Dataset Information

Estimating the true effectiveness of smoking cessation interventions under variable comparator conditions: A systematic review and meta-regression.

ABSTRACT:

Background and aims

Behavioural smoking cessation trials have used comparators that vary considerably between trials. Although some previous meta-analyses made attempts to account for variability in comparators, these relied on subsets of trials and incomplete data on comparators. This study aimed to estimate the relative effectiveness of (individual) smoking cessation interventions while accounting for variability in comparators using comprehensive data on experimental and comparator interventions.

Methods

A systematic review and meta-regression was conducted including 172 randomised controlled trials with at least 6 months follow-up and biochemically verified smoking cessation. Authors were contacted to obtain unpublished information. This information was coded in terms of active content and attributes of the study population and methods. Meta-regression was used to create a model predicting smoking cessation outcomes. This model was used to re-estimate intervention effects, as if all interventions have been evaluated against the same comparators. Outcome measures included log odds of smoking cessation for the meta-regression models and smoking cessation differences and ratios to compare relative effectiveness.

Results

The meta-regression model predicted smoking cessation rates well (pseudo R² = 0.44). Standardising the comparator had substantial impact on conclusions regarding the (relative) effectiveness of trials and types of intervention. Compared with a 'no support comparator', self-help was 1.33 times (95% CI = 1.16-1.49), brief physician advice 1.61 times (95% CI = 1.31-1.90), nurse individual counselling 1.76 times (95% CI = 1.62-1.90), psychologist individual counselling 2.04 times (95% CI = 1.95-2.15) and group psychologist interventions 2.06 times (95% CI = 1.92-2.20) more effective. Notably, more elaborate experimental interventions (e.g. psychologist counselling) were typically compared with more elaborate comparators, masking their effectiveness.

Conclusions

Comparator variability and underreporting of comparators obscures the interpretation, comparison and generalisability of behavioural smoking cessation trials. Comparator variability should, therefore, be taken into account when interpreting and synthesising evidence from trials. Otherwise, policymakers, practitioners and researchers may draw incorrect conclusions about the (cost) effectiveness of smoking cessation interventions and their constituent components.

SUBMITTER: Kraiss J

PROVIDER: S-EPMC10952237 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Estimating the true effectiveness of smoking cessation interventions under variable comparator conditions: A systematic review and meta-regression.

Kraiss Jannis J Viechtbauer Wolfgang W Black Nicola N Johnston Marie M Hartmann-Boyce Jamie J Eisma Maarten M Javornik Neza N Bricca Alessio A Michie Susan S West Robert R de Bruin Marijn M

Addiction (Abingdon, England) 20230524 10

<h4>Background and aims</h4>Behavioural smoking cessation trials have used comparators that vary considerably between trials. Although some previous meta-analyses made attempts to account for variability in comparators, these relied on subsets of trials and incomplete data on comparators. This study aimed to estimate the relative effectiveness of (individual) smoking cessation interventions while accounting for variability in comparators using comprehensive data on experimental and comparator in ...[more]

PMID: 37132077

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Project description:ImportanceGuidelines recommend cancer care clinicians offer smoking cessation treatment. Cost analyses will help stakeholders understand and plan for implementation of cessation programs.ObjectiveTo estimate the incremental cost per quit (ICQ) of adopting an intensive smoking cessation intervention among patients undergoing treatment at cancer care clinics, from a clinic perspective.Design, setting, and participantsThis economic evaluation, a secondary analysis of the Smokefree Support Study (conducted 2013-2018; completed 2021), used microcosting methods and sensitivity analyses to estimate the ICQ of the interventions. Participants included patients undergoing treatment for a broad range of solid tumors and lymphomas who reported current smoking and were receiving care at cancer care clinics within 2 academic medical centers.ExposuresIntensive smoking cessation treatment (up to 11 counseling sessions with free medications), standard of care (up to 4 counseling sessions with medication advice), or usual care (referral to the state quitline).Main outcomes and measuresTotal costs, component-specific costs, and the ICQ of the intensive smoking cessation treatment relative to both standard of care (comparator in the parent randomized trial) and usual care (a common comparator outside this trial) were calculated. Overall and post hoc site-specific estimates are provided. Because usual care was not included in the parent trial, sensitivity analyses were conducted to assess how assumptions about usual care quit rates affected study outcomes (ie, base case [from a published smoking cessation trial among patients with thoracic cancer], best case, and conservative case scenarios).ResultsThe per-patient costs of offering intensive smoking cessation treatment, standard of care, and usual care were $1989, $1482, and $0, respectively. For intensive treatment, the dominant costs were treatment (35%), staff supervision (26%), and patient enrollment (24%). Relative to standard of care, intensive treatment had an overall ICQ of $3906, and one site had an ICQ of $2892. Relative to usual care, intensive treatment had an ICQ of $9866 overall (base case), although at one site, the ICQ was $5408 (base case) and $3786 (best case).Conclusions and relevanceIn this economic evaluation study, implementation of an intensive smoking cessation treatment intervention was moderately to highly cost-effective, depending on existing smoking cessation services in place.

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:IntroductionHospitalization is a unique opportunity for smoking cessation, but prior interventions have measured efficacy with narrowly defined populations. The objective of this study was to enroll smokers admitted to two "safety net" hospitals and compare the effectiveness of two post-discharge cessation interventions.DesignA randomized comparative effectiveness trial was conducted.Setting/participantsAt two New York City public hospitals, every hospitalized patient identified as a smoker (based on admission records) was approached. Inclusion criteria were: smoked cigarettes in the past 30 days; spoke English, Spanish, or Mandarin; had a U.S. phone number; not discharged to an institution where follow-up or smoking was limited; and not pregnant/breastfeeding. Of 18,797 patients identified as current smokers between July 2011 and April 2014, a total of 3,047 (16%) were discharged before being approached, 3,273 (17%) were not current smokers, 4,026 (21%) had no U.S. phone number, 2,831 (15%) were ineligible for other reasons, and 3,983 (21%) refused participation. In total, 1,618 (9%) participants enrolled in the study. During follow-up, 69% of participants were reached at 2 months and 68% at 6 months.InterventionAt discharge, participants were randomized to multisession telephone counseling from study staff (n=804) or referral to the state quitline for proactive outreach and counseling (n=814).Main outcome measuresSelf-reported abstinence at 6 months was measured. Analyses were conducted in late 2015.ResultsOne quarter of participants were homeless or in unstable housing, 60% had a history of substance abuse, 43% reported current hazardous drinking, and half had a psychiatric diagnosis other than substance abuse. At follow-up, the rate of abstinence (30-day point prevalence) was higher in the intensive counseling arm than the quitline arm at 2 months (29.0% vs 20.7%; relative risk=1.40; 95% CI=1.13, 1.73) and 6 months (37.4% vs 31.5%; relative risk=1.19; 95% CI=1.01, 1.40).ConclusionsIntensive counseling was more effective than referral to the state quitline. Long-term abstinence was excellent in both groups. Many patients were not eligible for enrollment despite minimal exclusion criteria.Trial registrationThis study is registered at www.clinicaltrials.gov NCT01363245.

Project description:BackgroundHealthcare professionals, including nurses, frequently advise people to improve their health by stopping smoking. Such advice may be brief, or part of more intensive interventions.ObjectivesTo determine the effectiveness of nursing-delivered smoking cessation interventions in adults. To establish whether nursing-delivered smoking cessation interventions are more effective than no intervention; are more effective if the intervention is more intensive; differ in effectiveness with health state and setting of the participants; are more effective if they include follow-ups; are more effective if they include aids that demonstrate the pathophysiological effect of smoking.Search methodsWe searched the Cochrane Tobacco Addiction Group Specialized Register and CINAHL in January 2017.Selection criteriaRandomized trials of smoking cessation interventions delivered by nurses or health visitors with follow-up of at least six months.Data collection and analysisTwo review authors extracted data independently. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates if available. Where statistically and clinically appropriate, we pooled studies using a Mantel-Haenszel fixed-effect model and reported the outcome as a risk ratio (RR) with a 95% confidence interval (CI).Main resultsFifty-eight studies met the inclusion criteria, nine of which are new for this update. Pooling 44 studies (over 20,000 participants) comparing a nursing intervention to a control or to usual care, we found the intervention increased the likelihood of quitting (RR 1.29, 95% CI 1.21 to 1.38); however, statistical heterogeneity was moderate (I2 = 50%) and not explained by subgroup analysis. Because of this, we judged the quality of evidence to be moderate. Despite most studies being at unclear risk of bias in at least one domain, we did not downgrade the quality of evidence further, as restricting the main analysis to only those studies at low risk of bias did not significantly alter the effect estimate. Subgroup analyses found no evidence that high-intensity interventions, interventions with additional follow-up or interventions including aids that demonstrate the pathophysiological effect of smoking are more effective than lower intensity interventions, or interventions without additional follow-up or aids. There was no evidence that the effect of support differed by patient group or across healthcare settings.Authors' conclusionsThere is moderate quality evidence that behavioural support to motivate and sustain smoking cessation delivered by nurses can lead to a modest increase in the number of people who achieve prolonged abstinence. There is insufficient evidence to assess whether more intensive interventions, those incorporating additional follow-up, or those incorporating pathophysiological feedback are more effective than one-off support. There was no evidence that the effect of support differed by patient group or across healthcare settings.

Project description:BackgroundSmoking cessation represents an opportunity to reduce both short and long-term effects of smoking on complications after lumbar fusion and smoking-related morbidity and mortality. However, the cost-effectiveness of smoking-cessation interventions prior to lumbar fusion is not fully known.MethodsWe created a decision-analytic Markov model to evaluate the cost-effectiveness of 5 smoking-cessation strategies (behavioral counseling, nicotine replacement therapy [NRT], bupropion or varenicline monotherapy, and a combined intervention) prior to single-level, instrumented lumbar posterolateral fusion (PLF) from the health payer perspective. Probabilities, costs, and utilities were obtained from published sources. We calculated the costs and quality-adjusted life years (QALYs) associated with each strategy over multiple time horizons and accounted for uncertainty with probabilistic sensitivity analyses (PSAs) consisting of 10,000 second-order Monte Carlo simulations.ResultsEvery smoking-cessation intervention was more effective and less costly than usual care at the lifetime horizon. In the short term, behavioral counseling, NRT, varenicline monotherapy, and the combined intervention were also cost-saving, while bupropion monotherapy was more effective but more costly than usual care. The mean lifetime cost savings for behavioral counseling, NRT, bupropion monotherapy, varenicline monotherapy, and the combined intervention were $3,291 (standard deviation [SD], $868), $2,571 (SD, $479), $2,851 (SD, $830), $6,767 (SD, $1,604), and $34,923 (SD, $4,248), respectively. The minimum efficacy threshold (relative risk for smoking cessation) for lifetime cost savings varied from 1.01 (behavioral counseling) to 1.15 (varenicline monotherapy). A PSA revealed that the combined smoking-cessation intervention was always more effective and less costly than usual care.ConclusionsEven brief smoking-cessation interventions yield large short-term and long-term cost savings. Smoking-cessation interventions prior to PLF can both reduce costs and improve patient outcomes as health payers/systems shift toward value-based reimbursement (e.g., bundled payments) or population health models.Level of evidenceEconomic Level II. See Instructions for Authors for a complete description of levels of evidence.

Dataset Information

Estimating the true effectiveness of smoking cessation interventions under variable comparator conditions: A systematic review and meta-regression.

Background and aims

Methods

Results

Conclusions

Publications

Estimating the true effectiveness of smoking cessation interventions under variable comparator conditions: A systematic review and meta-regression.

Similar Datasets

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