Comparative efficacy and safety of pharmacological interventions for smoking cessation in healthy adults: A network meta-analysis

Effects of interventions on smoking cessation: A systematic review and network meta-analysis

A network meta-analysis (NMA) including randomized controlled trials (RCTs) was conducted to evaluate the effects of different interventions on smoking cessation. Studies were collected from online databases including PubMed, EMBASE, Cochrane Library, and Web of Science based on inclusion and exclusion criteria. Eligible studies were further examined in the NMA to compare the effect of 14 interventions on smoking cessation. Thirty-four studies were examined in the NMA, including a total of 14 interventions and 28 733 participants. The results showed that health education (HE; odds ratio ([OR] = 200.29, 95% CI [1.62, 24 794.61])), other interventions (OI; OR = 29.79, 95% CI [1.07, 882.17]) and multimodal interventions (MUIs; OR = 100.16, 95% CI [2.06, 4867.24]) were better than self-help material (SHM). HE (OR = 243.31, 95% CI [1.39, 42531.33]), MUI (OR = 121.67, 95% CI [1.64, 9004.86]) and financial incentive (FI; OR = 14.09, 95% CI [1.21, 164.31]) had positive effects on smoking cessation rate than smoking cessation or quitting APP (QA). Ranking results showed that HE (83.6%) and motivation interviewing (MI; 69.6%) had better short-term effects on smoking cessation. HE and MUI provided more smoking cessation benefits than SHM and QA. FI was more effective at quitting smoking than QA. Also, HE and MI were more likely to be optimal smoking cessation interventions.

Appeal of Tobacco Quitline Services Among Low-Income Smokers

INTRODUCTION

State tobacco quitlines are delivering cessation assistance through an increasingly diverse range of channels. However, offerings vary from state to state, many smokers are unaware of what is available, and it is not yet clear how much demand exists for different types of assistance. In particular, the demand for online and digital cessation interventions among low-income smokers, who bear a disproportionate burden of tobacco-related disease, is not well understood.

METHODS

We examined interest in using 13 tobacco quitline services in a racially diverse sample of 1,605 low-income smokers in 9 states who had called a 2-1-1 helpline and participated in an ongoing intervention trial from June 2020 through September 2022. We classified services as standard (used by ≥90% of state quitlines [eg, calls from a quit coach, nicotine replacement therapy, printed cessation booklets]) or nonstandard (mobile app, personalized web, personalized text, online chat with quit coach).

RESULTS

Interest in nonstandard services was high. Half or more of the sample reported being very or somewhat interested in a mobile app (65%), a personalized web program (59%), or chatting online with quit coaches (49%) to help them quit. In multivariable regression analyses, younger smokers were more interested than older smokers in digital and online cessation services, as were women and smokers with greater nicotine dependence.

CONCLUSION

On average, participants were very interested in at least 3 different cessation services, suggesting that bundled or combination interventions might be designed to appeal to different groups of low-income smokers. Findings provide some initial hints about potential subgroups and the services they might use in a rapidly changing landscape of behavioral interventions for smoking cessation.

Conversational artificial intelligence interventions to support smoking cessation: A systematic review and meta-analysis

Background

Conversational artificial intelligence (chatbots and dialogue systems) is an emerging tool for tobacco cessation that has the potential to emulate personalised human support and increase engagement. We aimed to determine the effect of conversational artificial intelligence interventions with or without standard tobacco cessation interventions on tobacco cessation outcomes among adults who smoke, compared to no intervention, placebo intervention or an active comparator.

Methods

A comprehensive search of six databases was completed in June 2022. Eligible studies included randomised controlled trials published since 2005. The primary outcome was sustained tobacco abstinence, self-reported and/or biochemically validated, for at least 6 months. Secondary outcomes included point-prevalence abstinence and sustained abstinence of less than 6 months. Two authors independently extracted data on cessation outcomes and completed the risk of bias assessment. Random effects meta-analysis was conducted.

Results

From 819 studies, five randomised controlled trials met inclusion criteria (combined sample size n = 58,796). All studies differed in setting, methodology, intervention, participants and end-points. Interventions included chatbots embedded in multi- and single-component smartphone apps (n = 3), a social media-based (n = 1) chatbot, and an internet-based avatar (n = 1). Random effects meta-analysis of three studies found participants in the conversational artificial intelligence enhanced intervention were significantly more likely to quit smoking at 6-month follow-up compared to control group participants (RR = 1.29, 95% CI (1.13, 1.46), p < 0.001). Loss to follow up was generally high. Risk of bias was high overall.

Conclusion

We found limited but promising evidence on the effectiveness of conversational artificial intelligence interventions for tobacco cessation. Although all studies found benefits from conversational artificial intelligence interventions, results should be interpreted with caution due to high heterogeneity. Given the rapid evolution and potential of artificial intelligence interventions, further well-designed randomised controlled trials following standardised reporting guidelines are warranted in this emerging area.

F, Deng X, Wang Y, Wang Z, Wu Y, Xu M, Yang C, Li X, Yang K. Pharmacological interventions on smoking cessation: A systematic review and network meta-analysis

Objective: A network meta-analysis based on randomized controlled trials was conducted to investigate the effects of pharmacological interventions on smoking cessation.

Methods: English databases were searched to obtain randomized controlled trials reporting the effect of pharmacological interventions on smoking cessation. The risk of bias for the included trials was assessed using Cochrane Handbook tool. Stata 15.1 software was used to perform network meta-analysis, and GRADE approach was used to assess the evidence credibility on the effects of different interventions on smoking cessation.

Results: A total of 159 studies involving 60,285 smokers were included in the network meta-analysis. The analysis involved 15 interventions and which yielded 105 pairs of comparisons. Network meta-analysis showed that varenicline was more helpful for smoking cessation than other monotherapies, such as nicotine replacement therapy [Odds Ratio (OR) = 1.42, 95% confidence interval (CI) (1.16, 1.73)] and bupropion [OR = 1.52, 95% CI (1.22, 1.89)]. Furthermore, combined interventions were superior to monotherapy in achieving smoking cessation, such as varenicline plus bupropion over bupropion [OR = 2.00, 95% CI (1.11, 3.61)], varenicline plus nicotine replacement therapy over nicotine replacement therapy [OR = 1.84, 95% CI (1.07, 3.18)], and nicotine replacement therapy plus mecamylamine over naltrexone [OR = 6.29, 95% CI (1.59, 24.90)]. Finally, the surface under the cumulative ranking curve value indicated that nicotine replacement therapy plus mecamylamine had the greatest probability of becoming the best intervention.

Conclusion: Most pharmacological interventions demonstrated a benefit in smoking cessation compared with placebo, whether monotherapy or combination therapy. Moreover, confirmed evidence suggested that some combination treatments, such as varenicline plus bupropion and nicotine replacement therapy plus mecamylamine have a higher probability of being the best smoking cessation in