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Hock ES, Franklin M, Baxter S, Clowes M, Chilcott J, Gillespie D. Covariates of success in quitting smoking: a systematic review of studies from 2008 to 2021 conducted to inform the statistical analyses of quitting outcomes of a hospital-based tobacco dependence treatment service in the United Kingdom. NIHR OPEN RESEARCH 2023; 3:28. [PMID: 37881466 PMCID: PMC10596416 DOI: 10.3310/nihropenres.13427.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 10/06/2023] [Indexed: 10/27/2023]
Abstract
Background Smoking cessation interventions are being introduced into routine secondary care in the United Kingdom (UK), but there are person and setting-related factors that could moderate their success in quitting smoking. This review was conducted as part of an evaluation of the QUIT hospital-based tobacco dependence treatment service ( https://sybics-quit.co.uk). The aim of the review was to identify a comprehensive set of variables associated with quitting success among tobacco smokers contacting secondary healthcare services in the UK who are offered support to quit smoking and subsequently set a quit date. The results would then be used to inform the development of a statistical analysis plan to investigate quitting outcomes. Methods Systematic literature review of five electronic databases. Studies eligible for inclusion investigated quitting success in one of three contexts: (a) the general population in the UK; (b) people with a mental health condition; (c) quit attempts initiated within a secondary care setting. The outcome measures were parameters from statistical analysis showing the effects of covariates on quitting success with a statistically significant (i.e., p-value <0.05) association. Results The review identified 29 relevant studies and 14 covariates of quitting success, which we grouped into four categories: demographics (age; sex; ethnicity; socio-economic conditions; relationship status, cohabitation and social network), individual health status and healthcare setting (physical health, mental health), tobacco smoking variables (current tobacco consumption, smoking history, nicotine dependence; motivation to quit; quitting history), and intervention characteristics (reduction in amount smoked prior to quitting, the nature of behavioural support, tobacco dependence treatment duration, pharmacological aids). Conclusions In total, 14 data fields were identified that should be considered for inclusion in datasets and statistical analysis plans for evaluating the quitting outcomes of smoking cessation interventions initiated in secondary care contexts in the UK. PROSPERO registration CRD42021254551 (13/05/2021).
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Affiliation(s)
- Emma S. Hock
- Sheffield Centre for Health and Related Research (SCHARR), Division of Population Health, School of Medicine and Population Health School, The University of Sheffield, Sheffield, England, UK
| | - Matthew Franklin
- Sheffield Centre for Health and Related Research (SCHARR), Division of Population Health, School of Medicine and Population Health School, The University of Sheffield, Sheffield, England, UK
| | - Susan Baxter
- Sheffield Centre for Health and Related Research (SCHARR), Division of Population Health, School of Medicine and Population Health School, The University of Sheffield, Sheffield, England, UK
| | - Mark Clowes
- Sheffield Centre for Health and Related Research (SCHARR), Division of Population Health, School of Medicine and Population Health School, The University of Sheffield, Sheffield, England, UK
| | - James Chilcott
- Sheffield Centre for Health and Related Research (SCHARR), Division of Population Health, School of Medicine and Population Health School, The University of Sheffield, Sheffield, England, UK
| | - Duncan Gillespie
- Sheffield Centre for Health and Related Research (SCHARR), Division of Population Health, School of Medicine and Population Health School, The University of Sheffield, Sheffield, England, UK
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Wang Y, Bos JH, Schuiling-Veninga CCM, Boezen HM, van Boven JFM, Wilffert B, Hak E. Neuropsychiatric safety of varenicline in the general and COPD population with and without psychiatric disorders: a retrospective cohort study in a real-world setting. BMJ Open 2021; 11:e042417. [PMID: 34035088 PMCID: PMC8154988 DOI: 10.1136/bmjopen-2020-042417] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVES To evaluate the real-world association between varenicline and neuropsychiatric adverse events (NPAEs) in general and chronic obstructive pulmonary disease (COPD) population with and without psychiatric disorders compared with nicotine replacement therapy (NRT) to strengthen the knowledge of varenicline safety. DESIGN A retrospective cohort study. SETTING Prescription database IADB.nl, the Netherlands. PARTICIPANTS New users of varenicline or NRT among general (≥18 years) and COPD (≥40 years) population. Psychiatric subcohort was defined as people prescribed psychotropic medications (≥2) within 6 months before the index date. OUTCOME MEASURES The incidence of NPAEs including depression, anxiety and insomnia, defined by new or naive prescriptions of related medications in IADB.nl within 24 weeks after the first treatment initiation of varenicline or NRT. RESULTS For the general population in non-psychiatric cohort, the incidence of total NPAEs in varenicline (4480) and NRT (1970) groups was 10.5% and 12.6%, respectively (adjusted OR (aOR) 0.85, 95% CI 0.72 to 1.00). For the general population in psychiatric cohort, the incidence of total NPAEs was much higher, 75.3% and 78.5% for varenicline (1427) and NRT (1200) groups, respectively (aOR 0.82, 95% CI 0.68 to 0.99). For the COPD population (1598), there were no differences in the incidence of NPAEs between comparison groups in both the psychiatric cohort (aOR 0.97, 95% CI 0.66 to 1.44) and non-psychiatric cohort (aOR 0.81, 95% CI 0.54 to 1.20). Results from subgroup or sensitivity analyses also did not reveal increased risks of NPAEs but showed decreased risk of some subgroup NPAEs associated with varenicline. CONCLUSIONS In contrast to the concerns of a possible increased risk of NPAEs among varenicline users, we found a relative decreased risk of total NPAEs in varenicline users of the general population in psychiatric or non-psychiatric cohorts compared with NRT and no difference for NPAEs between varenicline and NRT users in smaller population with COPD.
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Affiliation(s)
- Yuanyuan Wang
- Department of PharmacoTherapy, -Epidemiology & -Economics, Groningen Research Institutte of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Jens H Bos
- Department of PharmacoTherapy, -Epidemiology & -Economics, Groningen Research Institutte of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Catharina C M Schuiling-Veninga
- Department of PharmacoTherapy, -Epidemiology & -Economics, Groningen Research Institutte of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - H Marike Boezen
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Job F M van Boven
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Clinical Pharmacy & Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Bob Wilffert
- Department of PharmacoTherapy, -Epidemiology & -Economics, Groningen Research Institutte of Pharmacy, University of Groningen, Groningen, The Netherlands
- Department of Clinical Pharmacy & Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Eelko Hak
- Department of PharmacoTherapy, -Epidemiology & -Economics, Groningen Research Institutte of Pharmacy, University of Groningen, Groningen, The Netherlands
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Feasibility of Delivering Varenicline Through a Telephone Quitline to Promote Smoking Cessation. J Smok Cessat 2018. [DOI: 10.1017/jsc.2018.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Introduction: Telephone quitlines are an easily accessible and effective means for delivering cessation services including nicotine replacement therapy (NRT). Varenicline (VAR) may show superior quit rates to NRT, but has not been routinely evaluated in the context of quitlines.Aims: To assess the feasibility of distributing VAR through a quitline, and preliminarily compare cessation rates between participants receiving VAR and NRT.Methods: Participants were recruited through the New York State Smokers’ Quitline. Those randomised to VAR (n = 200) were instructed to obtain a prescription from their primary care physician (PCP) to be filled by mail through the research pharmacy. Those randomised to NRT (n = 100) were mailed NRT using an existing protocol. Outcome measures were number of submitted prescriptions and dispensed medication kits, and self-reported 7-day point prevalence abstinence at follow-up.Results: The research pharmacy filled 100% of prescriptions through the quitline. However, only 27% of the VAR Arm submitted a prescription. An intent-to-treat analysis revealed that those receiving NRT were more likely to be abstinent at follow-up than the VAR Arm (OR, 2.42; 95% CI, 1.27–4.60; p < 0.01). The per-protocol analysis, which only included those in the VAR Arm who submitted a prescription, showed no difference in quit rates.Conclusions: The present protocol resulted in successful delivery of VAR through the quitline, but a sizable proportion of the VAR Arm did not submit a prescription. Self-reported barriers included being unable to obtain a prescription from a PCP. Future studies should explore alternative methods for delivering VAR through quitlines.
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Duffy SA, Ignacio RV, Kim HM, Geraci MC, Essenmacher CA, Hall SV, Chow A, Pfeiffer PN, Sherman SE, Bohnert KM, Zivin K, Barnett PG. Effectiveness of tobacco cessation pharmacotherapy in the Veterans Health Administration. Tob Control 2018; 28:540-547. [PMID: 30181383 DOI: 10.1136/tobaccocontrol-2018-054473] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 07/30/2018] [Accepted: 08/07/2018] [Indexed: 11/03/2022]
Abstract
INTRODUCTION In 2003, the Veterans Health Administration (VHA) implemented a directive that cessation pharmacotherapy be made available to all who use tobacco and are interested in quitting. Despite the efficacy of cessation pharmacotherapy shown in clinical trials, the generalisability of the results in real-world settings has been challenged. Hence, the specific aim of this study was to determine the effectiveness of cessation pharmacotherapies in the VHA. METHODS This retrospective cohort study used VHA's electronic medical record data to compare quit rates among those who use tobacco and who did vs. did not receive any type of cessation pharmacotherapy. Included were 589 862 Veterans identified as current tobacco users during fiscal year 2011 who had not received cessation pharmacotherapy in the prior 12 months. Following a 6-month period to assess treatment, quit rates among those who were treated versus untreated were compared during the 7-18 months (12 months) post-treatment follow-up period. The estimated treatment effect was calculated from a logistic regression model adjusting for inverse probability of treatment weights (IPTWs) and covariates. Marginal probabilities of quitting were also obtained among those treated versus untreated. RESULTS Adjusting for IPTWs and covariates, the odds of quitting were 24% higher among those treated versus untreated (OR=1.24, 95% CI 1.23 to 1.25, p<0.001). The marginal probabilities of quitting were 16.7% for the untreated versus 19.8% for the treated based on the weighted model. CONCLUSION The increased quit rates among Veterans treated support the effectiveness and continuation of the VHA tobacco cessation pharmacotherapy policy.
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Affiliation(s)
- Sonia A Duffy
- College of Nursing, Ohio State University, Columbus, Michigan, USA.,Department of Veterans Affairs, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Rosalinda V Ignacio
- Department of Veterans Affairs, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Hyungjin Myra Kim
- Department of Veterans Affairs, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.,Center for Statistical Consultation and Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Mark C Geraci
- Pharmacy Benefits Management Services, Department of Veterans Affairs, Hines, Illinois, USA
| | - Carol A Essenmacher
- Department of Veterans Affairs, Battle Creek VA Medical Center, Battle Creek, Michigan, USA
| | - Stephanie V Hall
- Department of Veterans Affairs, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA
| | - Adam Chow
- Department of Veterans Affairs, Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, USA
| | - Paul N Pfeiffer
- Department of Veterans Affairs, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Scott E Sherman
- Department of Veterans Affairs, VA New York Harbor Healthcare System, New York, New York, USA.,Department of Population Health, NYU School of Medicine, New York University, New York, USA
| | - Kipling M Bohnert
- Department of Veterans Affairs, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Kara Zivin
- Department of Veterans Affairs, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.,Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Paul George Barnett
- Department of Veterans Affairs, Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, California, USA
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