Assessment of Lung Cancer Risk Among Smokers for Whom Annual Screening Is Not Recommended

Charles Faselis; Joel A Nations; Charity J Morgan; Jared Antevil; Jeffrey M Roseman; Sijian Zhang; Gregg C Fonarow; Helen M Sheriff; Gregory D Trachiotis; Richard M Allman; Prakash Deedwania; Qing Zeng-Trietler; Daniel D Taub; Amiya A Ahmed; George Howard; Ali Ahmed

doi:10.1001/jamaoncol.2022.2952

. 2022 Jul 28;8(10):1428–1437. doi: 10.1001/jamaoncol.2022.2952

Assessment of Lung Cancer Risk Among Smokers for Whom Annual Screening Is Not Recommended

Charles Faselis ^1,^2,^3,^✉, Joel A Nations ^1,³, Charity J Morgan ^1,⁴, Jared Antevil ^1,³, Jeffrey M Roseman ⁵, Sijian Zhang ¹, Gregg C Fonarow ⁶, Helen M Sheriff ^1,², Gregory D Trachiotis ^1,^7,⁸, Richard M Allman ^2,⁹, Prakash Deedwania ^1,¹⁰, Qing Zeng-Trietler ^1,², Daniel D Taub ¹, Amiya A Ahmed ¹¹, George Howard ⁴, Ali Ahmed ^1,^2,^12,^✉

¹Veterans Affairs Medical Center, Washington, DC

²Department of Medicine, School of Medicine, George Washington University, Washington, DC

³Department of Medicine, School of Medicine, Uniformed Services University, Washington, DC

⁴Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham

⁵Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham

⁶Department of Medicine, School of Medicine, University of California, Los Angeles, Los Angeles

⁷Department of Surgery, School of Medicine, George Washington University, Washington, DC

⁸Department of Biomedical Engineering, School of Engineering and Applied Science, George Washington University, Washington, DC

⁹Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham

¹⁰Department of Medicine, School of Medicine, University of California, San Francisco, San Francisco

¹¹Department of Medicine, School of Medicine, Yale University, New Haven, Connecticut

¹²Department of Medicine, School of Medicine, Georgetown University, Washington, DC

Accepted for Publication: May 31, 2022.

Published Online: July 28, 2022. doi:10.1001/jamaoncol.2022.2952

Correction: This article was corrected on September 1, 2022, to fix typographical errors in the Abstract and an author’s affiliations.

^✉

Corresponding Author: Ali Ahmed, MD, MPH (ali.ahmed@va.gov), and Charles Faselis, MD (charles.faselis@va.gov), VA Medical Center, 50 Irving St NW, Washington, DC 20422.

Author Contributions: Drs A. Ahmed and Morgan had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Faselis, Trachiotis, Deedwania, Taub, Howard, A. Ahmed.

Acquisition, analysis, or interpretation of data: Faselis, Nations, Morgan, Antevil, Roseman, Zhang, Fonarow, Sheriff, Allman, Zeng-Trietler, A.A. Ahmed, A. Ahmed.

Drafting of the manuscript: Faselis, Morgan, Trachiotis, Zeng-Trietler, A. Ahmed.

Critical revision of the manuscript for important intellectual content: Faselis, Nations, Morgan, Antevil, Roseman, Zhang, Fonarow, Sheriff, Trachiotis, Allman, Deedwania, Taub, A.A. Ahmed, Howard, A. Ahmed.

Statistical analysis: Nations, Morgan, Roseman, Zhang, A. Ahmed.

Obtained funding: Faselis, A. Ahmed.

Administrative, technical, or material support: Faselis, Sheriff, Taub, Howard, A. Ahmed.

Supervision: Faselis, Trachiotis, Deedwania, A. Ahmed.

Conflict of Interest Disclosures: Dr Fonarow reported being Associate Section Editor for JAMA Cardiology and receiving consulting fees from Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Janssen, Medtronic, Merck, and Novartis. Dr A. Ahmed reported being primary investigator and a coinvestigator in multiple National Institutes of Health– and Veterans Administration Office of Research and Development–funded projects, having paid full-time employment at the Washington DC Veterans Affairs Medical Center, and unpaid faculty appointments at George Washington University and Georgetown University, all in Washington DC. No other disclosures were reported.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, the NHLBI, the Department of Veterans Affairs, or researchers who conducted the Cardiovascular Health Study.

^✉

Corresponding author.

PMCID: PMC9335253 PMID: 35900734

Key Points

Question

What is the risk of lung cancer among smokers for whom annual low-dose computed tomography screening is not recommended?

Findings

In this cohort study of 4279 individuals 65 years and older who were followed up for a median (IQR) of 13.3 (7.9-18.8) years, former smokers with a 20 pack-year or greater smoking history who quit 15 or more years before baseline and current smokers with less than 20 pack-years of smoking (2 groups not recommended for lung cancer screening) had a 10-fold greater risk of lung cancer than never smokers.

Meaning

These findings suggest that there is a need to develop and test prediction models to identify high-risk subsets of these smokers for lung cancer screening and highlight the importance of abstinence and early cessation.

Abstract

Importance

The US Preventive Services Task Force does not recommend annual lung cancer screening with low-dose computed tomography (LDCT) for adults aged 50 to 80 years who are former smokers with 20 or more pack-years of smoking who quit 15 or more years ago or current smokers with less than 20 pack-years of smoking.

Objective

To determine the risk of lung cancer in older smokers for whom LDCT screening is not recommended.

Design, Settings, and Participants

This cohort study used the Cardiovascular Health Study (CHS) data sets obtained from the National Heart, Lung and Blood Institute, which also sponsored the study. The CHS enrolled 5888 community-dwelling individuals aged 65 years and older in the US from June 1989 to June 1993 and collected extensive baseline data on smoking history. The current analysis was restricted to 4279 individuals free of cancer who had baseline data on pack-year smoking history and duration of smoking cessation. The current analysis was conducted from January 7, 2022, to May 25, 2022.

Exposures

Current and prior tobacco use.

Main Outcomes and Measures

Incident lung cancer during a median (IQR) of 13.3 (7.9-18.8) years of follow-up (range, 0 to 22.6) through December 31, 2011. A Fine-Gray subdistribution hazard model was used to estimate incidence of lung cancer in the presence of competing risk of death. Cox cause-specific hazard regression models were used to estimate hazard ratios (HRs) and 95% CIs for incident lung cancer.

Results

There were 4279 CHS participants (mean [SD] age, 72.8 [5.6] years; 2450 [57.3%] women; 663 [15.5%] African American, 3585 [83.8%] White, and 31 [0.7%] of other race or ethnicity) included in the current analysis. Among the 861 nonheavy smokers (<20 pack-years), the median (IQR) pack-year smoking history was 7.6 (3.3-13.5) pack-years for the 615 former smokers with 15 or more years of smoking cessation, 10.0 (5.3-14.9) pack-years for the 146 former smokers with less than 15 years of smoking cessation, and 11.4 (7.3-14.4) pack-years for the 100 current smokers. Among the 1445 heavy smokers (20 or more pack-years), the median (IQR) pack-year smoking history was 34.8 (26.3-48.0) pack-years for the 516 former smokers with 15 or more years of smoking cessation, 48.0 (35.0-70.0) pack-years for the 497 former smokers with less than 15 years of smoking cessation, and 48.8 (31.6-57.0) pack-years for the 432 current smokers. Incident lung cancer occurred in 10 of 1973 never smokers (0.5%), 5 of 100 current smokers with less than 20 pack-years of smoking (5.0%), and 26 of 516 former smokers with 20 or more pack-years of smoking with 15 or more years of smoking cessation (5.0%). Compared with never smokers, cause-specific HRs for incident lung cancer in the 2 groups for whom LDCT is not recommended were 10.54 (95% CI, 3.60-30.83) for the current nonheavy smokers and 11.19 (95% CI, 5.40-23.21) for the former smokers with 15 or more years of smoking cessation; age, sex, and race–adjusted HRs were 10.06 (95% CI, 3.41-29.70) for the current nonheavy smokers and 10.22 (4.86-21.50) for the former smokers with 15 or more years of smoking cessation compared with never smokers.

Conclusions and Relevance

The findings of this cohort study suggest that there is a high risk of lung cancer among smokers for whom LDCT screening is not recommended, suggesting that prediction models are needed to identify high-risk subsets of these smokers for screening.

This cohort study of data on participants in the Cardiovascular Health Study assesses risk of lung cancer in smokers for whom low-density computed tomographic screening is not recommended.

Introduction

Lung cancer is the leading cause of cancer death in the US.¹ Tobacco use is the single largest cause of preventable lung cancer, the risk of which is directly related to the amount and duration of smoking and is inversely related to duration of smoking cessation.^2,3 Screening smokers who are at high risk with low-dose computed tomography (LDCT) may reduce lung cancer mortality.^4,5,6 The 2021 US Preventive Services Task Force recommended annual lung cancer screening with LDCT for adults aged 50 to 80 years who have a 20 pack-year smoking history and currently smoke or have quit within the past 15 years.⁷ The guideline did not recommend LDCT screening for former smokers with a 20 pack-year or greater smoking history who quit 15 or more years ago or for current smokers with a smoking history of 20 pack-years or less.⁷ The objective of the current study was to examine the risk of lung cancer, accounting for the competing risk of death, among smokers for whom LDCT screening is not currently recommended.

Methods

Study Design, Setting, Participants, and Study Size

The Cardiovascular Health Study (CHS), sponsored by the National Heart, Lung, and Blood Institute (NHLBI), is an ongoing prospective, population-based study of risk factors for cardiovascular disease in community-dwelling Medicare-eligible older adults in the US.⁸ Between June 1989 and June 1993,⁹ the study enrolled 5888 individuals aged 65 years or older from 4 US communities. Informed consent was obtained from each participant. Extensive interviews and clinical examinations during home and clinic visits were conducted to assess and collect data on baseline psychological and life-style factors, medical history, medications, vital signs, and laboratory data.⁸ The current study is based on a deidentified copy of the CHS data sets obtained from the Biologic Specimen and Data Repository Information Coordinating Center that includes 5795 participants who consented to be included in this database. Established by the NHLBI in 2008, the Biologic Specimen and Data Repository Information Coordinating Center prepares data sets from NHLBI-sponsored studies for public use to maximize their scientific value.^10,11,12,13 We excluded 827 participants from the data set with a history of cancer at baseline and 10 with missing history. From the remaining 4958 participants, we excluded 168 patients with missing data on pack-year smoking history and 1 former smoker with missing data on duration of cessation, 230 never smokers exposed to passive smoking, and 280 participants with missing data on hospitalization. The final sample size consisted of 4279 participants (Figure 1). The current analysis was conducted from January 7, 2022, to May 25, 2022. The study was approved by the Institutional Review Board of the Veterans Affairs Medical Center, Washington, DC. Informed consent was not required because of the use of publicly available, deidentified patient information. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline on cohort studies.

Study Exposure and Other Baseline Measurements

Extensive information about cigarette smoking was collected at baseline from all CHS participants as a part of personal history using a self-administered questionnaire, which was left with the participant at the end of the home visit with instruction to complete and bring to the clinic visit.¹⁴ The completed forms were reviewed by CHS interviewers, and errors or inconsistent responses were corrected after discussion with the participant.¹⁴ Relevant questions related to smoking included: (1) How old were you when you first started to smoke cigarettes? (2) On the average of the entire time you smoked, how many cigarettes did you smoke per day? and (3) If you have stopped smoking cigarettes completely, how old were you when you stopped?^15,16

Pack-years of cigarette smoking were estimated by multiplying the number of packs of 20 cigarettes smoked per day by the the number of years smoked at this level, summed over all levels of smoking. Study participants were categorized into 7 categories based on pack-years and years of smoking cessation, as shown in Figure 1. There were 1973 never smokers. The 861 nonheavy smokers included 761 former smokers (615 quit ≥15 and 146 quit <15 years ago), and the 1445 heavy smokers included 1013 former smokers (516 quit ≥15 and 497 quit <15 years ago; Figure 1). We have used the word “nonheavy,” as opposed to “light” to describe smokers with less than 20 pack-year smoking history because a 10 to 15 pack-year smoking history may not be considered light.

Baseline cardiovascular disease was adjudicated by CHS investigators, the details of which have been previously published.¹⁷ Briefly, self-reports were confirmed by baseline examination, medical record reviews, surveys of treating physicians, and postbaseline surveillance. Information about annual household income was collected at baseline from all CHS participants during the eligibility phase.¹⁸ Information about physical activity is expressed as metabolic equivalent task-minutes and were calculated from kilocalories of energy expended per week assessed using a modified Minnesota Leisure-Time Activities questionnaire.^19,20 General health was self-reported as excellent, very good, good, fair, or poor.²¹

Study Outcomes

Our primary outcome was incident lung cancer during a median (IQR) of 13.3 (7.9-18.8) years of follow-up (range, 0 to 22.6 years) from study baseline up to December 31, 2011. Information on incident lung cancer was obtained from hospitalization data, which was collected by twice-yearly calls to study participants and reviewed by CHS field centers.²² International Classification of Diseases, Ninth Revision (ICD-9) codes from those hospitalizations are available from the CHS ICD-9 folder. We used both primary and secondary discharge diagnosis codes (ICD-9 codes 162.x for malignant neoplasm of trachea bronchus and lung) to identify lung cancer, and the date of first mention was used to define time to event. The secondary discharge diagnosis codes allowed us to identify patients who were not hospitalized for lung cancer. All-cause mortality was centrally adjudicated by the CHS Events Subcommittee that includes CHS investigators from the field centers, the coordinating center, and the NHLBI project office.²²

Statistical Analysis

Baseline characteristics were compared using Pearson χ² for categorical variables and 1-way analysis of variance test for continuous variables. Continuous variables that were not normally distributed were presented as median (IQR) and between-group differences were tested using independent-samples Kruskal-Wallis tests. We used a Fine-Gray subdistribution hazard model to estimate marginal probability of incident lung cancer and to compare cumulative incidence of lung cancer accounting for death as a competing risk.²³ In the model, individuals with competing events (eg, death) remained at risk for the primary event (lung cancer); because Fine-Gray models are not considered suitable for estimating associations,^23,24,25,26 we used Cox cause-specific hazard regression models as our primary approach for the estimation of hazard ratios (HRs) and 95% CIs for incident lung cancer. In the model, time to first mention of an ICD code for lung cancer as a primary or secondary discharge diagnosis was used as the time to event, and those without lung cancer were censored at death or study end, whichever came first. Despite some indication of nonproportionality, we used the Cox model, as the HR estimates from Cox models provide the weighted average of the time-varying HRs, which is a convenient summary of the treatment effect during the follow-up.²⁷ For a full understanding of the association between smoking and lung cancer, we also estimated subdistribution HRs from the Fine-Gray model.²³ Considering the potential diagnosis-to-hospitalization gap,²⁸ we used logistic regression models to estimate odds ratios (ORs) and 95% CIs for incident lung cancer. In all regression models, we estimated associations in 3 steps: unadjusted; adjusted for age, sex, and race; and additional adjustments for income, body mass index, physical activity, chronic obstructive pulmonary disease, and self-reported general health. For all analyses, never smokers were used as the reference. All statistical tests were 2-tailed and P < .05 was considered statistically significant. Statistical analyses were conducted using IBM SPSS Statistics software for Windows, version 28.0 (IBM Corp), and SAS for Windows, version 9.4 (SAS Institute, Inc).

Results

Baseline Characteristics

There were 4279 CHS participants (mean [SD] age, 72.8 [5.6] years; 2450 [57.3%] women and 1829 [42.7%] men; and 663 [15.5%] African American, 3585 [83.8%] White, and 31 [0.7%] of other race or ethnicity [including Native American, Alaska Native, Asian or Pacific Islander, and other race; because of the small numbers in these groups, these data were not provided in the public-use copy of the CHS data]) included in the current analysis (Table 1). Smoking history among 861 nonheavy smokers (<20 pack-years) included a median (IQR) of 7.6 (3.3-13.5) pack-years (median [IQR] cigarettes per day, 10.0 [5.0-11.0]; median [IQR] cessation duration, 33.0 [24.0-41.0] years) for the 615 former smokers with a smoking duration of 15 or more years, a median (IQR) of 10.0 (5.3-14.9) pack-years (median [IQR] cigarettes per day, 5.0 [3.0-9.3]; median [IQR] cessation duration, 9.0 [4.0-11.0] years) for the 146 former smokers with a smoking duration of less than 15 years, and a median (IQR) of 11.4 (7.3-14.4) pack-years (median [IQR] cigarettes per day, 5.0 [4.0-7.0]) for the 100 current smokers. Smoking history among 1445 heavy smokers (≥20 pack-years) included a median (IQR) of 34.8 (26.3-48.0) pack-years (median [IQR] cigarettes per day, 20.0 [20.0-30.0]; median [IQR] cessation duration, 22.0 [18.3-28.0] years) for those who smoked 15 years or longer, a median (IQR) of 48.0 (35.0-70.0) pack-years (median [IQR] cigarettes per day, 20.0 [17.0-30.0]; median [IQR] cessation duration, 7.0 [3.0-11.0] years) for those who smoked less than 15 years, and a median (IQR) 48.8 (31.6-57.0) pack-years (median [IQR] cigarettes per day, 20.0 [12.0-20.0]) for current smokers.

Table 1. Demographic and Clinical Characteristics and Smoking History Among Older Adults Free of Cancer at Baseline (N = 4279).

Characteristic	Pack-year smoking history, No. (%)							P value
	Never smokers (n = 1973)	<20 pack-years (n = 861)			≥20 pack-years (n = 1445)
		Former smokers (n = 761), duration of smoking cessation		Current smokers (n = 100)	Former smokers (n = 1013), duration of smoking cessation		Current smokers (n = 432)
		≥15 y (n = 615)	<15 y (n = 146)	Current smokers (n = 100)	≥15 y (n = 516)	<15 y (n = 497)	Current smokers (n = 432)
Age, mean (SD), y	73.7 (6.0)	72.7 (5.2)	71.1 (5.2)	71.2 (5.2)	73.1 (5.4)	71.7 (4.7)	70.6 (4.5)	<.001
Sex
Women	1402 (71.1)	285 (46.3)	104 (71.2)	71 (71.0)	130 (25.2)	211 (42.5)	247 (57.2)	<.001
Men	571 (28.9)	330 (53.7)	42 (28.8)	29 (29.0)	386 (74.8)	286 (57.5)	185 (42.8)	<.001
Race and ethnicity, No. (%)
African American	325 (16.5)	88 (14.3)	37 (25.3)	41 (41.0)	39 (7.6)	66 (13.3)	67 (15.5)	<.001
White	1628 (82.5)	525 (85.4)	108 (74.0)	57 (57.0)	475 (92.1)	428 (86.1)	364 (84.3)
Other^a	20 (1.0)	2 (0.3)	1 (0.7)	2 (2.0)	2 (0.4)	3 (0.6)	1 (0.2)
Smoking history, pack-years
Mean (SD)	NA	8.4 (5.7)	10.1 (5.3)	10.8 (4.9)	41.2 (21.6)	55.9 (30.0)	50.8 (26.7)	<.001
Median (IQR)	NA	7.6 (3.3-13.5)	10.0 (5.3-14.9)	11.4 (7.3-14.4)	34.8 (26.3-48.0)	48.0 (35.0-70.0)	48.8 (31.6-57.0	<.001
Duration of smoking cessation, y
Mean (SD)	NA	32.9 (10.7)	7.9 (4.2)	NA	23.8 (7.0)	6.9 (4.3)	NA	<.001
Median (IQR)	NA	33.0 (24.0-41.0)	9.0 (4.0-11.0)	NA	22.0 (18.3-28.0)	7.0 (3.0-11.0)	NA	<.001
Cigarettes smoked per day, median (IQR)	NA	10.0 (5.0-11.0)	5.0 (3.0-9.3)	5.0 (4.0-7.0)	20.0 (20.0-30.0)	20.0 (17.0-30.0)	20.0 (12.0-20.0)	<.001^b
Alcohol consumption, median (IQR) drinks/wk	0.0 (0.0-0.25)	0.04 (0.0-2.0)	0.04 (0.0-1.6)	0.01 (0.0-1.3)	0.27 (0.0-4.0)	0.02 (0.0-2.0)	0.25 (0.0-3.0)	<.001^b
Married, No. (%)	1217 (61.7)	454 (73.9)	93 (63.7)	44 (44.0)	394 (76.4)	346 (69.6)	258 (60)	<.001
Annual household income ≥$25 000, No. (%)	654 (33.1)	269 (43.7)	53 (36.3)	22 (22.0)	228 (44.2)	163 (32.8)	116 (26.9)	<.001
BMI, mean (SD)	26.7 (4.2)	26.6 (4.0)	26.9 (3.9)	25.9 (4.1)	27.0 (3.6)	26.9 (3.9)	25.4 (3.9)	<.001
Fair to poor self-reported general health, No. (%)	487 (24.7)	118 (19.2)	46 (31.5)	28 (28.0)	112 (21.7)	148 (29.8)	131 (30.3)	<.001
Physical activity, median (IQR), MET-minutes per week^c	848.1 (301.8-1777.4)	1005.4 (383.7-2168.4)	779.9 (197.8-1866.6)	727.8 (200.0-1722.2)	1003.1 (351.2-1964.8)	757.4 (252.7-1526.0)	834.0 (277.1-1764.7)	<.001^b
History of hypertension, No., (%)	1242 (62.9)	340 (55.3)	86 (58.9)	56 (56.0)	305 (59.1)	294 (59.2)	228 (52.8)	.001
Coronary artery disease, No. (%)	343 (17.4)	124 (20.2)	27 (18.5)	16 (16.0)	137 (26.6)	123 (24.7)	70 (16.2)	<.001
Diabetes, No., (%)	308 (15.8)	94 (15.4)	24 (16.8)	10 (10.2)	112 (21.7)	95 (19.2)	58 (13.5)	.003
COPD, No, (%)	199 (10.1)	59 (9.6)	18 (12.3)	13 (13.0)	78 (15.1)	93 (18.7)	74 (17.1)	<.001
Serum C-reactive protein, median (IQR), mg/dL	2.4 (1.2-4.4)	2.2 (1.0-3.9)	2.8 (1.5-4.5)	3.7 (1.5-7.3)	2.6 (1.3-4.5)	3.1 (1.7-6.2)	3.4 (1.8-6.8)	<.001

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Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); COPD, chronic obstructive pulmonary disease; MET, metabolic equivalent task; NA, not applicable.

SI conversion factor: To convert serum C-reactive protein to mg/L, multiply by 10.

^{^a}

Other races inlcuded Native American, Alaska Native, Asian or Pacific Islander, and other races. Because of the small numbers in these groups, these data were not provided in the public-use copy of the Cardiovascular Health Study data.

^{^b}

P value comparing median values are based on independent-samples Kruskal-Wallis tests.

^{^c}

MET was calculated from baseline kilocalories of energy expended per week based on leisure-time physical activity that evaluated frequency and duration of 15 different activities during a 2 week period. One MET is the resting energy expenditure, walking at 3 METs means spending 3 time more energy than resting, and walking at 3 METs for 20 minutues would be 3 × 20 or 60 MET-minutes.

Lung Cancer Among Smokers for Whom Annual Screening Is Not Recommended

During a median (IQR) of 13.3 (7.9-18.8) years of follow-up (range, 0 to 22.6 years), incident lung cancer occurred in 10 of 1973 never smokers (0.5%), 5 of 100 current nonheavy smokers (5.0%), and 26 of 516 former heavy smokers with 15 or more years of smoking cessation (5.0%) (Table 2). Unadjusted cumulative incidences of lung cancer accounting for competing risk of death based on Fine-Gray subdistribution hazard model are shown in Figure 2 and the eFigure in the Supplement. Median (IQR) times to event from study baseline among those with incident lung cancer were 5.3 (3.5-10.0) years for never smokers, 7.0 (4.8-8.2) years for current nonheavy smokers, and 5.8 (3.9-13.2) years for former heavy smokers with 15 or more years of smoking cessation (Table 2).

Table 2. Risk of Lung Cancer in Older Adults Free of Cancer at Baseline by Smoking and Smoking Cessation History (N = 4279).

Outcome	Amount and duration of smoking in pack-years
	Never smokers (n = 1973)	<20 Pack-years (n = 861)			≥20 Pack-years (n = 1445)
		Former smokers (n = 761)		Current smokers (n = 100)	Former smokers (n = 758)		Current smokers (n = 432)
		Quit ≥15 y (n = 615)	Quit <15 y (n = 146)	Current smokers (n = 100)	Quit ≥15 y (n = 516)	Quit <15 y (n = 497)	Current smokers (n = 432)
Baseline exposure
Smoking history, median (IQR), pack-years	NA	7.6 (3.3-13.5)	10.0 (5.3-14.9)	11.4 (7.3-14.4)	34.8 (26.3-48.0)	48.0 (35.0-70.0)	48.8 (31.6-57.0)
Smoking cessation, median (IQR), y	NA	33.0 (24.0-41.0)	9.0 (4.0-11.0)	0.0 (0.0)	22.0 (18.3-28.0)	7.0 (3.0-11.0)	9.0 (0.0)
Incident lung cancer, No. (%)	10 (0.5)	10 (1.6)	2 (1.4)	5 (5.0)	26 (5.0)	50 (10.1)	70 (16.2)
Time to event among those with incident lung cancer, median (IQR), y	5.3 (3.5-10.0)	7.3 (5.5-15.2)	9.7^a	7.0 (4.8-8.2)	5.8 (3.9-13.2)	7.6 (4.1-12.7)	6.8 (3.5-10.6)
Cause-specific hazard of lung cancer based on Cox regression model, HR (95% CI)
Unadjusted	1 [Reference]	3.22 (1.34-7.73)	2.64 (0.58-12.04)	10.54 (3.60-30.83)	11.19 (5.40-23.21)	23.51 (11.92-43.36)	39.29 (20.24-76.25)
Adjusted for age, sex, and race	1 [Reference]	3.05 (1.26-7.36)	2.66 (0.58-12.17)	10.06 (3.41-29.70)	10.22 (4.86-21.50)	22.59 (11.36-44.93)	39.95 (20.14-76.86)
Multivariable-adjusted^b	1 [Reference]	3.09 (1.28-7.45)	2.62 (0.57-12.01)	9.35 (3.15-27.69)	10.49 (4.98-22.08)	22.07 (11.08-43.97)	36.15 (18.42-70.93)
Subdistribution hazard of lung cancer based on Fine-Gray regression model, HR (95% CI)
Unadjusted	1 [Reference]	3.22 (1.34-7.73)	2.71 (0.60-12.38)	10.12 (3.46-29.65)	10.18 (4.91-21.12)	20.82 (10.55-41.06)	34.74 (17.90-67.43)
Adjusted for age, sex, and race	1 [Reference]	3.10 (1.28-7.51)	2.46 (0.54-11.21)	8.84 (3.08-25.37)	9.91 (4.66-21.05)	19.51 (9.75-39.07)	31.82 (16.26-62.29)
Multivariable-adjusted^b	1 [Reference]	3.08 (1.27-7.45)	2.46 (0.54-11.19)	8.39 (2.94-23.95)	10.07 (4.74-21.43)	19.76 (9.88-39.52)	30.37 (15.42-59.84)
Odds of lung cancer based on binary logistic regression model, OR (95% CI)
Unadjusted	1 [Reference]	3.25 (1.34-7.83)	2.73 (0.59-12.56)	10.33 (3.46-30.82)	10.42 (5.00-21.74)	21.96 (11.05-43.63)	37.96 (19.39-74.33)
Adjusted for age, sex, and race	1 [Reference]	3.11 (1.28-7.55)	2.46 (0.53-11.35)	8.91 (2.96-26.84)	10.12 (4.77-21.48)	20.47 (10.20-41.06)	34.55 (17.50-68.18)
Multivariable-adjusted^b	1 [Reference]	3.09 (1.27-7.49)	2.45 (0.53-12.35)	8.44 (2.79-25.54)	10.31 (4.85-21.91)	20.83 (10.36-41.88)	33.03 (16.65-68.53)

Open in a new tab

Abbreviation: HR, hazard ratio; OR, odds ratio.

^{^a}

No IQR was available for this group.

^{^b}

Additional variables included income, body mass index, physical activity (metabolic equivalent task-minutes per week), chronic obstructive pulmonary disease, and self-reported general health fair to poor.

Figure 2. — Cumulative incidence function estimates of lung cancer in the presence of the single competing risk of all-cause death before lung cancer, based on a Fine-Gray subdistribution hazard function model, by pack-year smoking history and duration of smoking cessation.

Compared with never smokers, unadjusted cause-specific HRs for incident lung cancer were 10.54 (95% CI, 3.60-30.83) for current nonheavy smokers and 11.19 (95% CI, 5.40-23.21) for former heavy smokers with 15 or more years of smoking cessation (Table 2). Age, sex, and race–adjusted cause-specific HRs were 10.06 (95% CI, 3.41-29.70) for current nonheavy smokers and 10.22 (95% CI, 4.86-21.50) for former heavy smokers with 15 or more years of smoking cessation, which remained unchanged after multivariable adjustment for other baseline characteristics (Table 2).

Lung Cancer Among Older Smokers for Whom Annual Screening Is Recommended

Among the 1445 heavy smokers (≥20 pack-year smoking history), incident lung cancer occurred in 70 of 432 current smokers (16.2%) and 50 of 497 former smokers with less than 15 years of cessation (10.1%) (Table 2). Unadjusted cumulative incidence of lung cancer accounting for competing risk of death based on Fine-Gray subdistribution hazard model is shown in Figure 2. Compared with never smokers, HRs for incident lung cancer in those for whom screening is recommended were 23.51 (11.92-43.36) among former heavy smokers with less than 15 years of cessation and 39.29 (20.24-76.25) among current heavy smokers (Table 2). These associations remained unchanged after additional adjustments of other baseline characteristics or the use of other regression models.

Mortality Among Smokers for Whom Annual Screening Is Not Recommended

All-cause mortality among never smokers was 78.6% (1551 of 1973 participants), 81.0% (81 of 100 participants) among current nonheavy smokers, and 85.6% (443 of 516 participants) among former heavy smokers with 15 or more years of smoking cessation. Compared with never smokers, unadjusted cause-specific HRs for all-cause death for current nonheavy smokers were 1.17 (95% CI, 0.93-1.47), which increased and became statistically significant in the age, sex, and race–adjusted model (cause-specific HR, 1.53; 95% CI, 1.22-1.92) but remained unchanged in the final multivariable-adjusted model. The unadjusted cause-specific HR for all-cause death for former heavy smokers who quit more than 15 years ago was 1.27 (95% CI, 1.14-1.42), which was attenuated in the age, sex, and race–adjusted model (cause-specific HR, 1.18; 95% CI, 1.05-1.32) but remained unchanged in the final multivariable-adjusted model.

Discussion

This cohort study of 4279 participants in the CHS found that community-dwelling older smokers, for whom annual LDCT screening is not currently recommended, had an approximately 10-fold higher risk of developing lung cancer compared with never smokers. Although this risk was lower than that of smokers for whom annual LDCT screening is recommended, a 10-fold higher risk suggests that future studies should assess whether LDCT screening may reduce lung cancer mortality in this population. Considering the lower absolute risk relative to smokers for whom screening is recommended, future studies should also develop and test data science–based precision medicine approaches to identify high-risk subsets of these smokers for potential screening.

Cigarette smoking is associated with 80% to 90% of lung cancer deaths.²⁹ The relative risk of lung cancer decreases steadily after smoking cessation, dropping to half after 10 to 15 years of cessation.³ The findings from the current study, based on older smokers in a population setting, support that observation and provide important new insights. In our study, compared with never smokers, current heavy smokers with a nearly 50 pack-year smoking history had about 40 times higher risk of lung cancer. The risk was almost halved after a median (IQR) 7.0 (3.0-11.0) years of cessation in former heavy smokers who also had a 50 pack-year smoking history, highlighting the dramatic early benefit of smoking cessation for heavy smokers. This risk was further halved after a median (IQR) 22.0 (18.3-28.0) years of smoking cessation before study baseline but remained high, with a 10-fold higher risk of lung cancer compared with never smokers. If the cessation continued during the follow-up, the actual duration of cessation was even longer. This suggests that the lung cancer risk among heavy smokers may never drop to the level of never smokers, even after decades of smoking cessation, and highlights the importance of abstinence, early cessation, and possible screening. Taken together, these findings suggest that current heavy smokers receive immediate risk reduction from smoking cessation but high-level risk persists despite very prolonged cessation. Yet this latter group of smokers is not currently considered for lung cancer screening.

Another group of smokers who have a similar high risk of lung cancer but are not currently considered for screening are current nonheavy smokers. The nonheavy current smokers in our study had a median (IQR) smoking history of 11.4 (7.3-14.4) pack-years. Considering that these smokers had a mean age of 71.7 years at baseline and that most smokers begin smoking during their teens,³⁰ these smokers likely smoked for over 50 years. To accrue a 12 pack-year smoking history over 12 years, one must smoke 1 pack of 20 cigarettes a day. However, to accrue a 12 pack-year smoking history in 48 years, one must smoke one-quarter of 1 pack, or 5 cigarettes per day. This is consistent with our observation that these smokers smoked a median (IQR) of 5.0 (4.0-7.0) cigarettes per day, which would be considered light. A 10-fold higher risk of lung cancer in these so-called light smokers highlights the relative importance of years smoked vs cigarettes smoked per day (the 2 variables used in calculating pack-years). While less is known about the risk of lung cancer in current smokers with a 12 pack-year smoking history accrued by smoking 20 cigarettes a day for 12 years, our findings suggest that current smokers who accrued a 12 pack-year smoking history by smoking 5 cigarettes a day for 48 years have a 10-fold higher risk of developing lung cancer. This new information about the high risk of lung cancer in nonheavy smokers emphasizes the importance of early cessation. The benefit of early cessation is further highlighted in the former nonheavy smokers who had a similar median (IQR) pack-year (10.0 [5.3-14.9] vs 11.4 [7.3-14.4]) and median (IQR) cigarettes-per-day (5.0 [3.0-9.3] vs 5.0 [4.0-7.0]) smoking history as current nonheavy smokers but a median (IQR) duration of smoking cessation of 9.0 (4.0-11.0) years: they had nearly 75% (HR, 2.66 [95% CI, 0.58-12.17] vs HR 10.06 [95% CI, 3.41-29.70]) lower risk of incident lung cancer (Table 2). Because delayed cessation results in a higher pack-year smoking history, the number of years of cessation required to lower the risk of lung cancer is also longer. Former heavy smokers had a lower median (IQR) pack-year (34.8 [26.3-48.0] vs 48.8 [31.6-57.0]) and similar median (IQR) cigarettes per day (20 [20.0-30.0] vs 20.0 [12.0-20.0]) smoking history as current heavy smokers. The lung cancer risk of these former smokers was also 75% lower than that of current heavy smokers (HR, 10.22 [95% CI, 4.86-21.50] vs 39.95 [95% CI, 20.14-76.86]) but after a median (IQR) duration of smoking cessation of 22.0 (18.3-28.0) years (Table 2).

The current US Preventive Services Task Force recommendations are informed by validated microsimulation models.³¹ To our knowledge, this is the first study of lung cancer with detailed information on pack-years and years of smoking cessation using data from a prospectively enrolled cohort of older smokers with over 20 years of follow-up. Because all participants were aged 65 years or older at baseline with a mean age of 72.8 years, we could better ascertain both prolonged smoking and prolonged cessation without confounding by age, as young smokers generally have a lower pack-year history and shorter duration of cessation. These findings are important, as they provide evidence from smokers in a community setting that supports the US Preventive Services Task Force recommendation of annual LDCT screening.³¹ However, our findings also provide new information about the high risk of lung cancer in smokers currently not recommended for screening. Although a 10-fold higher risk is substantial, the absolute risk among these smokers was relatively small. For example, among older adults with a less than 20 pack-year smoking history, current smokers represented 11.6% of that population (100 of 861 participants), and among older heavy smokers, those who quit 15 or more years ago represented 35.7% of that population (516 of 1445 participants). In both groups of smokers, only 5.0% developed lung cancer. Considering the potential of harm from annual screening,³² future studies should develop and validate machine learning and/or artificial intelligence–based precision medicine approaches to identify higher-risk subsets of these smokers who might benefit from annual LDCT screening.^33,34 This is also important for heavy smokers for whom annual LDCT screen is recommended, as only between 10.1% (50 of 497) and 16.2% (70 of 432) of these older smokers were diagnosed with lung cancer in our study.

Limitations

This study has several limitations. Residual and unmeasured bias may cofound the associations observed in our study. However, the very high risk of lung cancer suggests that the effect of any bias would be minimal. We had no data on smoking during follow-up. Potential crossover of smoking categories during follow-up may have attenuated the observed between-group differences. Smokers are known to underreport cigarette use, which may have underestimated the true association between smoking and lung cancer. The CHS cohort was assembled before lung cancer screening was instituted, which may have underestimated the incidence and may have identified those with advanced disease. The deidentified data sets used in the current study do not have dates, and we were therefore not able to adjust for calendar times. Although the rate of lung cancer dropped during the CHS study period (1999 to 2011), the absolute number of new cases increased as a result of aging and growth of the population.³⁵ Participants in our study are aged 65 years or older, which may limit generalizability to younger smokers.

Conclusions

The findings of this cohort study from a prospectively enrolled cohort of community-dwelling older adults in the US who were followed up for more than 13 years provide evidence from a community setting of a very high risk of lung cancer in smokers for whom annual LDCT screening is recommended and provide new evidence of a high risk of lung cancer among smokers for whom LDCT screening is not recommended. These findings suggest that future studies should determine whether annual LDCT screening could reduce lung cancer mortality in these smokers. Future studies should also include development of machine learning and/or artificial intelligence algorithms to identify high-risk subsets of these smokers to optimize the risk-benefit ratio of such screening. These findings highlight the importance of abstinence and early smoking cessation for prevention of lung cancer.

Supplement.

eFigure. Cumulative Incidence (95% CIs) of Incident Lung Cancer by Smoking

Click here for additional data file.^{(249.8KB, pdf)}

Refernces

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eFigure. Cumulative Incidence (95% CIs) of Incident Lung Cancer by Smoking

Click here for additional data file.^{(249.8KB, pdf)}

[coi220036r1] 1.Henley SJ, Richards TB, Underwood JM, Eheman CR, Plescia M, McAfee TA; Centers for Disease Control and Prevention (CDC) . Lung cancer incidence trends among men and women–United States, 2005-2009. MMWR Morb Mortal Wkly Rep. 2014;63(1):1-5. [PMC free article] [PubMed] [Google Scholar]

[coi220036r2] 2.Office on Smoking and Health, Office of the Surgeon General. The Health Consequences of Smoking: A Report of the Surgeon General. Centers for Disease Control and Prevention; 2004. https://www.ncbi.nlm.nih.gov/books/NBK44695/ [Google Scholar]

[coi220036r3] 3.Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. Smoking cessation: a report of the surgeon general. US Department of Health and Human Services; 2020. https://www.cdc.gov/tobacco/sgr/2020-smoking-cessation/index.html#full-report2020

[coi220036r4] 4.Aberle DR, Adams AM, Berg CD, et al. ; National Lung Screening Trial Research Team . Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5):395-409. doi: 10.1056/NEJMoa1102873 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r5] 5.de Koning HJ, van der Aalst CM, de Jong PA, et al. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med. 2020;382(6):503-513. doi: 10.1056/NEJMoa1911793 [DOI] [PubMed] [Google Scholar]

[coi220036r6] 6.Jonas D, Reuland DS, Reddy SM, et al. Screening for Lung Cancer With Low-Dose Computed Tomography: An Evidence Review for the US Preventive Services Task Force. Evidence Synthesis No. 198. Agency for Healthcare Research and Quality; 2021. AHRQ publication 20-05266-EF-1. [PubMed] [Google Scholar]

[coi220036r7] 7.Krist AH, Davidson KW, Mangione CM, et al. ; US Preventive Services Task Force . Screening for lung cancer: US Preventive Services Task Force recommendation statement. JAMA. 2021;325(10):962-970. doi: 10.1001/jama.2021.1117 [DOI] [PubMed] [Google Scholar]

[coi220036r8] 8.Fried LP, Borhani NO, Enright P, et al. The Cardiovascular Health Study: design and rationale. Ann Epidemiol. 1991;1(3):263-1 276. doi: 10.1016/1047-2797(91)90005-W [DOI] [PubMed] [Google Scholar]

[coi220036r9] 9.Ip EH, Efendi A, Molenberghs G, Bertoni AG. Comparison of risks of cardiovascular events in the elderly using standard survival analysis and multiple-events and recurrent-events methods. BMC Med Res Methodol. 2015;15:15. doi: 10.1186/s12874-015-0004-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r10] 10.Ahmed A, Rich MW, Fleg JL, et al. Effects of digoxin on morbidity and mortality in diastolic heart failure: the ancillary digitalis investigation group trial. Circulation. 2006;114(5):397-403. doi: 10.1161/CIRCULATIONAHA.106.628347 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r11] 11.Meyer P, Filippatos GS, Ahmed MI, et al. Effects of right ventricular ejection fraction on outcomes in chronic systolic heart failure. Circulation. 2010;121(2):252-258. doi: 10.1161/CIRCULATIONAHA.109.887570 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r12] 12.Guichard JL, Desai RV, Ahmed MI, et al. Isolated diastolic hypotension and incident heart failure in older adults. Hypertension. 2011;58(5):895-901. doi: 10.1161/HYPERTENSIONAHA.111.178178 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r13] 13.Ahmed AA, Patel K, Nyaku MA, et al. Risk of heart failure and death after prolonged smoking cessation: role of amount and duration of prior smoking. Circ Heart Fail. 2015;8(4):694-701. doi: 10.1161/CIRCHEARTFAILURE.114.001885 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r14] 14.CHS Investigators. The Cardiovascular Health Study: record 8, baseline personal history. Accessed June 22, 2022. https://biolincc.nhlbi.nih.gov/media/studies/chs/rec08.pdf

[coi220036r15] 15.CHS Investigators. The Cardiovascular Health Study: record 8, CHS data collection forms. Accessed June 22, 2022. https://chs-nhlbi.org/forms/r8p2

[coi220036r16] 16.Gottdiener JS, Buzkova P, Kahn PA, et al. Relation of cigarette smoking and heart failure in adults ≥65 Years of Age (from the Cardiovascular Health Study). Am J Cardiol. Apr 1 2022;168:90-98. doi: 10.1016/j.amjcard.2021.12.021. [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r17] 17.Psaty BM, Kuller LH, Bild D, et al. Methods of assessing prevalent cardiovascular disease in the Cardiovascular Health Study. Ann Epidemiol. 1995;5(4):270-277. doi: 10.1016/1047-2797(94)00092-8 [DOI] [PubMed] [Google Scholar]

[coi220036r18] 18.Faselis C, Safren L, Allman RM, et al. Income disparity and incident cardiovascular disease in older Americans. Prog Cardiovasc Dis. 2022;71:92-99. doi: 10.1016/j.pcad.2021.07.010 [DOI] [PubMed] [Google Scholar]

[coi220036r19] 19.Siscovick DS, Fried L, Mittelmark M, Rutan G, Bild D, O’Leary DH. Exercise intensity and subclinical cardiovascular disease in the elderly: the Cardiovascular Health Study. Am J Epidemiol. 1997;145(11):977-986. doi: 10.1093/oxfordjournals.aje.a009066 [DOI] [PubMed] [Google Scholar]

[coi220036r20] 20.Patel K, Sui X, Zhang Y, et al. Prevention of heart failure in older adults may require higher levels of physical activity than needed for other cardiovascular events. Int J Cardiol. 2013;168(3):1905-1909. doi: 10.1016/j.ijcard.2012.12.053 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r21] 21.Strotmeyer ES, Arnold AM, Boudreau RM, et al. Long-term retention of older adults in the Cardiovascular Health Study: implications for studies of the oldest old. J Am Geriatr Soc. 2010;58(4):696-701. doi: 10.1111/j.1532-5415.2010.02770.x [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r22] 22.Psaty BM, Delaney JA, Arnold AM, et al. Study of cardiovascular health outcomes in the era of claims data: the Cardiovascular Health Study. Circulation. 2016;133(2):156-164. doi: 10.1161/CIRCULATIONAHA.115.018610 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r23] 23.Austin PC, Lee DS, Fine JP. Introduction to the analysis of survival data in the presence of competing risks. Circulation. 2016;133(6):601-609. doi: 10.1161/CIRCULATIONAHA.115.017719 [DOI] [PMC free article] [PubMed] [Google Scholar]

[coi220036r24] 24.Buzkova P. Competing risk of mortality in association studies of non-fatal events. PLoS One. 2021;16(8):e0255313. doi: 10.1371/journal.pone.0255313 [DOI] [PMC free article] [PubMed] [Google Scholar]

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Assessment of Lung Cancer Risk Among Smokers for Whom Annual Screening Is Not Recommended

Charles Faselis, MD

Joel A Nations, MD

Charity J Morgan, PhD

Jared Antevil, MD

Jeffrey M Roseman, MD, PhD, MPH

Sijian Zhang, MB, MS, MPH

Gregg C Fonarow, MD

Helen M Sheriff, MD

Gregory D Trachiotis, MD

Richard M Allman, MD

Prakash Deedwania, MD

Qing Zeng-Trietler, PhD

Daniel D Taub, PhD

Amiya A Ahmed, MD

George Howard, DrPH

Ali Ahmed, MD, MPH

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Settings, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Design, Setting, Participants, and Study Size

Figure 1. Flowchart of Study Participants.

Study Exposure and Other Baseline Measurements

Study Outcomes

Statistical Analysis

Results

Baseline Characteristics

Table 1. Demographic and Clinical Characteristics and Smoking History Among Older Adults Free of Cancer at Baseline (N = 4279).

Lung Cancer Among Smokers for Whom Annual Screening Is Not Recommended

Table 2. Risk of Lung Cancer in Older Adults Free of Cancer at Baseline by Smoking and Smoking Cessation History (N = 4279).

Figure 2. Cumulative Incidence of Lung Cancer by Smoking.

Lung Cancer Among Older Smokers for Whom Annual Screening Is Recommended

Mortality Among Smokers for Whom Annual Screening Is Not Recommended

Discussion

Limitations

Conclusions

Refernces

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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