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Tobacco Smoking and Risk of Second Primary Lung Cancer

Open AccessPublished:March 12, 2021DOI:https://doi.org/10.1016/j.jtho.2021.02.024

      Abstract

      Introduction

      Lung cancer survivors are at high risk of developing a second primary lung cancer (SPLC). However, SPLC risk factors have not been established and the impact of tobacco smoking remains controversial. We examined the risk factors for SPLC across multiple epidemiologic cohorts and evaluated the impact of smoking cessation on reducing SPLC risk.

      Methods

      We analyzed data from 7059 participants in the Multiethnic Cohort (MEC) diagnosed with an initial primary lung cancer (IPLC) between 1993 and 2017. Cause-specific proportional hazards models estimated SPLC risk. We conducted validation studies using the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (N = 3423 IPLC cases) and European Prospective Investigation into Cancer and Nutrition (N = 4731 IPLC cases) cohorts and pooled the SPLC risk estimates using random effects meta-analysis.

      Results

      Overall, 163 MEC cases (2.3%) developed SPLC. Smoking pack-years (hazard ratio [HR] = 1.18 per 10 pack-years, p < 0.001) and smoking intensity (HR = 1.30 per 10 cigarettes per day, p < 0.001) were significantly associated with increased SPLC risk. Individuals who met the 2013 U.S. Preventive Services Task Force’s screening criteria at IPLC diagnosis also had an increased SPLC risk (HR = 1.92; p < 0.001). Validation studies with the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and European Prospective Investigation into Cancer and Nutrition revealed consistent results. Meta-analysis yielded pooled HRs of 1.16 per 10 pack-years (pmeta < 0.001), 1.25 per 10 cigarettes per day (pmeta < 0.001), and 1.99 (pmeta < 0.001) for meeting the U.S. Preventive Services Task Force’s criteria. In MEC, smoking cessation after IPLC diagnosis was associated with an 83% reduction in SPLC risk (HR = 0.17; p < 0.001).

      Conclusions

      Tobacco smoking is a risk factor for SPLC. Smoking cessation may reduce the risk of SPLC. Additional strategies for SPLC surveillance and screening are warranted.

      Keywords

      Introduction

      Lung cancer has the second highest cancer incidence among women and men and continues to lead cancer-related mortality in the United States. Thus, lung cancer remains a major public health problem. However, the past decade saw a 26% improvement in 5-year survival rates,

      American Lung Association. State of Lung Cancer 2019. https://www.lung.org/research/state-of-lung-cancer. Accessed May 16, 2021.

      indicating the number of lung cancer survivors is increasing. Multiple studies have revealed that survivors of an initial primary lung cancer (IPLC) are at high risk of developing a second primary lung cancer (SPLC),
      • Johnson B.E.
      Second lung cancers in patients after treatment for an initial lung cancer.
      • Thakur M.K.
      • Ruterbusch J.J.
      • Schwartz A.G.
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      Risk of second lung cancer in patients with previously treated lung cancer: analysis of surveillance, epidemiology, and end results (SEER) data.
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      Stage I lung cancer survivorship: risk of second malignancies and need for individualized care plan.
      • Rice D.
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      • Sabichi A.
      • et al.
      The risk of second primary tumors after resection of stage I nonsmall cell lung cancer.
      with incidence rates after IPLC surgical resection ranging from 1% to 2% per patient-year.
      • Johnson B.E.
      Second lung cancers in patients after treatment for an initial lung cancer.
      Development of a SPLC can complicate a patient’s clinical assessment and may require further aggressive intervention, adding to an already heavy burden for lung cancer survivors.
      In 2013, the U.S. Preventive Services Task Force (USPSTF) established national guidelines for IPLC screening on the basis of age (55–80 y) and smoking history (≥30 pack-years, cessation ≤15 y)
      • Moyer V.A.
      U.S. Preventive Services Task Force. Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement.
      —known risk factors for IPLC—which are currently under revision.

      US Preventive Services Task Force. Draft Recommendation Statement- Lung Cancer: Screening.

      However, evidence-based guidelines for SPLC surveillance and screening are lacking,
      • Wood D.E.
      National Comprehensive Cancer Network (NCCN) clinical practice guidelines for lung cancer screening.
      in large part owing to an absence of established risk factors for SPLC.
      • Wozniak A.J.
      • Schwartz A.G.
      The risk of second primary lung cancer: an unsolved dilemma.
      Previous studies have sought to identify SPLC risk factors, but these have been limited to single institutions or population-based registries comprising selected patient populations without validation in independent cohorts.
      • Boyle J.M.
      • Tandberg D.J.
      • Chino J.P.
      • D’Amico T.A.
      • Ready N.E.
      • Kelsey C.R.
      Smoking history predicts for increased risk of second primary lung cancer: a comprehensive analysis.
      • Ripley R.T.
      • McMillan R.R.
      • Sima C.S.
      • et al.
      Second primary lung cancers: smokers versus nonsmokers after resection of stage I lung adenocarcinoma.
      • Leroy T.
      • Monnet E.
      • Guerzider S.
      • et al.
      Let us not underestimate the long-term risk of SPLC after surgical resection of NSCLC.
      • Han S.S.
      • Rivera G.A.
      • Tammemägi M.C.
      • et al.
      Risk stratification for second primary lung cancer.
      Furthermore, these studies have used different methodological designs or statistical approaches for identifying SPLC risk factors and, accordingly, have reached conflicting conclusions. For example, although tobacco smoking is an established risk factor for IPLC, the association between smoking and SPLC risk has been controversial, with some studies reporting a positive association
      • Rice D.
      • Kim H.W.
      • Sabichi A.
      • et al.
      The risk of second primary tumors after resection of stage I nonsmall cell lung cancer.
      ,
      • Boyle J.M.
      • Tandberg D.J.
      • Chino J.P.
      • D’Amico T.A.
      • Ready N.E.
      • Kelsey C.R.
      Smoking history predicts for increased risk of second primary lung cancer: a comprehensive analysis.
      and others revealing not significant relationships.
      • Ripley R.T.
      • McMillan R.R.
      • Sima C.S.
      • et al.
      Second primary lung cancers: smokers versus nonsmokers after resection of stage I lung adenocarcinoma.
      ,
      • Leroy T.
      • Monnet E.
      • Guerzider S.
      • et al.
      Let us not underestimate the long-term risk of SPLC after surgical resection of NSCLC.
      Our group previously used a risk stratification approach to distinguish between patients with IPLC at high versus low risk of SPLC using the Surveillance, Epidemiology, and End Results database.
      • Han S.S.
      • Rivera G.A.
      • Tammemägi M.C.
      • et al.
      Risk stratification for second primary lung cancer.
      However, this cohort did not contain data on potentially important risk factors such as tobacco smoking.
      In this study, we leveraged data from the Multiethnic Cohort (MEC) to identify risk factors for SPLC among IPLC cases with a focus on tobacco smoking. We validated these findings with the following two additional cohorts: the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and the European Prospective Investigation into Cancer and Nutrition (EPIC). Finally, in a subset analysis in MEC, we evaluated the impact of smoking cessation on reducing SPLC risk.

      Materials and Methods

      MEC: Participants and Study Design (Discovery Cohort)

      MEC is a population-based cohort that prospectively follows more than 215,000 California and Hawaii residents aged 45 to 75 years at enrollment (1993–1996).
      • Kolonel L.N.
      • Henderson B.E.
      • Hankin J.H.
      • et al.
      A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics.
      In this study, we included all participants who were diagnosed with having an incident IPLC between 1993 and 2017 and who had nonmissing tobacco smoking data (see Supplementary Methods for details). Demographic and behavioral data were analyzed as self-reported in the baseline questionnaire; smoking-related variables were assigned values from the questionnaire nearest in time and before IPLC diagnosis: either the baseline (1993–1996) or 10-year follow-up questionnaire (2003–2008), if available (N = 1872; Supplementary Methods). Smoking-related variables included the following: smoking status, pack-years, intensity (i.e., cigarettes per day [CPD]), and quit years (i.e., years since cessation). Smoking intensity reflected the average lifetime consumption of cigarettes. Incident IPLC and SPLC were identified through linkage to Surveillance, Epidemiology, and End Results registries together with IPLC age at diagnosis, stage, histology, and therapies. Lung cancer histology was classified on the basis of tumor ICD-O-3 morphology codes (Supplementary Methods). SPLC was defined according to Martini and Melamed criteria (Supplementary Methods).
      • Martini N.
      • Melamed M.R.
      Multiple primary lung cancers.
      Deaths were ascertained by means of linkage to the National Death Index and death certificate files.
      • Kolonel L.N.
      • Henderson B.E.
      • Hankin J.H.
      • et al.
      A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics.
      As primary analyses, we evaluated potential risk factors for SPLC focusing on smoking-related variables and clinical variables that have not previously been evaluated in the literature (i.e., body mass index [BMI], personal history of cancer, family history of lung cancer).
      • Boyle J.M.
      • Tandberg D.J.
      • Chino J.P.
      • D’Amico T.A.
      • Ready N.E.
      • Kelsey C.R.
      Smoking history predicts for increased risk of second primary lung cancer: a comprehensive analysis.
      • Ripley R.T.
      • McMillan R.R.
      • Sima C.S.
      • et al.
      Second primary lung cancers: smokers versus nonsmokers after resection of stage I lung adenocarcinoma.
      • Leroy T.
      • Monnet E.
      • Guerzider S.
      • et al.
      Let us not underestimate the long-term risk of SPLC after surgical resection of NSCLC.
      • Han S.S.
      • Rivera G.A.
      • Tammemägi M.C.
      • et al.
      Risk stratification for second primary lung cancer.
      We also estimated the SPLC risk associated with meeting the 2013 USPSTF lung cancer screening criteria at IPLC diagnosis, as a composite smoking and age measure of individuals at particularly high risk of IPLC. We also conducted a set of confirmatory secondary analyses to evaluate the associations between SPLC and factors that were examined in previous studies (i.e., sex, race/ethnicity, education, IPLC therapies).
      • Boyle J.M.
      • Tandberg D.J.
      • Chino J.P.
      • D’Amico T.A.
      • Ready N.E.
      • Kelsey C.R.
      Smoking history predicts for increased risk of second primary lung cancer: a comprehensive analysis.
      ,
      • Leroy T.
      • Monnet E.
      • Guerzider S.
      • et al.
      Let us not underestimate the long-term risk of SPLC after surgical resection of NSCLC.
      ,
      • Han S.S.
      • Rivera G.A.
      • Tammemägi M.C.
      • et al.
      Risk stratification for second primary lung cancer.
      Given the focus on the smoking-SPLC association, we conducted a subset analysis evaluating the impact of smoking cessation on SPLC risk using the longitudinal measurements of smoking at baseline and 10-year follow-up. Smoking cessation was defined as the change in smoking status from “current” at baseline to “former” at follow-up (versus “current” at baseline and “current” at follow-up). Participants included those who were current smoking at baseline, had 10-year follow-up smoking data, and were diagnosed with their IPLC before 10-year follow-up (N = 156; Supplementary Fig. 1). We evaluated the association between smoking cessation after IPLC diagnosis and SPLC after 10-year follow-up.

      MEC: Statistical Analyses

      Cause-specific proportional hazards models evaluated the associations between candidate risk factors and SPLC, accounting for the competing risk of death from all causes.
      • Lau B.
      • Cole S.R.
      • Gange S.J.
      Competing risk regression models for epidemiologic data.
      The cause-specific function was selected because it can estimate the effects of factors on SPLC risk with sustained power in multiple competing risk scenarios while minimizing type I error.
      • Varadhan R.
      • Weiss C.O.
      • Segal J.B.
      • Wu A.W.
      • Scharfstein D.
      • Boyd C.
      Evaluating health outcomes in the presence of competing risks: a review of statistical methods and clinical applications.
      All models evaluated SPLC risk from the date of IPLC diagnosis. The proportional hazards assumption was confirmed for all models. In light of previous data indicating that IPLC age at diagnosis, stage, and histology are relevant predictors for SPLC,
      • Han S.S.
      • Rivera G.A.
      • Tammemägi M.C.
      • et al.
      Risk stratification for second primary lung cancer.
      we adjusted for these as covariates in all analyses. To account for multiple testing, we implemented a Bonferroni threshold for the primary analyses (p = 0.05/9 = 0.005). For all other analyses, statistical significance was defined at a two-sided p value less than 0.05. Cumulative incidences were calculated using Gray’s method.
      • Gray R.J.
      A class of K-sample tests for comparing the cumulative incidence of a competing risk.
      We handled missing data by performing multiple imputation
      • Graham J.W.
      • Hofer S.M.
      Multiple imputation in multivariate research.
      ,
      • Sterne J.A.
      • White I.R.
      • Carlin J.B.
      • et al.
      Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.
      and evaluated the robustness of the findings using complete cases (Supplementary Methods).
      We further evaluated the smoking-related variables in a subgroup analysis of early-stage IPLC cases to reduce potential noncausal effects from the competing risk of death
      • Varadhan R.
      • Weiss C.O.
      • Segal J.B.
      • Wu A.W.
      • Scharfstein D.
      • Boyd C.
      Evaluating health outcomes in the presence of competing risks: a review of statistical methods and clinical applications.
      and to make the results comparable to previous data.
      • Boyle J.M.
      • Tandberg D.J.
      • Chino J.P.
      • D’Amico T.A.
      • Ready N.E.
      • Kelsey C.R.
      Smoking history predicts for increased risk of second primary lung cancer: a comprehensive analysis.
      • Ripley R.T.
      • McMillan R.R.
      • Sima C.S.
      • et al.
      Second primary lung cancers: smokers versus nonsmokers after resection of stage I lung adenocarcinoma.
      • Leroy T.
      • Monnet E.
      • Guerzider S.
      • et al.
      Let us not underestimate the long-term risk of SPLC after surgical resection of NSCLC.
      Additional sensitivity analyses evaluated the smoking-SPLC associations among ever smokers, within major IPLC histologic subtypes (i.e., adenocarcinoma, squamous cell carcinoma), and among advanced-stage IPLC cases. For continuous smoking variables (i.e., pack-years, CPD), we evaluated their potential nonlinear effects using natural cubic splines.
      • Wahba G.
      Spline Models for Observational Data.
      All analyses were performed using R version 4.0.2 (Vienna, Austria).

      PLCO and EPIC: Validation Cohorts

      We validated the SPLC associations using the following two additional epidemiologic cohorts: PLCO (N = 3423 IPLC cases with 110 SPLC) and EPIC (N = 4731 IPLC cases with 16 SPLC). Detailed information on these cohorts is included in the Supplementary Methods. As with the discovery cohort, cause-specific proportional hazards models evaluated the SPLC associations in PLCO and EPIC. To pool the SPLC associations across the three cohorts (discovery and validation), we used random effects meta-analysis.
      • DerSimonian R.
      • Laird N.
      Meta-analysis in clinical trials.
      Statistical significance was defined at a two-sided p value less than 0.05. Smoking cessation was not evaluated in these cohorts because longitudinal smoking data were unavailable for this collaborative study.

      Results

      MEC: Participant Characteristics

      Among 7059 IPLC cases in MEC, the mean age at diagnosis was 74.3 years and a slight majority were of male sex (55.9%) (Table 1). Most IPLC cases were former or current smoking (87.8%), but prospective SPLC cases had particularly high mean smoking pack-years (31.2) and mean CPD (17.6). SPLC cases also had high frequencies of local IPLC stage (57.1%), adenocarcinoma IPLC (58.3%), previous IPLC surgery (73.6%), and meeting the USPSTF screening criteria (41.7%).
      Table 1MEC Participant Characteristics
      CharacteristicsOverall N = 7059Outcome
      SPLC n = 163Deceased n = 5646Censored n = 1250
      Age at IPLC diagnosis (y), mean (SD)74.3 (8.3)72.2 (8.1)74.0 (8.2)76.2 (8.7)
      BMI (kg/m2),
      BMI was unknown in 80 (1.1%) participants: 0 (0.0%) SPLC, 72 (1.3%) deceased, and 8 (0.6%) censored.
      mean (SD)
      25.9 (4.7)26.1 (4.6)25.9 (4.7)26.2 (4.8)
      Sex, n (%)
       Male3949 (55.9)84 (51.5)3297 (58.4)568 (45.4)
       Female3110 (44.1)79 (48.5)2349 (41.6)682 (54.6)
      Race/ethnicity, n (%)
       African American1798 (25.5)37 (22.7)1477 (26.2)284 (22.7)
       Japanese American1603 (22.7)37 (22.7)1289 (22.8)277 (22.2)
       Latino998 (14.1)20 (12.3)723 (12.8)255 (20.4)
       Native Hawaiian573 (8.1)14 (8.6)481 (8.5)78 (6.2)
       White1714 (24.3)47 (28.8)1382 (24.5)285 (22.8)
       Other373 (5.3)8 (4.9)294 (5.2)71 (5.7)
      Education, n (%)
       High school or less3592 (50.9)71 (43.6)2974 (52.7)547 (43.8)
       Some college or graduate2811 (39.8)77 (47.2)2170 (38.4)564 (45.1)
       Postgraduate626 (8.9)15 (9.2)481 (8.5)130 (10.4)
       Unknown30 (0.4)0 (0.0)21 (0.4)9 (0.7)
      Personal history of cancer, n (%)
       Yes1824 (25.8)52 (31.9)1429 (25.3)343 (27.4)
       No5235 (74.2)111 (68.1)4217 (74.7)907 (72.6)
      Family history of lung cancer, n (%)
       Yes622 (8.8)14 (8.6)483 (8.6)125 (10.0)
       No6437 (91.2)149 (91.4)5163 (91.4)1125 (90.0)
      Smoking status, n (%)
       Never863 (12.2)19 (11.7)607 (10.8)237 (19.0)
       Former3243 (45.9)72 (44.2)2603 (46.1)568 (45.4)
       Current2953 (41.8)72 (44.2)2436 (43.1)445 (35.6)
      Smoking pack-years,
      Smoking-related variables are from the questionnaire closest in time and before the date of IPLC: at baseline or at 10-year follow-up, if available (n = 1872).
      mean (SD)
      27.0 (20.0)31.2 (21.3)28.0 (20.0)22.1 (19.5)
      Cigarettes per day,
      Smoking-related variables are from the questionnaire closest in time and before the date of IPLC: at baseline or at 10-year follow-up, if available (n = 1872).
      mean (SD)
      15.5 (10.0)17.6 (10.8)16.0 (9.9)13.3 (10.2)
      Smoking quit years,
      Smoking-related variables are from the questionnaire closest in time and before the date of IPLC: at baseline or at 10-year follow-up, if available (n = 1872).
      ,
      Smoking quit years were evaluated only among ever smokers (n = 6196).
      median (IQR)
      0.5 (0–13)0.3 (0–11)0.5 (0–13)4.0 (0–18)
      IPLC stage, n (%)
       Local1223 (17.3)93 (57.1)702 (12.4)428 (34.2)
       Regional1583 (22.4)51 (31.3)1185 (21.0)347 (27.8)
       Distant3811 (54.0)17 (10.4)3378 (59.8)416 (33.3)
       Unknown442 (6.3)2 (1.2)381 (6.7)59 (4.7)
      IPLC histology, n (%)
       Adenocarcinoma2832 (40.1)95 (58.3)2070 (36.7)667 (53.4)
       Squamous cell carcinoma1401 (19.8)36 (22.1)1120 (19.8)245 (19.6)
       Large cell carcinoma225 (3.2)9 (5.5)189 (3.3)27 (2.2)
       Small cell lung carcinoma731 (10.4)3 (1.8)651 (11.5)77 (6.2)
       Other
      Other histologies are listed in the Supplementary Methods and include histologies such as adenosquamous, lung neuroendocrine tumors, carcinoma not otherwise specified, and others.
      1870 (26.5)20 (12.3)1616 (28.6)234 (18.7)
      IPLC surgery, n (%)
       Yes1512 (21.4)120 (73.6)830 (14.7)562 (45.0)
       No4942 (70.0)34 (20.9)4264 (75.5)644 (51.5)
       Unknown605 (8.6)9 (5.5)552 (9.8)44 (3.5)
      IPLC radiotherapy, n (%)
       Yes2375 (33.6)26 (16.0)2050 (36.3)299 (23.9)
       No4496 (63.7)137 (84.0)3443 (61.0)916 (73.3)
       Unknown188 (2.7)0 (0.0)153 (2.7)35 (2.8)
      IPLC chemotherapy, n (%)
       Yes2299 (32.6)23 (14.1)1906 (33.8)370 (29.6)
       No4426 (62.7)139 (85.3)3454 (61.2)833 (66.6)
       Unknown334 (4.7)1 (0.6)286 (5.1)47 (3.8)
      Met the USPSTF criteria, n (%)
       Yes2058 (29.2)68 (41.7)1755 (31.1)235 (18.8)
       No5001 (70.8)95 (58.3)3891 (68.9)1015 (81.2)
      Follow-up (mo), median (IQR)10.0 (3–33)46.0 (15–78)7.0 (2–17)59.0 (35–111)
      Note: Demographic variables were collected from the baseline MEC questionnaire except smoking-related variables (see subsequent texts). Age at IPLC diagnosis, IPLC stage, IPLC histology, and IPLC therapies were obtained through linkage to SEER registries. The 2013 USPSTF lung cancer screening eligibility was calculated using age at IPLC diagnosis and smoking-related variables from the MEC questionnaires. Percentages may not sum to 100% owing to rounding.
      BMI, body mass index; IPLC, initial primary lung cancer; IQR, interquartile range; MEC, Multiethnic Cohort; SEER, Surveillance, Epidemiology, and End Results; SPLC, second primary lung cancer; USPSTF, U.S. Preventive Services Task Force.
      a BMI was unknown in 80 (1.1%) participants: 0 (0.0%) SPLC, 72 (1.3%) deceased, and 8 (0.6%) censored.
      b Smoking-related variables are from the questionnaire closest in time and before the date of IPLC: at baseline or at 10-year follow-up, if available (n = 1872).
      c Smoking quit years were evaluated only among ever smokers (n = 6196).
      d Other histologies are listed in the Supplementary Methods and include histologies such as adenosquamous, lung neuroendocrine tumors, carcinoma not otherwise specified, and others.

      MEC: SPLC Incidence and Risk Factors

      Median follow-up in the cohort was 10.0 months overall and 57.0 months among SPLC or censored cases (Table 1). Overall, 163 IPLC cases (2.3%) developed a SPLC (Supplementary Fig. 2), with a median time from IPLC diagnosis to SPLC diagnosis of 3.8 years (Supplementary Fig. 3). Smoking pack-years (hazard ratio [HR] = 1.18 per 10 pack-years, 95% confidence interval [CI]: 1.09–1.27, p < 0.001) and smoking intensity (HR = 1.30 per 10 CPD, 95% CI: 1.12–1.51, p < 0.001) were significantly associated with an increased risk of SPLC after adjusting for IPLC age at diagnosis, stage, and histology (Table 2 and Fig. 1A). Participants who met the USPSTF criteria had a nearly twofold increased risk of SPLC (HR = 1.92, 95% CI: 1.39–2.64, p < 0.001). Current smoking status and quit years trended toward having significant associations with SPLC but did not meet the Bonferroni threshold. Other primary variables (e.g., BMI) were not associated with SPLC. Sensitivity analyses using complete cases provided consistent results (Supplementary Table 1).
      Table 2Associations Between SPLC and Participant Characteristics in the Multiethnic Cohort
      CharacteristicsHR (95% CI)P
       Primary analyses
      Smoking status
      NeverReference
      Former1.32 (0.79–2.20)0.284
      Current1.80 (1.07–3.03)0.028
      Smoking per 10 pack-years1.18 (1.09–1.27)<0.001
      Smoking per 10 cigarettes per day1.30 (1.12–1.51)<0.001
      Smoking per 1 quit year
      Smoking quit years were evaluated only among ever smokers (n = 6196).
      0.97 (0.95–0.99)0.010
      Met the USPSTF criteria
      NoReference
      Yes1.92 (1.39–2.64)<0.001
      BMI (per 1 kg/m2)1.02 (0.99–1.05)0.267
      Personal history of cancer
      NoReference
      Yes1.30 (0.93–1.82)0.120
      Family history of lung cancer
      NoReference
      Yes0.82 (0.47–1.42)0.472
       Secondary analyses
      Sex
      FemaleReference
      Male1.24 (0.91–1.70)0.179
      Race/ethnicity
      WhiteReference
      African American1.00 (0.65–1.55)0.989
      Japanese American0.80 (0.52–1.24)0.324
      Latino0.89 (0.53–1.51)0.679
      Native Hawaiian1.09 (0.60–2.00)0.769
      Other0.71 (0.33–1.50)0.370
      Education
      High school or lessReference
      Some college or graduate1.12 (0.81–1.55)0.501
      Postgraduate0.93 (0.53–1.63)0.799
      IPLC surgery
      NoReference
      Yes1.89 (1.16–3.07)0.010
      IPLC radiotherapy
      NoReference
      Yes0.64 (0.41–0.98)0.041
      IPLC chemotherapy
      NoReference
      Yes0.55 (0.35–0.88)0.013
       Covariates
      Age at IPLC diagnosis (per 1 y)1.00 (0.98–1.02)0.841
      IPLC stage
      Local/regionalReference
      Distant0.33 (0.20–0.56)<0.001
      Expanded IPLC stage
      LocalReference
      Regional0.68 (0.48–0.96)0.028
      Distant0.28 (0.16–0.47)<0.001
      IPLC histology
      Squamous cell carcinomaReference
      Adenocarcinoma1.11 (0.76–1.64)0.584
      Large cell carcinoma1.66 (0.80–3.46)0.173
      Small cell carcinoma0.43 (0.13–1.40)0.162
      Other0.65 (0.38–1.13)0.130
      Note: All cause-specific proportional hazards models accounted for the competing risk of death. Variables in the primary and secondary analyses were evaluated in individual cause-specific proportional hazards models adjusting for age at IPLC diagnosis, IPLC histology, and IPLC stage. Among covariates, age at IPLC diagnosis was adjusted for IPLC histology and stage, IPLC histology was adjusted for IPLC age and stage, and IPLC stage was adjusted for IPLC age and histology.
      BMI, body mass index; CI, confidence interval; HR, hazard ratio; IPLC, initial primary lung cancer; SPLC, second primary lung cancer; USPSTF, U.S. Preventive Services Task Force
      a Smoking quit years were evaluated only among ever smokers (n = 6196).
      Figure thumbnail gr1
      Figure 1Forest plots of associations between smoking-related factors and SPLC in the Multiethnic Cohort. The smoking-SPLC associations were evaluated among (A) all IPLC cases (N = 7059) and (B) early-stage (I–III) IPLC cases (N = 2806). Smoking-related data were collected from the baseline questionnaire or 10-year follow-up questionnaire before IPLC diagnosis, if available. Meeting the 2013 USPSTF criteria was determined at IPLC diagnosis. All variables were evaluated in individual cause-specific proportional hazards models accounting for the competing risk of death. Models for all-stage IPLC cases adjusted for age at IPLC diagnosis, IPLC histology, and IPLC stage; models for early-stage IPLC cases adjusted for age at IPLC diagnosis and IPLC histology. CI, confidence interval; HR, hazard ratio; IPLC, initial primary lung cancer; SPLC, second primary lung cancer; USPSTF, U.S. Preventive Services Task Force.
      In the secondary analyses, only the treatment variables demonstrated significant associations with SPLC, including IPLC surgery which was associated with an increased risk of SPLC (HR = 1.89, 95% CI: 1.16–3.07, p = 0.010; Table 2). Other secondary variables such as sex, race/ethnicity, and education did not have significant associations with SPLC, consistent with previous assessments.
      • Han S.S.
      • Rivera G.A.
      • Tammemägi M.C.
      • et al.
      Risk stratification for second primary lung cancer.
      Distant IPLC stage was associated with a reduced risk of SPLC compared with local or regional IPLC (HR = 0.33, 95% CI: 0.20–0.56, p < 0.001), reflecting higher mortality before developing SPLC.
      The subgroup analysis of early-stage IPLC cases revealed that the point estimates and statistical significance for almost all smoking-related variables were heightened (Fig. 1B). Among ever smokers, the SPLC risk estimates were consistent (Supplementary Fig. 4A). Stratified by IPLC histology, the effects of smoking remained largely consistent, although the significance was reduced among those with squamous IPLCs (N = 1401), possibly owing to a smaller sample size (Supplementary Fig. 4B and C). Among advanced-stage IPLC cases, none of the smoking variables had a significant association with SPLC, except for smoking intensity which had an inverted point estimate (HR = 0.57 per 10 CPD, 95% CI: 0.33–0.98; Supplementary Fig. 4D) compared with that in all-stage and early-stage IPLC cases; this inverse association potentially reflects a higher competing risk of mortality—and, hence, a reduced SPLC incidence—among advanced-stage IPLC cases.
      Categorization of smoking pack-years and CPD revealed that the highest levels (≥30 pack-years and ≥30 CPD) conferred the greatest risk of SPLC (Fig. 2A and B). In applying smoothing splines, we confirmed that the linear models offered the best fit for both smoking pack-years and smoking intensity (Supplementary Fig. 5).
      Figure thumbnail gr2
      Figure 2Sensitivity analyses for associations between categorical (A) smoking pack-years and (B) cigarettes per day and SPLC in the Multiethnic Cohort. All risk estimates were generated from cause-specific proportional hazards models adjusting for age at IPLC diagnosis, IPLC histology, and IPLC stage and accounting for the competing risk of death. CI, confidence interval; IPLC, initial primary lung cancer; SPLC, second primary lung cancer.

      PLCO and EPIC: SPLC Validation Cohorts and Meta-Analysis

      The validation PLCO cohort included 3423 IPLC cases and EPIC included 4731 IPLC cases (Supplementary Tables 2 and 3). In PLCO, smoking pack-years (HR = 1.10 per 10 pack-years, 95% CI: 1.04–1.15, p < 0.001), smoking intensity (HR = 1.20 per 10 CPD, 95% CI: 1.06–1.36, p = 0.004), and meeting the USPSTF criteria (HR = 2.09, 95% CI: 1.35–3.24, p = 0.001) were significantly associated with an increased risk of SPLC after adjusting for IPLC age, stage, and histology (Supplementary Table 4 and Fig. 3AC). In EPIC, smoking pack-years (HR = 1.37 per 10 pack-years, 95% CI: 1.11–1.68, p = 0.003) was significantly associated with an increased risk of SPLC after adjusting for IPLC age and histology, whereas smoking intensity (HR = 1.52 per 10 CPD, 95% CI: 0.96–2.41, p = 0.074) and meeting the USPSTF criteria (HR = 2.34, 95% CI: 0.80–6.85; p = 0.120) both trended toward statistical significance in the same directions of the HRs in MEC.
      Figure thumbnail gr3
      Figure 3Meta-analyses of associations between smoking-related factors and SPLC across MEC, PLCO, and EPIC. Cause-specific proportional hazards models accounting for the competing risk of death from all causes were used to evaluate the risk of SPLC by (A) smoking per 10 pack-years, (B) smoking per 10 cigarettes per day, and (C) meeting the 2013 USPSTF screening criteria, adjusting for IPLC age at diagnosis, stage, and histology in MEC and PLCO and by IPLC age at diagnosis and histology in EPIC. CI, confidence interval; EPIC, European Prospective Investigation into Cancer and Nutrition; HR, hazard ratio; IPLC, initial primary lung cancer; MEC, Multiethnic Cohort; PLCO, Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; SPLC, second primary lung cancer; USPSTF, U.S. Preventive Services Task Force.
      When pooling the SPLC associations across all three cohorts through random effects meta-analysis, smoking pack-years (HR = 1.16 per 10 pack-years, 95% CI: 1.06–1.26; pmeta < 0.001), smoking intensity (HR = 1.25 per 10 CPD, 95% CI: 1.14–1.38, pmeta < 0.001), and meeting the USPSTF criteria (HR = 1.99, 95% CI: 1.55–2.57, pmeta < 0.001) were all significantly associated with an increased risk of SPLC (Fig. 3). In contrast, the other primary and secondary variables did not exhibit significant associations with SPLC, with the exception of the IPLC therapies (Supplementary Fig. 6).

      MEC: Smoking Cessation Analysis

      To follow up on the smoking-SPLC association, we evaluated the effect of smoking cessation after IPLC diagnosis on SPLC risk in the MEC subset of 156 participants (Supplementary Fig. 1). Of these, 125 participants (80.1%) who were current smoking at baseline reported having quit smoking at the 10-year follow-up (Supplementary Table 5). Overall, 15 IPLC cases (9.6%) developed a SPLC after the 10-year follow-up (Fig. 4). When adjusting for age at IPLC diagnosis solely (to support model convergence in the small sample size), smoking cessation was associated with an 83% reduction in SPLC risk (HR = 0.17, 95% CI: 0.06–0.47, p < 0.001; Supplementary Table 6).
      Figure thumbnail gr4
      Figure 4Smoking cessation and risk of SPLC in the Multiethnic Cohort (N = 156). Participants in this subset analysis were current smoking at baseline, had 10-year follow-up smoking data, and were diagnosed with an IPLC before follow-up. Participants who reported that they were “former” smoking at 10-year follow-up were classified as undergoing smoking cessation (“yes”), whereas those who reported that they were “current” smoking at 10-year follow-up were classified as not undergoing smoking cessation (“no”). Participants were followed for the development of SPLC after 10-year follow-up. This cumulative incidence plot was generated using Gray’s method, accounting for the competing risk of death from all causes. IPLC, initial primary lung cancer; SPLC, second primary lung cancer.

      Discussion

      In this study, we found that tobacco smoking is a prominent risk factor for SPLC among IPLC cases on the basis of three epidemiologic cohorts. We also revealed in a landmark analysis that smoking cessation after IPLC diagnosis is associated with a substantial reduction in the risk of SPLC. To the best of our knowledge, this is the first population-based study to leverage multiple epidemiologic cohorts in identifying and validating risk factors for SPLC, including tobacco smoking. We evaluated several candidate SPLC risk factors that have not been previously examined (e.g., personal history of cancer, family history of lung cancer) and evaluated detailed smoking exposures through multiple measures, including smoking status, pack-years, intensity, and years since cessation.
      Importantly, these data support tobacco smoking as a modifiable risk factor for SPLC, with smoking cessation after IPLC diagnosis associated with a significant reduction in SPLC risk. Although this effect was observed in a small subset analysis, it lends further support to smoking cessation efforts in patients even after an IPLC diagnosis or treatment. This finding further supports the relationship between tobacco smoking and SPLC,
      Office of the Surgeon General (US), Office on Smoking and Health (US).
      though additional validation of the precise effect is required.
      The smoking-SPLC associations in the literature have been inconsistent, possibly owing to a lack of appropriate statistical methods, small sample sizes, or heterogeneity in the smoking exposures evaluated across studies. The smoking-SPLC relationship was first detailed by Boyle et al.
      • Boyle J.M.
      • Tandberg D.J.
      • Chino J.P.
      • D’Amico T.A.
      • Ready N.E.
      • Kelsey C.R.
      Smoking history predicts for increased risk of second primary lung cancer: a comprehensive analysis.
      who reported that smoking per 10 pack-years was associated with an 8% increased risk of SPLC in ever-smoking patients after definitive surgery. This is in contrast to two other studies which failed to find a smoking-SPLC association.
      • Ripley R.T.
      • McMillan R.R.
      • Sima C.S.
      • et al.
      Second primary lung cancers: smokers versus nonsmokers after resection of stage I lung adenocarcinoma.
      ,
      • Leroy T.
      • Monnet E.
      • Guerzider S.
      • et al.
      Let us not underestimate the long-term risk of SPLC after surgical resection of NSCLC.
      Notably, the latter two studies applied a Fine and Gray subdistribution model which may be underpowered to detect a smoking-SPLC effect,
      • Varadhan R.
      • Weiss C.O.
      • Segal J.B.
      • Wu A.W.
      • Scharfstein D.
      • Boyd C.
      Evaluating health outcomes in the presence of competing risks: a review of statistical methods and clinical applications.
      ,
      • Fine J.P.
      • Gray R.J.
      A proportional hazards model for the subdistribution of a competing risk.
      as smoking is associated with both SPLC (the event of interest) and the competing risk of mortality.
      National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health
      The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General.
      In this analytical setting, a cause-specific hazard model may more accurately estimate the effect of smoking on SPLC risk and is the preferred approach for “causal” (i.e., risk-centered) analyses.
      • Varadhan R.
      • Weiss C.O.
      • Segal J.B.
      • Wu A.W.
      • Scharfstein D.
      • Boyd C.
      Evaluating health outcomes in the presence of competing risks: a review of statistical methods and clinical applications.
      ,
      • Freidlin B.
      • Korn E.L.
      Testing treatment effects in the presence of competing risks.
      Accordingly, when we applied a Fine and Gray model to the MEC data, we found that the smoking effects, while still present, were attenuated (data not shown).
      In stratifying the MEC population by IPLC stage at diagnosis, we found that the smoking effects were especially prominent among participants with an early-stage (I–III) IPLC. However, in participants who were diagnosed with having an advanced IPLC, most of the smoking-related variables did not have a significant association with SPLC, except for smoking intensity which had an inverted point estimate compared with that in all-stage and early-stage IPLC cases. This inverse association is likely owing to a higher competing risk of mortality and, hence, a reduced SPLC incidence among advanced-stage IPLC cases. As described previously, smoking is not only associated with an increased risk of SPLC but also with an increased risk of mortality,
      National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health
      The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General.
      ,
      • Tammemagi C.M.
      • Neslund-Dudas C.
      • Simoff M.
      • Kvale P.
      Smoking and lung cancer survival: the role of comorbidity and treatment.
      ,
      • Fares A.F.
      • Jiang M.
      • Yang P.
      • et al.
      Smoking cessation (SC) and lung cancer (LC) outcomes: a survival benefit for recent-quitters? A pooled analysis of 34,649 International Lung Cancer Consortium (ILCCO) patients.
      and among participants with advanced IPLCs, the competing risk of mortality predominates. However, a definitive conclusion among these participants is precluded given the relatively few number of SPLC events. Regardless, smoking cessation efforts targeted to this population—while perhaps having less impact on the risk of SPLC—could potentially reduce the risk of smoking-associated mortality and should still be explored.
      • Fares A.F.
      • Jiang M.
      • Yang P.
      • et al.
      Smoking cessation (SC) and lung cancer (LC) outcomes: a survival benefit for recent-quitters? A pooled analysis of 34,649 International Lung Cancer Consortium (ILCCO) patients.
      Interestingly, the 2013 USPSTF criteria, a composite measure of smoking and age that identifies individuals at high risk of IPLC, were a significant indicator of a twofold increased risk of SPLC. This effect was largely driven by the risk conferred from a heavy smoking history, as observed in the categorical smoking plots. Although the smoking-SPLC associations were significant, the magnitude and significance of the smoking effects on SPLC are smaller than those reported for IPLC.
      • Alberg A.J.
      • Samet J.M.
      Epidemiology of lung cancer.
      • Remen T.
      • Pintos J.
      • Abrahamowicz M.
      • Siemiatycki J.
      Risk of lung cancer in relation to various metrics of smoking history: a case-control study in Montreal.
      • Pesch B.
      • Kendzia B.
      • Gustavsson P.
      • et al.
      Cigarette smoking and lung cancer—relative risk estimates for the major histological types from a pooled analysis of case-control studies.
      • O’Keeffe L.M.
      • Taylor G.
      • Huxley R.R.
      • Mitchell P.
      • Woodward M.
      • Peters S.A.E.
      Smoking as a risk factor for lung cancer in women and men: a systematic review and meta-analysis.
      This attenuation is partly because the comparison of SPLC cases with non-SPLC cases among patients with lung cancer likely represents a comparison of heavier and lighter smoking histories, whereas the comparison of IPLC cases with non-cases more likely represents a comparison of ever-smoking and never-smoking histories. Furthermore, to develop a SPLC, an individual must first survive the IPLC long enough to develop another lung cancer, which itself can carry a long latency period.
      • de Bruin E.C.
      • McGranahan N.
      • Mitter R.
      • et al.
      Spatial and temporal diversity in genomic instability processes defines lung cancer evolution.
      Thus, although there is a biological rationale for tobacco smoke carcinogens inducing SPLC oncogenesis through similar DNA-damaging mechanisms as with IPLC,
      Centers for Disease Control and Prevention (US)
      National Center for Chronic Disease Prevention and Health Promotion (US); Office on Smoking and Health (US).
      it seems that the effect of tobacco smoking, while present, is modulated somewhat with SPLC.
      BMI, personal history of cancer, and family history of lung cancer—while protective or risk factors for IPLC
      • Duan P.
      • Hu C.
      • Quan C.
      • et al.
      Body mass index and risk of lung cancer: systematic review and dose–response meta-analysis.
      • Ang L.
      • Chan C.P.Y.
      • Yau W.P.
      • Seow W.J.
      Association between family history of lung cancer and lung cancer risk: a systematic review and meta-analysis.
      • Cassidy A.
      • Myles J.P.
      • van Tongeren M.
      • et al.
      The LLP risk model: an individual risk prediction model for lung cancer.
      • Mery C.M.
      • Pappas A.N.
      • Bueno R.
      • et al.
      Relationship between a history of antecedent cancer and the probability of malignancy for a solitary pulmonary nodule.
      —had negligible associations with SPLC, as did demographics including sex, race/ethnicity, and education. This study confirmed IPLC age at diagnosis, histology, and stage as relevant predictors of SPLC, which were previously identified in a large, population-based cohort.
      • Han S.S.
      • Rivera G.A.
      • Tammemägi M.C.
      • et al.
      Risk stratification for second primary lung cancer.
      IPLC surgery and chemotherapy had significant associations with SPLC as risk and protective factors, respectively, in the meta-analyses. However, these effects were driven largely by MEC and were not observed in PLCO. It is possible that these effects are not directly associated with the therapies themselves but perhaps mediated through mortality, as IPLC surgeries are typically performed in the early-stage setting and chemotherapies reserved for more advanced disease. Thus, these treatment effects should be interpreted with caution.
      Despite its strengths, this study has several limitations. MEC includes a diverse population of subjects, but it enrolled lower rates of individuals with a current smoking status compared with national surveys at the time of enrollment,
      • Kolonel L.N.
      • Henderson B.E.
      • Hankin J.H.
      • et al.
      A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics.
      though these rates were comparable to the general U.S. population in 2018.
      • Creamer M.R.
      • Wang T.W.
      • Babb S.
      • et al.
      Tobacco product use and cessation indicators among adults—United States, 2018.
      Furthermore, validation of the smoking-related findings in two independent cohorts—which consisted of distinct study populations from various geographic regions—revealed consistent results. EPIC, although a sizable cohort, contained few SPLC events and lacked data on certain secondary variables. It is possible that SPLC cases were not fully captured owing to different cohort surveillance strategies between Europe and the United States. Nonetheless, these deficiencies were accounted for appropriately in the meta-analyses using random effects models. Demographic and environmental data were collected through self-reported questionnaires in all cohorts; thus, misclassification is possible, but the consistency of the SPLC associations strengthens these findings. The smoking cessation analysis consisted of a small subset of MEC participants and requires further validation in independent cohorts, which is currently underway. Finally, one relevant question concerns the relationship between tobacco smoking and overall survival in patients with IPLC, specifically regarding the impact of SPLC on survival and how tobacco smoking contributes to survival differences. Future directions should aim to elucidate these relationships, which are beyond the scope of the present study.
      In summary, tobacco smoking is a risk factor for SPLC among patients with lung cancer in multiple large epidemiologic cohorts with long-term follow-up. Smoking cessation after an IPLC diagnosis may reduce the risk of SPLC. Comprehensive risk models for SPLC that incorporate relevant risk factors, including tobacco smoking, are needed to identify IPLC cases at high risk of SPLC and guide the development of evidence-based SPLC surveillance and screening strategies.

      Acknowledgments

      This work was supported by the National Institutes of Health (1R37CA226081, U01 CA164973) and a Stanford Medical Scholars research grant. The funders had no role in the design and conduct of the study; management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Where authors are identified as personnel of the International Agency for Research on Cancer/WHO, the authors alone are responsible for the views expressed in this article and do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/WHO. Cancer incidence data have been provided by the Alabama Statewide Cancer Registry, Arizona Cancer Registry, Colorado Central Cancer Registry, District of Columbia Cancer Registry, Georgia Cancer Registry, Hawaii Cancer Registry, Cancer Data Registry of Idaho, Maryland Cancer Registry, Michigan Cancer Surveillance Program, Minnesota Cancer Surveillance System, Missouri Cancer Registry, Nevada Central Cancer Registry, Ohio Cancer Incidence Surveillance System, Pennsylvania Cancer Registry, Texas Cancer Registry, Utah Cancer Registry, Virginia Cancer Registry, and Wisconsin Cancer Reporting System. All are supported in part by funds from the Center for Disease Control and Prevention, National Program for Central Registries, local states or by the National Cancer Institute, Surveillance, Epidemiology, and End Results program. The results reported here and the conclusions derived are the sole responsibility of the authors.

      Supplementary Data

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          Ignoring the effects of smoking on overall survival, cancer-related survival, or toxicity from cancer treatment is no longer scientifically or ethically acceptable. Robust evidence reveals that smoking by patients with cancer and survivors causes adverse outcomes including increased overall and cancer-related mortality.1 Smoking cessation after a cancer diagnosis is associated with improved overall survival, and the survival benefits from smoking cessation extend to noncancer outcomes.2 Despite the strong evidence base that smoking can alter the primary or secondary objectives for virtually all clinical trial designs, relatively few clinical trials have evaluated on how smoking or cessation affects clinical outcomes.
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