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Impact of genetic notification on smoking cessation: systematic review and pooled-analysis.

ABSTRACT: OBJECTIVES: This study aimed to evaluate the impact of genetic notification of smoking-related disease risk on smoking cessation in the general population. Secondary objectives were to assess the impact of genetic notification on intention-to-quit smoking and on emotional outcomes as well as the understanding and the recall of this notification. METHODS: A systematic review of articles from inception to August 2011 without language restriction was realized using PubMed, Embase, Scopus, Web of Science, PsycINFO and Toxnet. Other publications were identified using hand search. The pooled-analysis included only randomized trials. Comparison groups were (i) high and low genetic risk versus control, and (ii) high versus low genetic risk. For the pooled-analysis random effect models were applied and sensitivity analyses were conducted. RESULTS: Eight papers from seven different studies met the inclusion criteria of the review. High genetic risk notification was associated with short-term increased depression and anxiety. Four randomized studies were included in the pooled-analysis, which revealed a significant impact of genetic notification on smoking cessation in comparison to controls (clinical risk notification or no intervention) in short term follow-up less than 6 months (RR = 1.55, 95% CI 1.09-2.21). CONCLUSIONS: In short term follow-up, genetic notification increased smoking cessation in comparison to control interventions. However, there is no evidence of long term effect (up to 12 month) on smoking cessation. Further research is needed to assess more in depth how genetic notification of smoking-related disease could contribute to smoking cessation.

SUBMITTER: de Viron S

PROVIDER: S-EPMC3394798 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Impact of genetic notification on smoking cessation: systematic review and pooled-analysis.

de Viron Sylviane S Van der Heyden Johan J Ambrosino Elena E Arbyn Marc M Brand Angela A Van Oyen Herman H

PloS one 20120711 7

<h4>Objectives</h4>This study aimed to evaluate the impact of genetic notification of smoking-related disease risk on smoking cessation in the general population. Secondary objectives were to assess the impact of genetic notification on intention-to-quit smoking and on emotional outcomes as well as the understanding and the recall of this notification.<h4>Methods</h4>A systematic review of articles from inception to August 2011 without language restriction was realized using PubMed, Embase, Scop ...[more]

PMID: 22808123

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Project description:BACKGROUND: Smoking remains the leading preventable cause of premature deaths. Several pharmacological interventions now exist to aid smokers in cessation. These include Nicotine Replacement Therapy [NRT], bupropion, and varenicline. We aimed to assess their relative efficacy in smoking cessation by conducting a systematic review and meta-analysis. METHODS: We searched 10 electronic medical databases (inception to Sept. 2006) and bibliographies of published reviews. We selected randomized controlled trials [RCTs] evaluating interventions for smoking cessation at 1 year, through chemical confirmation. Our primary endpoint was smoking cessation at 1 year. Secondary endpoints included short-term smoking cessation (approximately 3 months) and adverse events. We conducted random-effects meta-analysis and meta-regression. We compared treatment effects across interventions using head-to-head trials and when these did not exist, we calculated indirect comparisons. RESULTS: We identified 70 trials of NRT versus control at 1 year, Odds Ratio [OR] 1.71, 95% Confidence Interval [CI], 1.55-1.88, P =< 0.0001). This was consistent when examining all placebo-controlled trials (49 RCTs, OR 1.78, 95% CI, 1.60-1.99), NRT gum (OR 1.60, 95% CI, 1.37-1.86) or patch (OR 1.63, 95% CI, 1.41-1.89). NRT also reduced smoking at 3 months (OR 1.98, 95% CI, 1.77-2.21). Bupropion trials were superior to controls at 1 year (12 RCTs, OR1.56, 95% CI, 1.10-2.21, P = 0.01) and at 3 months (OR 2.13, 95% CI, 1.72-2.64). Two RCTs evaluated the superiority of bupropion versus NRT at 1 year (OR 1.14, 95% CI, 0.20-6.42). Varenicline was superior to placebo at 1 year (4 RCTs, OR 2.96, 95% CI, 2.12-4.12, P =< 0.0001) and also at approximately 3 months (OR 3.75, 95% CI, 2.65-5.30). Three RCTs evaluated the effectiveness of varenicline versus bupropion at 1 year (OR 1.58, 95% CI, 1.22-2.05) and at approximately 3 months (OR 1.61, 95% CI, 1.16-2.21). Using indirect comparisons, varenicline was superior to NRT when compared to placebo controls (OR 1.66, 95% CI 1.17-2.36, P = 0.004) or to all controls at 1 year (OR 1.73, 95% CI 1.22-2.45, P = 0.001). This was also the case for 3-month data. Adverse events were not systematically different across studies. CONCLUSION: NRT, bupropion and varenicline all provide therapeutic effects in assisting with smoking cessation. Direct and indirect comparisons identify a hierarchy of effectiveness.

Project description:BackgroundRapid advancements in eHealth and mobile health (mHealth) technologies have driven researchers to design and evaluate numerous technology-based interventions to promote smoking cessation. The evolving nature of cessation interventions emphasizes a strong need for knowledge synthesis.ObjectiveThis systematic review and meta-analysis aimed to summarize recent evidence from randomized controlled trials regarding the effectiveness of eHealth-based smoking cessation interventions in promoting abstinence and assess nonabstinence outcome indicators, such as cigarette consumption and user satisfaction, via narrative synthesis.MethodsWe searched for studies published in English between 2017 and June 30, 2022, in 4 databases: PubMed (including MEDLINE), PsycINFO, Embase, and Cochrane Library. Two independent reviewers performed study screening, data extraction, and quality assessment based on the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. We pooled comparable studies based on the population, follow-up time, intervention, and control characteristics. Two researchers performed an independent meta-analysis on smoking abstinence using the Sidik-Jonkman random-effects model and log risk ratio (RR) as the effect measurement. For studies not included in the meta-analysis, the outcomes were narratively synthesized.ResultsA total of 464 studies were identified through an initial database search after removing duplicates. Following screening and full-text assessments, we deemed 39 studies (n=37,341 participants) eligible for this review. Of these, 28 studies were shortlisted for meta-analysis. According to the meta-analysis, SMS or app text messaging can significantly increase both short-term (3 months) abstinence (log RR=0.50, 95% CI 0.25-0.75; I2=0.72%) and long-term (6 months) abstinence (log RR=0.77, 95% CI 0.49-1.04; I2=8.65%), relative to minimal cessation support. The frequency of texting did not significantly influence treatment outcomes. mHealth apps may significantly increase abstinence in the short term (log RR=0.76, 95% CI 0.09-1.42; I2=88.02%) but not in the long term (log RR=0.15, 95% CI -0.18 to 0.48; I2=80.06%), in contrast to less intensive cessation support. In addition, personalized or interactive interventions showed a moderate increase in cessation for both the short term (log RR=0.62, 95% CI 0.30-0.94; I2=66.50%) and long term (log RR=0.28, 95% CI 0.04-0.53; I2=73.42%). In contrast, studies without any personalized or interactive features had no significant impact. Finally, the treatment effect was similar between trials that used biochemically verified or self-reported abstinence. Among studies reporting outcomes besides abstinence (n=20), a total of 11 studies reported significantly improved nonabstinence outcomes in cigarette consumption (3/14, 21%) or user satisfaction (8/19, 42%).ConclusionsOur review of 39 randomized controlled trials found that recent eHealth interventions might promote smoking cessation, with mHealth being the dominant approach. Despite their success, the effectiveness of such interventions may diminish with time. The design of more personalized interventions could potentially benefit future studies.Trial registrationPROSPERO CRD42022347104; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=347104.

Project description:ObjectivesThe negative effects of smoking on numerous cardiovascular and metabolic diseases have been widely acknowledged. However, the potential effect of smoking cessation is relatively unelucidated. The objective of this study is to explore whether the prevalence of non-alcoholic fatty liver disease (NAFLD) in former smokers differs from the prevalence in current smokers.DesignSystematic review and meta-analysis.Data sourcesFour databases, that is, PubMed, Web of Science, Journal@Ovid and Scopus were searched from inception to 31 January 2023.Eligibility criteriaPopulation-based cross-sectional studies, including the baseline data of cohort studies with identified NAFLD diagnostic methods, and smoking status (current smoker or former smoker) of participants were included.Data extraction and synthesisTwo reviewers independently extracted the data including cigarette smoking status, country/region of studies, NAFLD diagnostic methods, sex, the average age and body mass index (BMI) of NAFLD participants and assessed the risk of bias with Agency for Healthcare Research and Quality (AHRQ) methodology checklist. Risk ratio (RR) of NAFLD prevalence in former smokers was pooled using the random-effects model.Results28 studies involving 4 465 862 participants were included. Compared with current smokers, the RR of overall NAFLD prevalence in former smokers was 1.13 (95% CI: 1.08 to 1.19, prediction interval: 0.92-1.39). This result persisted after adjustment for diagnostic methods, country/region, sex, age and BMI. Sensitivity analysis and risk of bias assessment indicated a stable conclusion.ConclusionsNAFLD prevalence in former smokers was at least not lower than that in current smokers and was partially related to increased BMI after smoking cessation, indicating that smoking cessation was possibly not a protective factor against NAFLD. Although the meta-analysis based on cross-sectional studies cannot conclude the causal relationships between smoking cessation and NAFLD onset, the potential onset of NAFLD associated with smoking cessation should be highlighted.Prospero registration numberCRD42023394944.

Project description:ObjectiveTo investigate change in mental health after smoking cessation compared with continuing to smoke.DesignSystematic review and meta-analysis of observational studies.Data sourcesWeb of Science, Cochrane Central Register of Controlled Trials, Medline, Embase, and PsycINFO for relevant studies from inception to April 2012. Reference lists of included studies were hand searched, and authors were contacted when insufficient data were reported.Eligibility criteria for selecting studiesLongitudinal studies of adults that assessed mental health before smoking cessation and at least six weeks after cessation or baseline in healthy and clinical populations.Results26 studies that assessed mental health with questionnaires designed to measure anxiety, depression, mixed anxiety and depression, psychological quality of life, positive affect, and stress were included. Follow-up mental health scores were measured between seven weeks and nine years after baseline. Anxiety, depression, mixed anxiety and depression, and stress significantly decreased between baseline and follow-up in quitters compared with continuing smokers: the standardised mean differences (95% confidence intervals) were anxiety -0.37 (95% confidence interval -0.70 to -0.03); depression -0.25 (-0.37 to -0.12); mixed anxiety and depression -0.31 (-0.47 to -0.14); stress -0.27 (-0.40 to -0.13). Both psychological quality of life and positive affect significantly increased between baseline and follow-up in quitters compared with continuing smokers 0.22 (0.09 to 0.36) and 0.40 (0.09 to 0.71), respectively). There was no evidence that the effect size differed between the general population and populations with physical or psychiatric disorders.ConclusionsSmoking cessation is associated with reduced depression, anxiety, and stress and improved positive mood and quality of life compared with continuing to smoke. The effect size seems as large for those with psychiatric disorders as those without. The effect sizes are equal or larger than those of antidepressant treatment for mood and anxiety disorders.

Project description:Objective:The authors carried out a systematic review and a meta-analysis on smoking cessation interventions on health -care workers to clarify the state of the art interventions and to identify the best one. Materials and Methods:This review was registered with PROSPERO: CRD42019130117. The databases PubMed, Scopus, Web of Science and CINAHL were searched until December 2018. Quality of all studies included in the systematic review was assessed according to the Newcastle-Ottawa Scale (NOS) on cohort or cross-sectional studies and to the Cochrane Risk of Bias Tool for Randomized Controlled Trials. Meta-analysis and meta-regression analyses were also carried out for cohort studies (quasi-experimental or a before-after studies design) and clinical trials. Results:Twenty-four studies have been included in the analysis: four before-after, 13 cross-sectional, three quasi-experimental studies and four clinical trials. Articles were heterogeneous (P for homogeneity <0.01), but they have all shown positive results since they reached the goal of smoking cessation among health-care workers, even if with different proportions. Meta-analysis was performed on 10 studies (six cohort studies and four clinical trials), showing a 21% of success rate from the application of smoking cessation interventions, either pharmacological or behavioral ones. The resulted pooled RR (Risk Ratio) was 1.21 (95% CI [1.06-1.38]), being 24% of success rate from clinical trials (pooled RR 1.244; 95% CI [1.099-1.407]) and 19% of success rate from cohort studies (pooled RR 1.192; 0.996-1.426). However, two studies have confidence intervals which include unity and one study has a wide confidence interval; as a consequence, the meta-analysis for its results depends heavily on one single study. Meta-regression analysis revealed that results were influenced by the number of participants. Conclusion:Both policy and pharmaceutical interventions can obtain positive results in quitting smoking among health-care workers. However, as shown by our review, combination approaches can produce better results in terms of cessation percentages and smoking abstinence.

Dataset Information

Impact of genetic notification on smoking cessation: systematic review and pooled-analysis.

Publications

Impact of genetic notification on smoking cessation: systematic review and pooled-analysis.

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