Angiotensin converting enzyme inhibitors and risk of lung cancer: population based cohort study

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Abstract

Objective

To determine whether the use of angiotensin converting enzyme inhibitors (ACEIs), compared with use of angiotensin receptor blockers, is associated with an increased risk of lung cancer.

Design

Population based cohort study.

Setting

United Kingdom Clinical Practice Research Datalink.

Participants

A cohort of 992 061 patients newly treated with antihypertensive drugs between 1 January 1995 and 31 December 2015 was identified and followed until 31 December 2016.

Main outcome measures

Cox proportional hazards models were used to estimate adjusted hazard ratios with 95% confidence intervals of incident lung cancer associated with the time varying use of ACEIs, compared with use of angiotensin receptor blockers, overall, by cumulative duration of use, and by time since initiation.

Results

The cohort was followed for a mean of 6.4 (SD 4.7) years, generating 7952 incident lung cancer events (crude incidence 1.3 (95% confidence interval 1.2 to 1.3) per 1000 person years). Overall, use of ACEIs was associated with an increased risk of lung cancer (incidence rate 1.6 v 1.2 per 1000 person years; hazard ratio 1.14, 95% confidence interval 1.01 to 1.29), compared with use of angiotensin receptor blockers. Hazard ratios gradually increased with longer durations of use, with an association evident after five years of use (hazard ratio 1.22, 1.06 to 1.40) and peaking after more than 10 years of use (1.31, 1.08 to 1.59). Similar findings were observed with time since initiation.

Conclusions

In this population based cohort study, the use of ACEIs was associated with an increased risk of lung cancer. The association was particularly elevated among people using ACEIs for more than five years. Additional studies, with long term follow-up, are needed to investigate the effects of these drugs on incidence of lung cancer.

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Most cited references 39

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Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.

M A Hernán, B Brumback, J M Robins (2000)

Standard methods for survival analysis, such as the time-dependent Cox model, may produce biased effect estimates when there exist time-dependent confounders that are themselves affected by previous treatment or exposure. Marginal structural models are a new class of causal models the parameters of which are estimated through inverse-probability-of-treatment weighting; these models allow for appropriate adjustment for confounding. We describe the marginal structural Cox proportional hazards model and use it to estimate the causal effect of zidovudine on the survival of human immunodeficiency virus-positive men participating in the Multicenter AIDS Cohort Study. In this study, CD4 lymphocyte count is both a time-dependent confounder of the causal effect of zidovudine on survival and is affected by past zidovudine treatment. The crude mortality rate ratio (95% confidence interval) for zidovudine was 3.6 (3.0-4.3), which reflects the presence of confounding. After controlling for baseline CD4 count and other baseline covariates using standard methods, the mortality rate ratio decreased to 2.3 (1.9-2.8). Using a marginal structural Cox model to control further for time-dependent confounding due to CD4 count and other time-dependent covariates, the mortality rate ratio was 0.7 (95% conservative confidence interval = 0.6-1.0). We compare marginal structural models with previously proposed causal methods.

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Lung cancer in never smokers: a review.

Janakiraman Subramanian, Ramaswamy Govindan (2007)

Lung cancer is the leading cause of cancer-related death in the United States. Although tobacco smoking accounts for the majority of lung cancer, approximately 10% of patients with lung cancer in the United States are lifelong never smokers. Lung cancer in the never smokers (LCINS) affects women disproportionately more often than men. Only limited data are available on the etiopathogenesis, molecular abnormalities, and prognosis of LCINS. Several etiologic factors have been proposed for the development of LCINS, including exposure to radon, cooking fumes, asbestos, heavy metals, and environmental tobacco smoke, human papillomavirus infection, and inherited genetic susceptibility. However, the relative significance of these individual factors among different ethnic populations in the development of LCINS has not been well-characterized. Adenocarcinoma is the predominant histologic subtype reported with LCINS. Striking differences in response rates and outcomes are seen when patients with advanced non-small-cell lung cancer (NSCLC) who are lifelong never smokers are treated with epidermal growth factor receptor tyrosine kinase (EGFR-TK) inhibitors such as gefitinib or erlotinib compared with the outcomes with these agents in patients with tobacco-associated lung cancer. Interestingly, the activating mutations in the EGFR-TK inhibitors have been reported significantly more frequently in LCINS than in patients with tobacco-related NSCLC. This review will summarize available data on the epidemiology, risk factors, molecular genetics, management options, and outcomes of LCINS.

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Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data.

S Schneeweiss, J Seeger, M Maclure … (2001)

Comorbidity is an important confounder in epidemiologic studies. The authors compared the predictive performance of comorbidity scores for use in epidemiologic research with administrative databases. Study participants were British Columbia, Canada, residents aged >or=65 years who received angiotensin-converting enzyme inhibitors or calcium channel blockers at least once during the observation period. Six scores were computed for all 141,161 participants during the baseline year (1995-1996). Endpoints were death and health care utilization during a 12-month follow-up (1996-1997). Performance was measured by using the c statistic ranging from 0.5 for chance prediction of outcome to 1.0 for perfect prediction. In logistic regression models controlling for age and gender, four scores based on the International Classification of Diseases, Ninth Revision (ICD-9) generally performed better at predicting 1-year mortality (c = 0.771, c = 0.768, c = 0.745, c = 0.745) than medication-based Chronic Disease Score (CDS)-1 and CDS-2 (c = 0.738, c = 0.718). Number of distinct medications used was the best predictor of future physician visits (R(2) = 0.121) and expenditures (R(2) = 0.128) and a good predictor of mortality (c = 0.745). Combining ICD-9 and medication-based scores improved the c statistics (1.7% and 6.2%, respectively) for predicting mortality. Generalizability of results may be limited to an elderly, predominantly White population with equal access to state-funded health care.

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Author and article information

Contributors

Blánaid M Hicks: Role: postdoctoral research fellow

Kristian B Filion: Role: assistant professor of epidemiology

Hui Yin: Role: statistician

Lama Sakr: Role: pulmonologist

Jacob A Udell: Role: cardiologist and assistant professor of cardiology

Laurent Azoulay:

ORCID: http://orcid.org/0000-0001-5162-3556

Role: associate professor of epidemiology and oncology

Journal

Journal ID (nlm-ta): BMJ

Journal ID (iso-abbrev): BMJ

Journal ID (publisher-id): BMJ-US

Journal ID (hwp): bmj

Title: The BMJ

Publisher: BMJ Publishing Group Ltd.

ISSN (Print): 0959-8138

ISSN (Electronic): 1756-1833

Publication date Collection: 2018

Publication date (Electronic): 24 October 2018

Volume: 363

Electronic Location Identifier: k4209

Affiliations

[1 ]Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada, H3T 1E2

[2 ]Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada

[3 ]Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK

[4 ]Division of Clinical Epidemiology, Department of Medicine, McGill University, Montreal, QC, Canada

[5 ]Division of Pulmonary Diseases, Department of Medicine, Jewish General Hospital, Montreal, QC, Canada

[6 ]Women's College Research Institute and Cardiovascular Division, Department of Medicine, Women's College Hospital, University of Toronto, Toronto, ON, Canada

[7 ]Cardiovascular Division, Department of Medicine, Peter Munk Cardiac Centre, Toronto General Hospital, University of Toronto, Toronto, ON, Canada

[8 ]Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada

Author notes

Correspondence to: L Azoulay laurent.azoulay@ 123456mcgill.ca (or @LaurentAzoulay0 on Twitter)

Author information

Laurent Azoulay http://orcid.org/0000-0001-5162-3556

Article

Publisher ID: hicb044369

DOI: 10.1136/bmj.k4209

PMC ID: 6199558

PubMed ID: 30355745

SO-VID: f79d92f1-3de6-4587-b16a-c94d7da64bf2

License:

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

Angiotensin converting enzyme inhibitors and risk of lung cancer: population based cohort study

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Abstract

Objective

Design

Setting

Participants

Main outcome measures

Results

Conclusions

Related collections

Karger: Ophthalmology

Most cited references 39

Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.

Lung cancer in never smokers: a review.

Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data.

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