Tobacco Smoking and Risk of Second Primary Lung Cancer

Aredo, Jacqueline V.; Luo, Sophia J.; Gardner, Rachel; Sanyal, Nilotpal; Choi, Eunji; Hickey, Tom; Riley, Thomas L.; Huang, Wen‐Yi; Kurian, Allison W.; Leung, Ann N.; Wilkens, Lynne R.; Robbins, Hilary A.; Riboli, Elio; Kaaks, Rudolf; Tjønneland, Anne; Vermeulen, Roel; Panico, Salvatore; Marchand, Loı̈c Le; Amos, Christopher I.; Hung, Rayjean J.; Freedman, Neal D.; Cheng, Iona; Wakelee, Heather A.; Han, Summer S.

doi:10.1016/j.jtho.2021.02.024

Cited by 76 publications

(53 citation statements)

References 34 publications

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“…In evaluating the association between survival and SPLC, we considered SPLC diagnosis as a time-varying predictor to account for patients whose SPLC status changed from a single primary lung cancer to SPLC during the study period. The model was adjusted for known prognostic factors and risk factors for SPLC based on prior literature ( 8-10 , 13 , 17 ): sex, race, age at IPLC diagnosis, IPLC stage, and IPLC histology.…”

Section: Methodsmentioning

confidence: 99%

“…Numerous studies have examined potential risk factors and predictive models for SPLC in an effort to establish efficient screening strategies for SPLC ( 8-12 ). Radiotherapy for initial primary lung cancer (IPLC) is associated with an increased risk of SPLC ( 11 ), and smoking is a statistically significant risk factor for SPLC based on an international multicohort study ( 8 ). Prediction models for SPLC risk have been developed to identify high-risk lung cancer survivors for surveillance and screening for SPLC ( 9 , 12 , 13 ).…”

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confidence: 99%

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The Survival Impact of Second Primary Lung Cancer in Patients With Lung Cancer

Choi

Luo

Aredo

et al. 2021

JNCI: Journal of the National Cancer Institute

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Background Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC), but little is known about the survival impact of SPLC diagnosis. Methods We analyzed data from 138,969 patients in the Surveillance, Epidemiology, and End Results (SEER), who were surgically treated for initial primary lung cancer (IPLC) in 1988–2013. Each patient was followed from the date of IPLC diagnosis to SPLC diagnosis (for those with SPLC) and last vital status through 2016. We performed multivariable Cox regression to evaluate the association between overall survival and SPLC diagnosis as a time-varying predictor. To investigate potential effect modification, we tested interaction between SPLC and IPLC stage. Using data from the Multiethnic Cohort Study (MEC) (N = 1,540 IPLC patients with surgery), we evaluated the survival impact of SPLC by smoking status. All statistical tests were 2-sided. Results A total of 12,115 (8.7%) patients developed SPLC in SEER over 700,421 person-years of follow up. Compared to patients with single primary lung cancer, those with SPLC had statistically significantly reduced overall survival (hazard ratio [HR]=2.12, 95% confidence interval [CI] = 2.06–2.17; P < .001). The effect of SPLC on reduced survival was more pronounced among patients with early-stage IPLC vs. advanced-stage IPLC (HR = 2.14 [95% CI = 2.08–2.20] vs. 1.43 [95% CI = 1.21–1.70], respectively; Pinteraction <0.001). Analysis using MEC data showed that the effect of SPLC on reduced survival was statistically significantly larger among persons who actively smoked at initial diagnosis vs. those who formerly or never smoked (HR = 2.31 [95% CI = 1.48–3.61] vs. 1.41 [95% CI = 0.98–2.03], respectively; Pinteraction=0.04). Conclusions SPLC diagnosis is statistically significantly associated with decreased survival in SEER and MEC. Intensive surveillance targeting patients with early-stage IPLC and active smoking at IPLC diagnosis may lead to a larger survival benefit.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

The Survival Impact of Second Primary Lung Cancer in Patients With Lung Cancer

Choi

Luo

Aredo

et al. 2021

JNCI: Journal of the National Cancer Institute

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“…Furthermore, MEC helped increase the power of the study as a primary cohort by providing the largest number of SPLC cases with long-term follow-up and detailed exposure data among all cohorts considered. We used a binary IPLC staging variable in predicting SPLC risk, merging patients with stage IA to IIIA IPLCs into an early-stage IPLC group based on the literature ( 17 , 35 ); also, analyses using SEER showed that SPLC risk does not vary statistically significantly across stage IA to IIIA IPLCs (data not shown). Therefore, the clinical utility of the proposed model would not be diminished given that the model continues to capture well the SPLC risk variations using parsimonious dichotomous staging parameters.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Risk Prediction Model for Second Primary Lung Cancer

Choi

Sanyal

Ding

et al. 2021

JNCI: Journal of the National Cancer Institute

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Background With advancing therapeutics, lung cancer (LC) survivors are rapidly increasing in number. While mounting evidence suggests LC survivors have high risk of second primary lung cancer (SPLC), there is no validated prediction tool available for clinical use to identify high-risk LC survivors for SPLC. Methods Using data from 6,325 ever-smokers in the Multiethnic Cohort (MEC) diagnosed with initial primary lung cancer (IPLC) in 1993–2017, we developed a prediction model for 10-year SPLC risk after IPLC diagnosis using cause-specific Cox regression. We evaluated the model’s clinical utility using decision curve analysis and externally validated it using two population-based data, PLCO and NLST, that included 2,963 and 2,844 IPLC (101 and 93 SPLC cases), respectively. Results Over 14,063 person-years, 145 (2.3%) developed SPLC in MEC. Our prediction model demonstrated a high predictive accuracy (Brier score = 2.9, 95% confidence interval [CI] = 2.4–3.3) and discrimination (AUC = 81.9%, 95% CI = 78.2%–85.5%) based on bootstrap validation in MEC. Stratification by the estimated risk quartiles showed that the observed SPLC incidence was statistically significantly higher in the 4th versus 1st quartile (9.5% versus 0.2%; P < .001). Decision curve analysis indicated that in a wide range of 10-year risk thresholds from 1% to 20%, the model yielded a larger net-benefit versus hypothetical all-screening or no-screening scenarios. External validation using PLCO and NLST showed an AUC of 78.8% (95% CI = 74.6%–82.9%) and 72.7% (95% CI = 67.7%–77.7%), respectively. Conclusions We developed and validated a SPLC prediction model based on large population-based cohorts. The proposed prediction tool can help identify high-risk LC patients for SPLC and can be incorporated into clinical decision-making for SPLC surveillance and screening.

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“…Lung cancer, which accounts for 11.6% of all newly diagnosed cancer cases and 18.4% of cancer-related deaths [1], brings a growing global burden of disease. Smoking has been identified as the most common risk factor for lung cancer, and a large number of epidemiological researches support this connection [2][3][4]. Smoking cessation before middle age can effectively decrease lung cancer risk.…”

Section: Introductionmentioning

confidence: 98%

Association between Sleep Traits and Lung Cancer: A Mendelian Randomization Study

Wang

Tang

Duan

et al. 2021

Journal of Immunology Research

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Multidimensional sleep trait, which is related to circadian rhythms closely, affects some cancers predominantly, while the relationship between sleep and lung cancer is rarely illustrated. We aimed to investigate whether sleep is causally associated with risk of lung cancer, through a two-sample Mendelian randomization study. The main analysis used publicly available GWAS summary data from two large consortia (UK Biobank and International Lung Cancer Consortium). Two-sample Mendelian randomization (MR) analysis was used to examine whether chronotype, getting up in the morning, sleep duration, nap during the day, or sleeplessness was causally associated with the risk of lung cancer. Additionally, multivariate MR analysis was also conducted to estimate the direct effects between sleep traits and lung cancer risks independent of smoking status including pack years of smoking or current tobacco smoking. There was no evidence of causal association between chronotype, getting up in the morning, or nap during the day and lung cancer. Sleeplessness was associated with higher risk of lung adenocarcinoma (odds ratio 5.75, 95% confidence intervals 2.12-15.65), while sleep duration played a protective role in lung cancer (0.46, 0.26-0.83). In multivariate MR analysis, sleeplessness and sleep duration remained to have similar results. In conclusion, we found robust evidence for effect of sleeplessness on lung adenocarcinoma risk and inconsistent evidence for a protective effect of sleep duration on lung cancer risk.

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Tobacco Smoking and Risk of Second Primary Lung Cancer

Cited by 76 publications

References 34 publications

The Survival Impact of Second Primary Lung Cancer in Patients With Lung Cancer

The Survival Impact of Second Primary Lung Cancer in Patients With Lung Cancer

Development and Validation of a Risk Prediction Model for Second Primary Lung Cancer

Association between Sleep Traits and Lung Cancer: A Mendelian Randomization Study

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