OP84 Smoking cessation treatment and long-term risk of cardiovascular and respiratory disease, and mortality in the Clinical Practice Research Datalink

2016 ◽  
Vol 70 (Suppl 1) ◽  
pp. A46.2-A47
Author(s):  
AE Taylor ◽  
NM Davies ◽  
GMJ Taylor ◽  
RM Martin ◽  
MR Munafo ◽  
...  
2021 ◽  
Vol 31 (1) ◽  
Author(s):  
Daniel Kotz ◽  
Carolien van Rossem ◽  
Wolfgang Viechtbauer ◽  
Mark Spigt ◽  
Onno C. P. van Schayck

AbstractIn the context of smoking cessation treatment in primary care, identifying patients at the highest risk of relapse is relevant. We explored data from a primary care trial to assess the validity of two simple urges to smoke questions in predicting long-term relapse and their diagnostic value. Of 295 patients who received behavioural support and varenicline, 180 were abstinent at week 9. In this subgroup, we measured time spent with urges to smoke (TSU) and strength of urges to smoke (SUT; both scales 1 to 6 = highest). We used separate regression models with TSU or SUT as predictor and relapse from week 9–26 or week 9–52 as an outcome. We also calculated the sensitivity (SP), specificity and positive predictive values (PPV) of TSU and SUT in correctly identifying patients who relapsed at follow-up. The adjusted odds ratios (aOR) for predicting relapse from week 9–26 were 1.74 per point increase (95% CI = 1.05–2.89) for TSU and 1.59 (95% CI = 1.11–2.28) for SUT. The aORs for predicting relapse from week 9–52 were 2.41 (95% CI = 1.33–4.37) and 1.71 (95% CI = 1.14–2.56), respectively. Applying a cut-point of ≥3 on TSU resulted in SP = 97.1 and PPV = 70.0 in week 9–26, and SP = 98.8 and PPV = 90.0 in week 9–52. Applying a cut-point of ≥4 on SUT resulted in SP = 99.0 and PPV = 85.7 in week 9–26, and SP = 98.8 and PPV = 85.7 in week 9–52. Both TSU and SUT were valid predictors of long-term relapse in patients under smoking cessation treatment in primary care. These simple questions may be useful to implement in primary care.Trial registration: Dutch Trial Register (NTR3067).


2020 ◽  
Vol 212 ◽  
pp. 108007
Author(s):  
Ángel García-Pérez ◽  
Guillermo Vallejo-Seco ◽  
Sara Weidberg ◽  
Alba González-Roz ◽  
Roberto Secades-Villa

2020 ◽  
Vol 24 (9) ◽  
pp. 1-46
Author(s):  
Neil M Davies ◽  
Amy E Taylor ◽  
Gemma MJ Taylor ◽  
Taha Itani ◽  
Tim Jones ◽  
...  

Background Smoking is the leading avoidable cause of illness and premature mortality. The first-line treatments for smoking cessation are nicotine replacement therapy and varenicline. Meta-analyses of experimental studies have shown that participants allocated to the varenicline group were 1.57 times (95% confidence interval 1.29 to 1.91 times) as likely to be abstinent 6 months after treatment as those allocated to the nicotine replacement therapy group. However, there is limited evidence about the effectiveness of varenicline when prescribed in primary care. We investigated the effectiveness and rate of adverse events of these medicines in the general population. Objective To estimate the effect of prescribing varenicline on smoking cessation rates and health outcomes. Data sources Clinical Practice Research Datalink. Methods We conducted an observational cohort study using electronic medical records from the Clinical Practice Research Datalink. We extracted data on all patients who were prescribed varenicline or nicotine replacement therapy after 1 September 2006 who were aged ≥ 18 years. We investigated the effects of varenicline on smoking cessation, all-cause mortality and cause-specific mortality and hospitalisation for: (1) chronic lung disease, (2) lung cancer, (3) coronary heart disease, (4) pneumonia, (5) cerebrovascular disease, (6) diabetes, and (7) external causes; primary care diagnosis of myocardial infarction, chronic obstructive pulmonary disease, depression, or prescription for anxiety; weight in kg; general practitioner and hospital attendance. Our primary outcome was smoking cessation 2 years after the first prescription. We investigated the baseline differences between patients prescribed varenicline and patients prescribed nicotine replacement therapy. We report results using multivariable-adjusted, propensity score and instrumental variable regression. Finally, we developed methods to assess the relative bias of the different statistical methods we used. Results People prescribed varenicline were healthier at baseline than those prescribed nicotine replacement therapy in almost all characteristics, which highlighted the potential for residual confounding. Our instrumental variable analysis results found little evidence that patients prescribed varenicline had lower mortality 2 years after their first prescription (risk difference 0.67, 95% confidence interval –0.11 to 1.46) than those prescribed nicotine replacement therapy. They had similar rates of all-cause hospitalisation, incident primary care diagnoses of myocardial infarction and chronic obstructive pulmonary disease. People prescribed varenicline subsequently attended primary care less frequently. Patients prescribed varenicline were more likely (odds ratio 1.46, 95% confidence interval 1.42 to 1.50) to be abstinent 6 months after treatment than those prescribed nicotine replacement therapy when estimated using multivariable-adjusted for baseline covariates. Patients from more deprived areas were less likely to be prescribed varenicline. However, varenicline had similar effectiveness for these groups. Conclusion Patients prescribed varenicline in primary care were more likely to quit smoking than those prescribed nicotine replacement therapy, but there was little evidence that they had lower rates of mortality or morbidity in the 4 years following the first prescription. There was little evidence of heterogeneity in effectiveness across the population. Future work Future research should investigate the decline in prescribing of smoking cessation products; develop an optimal treatment algorithm for smoking cessation; use methods for using instruments with survival outcomes; and develop methods for comparing multivariable-adjusted and instrumental variable estimates. Limitations Not all of our code lists were validated, body mass index and Index of Multiple Deprivation had missing values, our results may suffer from residual confounding, and we had no information on treatment adherence. Trial registration This trial is registered as NCT02681848. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 9. See the NIHR Journals Library website for further project information.


2020 ◽  
Vol 8 (2) ◽  
Author(s):  
Pasquale Caponnetto ◽  
Riccardo Polosa

This review focuses on smoking cessation treatments for people with schizophrenia spectrum disorders. It concludes with comments on the significance of the research and why it constitutes an original contribution. We searched PubMed (National Library of Medicine), and PsycINFO (Ovid) (2006-2020) for studies on schizophrenic disorder (schizophrenia or psychotic or psychosis or severe mental illness) and smoking cessation treatment (smoking cessation treatment or varenicline or tobacco cessation or reduction or bupropion or NRT or behavioral treatment or e-cigarette). Studies found evidence suggesting that pharmacotherapy combined with behavioural therapy for smoking cessation is effective amongst smokers with schizophrenia spectrum disorders, although more long-term research is required. This review summarised and critically reviewed also studies on vaping as a smoking cessation strategy for smokers with schizophrenia spectrum disorders and evidence suggests that they may effective as smoking cessation tool and may be less harmful alternatives to combustible cigarette smoking. Consequently, e-cigarettes could be considered as an applicable instrument for Tobacco Harm Reduction (THR) and smoking cessation. Overall, there are very few studies of e-cigarettes for smoking cessation in patients with schizophrenia and these studies are very small. They have promising results, but more research is needed.


2017 ◽  
Author(s):  
Olalekan A Uthman ◽  
Chidozie U Nduka ◽  
Mustapha Abba ◽  
Rocio Enriquez ◽  
Helena Nordenstedt ◽  
...  

BACKGROUND The prevalence of smoking among people living with HIV (PLHIV) is higher than that reported in the general population, and it is a significant risk factor for noncommunicable diseases in this group. Mobile phone interventions to promote healthier behaviors (mobile health, mHealth) have the potential to reach a large number of people at a low cost. It has been hypothesized that mHealth interventions may not be as effective as face-to-face strategies in achieving smoking cessation, but there is no systematic evidence to support this, especially among PLHIV. OBJECTIVE This study aimed to compare two modes of intervention delivery (mHealth vs face-to-face) for smoking cessation among PLHIV. METHODS Literature on randomized controlled trials (RCTs) investigating effects of mHealth or face-to-face intervention strategies on short-term (4 weeks to <6 months) and long-term (≥6 months) smoking abstinence among PLHIV was sought. We systematically reviewed relevant RCTs and conducted pairwise meta-analyses to estimate relative treatment effects of mHealth and face-to-face interventions using standard care as comparison. Given the absence of head-to-head trials comparing mHealth with face-to-face interventions, we performed adjusted indirect comparison meta-analyses to compare these interventions. RESULTS A total of 10 studies involving 1772 PLHIV met the inclusion criteria. The average age of the study population was 45 years, and women comprised about 37%. In the short term, mHealth-delivered interventions were significantly more efficacious in increasing smoking cessation than no intervention control (risk ratio, RR, 2.81, 95% CI 1.44-5.49; n=726) and face-to-face interventions (RR 2.31, 95% CI 1.13-4.72; n=726). In the short term, face-to-face interventions were no more effective than no intervention in increasing smoking cessation (RR 1.22, 95% CI 0.94-1.58; n=1144). In terms of achieving long-term results among PLHIV, there was no significant difference in the rates of smoking cessation between those who received mHealth-delivered interventions, face-to-face interventions, or no intervention. Trial sequential analysis showed that only 15.16% (726/1304) and 5.56% (632/11,364) of the required information sizes were accrued to accept or reject a 25% relative risk reduction for short- and long-term smoking cessation treatment effects. In addition, sequential monitoring boundaries were not crossed, indicating that the cumulative evidence may be unreliable and inconclusive. CONCLUSIONS Compared with face-to-face interventions, mHealth-delivered interventions can better increase smoking cessation rate in the short term. The evidence that mHealth increases smoking cessation rate in the short term is encouraging but not sufficient to allow a definitive conclusion presently. Future research should focus on strategies for sustaining smoking cessation treatment effects among PLHIV in the long term.


2018 ◽  
Vol 44 (1) ◽  
pp. 42-48 ◽  
Author(s):  
Thaís Garcia ◽  
Sílvia Aline dos Santos Andrade ◽  
Angélica Teresa Biral ◽  
André Luiz Bertani ◽  
Laura Miranda de Oliveira Caram ◽  
...  

ABSTRACT Objective: To evaluate the effectiveness of a smoking cessation program, delivered by trained health care professionals, in patients hospitalized for acute respiratory disease (RD) or heart disease (HD). Methods: Of a total of 393 patients evaluated, we included 227 (146 and 81 active smokers hospitalized for HD and RD, respectively). All participants received smoking cessation treatment during hospitalization and were followed in a cognitive-behavioral smoking cessation program for six months after hospital discharge. Results: There were significant differences between the HD group and the RD group regarding participation in the cognitive-behavioral program after hospital discharge (13.0% vs. 35.8%; p = 0.003); smoking cessation at the end of follow-up (29% vs. 31%; p < 0.001); and the use of nicotine replacement therapy (3.4% vs. 33.3%; p < 0.001). No differences were found between the HD group and the RD group regarding the use of bupropion (11.0% vs. 12.3%; p = 0.92). Varenicline was used by only 0.7% of the patients in the HD group. Conclusions: In our sample, smoking cessation rates at six months after hospital discharge were higher among the patients with RD than among those with HD, as were treatment adherence rates. The implementation of smoking cessation programs for hospitalized patients with different diseases, delivered by the health care teams that treat these patients, is necessary for greater effectiveness in smoking cessation.


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