohort in China. Independent clinical data from two programs performed in Beijing and Shandong, respectively, were used as the external validation set. Multivariable logistic regression models were used to estimate the probability of lung cancer incidence in the whole population and in smokers and nonsmokers. Results In our cohort, 1,016,740 participants were enrolled between 2013 and 2018. Of 79,581 who received LDCT screening, 5165 participants with suspected pulmonary nodules were allocated into the training set, of which, 149 lung cancer cases were diagnosed. In the validation set, 1815 patients were included, and 800 developed lung cancer. The ages of patients and radiologic factors of nodules (calcification, density, mean diameter, edge, and pleural involvement) were included in our model. The area under the curve (AUC) values of the model were 0.868 (95% CI: 0.839–0.894) in the training set and 0.751 (95% CI: 0.727–0.774) in the validation set. The sensitivity and specificity were 70.5% and 70.9%, respectively, which could reduce the 68.8% false‐positive rate in simulated LDCT screening. There was no substantial difference between smokers' and nonsmokers' prediction models. Conclusion Our models could facilitate the diagnosis of suspected pulmonary nodules, effectively reducing the false‐positive rate of LDCT for lung cancer screening.

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“…We read with interest the article by Wang and colleagues regarding a great attempt to develop and validate a prediction model for the risk of lung cancer for never- and ever-smokers ( 1 ). The huge database ensured the degree of credibility of the model.…”

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confidence: 99%

Lung Cancer Attributable to Environmental Risk Factors

Lee

et al. 2023

Am J Respir Crit Care Med

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Risk-stratified Approach for Never- and Ever-Smokers in Lung Cancer Screening: A Prospective Cohort Study in China

Cited by 18 publications

References 39 publications

Lung cancer risk score for ever and never smokers in China

Lung cancer risk score for ever and never smokers in China

A strategy to reduce the false‐positive rate after low‐dose computed tomography in lung cancer screening: A multicenter prospective cohort study

Lung Cancer Attributable to Environmental Risk Factors

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