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      Cardiovascular and neuropsychiatric risks of varenicline: a retrospective cohort study

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      , Prof, PhD a , b , c , d , * , , PhD e , , PhD c , , Prof, PhD b , c , , Prof, PhD d , , Prof, MD b , c , f
      The Lancet. Respiratory Medicine
      Elsevier

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          Summary

          Background

          Varenicline is an effective pharmacotherapy to aid smoking cessation. However, its use is limited by continuing concerns about possible associated risks of serious adverse cardiovascular and neuropsychiatric events. The aim of this study was to investigate whether use of varenicline is associated with such events.

          Methods

          In this retrospective cohort study, we used data from patients included in the validated QResearch database, which holds data from 753 National Health Service general practices across England. We identified patients aged 18–100 years (registered for longer than 12 months before data extraction) who received a prescription of nicotine replacement treatment (NRT; reference group), bupropion, or varenicline. We excluded patients if they had used one of the drugs during the 12 months before the start date of the study, had received a prescription of a combination of these drugs during the follow-up period, or were temporary residents. We followed patients up for 6 months to compare incident cardiovascular (ischaemic heart disease, cerebral infarction, heart failure, peripheral vascular disease, and cardiac arrhythmia) and neuropsychiatric (depression and self-harm) events using Cox proportional hazards models, adjusted for potential confounders (primary outcomes).

          Findings

          We identified 164 766 patients who received a prescription (106 759 for nicotine replacement treatment; 6557 for bupropion; 51 450 for varenicline) between Jan 1, 2007, and June 30, 2012. Neither bupropion nor varenicline showed an increased risk of any cardiovascular or neuropsychiatric event compared with NRT (all hazard ratios [HRs] less than 1. Varenicline was associated with a significantly reduced risk of ischaemic heart disease (HR 0·80 [95%CI 0·72–0·87]), cerebral infarction (0·62 [0·52–0·73]), heart failure (0·61 [0·45–0·83]), arrhythmia (0·73 [0·60–0·88]), depression (0·66 [0·63–0·69]), and self-harm (0·56 [0·46–0·68]).

          Interpretation

          Varenicline does not seem to be associated with an increased risk of documented cardiovascular events, depression, or self-harm when compared with NRT. Adverse events that do not come to attention of general practitioners cannot be excluded. These findings suggest an opportunity for physicians to prescribe varenicline more broadly, even for patients with comorbidities, thereby helping more smokers to quit successfully than do at present.

          Funding

          Egton Medical Information Systems, University of Nottingham, Ministry of Innovation, Science and Research of the German Federal State of North Rhine-Westphalia, Cancer Research UK, Medical Research Council, Commonwealth Fund.

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          Most cited references54

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          21st-Century Hazards of Smoking and Benefits of Cessation in the United States

          Extrapolation from studies in the 1980s suggests that smoking causes 25% of deaths among women and men 35 to 69 years of age in the United States. Nationally representative measurements of the current risks of smoking and the benefits of cessation at various ages are unavailable. We obtained smoking and smoking-cessation histories from 113,752 women and 88,496 men 25 years of age or older who were interviewed between 1997 and 2004 in the U.S. National Health Interview Survey and related these data to the causes of deaths that occurred by December 31, 2006 (8236 deaths in women and 7479 in men). Hazard ratios for death among current smokers, as compared with those who had never smoked, were adjusted for age, educational level, adiposity, and alcohol consumption. For participants who were 25 to 79 years of age, the rate of death from any cause among current smokers was about three times that among those who had never smoked (hazard ratio for women, 3.0; 99% confidence interval [CI], 2.7 to 3.3; hazard ratio for men, 2.8; 99% CI, 2.4 to 3.1). Most of the excess mortality among smokers was due to neoplastic, vascular, respiratory, and other diseases that can be caused by smoking. The probability of surviving from 25 to 79 years of age was about twice as great in those who had never smoked as in current smokers (70% vs. 38% among women and 61% vs. 26% among men). Life expectancy was shortened by more than 10 years among the current smokers, as compared with those who had never smoked. Adults who had quit smoking at 25 to 34, 35 to 44, or 45 to 54 years of age gained about 10, 9, and 6 years of life, respectively, as compared with those who continued to smoke. Smokers lose at least one decade of life expectancy, as compared with those who have never smoked. Cessation before the age of 40 years reduces the risk of death associated with continued smoking by about 90%.
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            Mortality in relation to smoking: 50 years' observations on male British doctors.

            To compare the hazards of cigarette smoking in men who formed their habits at different periods, and the extent of the reduction in risk when cigarette smoking is stopped at different ages. Prospective study that has continued from 1951 to 2001. United Kingdom. 34 439 male British doctors. Information about their smoking habits was obtained in 1951, and periodically thereafter; cause specific mortality was monitored for 50 years. Overall mortality by smoking habit, considering separately men born in different periods. The excess mortality associated with smoking chiefly involved vascular, neoplastic, and respiratory diseases that can be caused by smoking. Men born in 1900-1930 who smoked only cigarettes and continued smoking died on average about 10 years younger than lifelong non-smokers. Cessation at age 60, 50, 40, or 30 years gained, respectively, about 3, 6, 9, or 10 years of life expectancy. The excess mortality associated with cigarette smoking was less for men born in the 19th century and was greatest for men born in the 1920s. The cigarette smoker versus non-smoker probabilities of dying in middle age (35-69) were 42% nu 24% (a twofold death rate ratio) for those born in 1900-1909, but were 43% nu 15% (a threefold death rate ratio) for those born in the 1920s. At older ages, the cigarette smoker versus non-smoker probabilities of surviving from age 70 to 90 were 10% nu 12% at the death rates of the 1950s (that is, among men born around the 1870s) but were 7% nu 33% (again a threefold death rate ratio) at the death rates of the 1990s (that is, among men born around the 1910s). A substantial progressive decrease in the mortality rates among non-smokers over the past half century (due to prevention and improved treatment of disease) has been wholly outweighed, among cigarette smokers, by a progressive increase in the smoker nu non-smoker death rate ratio due to earlier and more intensive use of cigarettes. Among the men born around 1920, prolonged cigarette smoking from early adult life tripled age specific mortality rates, but cessation at age 50 halved the hazard, and cessation at age 30 avoided almost all of it.
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              Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study.

              To derive a new cardiovascular disease risk score (QRISK) for the United Kingdom and to validate its performance against the established Framingham cardiovascular disease algorithm and a newly developed Scottish score (ASSIGN). Prospective open cohort study using routinely collected data from general practice. UK practices contributing to the QRESEARCH database. The derivation cohort consisted of 1.28 million patients, aged 35-74 years, registered at 318 practices between 1 January 1995 and 1 April 2007 and who were free of diabetes and existing cardiovascular disease. The validation cohort consisted of 0.61 million patients from 160 practices. First recorded diagnosis of cardiovascular disease (incident diagnosis between 1 January 1995 and 1 April 2007): myocardial infarction, coronary heart disease, stroke, and transient ischaemic attacks. Risk factors were age, sex, smoking status, systolic blood pressure, ratio of total serum cholesterol to high density lipoprotein, body mass index, family history of coronary heart disease in first degree relative aged less than 60, area measure of deprivation, and existing treatment with antihypertensive agent. A cardiovascular disease risk algorithm (QRISK) was developed in the derivation cohort. In the validation cohort the observed 10 year risk of a cardiovascular event was 6.60% (95% confidence interval 6.48% to 6.72%) in women and 9.28% (9.14% to 9.43%) in men. Overall the Framingham algorithm over-predicted cardiovascular disease risk at 10 years by 35%, ASSIGN by 36%, and QRISK by 0.4%. Measures of discrimination tended to be higher for QRISK than for the Framingham algorithm and it was better calibrated to the UK population than either the Framingham or ASSIGN models. Using QRISK 8.5% of patients aged 35-74 are at high risk (20% risk or higher over 10 years) compared with 13% when using the Framingham algorithm and 14% when using ASSIGN. Using QRISK 34% of women and 73% of men aged 64-75 would be at high risk compared with 24% and 86% according to the Framingham algorithm. UK estimates for 2005 based on QRISK give 3.2 million patients aged 35-74 at high risk, with the Framingham algorithm predicting 4.7 million and ASSIGN 5.1 million. Overall, 53 668 patients in the validation dataset (9% of the total) would be reclassified from high to low risk or vice versa using QRISK compared with the Framingham algorithm. QRISK performed at least as well as the Framingham model for discrimination and was better calibrated to the UK population than either the Framingham model or ASSIGN. QRISK is likely to provide more appropriate risk estimates to help identify high risk patients on the basis of age, sex, and social deprivation. It is therefore likely to be a more equitable tool to inform management decisions and help ensure treatments are directed towards those most likely to benefit. It includes additional variables which improve risk estimates for patients with a positive family history or those on antihypertensive treatment. However, since the validation was performed in a similar population to the population from which the algorithm was derived, it potentially has a "home advantage." Further validation in other populations is therefore required.
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                Author and article information

                Contributors
                Journal
                Lancet Respir Med
                Lancet Respir Med
                The Lancet. Respiratory Medicine
                Elsevier
                2213-2600
                2213-2619
                1 October 2015
                October 2015
                : 3
                : 10
                : 761-768
                Affiliations
                [a ]Institute of General Practice, Medical Faculty of the Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
                [b ]Department of Family Medicine, CAPHRI School for Public Health and Primary Care, Maastricht University Medical Centre, Maastricht, Netherlands
                [c ]Allergy and Respiratory Research Group, Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
                [d ]Cancer Research UK Health Behaviour Research Centre, University College London, London, UK
                [e ]MHeNS School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
                [f ]Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
                Author notes
                [* ]Correspondence to: Prof Daniel Kotz, Institute of General Practice, Medical Faculty of the Heinrich-Heine-University Düsseldorf, 40225 Düsseldorf, GermanyCorrespondence to: Prof Daniel KotzInstitute of General PracticeMedical Faculty of the Heinrich-Heine-University DüsseldorfDüsseldorf40225Germany daniel.kotz@ 123456med.uni-duesseldorf.de
                Article
                S2213-2600(15)00320-3
                10.1016/S2213-2600(15)00320-3
                4593936
                26355008
                d1525d4a-5df6-4137-b5ac-39fe26a4e43a
                © 2015 Kotz et al. Open Access article published under the terms of CC BY

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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