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Personalized Risk Assessment in Never, Light, and Heavy Smokers in a prospective cohort in Taiwan.

ABSTRACT: The objective of this study was to develop markedly improved risk prediction models for lung cancer using a prospective cohort of 395,875 participants in Taiwan. Discriminatory accuracy was measured by generation of receiver operator curves and estimation of area under the curve (AUC). In multivariate Cox regression analysis, age, gender, smoking pack-years, family history of lung cancer, personal cancer history, BMI, lung function test, and serum biomarkers such as carcinoembryonic antigen (CEA), bilirubin, alpha fetoprotein (AFP), and c-reactive protein (CRP) were identified and included in an integrative risk prediction model. The AUC in overall population was 0.851 (95% CI?=?0.840-0.862), with never smokers 0.806 (95% CI?=?0.790-0.819), light smokers 0.847 (95% CI?=?0.824-0.871), and heavy smokers 0.732 (95% CI?=?0.708-0.752). By integrating risk factors such as family history of lung cancer, CEA and AFP for light smokers, and lung function test (Maximum Mid-Expiratory Flow, MMEF_25-75%), AFP and CEA for never smokers, light and never smokers with cancer risks as high as those within heavy smokers could be identified. The risk model for heavy smokers can allow us to stratify heavy smokers into subgroups with distinct risks, which, if applied to low-dose computed tomography (LDCT) screening, may greatly reduce false positives.

SUBMITTER: Wu X

PROVIDER: S-EPMC5090352 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Personalized Risk Assessment in Never, Light, and Heavy Smokers in a prospective cohort in Taiwan.

Wu Xifeng X Wen Chi Pang CP Ye Yuanqing Y Tsai MinKwang M Wen Christopher C Roth Jack A JA Pu Xia X Chow Wong-Ho WH Huff Chad C Cunningham Sonia S Huang Maosheng M Wu Shuanbei S Tsao Chwen Keng CK Gu Jian J Lippman Scott M SM

Scientific reports 20161102

The objective of this study was to develop markedly improved risk prediction models for lung cancer using a prospective cohort of 395,875 participants in Taiwan. Discriminatory accuracy was measured by generation of receiver operator curves and estimation of area under the curve (AUC). In multivariate Cox regression analysis, age, gender, smoking pack-years, family history of lung cancer, personal cancer history, BMI, lung function test, and serum biomarkers such as carcinoembryonic antigen (CEA ...[more]

PMID: 27805040

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Project description:Objectives: Lung cancer is a heterogeneous disease. Presentation and prognosis are known to vary according to several factors, such as genetic and demographic characteristics. Small-cell lung cancer incidence is increasing in never-smokers. However, the disease phenotype in this population is different compared with patients who have a smoking history. Material and Methods: To further investigate the clinical and genetic characteristics of this patient subgroup, a cohort of small cell lung cancer patients was divided into smokers (n = 10) and never/ever-smokers (n = 10). A somatic mutation profile was obtained using a comprehensive NGS assay. Clinical outcomes were compared using the Kaplan-Meier method and Cox proportional models. Results: Median age was 63 years (46-81), 40% were men, and 90% had extended disease. Smoker patients had significantly more cerebral metastases (p = 0.04) and were older (p = 0.03) compared to their non-smoker counterparts. For never/ever smokers, the main genetic mutations were TP53 (80%), RB1 (40%), CYLD (30%), and EGFR (30%). Smoker patients had more RB1 (80%, p = 0.04), CDKN2A (30%, p = 0.05), and CEBPA (30%, p = 0.05) mutations. Response rates to first-line therapy with etoposide plus cisplatin/carboplatin were 50% in smokers and 90% in never/ever smokers (p = 0.141). Median overall survival was significantly longer in never smokers compared with smokers (29.1 months [23.5-34.6] vs. 17.3 months [4.8-29.7]; p = 0.0054). Never/ever smoking history (HR 0.543, 95% CI 0.41-0.80), limited-stage disease (HR 0.56, 95% CI 0.40-0.91) and response to first-line platinum-based chemotherapy (HR 0.63, 95% CI 0.60-0.92) were independently associated with good prognosis. Conclusion: Our data supports that never/ever smoker patients with small-cell lung cancer have better prognosis compared to their smoker counterparts. Further, patients with never/ever smoking history who present with small-cell lung cancer have a different mutation profile compared with smokers, including a high frequency of EGFR, MET, and SMAD4 mutations. Further studies are required to assess whether the differential mutation profile is a consequence of a diverse pathological mechanism for disease onset.

Project description:BackgroundMost 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.MethodsBased 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.ResultsA 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.ConclusionsThe LCRS can be an effective risk assessment tool designed for ever and never smokers aged 30 to 80 years.

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Personalized Risk Assessment in Never, Light, and Heavy Smokers in a prospective cohort in Taiwan.

Publications

Personalized Risk Assessment in Never, Light, and Heavy Smokers in a prospective cohort in Taiwan.

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