Opportunistic smoking cessation interventions for people accessing financial support settings: A scoping review.

AIM: The aim of this work was to systematically scope the evidence on opportunistic tobacco smoking cessation interventions for people accessing financial support settings. METHODS: We searched MEDLINE, Embase, PsycINFO and the Cochrane Tobacco Addiction Group specialized register to 21 March 2023. We duplicate screened 20% of titles/abstracts and all full texts. We included primary studies investigating smoking cessation interventions delivered opportunistically to people who smoked tobacco, within settings offering support for problems caused by financial hardship, for example homeless support services, social housing and food banks. Data were charted by one reviewer, checked by another and narratively synthesized. RESULTS: We included 25 studies conducted in a range of financial support settings using qualitative (e.g. interviews and focus groups) and quantitative (e.g. randomized controlled trials, surveys and single arm intervention studies) methodologies. Evidence on the acceptability and feasibility of opportunistic smoking cessation advice was investigated among both clients and providers. Approximately 90% of service providers supported such interventions; however, lack of resources, staff training and a belief that tobacco smoking reduced illicit substance use were perceived barriers. Clients welcomed being asked about smoking and offered assistance to quit and expressed interest in interventions including the provision of nicotine replacement therapy, e-cigarettes and incentives to quit smoking. Six studies investigated the comparative effectiveness of opportunistic smoking cessation interventions on quitting success, with five comparing more to less intensive interventions, with mixed results. CONCLUSIONS: Most studies investigating opportunistic smoking cessation interventions in financial support settings have not measured their effectiveness. Where they have, settings, populations, interventions and findings have varied. There is more evidence investigating acceptability, with promising results.

Transitions between smoking and vaping: Evidence (or lack thereof) on potential differences by gender and sex.

OBJECTIVE: To synthesize existing evidence on possible differential effects by sex and gender from two Cochrane reviews evaluating vaping and smoking transitions. METHODS: We screened included studies from two Cochrane reviews for studies reporting smoking outcomes based on gender or sex. The first review examines the effects of using e-cigarettes to help people quit smoking and includes randomized controlled trials and uncontrolled intervention studies published to July 2023. The second review aims to assess the evidence on the relationship between the use and availability of e-cigarettes and subsequent smoking in young people (aged 29 and younger) and includes quasi-experimental and cohort studies published to April 2023. Due to the paucity and heterogeneity of data, we report results narratively. RESULTS: 10 of 161 studies included in the two relevant reviews met our criteria. Only five reported analyzing whether observed effects or associations varied based on sex and/or gender. A further three provided relevant descriptive information, and two did not report overall outcomes regarding vaping and smoking transitions but did investigate whether these differed by sex/gender. Synthesized data were largely inconclusive, but there was some suggestion that vaping was more strongly associated with subsequent smoking in young males than females. No studies reported data on nonbinary participants. CONCLUSIONS: Despite plausible reasons why sex and gender may be moderators of vaping and smoking transitions, there is little evidence investigating this. Future studies of vaping and smoking transitions should conduct and report analyses investigating potential differences based on sex and gender.

Electronic cigarettes for smoking cessation.

BACKGROUND: Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol by heating an e-liquid. People who smoke, healthcare providers and regulators want to know if ECs can help people quit smoking, and if they are safe to use for this purpose. This is a review update conducted as part of a living systematic review. OBJECTIVES: To examine the safety, tolerability and effectiveness of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence, in comparison to non-nicotine EC, other smoking cessation treatments and no treatment. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's Specialized Register to 1 February 2023, and Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 July 2023, and reference-checked and contacted study authors. SELECTION CRITERIA: We included trials in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention as these studies have the potential to provide further information on harms and longer-term use. Studies had to report an eligible outcome. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods for screening and data extraction. Critical outcomes were abstinence from smoking after at least six months, adverse events (AEs), and serious adverse events (SAEs). We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in pairwise and network meta-analyses (NMA). MAIN RESULTS: We included 88 completed studies (10 new to this update), representing 27,235 participants, of which 47 were randomized controlled trials (RCTs). Of the included studies, we rated ten (all but one contributing to our main comparisons) at low risk of bias overall, 58 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There is high certainty that nicotine EC increases quit rates compared to nicotine replacement therapy (NRT) (RR 1.59, 95% CI 1.29 to 1.93; I2 = 0%; 7 studies, 2544 participants). In absolute terms, this might translate to an additional four quitters per 100 (95% CI 2 to 6 more). There is moderate-certainty evidence (limited by imprecision) that the rate of occurrence of AEs is similar between groups (RR 1.03, 95% CI 0.91 to 1.17; I2 = 0%; 5 studies, 2052 participants). SAEs were rare, and there is insufficient evidence to determine whether rates differ between groups due to very serious imprecision (RR 1.20, 95% CI 0.90 to 1.60; I2 = 32%; 6 studies, 2761 participants; low-certainty evidence). There is moderate-certainty evidence, limited by imprecision, that nicotine EC increases quit rates compared to non-nicotine EC (RR 1.46, 95% CI 1.09 to 1.96; I2 = 4%; 6 studies, 1613 participants). In absolute terms, this might lead to an additional three quitters per 100 (95% CI 1 to 7 more). There is moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 5 studies, 1840 participants). There is insufficient evidence to determine whether rates of SAEs differ between groups, due to very serious imprecision (RR 1.00, 95% CI 0.56 to 1.79; I2 = 0%; 9 studies, 1412 participants; low-certainty evidence). Due to issues with risk of bias, there is low-certainty evidence that, compared to behavioural support only/no support, quit rates may be higher for participants randomized to nicotine EC (RR 1.88, 95% CI 1.56 to 2.25; I2 = 0%; 9 studies, 5024 participants). In absolute terms, this represents an additional four quitters per 100 (95% CI 2 to 5 more). There was some evidence that (non-serious) AEs may be more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low-certainty evidence; 4 studies, 765 participants) and, again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 0.89, 95% CI 0.59 to 1.34; I2 = 23%; 10 studies, 3263 participants; very low-certainty evidence). Results from the NMA were consistent with those from pairwise meta-analyses for all critical outcomes, and there was no indication of inconsistency within the networks. Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued EC use. Very few studies reported data on other outcomes or comparisons, hence, evidence for these is limited, with CIs often encompassing both clinically significant harm and benefit. AUTHORS' CONCLUSIONS: There is high-certainty evidence that ECs with nicotine increase quit rates compared to NRT and moderate-certainty evidence that they increase quit rates compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain due to risk of bias inherent in the study design. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs nor between nicotine ECs and NRT. Overall incidence of SAEs was low across all study arms. We did not detect evidence of serious harm from nicotine EC, but the longest follow-up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates. Further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Optimizing process and methods for a living systematic review: 30 search updates and three review updates later.

OBJECTIVE: To describe the living systematic review (LSR) process and to share experience of planning, searches, screening, extraction, publishing and dissemination to inform and assist authors planning their own LSR. Many LSR do not publish more than one update, we hope this paper helps to increase this. STUDY DESIGN AND SETTING: A Cochrane LSR with an international author team that has been 'living' for two years, with monthly search updates and three full updates published in this time. LSRs are regularly updated systematic reviews that allow new evidence to be incorporated as it becomes available. LSR are ideally suited to policy-relevant topics where there is uncertainty and new evidence will likely impact the interpretation and/or certainty of outcomes. RESULTS: The key features of the process that require consideration are: specifying the frequency of searches and triggers for full updates in the protocol; stakeholder input; publishing and disseminating monthly search findings. A strong team, incorporating methodological and topic expertise, with core members that meet regularly is essential. Regular search updates make it important to have a clear cyclical schedule of activity. To achieve timely updates this process should be streamlined, for example, using automated monthly searches, and systematic reviewing software for screening. LSR provide a unique opportunity to incorporate stakeholder feedback. CONCLUSIONS: We recommend that LSRs should be: justified; carefully planned including the timing of search updates, triggers for publication and termination; published in a timely manner; have a clear dissemination plan; and a strong core team of authors.

Effectiveness of culturally tailoring smoking cessation interventions for reducing or quitting combustible tobacco: A systematic review and meta-analyses.

BACKGROUND AND AIMS: Standard approaches to smoking cessation may not be as effective for certain populations, and tailoring on cultural factors could improve their effectiveness. This systematic review measured the effectiveness of culturally tailoring smoking cessation interventions on quitting or reducing smoking combustible tobacco. METHOD: We searched MEDLINE, PsychInfo, Embase and Cochrane Central Register from inception to 21 June 2023 for randomized controlled trials (RCTs) of community-based, primary care or web-based interventions for smoking cessation in adults who smoked tobacco, with measurement of smoking abstinence or reduction at least 3 months following baseline. We examined comparisons between either an intensity-matched culturally tailored intervention and a non-tailored intervention or a standard non-tailored intervention and the same intervention plus a culturally tailored adjunct. We sub-grouped studies according to the level of tailoring and performed subgroup analyses where appropriate. We assessed risk of bias and certainty of evidence. RESULTS: We identified 43 studies, 33 of which were meta-analyzed (n = 12 346 participants). We found moderate certainty evidence, limited by heterogeneity, that intensity-matched culturally tailored cessation interventions increased quit success when compared with non-tailored interventions at 3-month follow-up or longer (n = 5602, risk ratio [RR] = 1.29 95% confidence interval [CI] 1.10, 1.51, I2  = 47%, 14 studies). We found a positive effect of adding a culturally tailored component to a standard intervention compared with the standard intervention alone (n = 6674, RR = 1.47, 95% CI 1.10, 1.95, I2  = 74%, 18 studies), but our certainty in this effect was low due to imprecision and substantial statistical heterogeneity. CONCLUSION: Culturally tailored smoking cessation interventions may help more people to quit smoking than a non-tailored intervention. Adapting or adding cultural components to smoking cessation interventions originally developed for majority populations could improve cessation rates in populations who do not fully identify with majority cultural norms.

Pharmacological and electronic cigarette interventions for smoking cessation in adults: component network meta-analyses.

BACKGROUND: Tobacco smoking is the leading preventable cause of death and disease worldwide. Stopping smoking can reduce this harm and many people would like to stop. There are a number of medicines licenced to help people quit globally, and e-cigarettes are used for this purpose in many countries. Typically treatments work by reducing cravings to smoke, thus aiding initial abstinence and preventing relapse. More information on comparative effects of these treatments is needed to inform treatment decisions and policies. OBJECTIVES: To investigate the comparative benefits, harms and tolerability of different smoking cessation pharmacotherapies and e-cigarettes, when used to help people stop smoking tobacco. SEARCH METHODS: We identified studies from recent updates of Cochrane Reviews investigating our interventions of interest. We updated the searches for each review using the Cochrane Tobacco Addiction Group (TAG) specialised register to 29 April 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs), cluster-RCTs and factorial RCTs, which measured smoking cessation at six months or longer, recruited adults who smoked combustible cigarettes at enrolment (excluding pregnant people) and randomised them to approved pharmacotherapies and technologies used for smoking cessation worldwide (varenicline, cytisine, nortriptyline, bupropion, nicotine replacement therapy (NRT) and e-cigarettes) versus no pharmacological intervention, placebo (control) or another approved pharmacotherapy. Studies providing co-interventions (e.g. behavioural support) were eligible if the co-intervention was provided equally to study arms. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods for screening, data extraction and risk of bias (RoB) assessment (using the RoB 1 tool). Primary outcome measures were smoking cessation at six months or longer, and the number of people reporting serious adverse events (SAEs). We also measured withdrawals due to treatment. We used Bayesian component network meta-analyses (cNMA) to examine intervention type, delivery mode, dose, duration, timing in relation to quit day and tapering of nicotine dose, using odds ratios (OR) and 95% credibility intervals (CrIs). We calculated an effect estimate for combination NRT using an additive model. We evaluated the influence of population and study characteristics, provision of behavioural support and control arm rates using meta-regression. We evaluated certainty using GRADE. MAIN RESULTS: Of our 332 eligible RCTs, 319 (835 study arms, 157,179 participants) provided sufficient data to be included in our cNMA. Of these, we judged 51 to be at low risk of bias overall, 104 at high risk and 164 at unclear risk, and 118 reported pharmaceutical or e-cigarette/tobacco industry funding. Removing studies at high risk of bias did not change our interpretation of the results. Benefits We found high-certainty evidence that nicotine e-cigarettes (OR 2.37, 95% CrI 1.73 to 3.24; 16 RCTs, 3828 participants), varenicline (OR 2.33, 95% CrI 2.02 to 2.68; 67 RCTs, 16,430 participants) and cytisine (OR 2.21, 95% CrI 1.66 to 2.97; 7 RCTs, 3848 participants) were associated with higher quit rates than control. In absolute terms, this might lead to an additional eight (95% CrI 4 to 13), eight (95% CrI 6 to 10) and seven additional quitters per 100 (95% CrI 4 to 12), respectively. These interventions appeared to be more effective than the other interventions apart from combination NRT (patch and a fast-acting form of NRT), which had a lower point estimate (calculated additive effect) but overlapping 95% CrIs (OR 1.93, 95% CrI 1.61 to 2.34). There was also high-certainty evidence that nicotine patch alone (OR 1.37, 95% CrI 1.20 to 1.56; 105 RCTs, 37,319 participants), fast-acting NRT alone (OR 1.41, 95% CrI 1.29 to 1.55; 120 RCTs, 31,756 participants) and bupropion (OR 1.43, 95% CrI 1.26 to 1.62; 71 RCTs, 14,759 participants) were more effective than control, resulting in two (95% CrI 1 to 3), three (95% CrI 2 to 3) and three (95% CrI 2 to 4) additional quitters per 100 respectively. Nortriptyline is probably associated with higher quit rates than control (OR 1.35, 95% CrI 1.02 to 1.81; 10 RCTs, 1290 participants; moderate-certainty evidence), resulting in two (CrI 0 to 5) additional quitters per 100. Non-nicotine/placebo e-cigarettes (OR 1.16, 95% CrI 0.74 to 1.80; 8 RCTs, 1094 participants; low-certainty evidence), equating to one additional quitter (95% CrI -2 to 5), had point estimates favouring the intervention over control, but CrIs encompassed the potential for no difference and harm. There was low-certainty evidence that tapering the dose of NRT prior to stopping treatment may improve effectiveness; however, 95% CrIs also incorporated the null (OR 1.14, 95% CrI 1.00 to 1.29; 111 RCTs, 33,156 participants). This might lead to an additional one quitter per 100 (95% CrI 0 to 2). Harms There were insufficient data to include nortriptyline and non-nicotine EC in the final SAE model. Overall rates of SAEs for the remaining treatments were low (average 3%). Low-certainty evidence did not show a clear difference in the number of people reporting SAEs for nicotine e-cigarettes, varenicline, cytisine or NRT when compared to no pharmacotherapy/e-cigarettes or placebo. Bupropion may slightly increase rates of SAEs, although the CrI also incorporated no difference (moderate certainty). In absolute terms bupropion may cause one more person in 100 to experience an SAE (95% CrI 0 to 2). AUTHORS' CONCLUSIONS: The most effective interventions were nicotine e-cigarettes, varenicline and cytisine (all high certainty), as well as combination NRT (additive effect, certainty not rated). There was also high-certainty evidence for the effectiveness of nicotine patch, fast-acting NRT and bupropion. Less certain evidence of benefit was present for nortriptyline (moderate certainty), non-nicotine e-cigarettes and tapering of nicotine dose (both low certainty). There was moderate-certainty evidence that bupropion may slightly increase the frequency of SAEs, although there was also the possibility of no increased risk. There was no clear evidence that any other tested interventions increased SAEs. Overall, SAE data were sparse with very low numbers of SAEs, and so further evidence may change our interpretation and certainty. Future studies should report SAEs to strengthen certainty in this outcome. More head-to-head comparisons of the most effective interventions are needed, as are tests of combinations of these. Future work should unify data from behavioural and pharmacological interventions to inform approaches to combined support for smoking cessation.

Different doses, durations and modes of delivery of nicotine replacement therapy for smoking cessation.

BACKGROUND: Nicotine replacement therapy (NRT) aims to replace nicotine from cigarettes. This helps to reduce cravings and withdrawal symptoms, and ease the transition from cigarette smoking to complete abstinence. Although there is high-certainty evidence that NRT is effective for achieving long-term smoking abstinence, it is unclear whether different forms, doses, durations of treatment or timing of use impacts its effects. OBJECTIVES: To determine the effectiveness and safety of different forms, deliveries, doses, durations and schedules of NRT, for achieving long-term smoking cessation. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group trials register for papers mentioning NRT in the title, abstract or keywords, most recently in April 2022. SELECTION CRITERIA: We included randomised trials in people motivated to quit, comparing one type of NRT use with another. We excluded studies that did not assess cessation as an outcome, with follow-up of fewer than six months, and with additional intervention components not matched between arms. Separate reviews cover studies comparing NRT to control, or to other pharmacotherapies. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods. We measured smoking abstinence after at least six months, using the most rigorous definition available. We extracted data on cardiac adverse events (AEs), serious adverse events (SAEs) and study withdrawals due to treatment.  MAIN RESULTS: We identified 68 completed studies with 43,327 participants, five of which are new to this update. Most completed studies recruited adults either from the community or from healthcare clinics. We judged 28 of the 68 studies to be at high risk of bias. Restricting the analysis only to those studies at low or unclear risk of bias did not significantly alter results for any comparisons apart from the preloading comparison, which tested the effect of using NRT prior to quit day whilst still smoking.  There is high-certainty evidence that combination NRT (fast-acting form plus patch) results in higher long-term quit rates than single form (risk ratio (RR) 1.27, 95% confidence interval (CI) 1.17 to 1.37; I2 = 12%; 16 studies, 12,169 participants). Moderate-certainty evidence, limited by imprecision, indicates that 42/44 mg patches are as effective as 21/22 mg (24-hour) patches (RR 1.09, 95% CI 0.93 to 1.29; I2 = 38%; 5 studies, 1655 participants), and that 21 mg patches are more effective than 14 mg (24-hour) patches (RR 1.48, 95% CI 1.06 to 2.08; 1 study, 537 participants). Moderate-certainty evidence, again limited by imprecision, also suggests a benefit of 25 mg over 15 mg (16-hour) patches, but the lower limit of the CI encompassed no difference (RR 1.19, 95% CI 1.00 to 1.41; I2 = 0%; 3 studies, 3446 participants). Nine studies tested the effect of using NRT prior to quit day (preloading) in comparison to using it from quit day onward. There was moderate-certainty evidence, limited by risk of bias, of a favourable effect of preloading on abstinence (RR 1.25, 95% CI 1.08 to 1.44; I2 = 0%; 9 studies, 4395 participants). High-certainty evidence from eight studies suggests that using either a form of fast-acting NRT or a nicotine patch results in similar long-term quit rates (RR 0.90, 95% CI 0.77 to 1.05; I2 = 0%; 8 studies, 3319 participants). We found no clear evidence of an effect of duration of nicotine patch use (low-certainty evidence); duration of combination NRT use (low- and very low-certainty evidence); or fast-acting NRT type (very low-certainty evidence). Cardiac AEs, SAEs and withdrawals due to treatment were all measured variably and infrequently across studies, resulting in low- or very low-certainty evidence for all comparisons. Most comparisons found no clear evidence of an effect on these outcomes, and rates were low overall. More withdrawals due to treatment were reported in people using nasal spray compared to patches in one study (RR 3.47, 95% CI 1.15 to 10.46; 1 study, 922 participants; very low-certainty evidence) and in people using 42/44 mg patches in comparison to 21/22 mg patches across two studies (RR 4.99, 95% CI 1.60 to 15.50; I2 = 0%; 2 studies, 544 participants; low-certainty evidence). AUTHORS' CONCLUSIONS: There is high-certainty evidence that using combination NRT versus single-form NRT and 4 mg versus 2 mg nicotine gum can result in an increase in the chances of successfully stopping smoking. Due to imprecision, evidence was of moderate certainty for patch dose comparisons. There is some indication that the lower-dose nicotine patches and gum may be less effective than higher-dose products. Using a fast-acting form of NRT, such as gum or lozenge, resulted in similar quit rates to nicotine patches. There is moderate-certainty evidence that using NRT before quitting may improve quit rates versus using it from quit date only; however, further research is needed to ensure the robustness of this finding. Evidence for the comparative safety and tolerability of different types of NRT use is limited. New studies should ensure that AEs, SAEs and withdrawals due to treatment are reported.

Antidepressants for smoking cessation.

BACKGROUND: The pharmacological profiles and mechanisms of antidepressants are varied. However, there are common reasons why they might help people to stop smoking tobacco: nicotine withdrawal can produce short-term low mood that antidepressants may relieve; and some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction. OBJECTIVES: To assess the evidence for the efficacy, harms, and tolerability of medications with antidepressant properties in assisting long-term tobacco smoking cessation in people who smoke cigarettes. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Specialised Register, most recently on 29 April 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs) in people who smoked, comparing antidepressant medications with placebo or no pharmacological treatment, an alternative pharmacotherapy, or the same medication used differently. We excluded trials with fewer than six months of follow-up from efficacy analyses. We included trials with any follow-up length for our analyses of harms. DATA COLLECTION AND ANALYSIS: We extracted data and assessed risk of bias using standard Cochrane methods. Our primary outcome measure was smoking cessation after at least six months' follow-up. We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Our secondary outcomes were harms and tolerance outcomes, including adverse events (AEs), serious adverse events (SAEs), psychiatric AEs, seizures, overdoses, suicide attempts, death by suicide, all-cause mortality, and trial dropouts due to treatment. We carried out meta-analyses where appropriate. MAIN RESULTS: We included a total of 124 studies (48,832 participants) in this review, with 10 new studies added to this update version. Most studies recruited adults from the community or from smoking cessation clinics; four studies focused on adolescents (with participants between 12 and 21 years old). We judged 34 studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk of bias did not change clinical interpretation of the results.  There was high-certainty evidence that bupropion increased smoking cessation rates when compared to placebo or no pharmacological treatment (RR 1.60, 95% CI 1.49 to 1.72; I2 = 16%; 50 studies, 18,577 participants). There was moderate-certainty evidence that a combination of bupropion and varenicline may have resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I2 = 15%; 3 studies, 1057 participants). However, there was insufficient evidence to establish whether a combination of bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.17, 95% CI 0.95 to 1.44; I2 = 43%; 15 studies, 4117 participants; low-certainty evidence). There was moderate-certainty evidence that participants taking bupropion were more likely to report SAEs than those taking placebo or no pharmacological treatment. However, results were imprecise and the CI also encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I2 = 0%; 23 studies, 10,958 participants). Results were also imprecise when comparing SAEs between people randomised to a combination of bupropion and NRT versus NRT alone (RR 1.52, 95% CI 0.26 to 8.89; I2 = 0%; 4 studies, 657 participants) and randomised to bupropion plus varenicline versus varenicline alone (RR 1.23, 95% CI 0.63 to 2.42; I2 = 0%; 5 studies, 1268 participants). In both cases, we judged evidence to be of low certainty. There was high-certainty evidence that bupropion resulted in more trial dropouts due to AEs than placebo or no pharmacological treatment (RR 1.44, 95% CI 1.27 to 1.65; I2 = 2%; 25 studies, 12,346 participants). However, there was insufficient evidence that bupropion combined with NRT versus NRT alone (RR 1.67, 95% CI 0.95 to 2.92; I2 = 0%; 3 studies, 737 participants) or bupropion combined with varenicline versus varenicline alone (RR 0.80, 95% CI 0.45 to 1.45; I2 = 0%; 4 studies, 1230 participants) had an impact on the number of dropouts due to treatment. In both cases, imprecision was substantial (we judged the evidence to be of low certainty for both comparisons). Bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.73, 95% CI 0.67 to 0.80; I2 = 0%; 9 studies, 7564 participants), and to combination NRT (RR 0.74, 95% CI 0.55 to 0.98; I2 = 0%; 2 studies; 720 participants). However, there was no clear evidence of a difference in efficacy between bupropion and single-form NRT (RR 1.03, 95% CI 0.93 to 1.13; I2 = 0%; 10 studies, 7613 participants). We also found evidence that nortriptyline aided smoking cessation when compared with placebo (RR 2.03, 95% CI 1.48 to 2.78; I2 = 16%; 6 studies, 975 participants), and some evidence that bupropion resulted in superior quit rates to nortriptyline (RR 1.30, 95% CI 0.93 to 1.82; I2 = 0%; 3 studies, 417 participants), although this result was subject to imprecision. Findings were sparse and inconsistent as to whether antidepressants, primarily bupropion and nortriptyline, had a particular benefit for people with current or previous depression. AUTHORS' CONCLUSIONS: There is high-certainty evidence that bupropion can aid long-term smoking cessation. However, bupropion may increase SAEs (moderate-certainty evidence when compared to placebo/no pharmacological treatment). There is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with people receiving placebo or no pharmacological treatment. Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo, although bupropion may be more effective. Evidence also suggests that bupropion may be as successful as single-form NRT in helping people to quit smoking, but less effective than combination NRT and varenicline. In most cases, a paucity of data made it difficult to draw conclusions regarding harms and tolerability. Further studies investigating the efficacy of bupropion versus placebo are unlikely to change our interpretation of the effect, providing no clear justification for pursuing bupropion for smoking cessation over other licensed smoking cessation treatments; namely, NRT and varenicline. However, it is important that future studies of antidepressants for smoking cessation measure and report on harms and tolerability.

Nicotine receptor partial agonists for smoking cessation.

BACKGROUND: Nicotine receptor partial agonists may help people to stop smoking by a combination of maintaining moderate levels of dopamine to counteract withdrawal symptoms (acting as an agonist) and reducing smoking satisfaction (acting as an antagonist). This is an update of a Cochrane Review first published in 2007. OBJECTIVES: To assess the effectiveness of nicotine receptor partial agonists, including varenicline and cytisine, for smoking cessation. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's Specialised Register in April 2022 for trials, using relevant terms in the title or abstract, or as keywords. The register is compiled from searches of CENTRAL, MEDLINE, Embase, and PsycINFO.  SELECTION CRITERIA: We included randomised controlled trials that compared the treatment drug with placebo, another smoking cessation drug, e-cigarettes, or no medication. We excluded trials that did not report a minimum follow-up period of six months from baseline. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods. Our main outcome was abstinence from smoking at longest follow-up using the most rigorous definition of abstinence, preferring biochemically validated rates where reported. We pooled risk ratios (RRs), using the Mantel-Haenszel fixed-effect model. We also reported the number of people reporting serious adverse events (SAEs). MAIN RESULTS: We included 75 trials of 45,049 people; 45 were new for this update. We rated 22 at low risk of bias, 18 at high risk, and 35 at unclear risk. We found moderate-certainty evidence (limited by heterogeneity) that cytisine helps more people to quit smoking than placebo (RR 1.30, 95% confidence interval (CI) 1.15 to 1.47; I2 = 83%; 4 studies, 4623 participants), and no evidence of a difference in the number reporting SAEs (RR 1.04, 95% CI 0.78 to 1.37; I2 = 0%; 3 studies, 3781 participants; low-certainty evidence). SAE evidence was limited by imprecision. We found no data on neuropsychiatric or cardiac SAEs. We found high-certainty evidence that varenicline helps more people to quit than placebo (RR 2.32, 95% CI 2.15 to 2.51; I2 = 60%, 41 studies, 17,395 participants), and moderate-certainty evidence that people taking varenicline are more likely to report SAEs than those not taking it (RR 1.23, 95% CI 1.01 to 1.48; I2 = 0%; 26 studies, 14,356 participants). While point estimates suggested increased risk of cardiac SAEs (RR 1.20, 95% CI 0.79 to 1.84; I2 = 0%; 18 studies, 7151 participants; low-certainty evidence), and decreased risk of neuropsychiatric SAEs (RR 0.89, 95% CI 0.61 to 1.29; I2 = 0%; 22 studies, 7846 participants; low-certainty evidence), in both cases evidence was limited by imprecision, and confidence intervals were compatible with both benefit and harm. Pooled results from studies that randomised people to receive cytisine or varenicline showed that more people in the varenicline arm quit smoking (RR 0.83, 95% CI 0.66 to 1.05; I2 = 0%; 2 studies, 2131 participants; moderate-certainty evidence) and reported SAEs (RR 0.67, 95% CI 0.44 to 1.03; I2 = 45%; 2 studies, 2017 participants; low-certainty evidence). However, the evidence was limited by imprecision, and confidence intervals incorporated the potential for benefit from either cytisine or varenicline. We found no data on neuropsychiatric or cardiac SAEs. We found high-certainty evidence that varenicline helps more people to quit than bupropion (RR 1.36, 95% CI 1.25 to 1.49; I2 = 0%; 9 studies, 7560 participants), and no clear evidence of difference in rates of SAEs (RR 0.89, 95% CI 0.61 to 1.31; I2 = 0%; 5 studies, 5317 participants), neuropsychiatric SAEs (RR 1.05, 95% CI 0.16 to 7.04; I2 = 10%; 2 studies, 866 participants), or cardiac SAEs (RR 3.17, 95% CI 0.33 to 30.18; I2 = 0%; 2 studies, 866 participants). Evidence of harms was of low certainty, limited by imprecision. We found high-certainty evidence that varenicline helps more people to quit than a single form of nicotine replacement therapy (NRT) (RR 1.25, 95% CI 1.14 to 1.37; I2 = 28%; 11 studies, 7572 participants), and low-certainty evidence, limited by imprecision, of fewer reported SAEs (RR 0.70, 95% CI 0.50 to 0.99; I2 = 24%; 6 studies, 6535 participants). We found no data on neuropsychiatric or cardiac SAEs. We found no clear evidence of a difference in quit rates between varenicline and dual-form NRT (RR 1.02, 95% CI 0.87 to 1.20; I2 = 0%; 5 studies, 2344 participants; low-certainty evidence, downgraded because of imprecision). While pooled point estimates suggested increased risk of SAEs (RR 2.15, 95% CI 0.49 to 9.46; I2 = 0%; 4 studies, 1852 participants) and neuropsychiatric SAEs (RR 4.69, 95% CI 0.23 to 96.50; I2 not estimable as events only in 1 study; 2 studies, 764 participants), and reduced risk of cardiac SAEs (RR 0.32, 95% CI 0.01 to 7.88; I2 not estimable as events only in 1 study; 2 studies, 819 participants), in all three cases evidence was of low certainty and confidence intervals were very wide, encompassing both substantial harm and benefit. AUTHORS' CONCLUSIONS: Cytisine and varenicline both help more people to quit smoking than placebo or no medication. Varenicline is more effective at helping people to quit smoking than bupropion, or a single form of NRT, and may be as or more effective than dual-form NRT. People taking varenicline are probably more likely to experience SAEs than those not taking it, and while there may be increased risk of cardiac SAEs and decreased risk of neuropsychiatric SAEs, evidence was compatible with both benefit and harm. Cytisine may lead to fewer people reporting SAEs than varenicline. Based on studies that directly compared cytisine and varenicline, there may be a benefit from varenicline for quitting smoking, however further evidence could strengthen this finding or demonstrate a benefit from cytisine. Future trials should test the effectiveness and safety of cytisine compared with varenicline and other pharmacotherapies, and should also test variations in dose and duration. There is limited benefit to be gained from more trials testing the effect of standard-dose varenicline compared with placebo for smoking cessation. Further trials on varenicline should test variations in dose and duration, and compare varenicline with e-cigarettes for smoking cessation.

Assessing and minimizing risk of bias in randomized controlled trials of tobacco cessation interventions: Guidance from the Cochrane Tobacco Addiction Group.

The Cochrane Tobacco Addiction Group has created risk of bias tools, which are topic-agnostic. In 2012 the Cochrane Tobacco Addiction Group created guidance specific to considerations for reviews of randomized controlled trials of tobacco cessation interventions, building on existing Cochrane tools. The guidance covers issues relating to selection bias, performance bias, detection bias, attrition bias and selective reporting. In this paper, we set out to make this guidance publicly available, so that others can use and cite it. We provide advice for using this tool to appraise trials critically as a systematic reviewer. We also provide guidance for triallists on ways to use this tool to improve trial design and reporting.

A systematic review and meta-analysis of interventions to induce attempts to quit tobacco among adults not ready to quit.

The prevalence of past-year smoking cessation remains below 10% in the U.S. Most who smoke are not ready to quit in the near future. Cessation requires both (a) initiating a quit attempt (QA) and (b) maintaining abstinence. Most research has focused on abstinence among people already motivated to quit. We systematically reviewed interventions to promote QAs among people not motivated to quit tobacco. We searched PubMed, CENTRAL, PsycINFO, Embase, and our personal libraries for randomized trials of tobacco interventions that reported QAs as an outcome among adults not ready to quit. We screened studies and extracted data in duplicate. We pooled findings of the 25 included studies using Mantel-Haenszel random effects meta-analyses when ≥ 2 studies tested the same intervention. Most (24) trials addressed cigarettes and one addressed smokeless tobacco. Substantial heterogeneity among trials resulted in a series of small meta-analyses. Findings indicate varenicline may increase QAs more than no varenicline, n = 320; RR = 1.4, 95% CI [1.1, 1.7]; I² = 0%, and nicotine replacement therapy (NRT) may increase QAs more than no NRT, n = 2,568; RR = 1.1, 95% CI [1.02, 1.3]; I² = 0%. Pooled effects for motivational counseling, reduction counseling, and very low nicotine content cigarettes showed no clear evidence of benefit or harm. The evidence was judged to be of medium to very low certainty due to imprecision, inconsistency, and risk of bias, suggesting that further research is likely to change interpretation of our results. Findings demonstrate the need for more high-quality research on interventions to induce QAs among adults not ready to quit tobacco. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Biomarkers of potential harm in people switching from smoking tobacco to exclusive e-cigarette use, dual use or abstinence: secondary analysis of Cochrane systematic review of trials of e-cigarettes for smoking cessation.

AIMS: This study aims to compare biomarkers of potential harm between people switching from smoking combustible cigarettes (CC) completely to electronic cigarettes (EC), continuing to smoke CC, using both EC and CC (dual users) and using neither (abstainers), based on behaviour during EC intervention studies. DESIGN: Secondary analysis following systematic review, incorporating inverse variance random-effects meta-analysis and effect direction plots. SETTING: This study was conducted in Greece, Italy, Poland, the United Kingdom and the United States. PARTICIPANTS: A total of 1299 adults smoking CC (nine studies) and provided EC. MEASUREMENTS: Measurements were conducted using carbon monoxide (CO) and 26 other biomarkers. FINDINGS: In pooled analyses, exhaled CO (eCO) was lower in EC versus EC + CC [mean difference (MD) = -4.40 parts per million (p.p.m.), 95% confidence interval (CI) = -12.04 to 3.24, two studies] and CC (MD = -9.57 p.p.m., 95% CI = -17.30 to -1.83, three studies). eCO was lower in dual users versus CC only (MD = -1.91 p.p.m., 95% CI = -3.38 to -0.45, two studies). Magnitude rather than direction of effect drove substantial statistical heterogeneity. Effect direction plots were used for other biomarkers. Comparing EC with CC, 12 of 13 biomarkers were significantly lower in EC users, with no difference for the 13th. Comparing EC with dual users, 12 of the 25 biomarkers were lower for EC, and five were lower for dual use. For the remaining eight measures, single studies did not detect statistically significant differences, or the multiple studies contributing to the outcome had inconsistent results. Only one study provided data comparing dual use with CC; of the 13 biomarkers measured, 12 were significantly lower in the dual use group, with no statistically significant difference detected for the 13th. Only one study provided data on abstainers. CONCLUSIONS: Switching from smoking to vaping or dual use appears to reduce levels of biomarkers of potential harm significantly.

An exploration of flavours in studies of e-cigarettes for smoking cessation: secondary analyses of a systematic review with meta-analyses.

AIMS: To estimate associations between e-cigarette flavour and smoking cessation and study product use at 6 months or longer. METHODS: Secondary analysis of data from a living systematic review, with meta-analyses and narrative synthesis, incorporating data up to January 2022. Included studies provided people who smoked combustible cigarettes with nicotine e-cigarettes for the purpose of smoking cessation compared with no treatment or other stop smoking interventions. Measurements included smoking cessation and study product use at 6 months or longer reported as risk ratios (RR) with 95% confidence intervals (CI); and flavour use at any time-points. RESULTS: We included 16 studies (n = 10 336); 14 contributed to subgroup analyses and 10 provided participants with a choice of e-cigarette flavour. We judged nine, five and two studies at high, low and unclear risk of bias, respectively. Subgroup analyses showed no clear associations between flavour and cessation or product use. In all but one analysis, tests for subgroup differences resulted in I2 values between 0 and 35%. In the comparison between nicotine e-cigarettes and nicotine replacement therapy (NRT) (I2  = 65.2% for subgroup differences), studies offering tobacco flavour e-cigarettes showed evidence of a greater proportion of participants still using at 6 months or longer (RR = 3.81; 95% CI = 1.45-10.05; n = 1181; I2  = 84%), whereas there was little evidence for greater 6-month use when studies offered a choice of flavours (RR = 1.44; 95% CI = 0.80-2.56; n = 454; I2  = 82%). However, substantial statistical heterogeneity within subgroups makes interpretation of this result unclear. In the 10 studies where participants had a choice of flavours, and this was tracked over time, some switching between flavours occurred, but there were no clear patterns in flavour preferences. CONCLUSIONS: There does not appear to be a clear association between e-cigarette flavours and smoking cessation or longer-term e-cigarette use, possibly due to a paucity of data. There is evidence that people using e-cigarettes to quit smoking switch between e-cigarette flavours.

Electronic cigarettes for smoking cessation.

BACKGROUND: Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, although some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit smoking, and if they are safe to use for this purpose. This is a review update conducted as part of a living systematic review. OBJECTIVES: To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 July 2022, and reference-checked and contacted study authors.  SELECTION CRITERIA: We included randomized controlled trials (RCTs) and randomized cross-over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants, or both. We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta-analyses. MAIN RESULTS: We included 78 completed studies, representing 22,052 participants, of which 40 were RCTs. Seventeen of the 78 included studies were new to this review update. Of the included studies, we rated ten (all but one contributing to our main comparisons) at low risk of bias overall, 50 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There was high certainty that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (RR 1.63, 95% CI 1.30 to 2.04; I2 = 10%; 6 studies, 2378 participants). In absolute terms, this might translate to an additional four quitters per 100 (95% CI 2 to 6). There was moderate-certainty evidence (limited by imprecision) that the rate of occurrence of AEs was similar between groups (RR 1.02, 95% CI 0.88 to 1.19; I2 = 0%; 4 studies, 1702 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.12, 95% CI 0.82 to 1.52; I2 = 34%; 5 studies, 2411 participants). There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 5 studies, 1840 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 1.00, 95% CI 0.56 to 1.79; I2 = 0%; 8 studies, 1272 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.66, 95% CI 1.52 to 4.65; I2 = 0%; 7 studies, 3126 participants). In absolute terms, this represents an additional two quitters per 100 (95% CI 1 to 3). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that (non-serious) AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants) and, again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.03, 95% CI 0.54 to 1.97; I2 = 38%; 9 studies, 1993 participants).  Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued EC use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit. AUTHORS' CONCLUSIONS: There is high-certainty evidence that ECs with nicotine increase quit rates compared to NRT and moderate-certainty evidence that they increase quit rates compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs nor between nicotine ECs and NRT. Overall incidence of SAEs was low across all study arms. We did not detect evidence of serious harm from nicotine EC, but longest follow-up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Longer-term use of electronic cigarettes when provided as a stop smoking aid: Systematic review with meta-analyses.

Moderate certainty evidence supports use of nicotine electronic cigarettes to quit smoking combustible cigarettes. However, there is less certainty regarding how long people continue to use e-cigarettes after smoking cessation attempts. We set out to synthesise data on the proportion of people still using e-cigarettes or other study products at 6 months or longer in studies of e-cigarettes for smoking cessation. We updated Cochrane searches (November 2021). For the first time, we meta-analysed prevalence of continued e-cigarette use among individuals allocated to e-cigarette conditions, and among those individuals who had successfully quit smoking. We updated meta-analyses comparing proportions continuing product use among individuals allocated to use nicotine e-cigarettes and other treatments. We included 19 studies (n = 7787). The pooled prevalence of continued e-cigarette use at 6 months or longer was 54% (95% CI: 46% to 61%, I2 86%, N = 1482) in participants assigned to e-cigarette conditions. Of participants who had quit combustible cigarettes overall 70% were still using e-cigarettes at six months or longer (95% CI: 53% to 82%, I2 73%, N = 215). Heterogeneity in direction of effect precluded meta-analysis comparing long-term use of nicotine e-cigarettes with NRT. More people were using nicotine e-cigarettes at longest follow-up compared to non-nicotine e-cigarettes, but CIs included no difference (risk ratio 1.15, 95% CI: 0.94 to 1.41, n = 601). The levels of continued e-cigarette use observed may reflect the success of e-cigarettes as a quitting tool. Further research is needed to establish drivers of variation in and implications of continued use of e-cigarettes.

Smoking cessation for secondary prevention of cardiovascular disease.

BACKGROUND: Smoking is a leading cause of cardiovascular disease (CVD), particularly coronary heart disease (CHD). However, quitting smoking may prevent secondary CVD events in people already diagnosed with CHD.  OBJECTIVES: To examine the impact of smoking cessation on death from CVD and major adverse cardiovascular events (MACE), in people with incident CHD. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's Specialised Register, CENTRAL, MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, and the trials registries clinicaltrials.gov and the International Clinical Trials Registry Platform. We ran all searches from database inception to 15 April 2021.  SELECTION CRITERIA: We included cohort studies, and both cluster- and individually randomised controlled trials of at least six months' duration. We treated all included studies as cohort studies and analysed them by smoking status at follow-up. Eligible studies had to recruit adults (> 18 years) with diagnosed CHD and who smoked tobacco at diagnosis, and assess whether they quit or continued smoking during the study. Studies had to measure at least one of our included outcomes with at least six months' follow-up. Our primary outcomes were death from CVD and MACE. Secondary outcomes included all-cause mortality, non-fatal myocardial infarction, non-fatal stroke, new-onset angina and change in quality of life.  DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods for screening and data extraction.  We assessed the risk of bias for the primary outcomes using the ROBINS-I tool. We compared the incidence of death from CVD and of MACE (primary outcomes) between participants who quit smoking versus those who continued to smoke for each included study that reported these outcomes. We also assessed differences in all-cause mortality, incidence of non-fatal myocardial infarction, incidence of non-fatal stroke and new onset angina. We calculated hazard ratios (HRs) and 95% confidence intervals (95% CI). For our outcome, change in quality of life, we calculated the pooled standardised mean difference (SMD) and 95% CI for the difference in change in quality of life from baseline to follow-up between those who had quit smoking and those who had continued to smoke. For all meta-analyses we used a generic inverse variance random-effects model and quantified statistical heterogeneity using the I²statistic. We assessed the certainty of evidence for our primary outcomes using the eight GRADE considerations relevant to non-randomised studies. MAIN RESULTS: We included 68 studies, consisting of 80,702 participants. For both primary outcomes, smoking cessation was associated with a decreased risk compared with continuous smoking: CVD death (HR 0.61, 95% CI 0.49 to 0.75; I² = 62%; 18 studies, 17,982 participants; moderate-certainty evidence) and MACE (HR 0.57, 95% CI 0.45 to 0.71; I² = 84%; 15 studies, 20,290 participants; low-certainty evidence). These findings were robust to our planned sensitivity analyses. Through subgroup analysis, for example comparing adjusted versus non-adjusted estimates, we found no evidence of differences in the effect size. While there was substantial heterogeneity, this was primarily in magnitude rather than the direction of the effect estimates. Overall, we judged 11 (16%) studies to be at moderate risk of bias and 18 (26%) at serious risk, primarily due to possible confounding. There was also some evidence of funnel plot asymmetry for MACE outcomes. For these reasons, we rated our certainty in the estimates for CVD death as moderate and MACE as low.  For our secondary outcomes, smoking cessation was associated with a decreased risk in all-cause mortality (HR 0.60, 95% CI 0.55 to 0.66; I² = 58%; 48 studies, 59,354 participants), non-fatal myocardial infarction (HR 0.64, 95% CI 0.58 to 0.72; I² = 2%; 24 studies, 23,264 participants) and non-fatal stroke (HR 0.70, 95% CI 0.53 to 0.90; I² = 0%; 9 studies, 11,352 participants). As only one study reported new onset of angina, we did not conduct meta-analysis, but this study reported a lower risk in people who stopped smoking. Quitting smoking was not associated with a worsening of quality of life and suggested improvement in quality of life, with the lower bound of the CI also consistent with no difference (SMD 0.12, 95% CI 0.01 to 0.24; I² = 48%; 8 studies, 3182 participants).  AUTHORS' CONCLUSIONS: There is moderate-certainty evidence that smoking cessation is associated with a reduction of approximately one-third in the risk of recurrent cardiovascular disease in people who stop smoking at diagnosis. This association may be causal, based on the link between smoking cessation and restoration of endothelial and platelet function, where dysfunction of both can result in increased likelihood of CVD events.  Our results provide evidence that there is a decreased risk of secondary CVD events in those who quit smoking compared with those who continue, and that there is a suggested improvement in quality of life as a result of quitting smoking. Additional studies that account for confounding, such as use of secondary CVD prevention medication, would strengthen the evidence in this area.

Mindfulness for smoking cessation.

BACKGROUND: Mindfulness-based smoking cessation interventions may aid smoking cessation by teaching individuals to pay attention to, and work mindfully with, negative affective states, cravings, and other symptoms of nicotine withdrawal. Types of mindfulness-based interventions include mindfulness training, which involves training in meditation; acceptance and commitment therapy (ACT); distress tolerance training; and yoga. OBJECTIVES: To assess the efficacy of mindfulness-based interventions for smoking cessation among people who smoke, and whether these interventions have an effect on mental health outcomes. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's specialised register, CENTRAL, MEDLINE, Embase, PsycINFO, and trial registries to 15 April 2021. We also employed an automated search strategy, developed as part of the Human Behaviour Change Project, using Microsoft Academic. SELECTION CRITERIA: We included randomised controlled trials (RCTs) and cluster-RCTs that compared a mindfulness-based intervention for smoking cessation with another smoking cessation programme or no treatment, and assessed smoking cessation at six months or longer. We excluded studies that solely recruited pregnant women. DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods. We measured smoking cessation at the longest time point, using the most rigorous definition available, on an intention-to-treat basis. We calculated risk ratios (RRs) and 95% confidence intervals (CIs) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of intervention and type of comparator. We carried out meta-analyses where appropriate, using Mantel-Haenszel random-effects models. We summarised mental health outcomes narratively. MAIN RESULTS: We included 21 studies, with 8186 participants. Most recruited adults from the community, and the majority (15 studies) were conducted in the USA. We judged four of the studies to be at low risk of bias, nine at unclear risk, and eight at high risk. Mindfulness-based interventions varied considerably in design and content, as did comparators, therefore, we pooled small groups of relatively comparable studies. We did not detect a clear benefit or harm of mindfulness training interventions on quit rates compared with intensity-matched smoking cessation treatment (RR 0.99, 95% CI 0.67 to 1.46; I2 = 0%; 3 studies, 542 participants; low-certainty evidence), less intensive smoking cessation treatment (RR 1.19, 95% CI 0.65 to 2.19; I2 = 60%; 5 studies, 813 participants; very low-certainty evidence), or no treatment (RR 0.81, 95% CI 0.43 to 1.53; 1 study, 325 participants; low-certainty evidence). In each comparison, the 95% CI encompassed benefit (i.e. higher quit rates), harm (i.e. lower quit rates) and no difference. In one study of mindfulness-based relapse prevention, we did not detect a clear benefit or harm of the intervention over no treatment (RR 1.43, 95% CI 0.56 to 3.67; 86 participants; very low-certainty evidence). We did not detect a clear benefit or harm of ACT on quit rates compared with less intensive behavioural treatments, including nicotine replacement therapy alone (RR 1.27, 95% CI 0.53 to 3.02; 1 study, 102 participants; low-certainty evidence), brief advice (RR 1.27, 95% CI 0.59 to 2.75; 1 study, 144 participants; very low-certainty evidence), or less intensive ACT (RR 1.00, 95% CI 0.50 to 2.01; 1 study, 100 participants; low-certainty evidence). There was a high level of heterogeneity (I2 = 82%) across studies comparing ACT with intensity-matched smoking cessation treatments, meaning it was not appropriate to report a pooled result. We did not detect a clear benefit or harm of distress tolerance training on quit rates compared with intensity-matched smoking cessation treatment (RR 0.87, 95% CI 0.26 to 2.98; 1 study, 69 participants; low-certainty evidence) or less intensive smoking cessation treatment (RR 1.63, 95% CI 0.33 to 8.08; 1 study, 49 participants; low-certainty evidence). We did not detect a clear benefit or harm of yoga on quit rates compared with intensity-matched smoking cessation treatment (RR 1.44, 95% CI 0.40 to 5.16; 1 study, 55 participants; very low-certainty evidence). Excluding studies at high risk of bias did not substantially alter the results, nor did using complete case data as opposed to using data from all participants randomised. Nine studies reported on changes in mental health and well-being, including depression, anxiety, perceived stress, and negative and positive affect. Variation in measures and methodological differences between studies meant we could not meta-analyse these data. One study found a greater reduction in perceived stress in participants who received a face-to-face mindfulness training programme versus an intensity-matched programme. However, the remaining eight studies found no clinically meaningful differences in mental health and well-being between participants who received mindfulness-based treatments and participants who received another treatment or no treatment (very low-certainty evidence). AUTHORS' CONCLUSIONS: We did not detect a clear benefit of mindfulness-based smoking cessation interventions for increasing smoking quit rates or changing mental health and well-being. This was the case when compared with intensity-matched smoking cessation treatment, less intensive smoking cessation treatment, or no treatment. However, the evidence was of low and very low certainty due to risk of bias, inconsistency, and imprecision, meaning future evidence may very likely change our interpretation of the results. Further RCTs of mindfulness-based interventions for smoking cessation compared with active comparators are needed. There is also a need for more consistent reporting of mental health and well-being outcomes in studies of mindfulness-based interventions for smoking cessation.

Association between smoking, e-cigarette use and severe COVID-19: a cohort study.

BACKGROUND: Smoking is a risk factor for most respiratory infections, but it may protect against SARS-CoV-2 infection. The objective was to assess whether smoking and e-cigarette use were associated with severe COVID-19. METHODS: This cohort ran from 24 January 2020 until 30 April 2020 at the height of the first wave of the SARS-CoV-2 epidemic in England. It comprised 7 869 534 people representative of the population of England with smoking status, demographic factors and diseases recorded by general practitioners in the medical records, which were linked to hospital and death data. The outcomes were COVID-19-associated hospitalization, intensive care unit (ICU) admission and death. The associations between smoking and the outcomes were assessed with Cox proportional hazards models, with sequential adjustment for confounding variables and indirect causal factors (body mass index and smoking-related disease). RESULTS: Compared with never smokers, people currently smoking were at lower risk of COVID-19 hospitalization, adjusted hazard ratios (HRs) were 0.64 (95% confidence intervals 0.60 to 0.69) for <10 cigarettes/day, 0.49 (0.41 to 0.59) for 10-19 cigarettes/day, and 0.61 (0.49 to 0.74) for ≥20 cigarettes/day. For ICU admission, the corresponding HRs were 0.31 (0.24 to 0.40), 0.15 (0.06 to 0.36), and 0.35 (0.17 to 0.74) and death were: 0.79 (0.70 to 0.89), 0.66 (0.48 to 0.90), and 0.77 (0.54 to 1.09) respectively. Former smokers were at higher risk of severe COVID-19: HRs: 1.07 (1.03 to 1.11) for hospitalization, 1.17 (1.04 to 1.31) for ICU admission, and 1.17 (1.10 to 1.24) for death. All-cause mortality was higher for current smoking than never smoking, HR 1.42 (1.36 to 1.48). Among e-cigarette users, the adjusted HR for e-cigarette use and hospitalization with COVID-19 was 1.06 (0.88 to 1.28), for ICU admission was 1.04 (0.57 to 1.89, and for death was 1.12 (0.81 to 1.55). CONCLUSIONS: Current smoking was associated with a reduced risk of severe COVID-19 but the association with e-cigarette use was unclear. All-cause mortality remained higher despite this possible reduction in death from COVID-19 during an epidemic of SARS-CoV-2. Findings support investigating possible protective mechanisms of smoking for SARS-CoV-2 infection, including the ongoing trials of nicotine to treat COVID-19.

Behavioural programmes for cigarette smoking cessation: investigating interactions between behavioural, motivational and delivery components in a systematic review and component network meta-analysis.

AIMS: To investigate the comparative and combined effectiveness of four types of components of behavioural interventions for cigarette smoking cessation: behavioural (e.g. counselling), motivational (e.g. focus on reasons to quit), delivery mode (e.g. phone) and provider (e.g. nurse). DESIGN: Systematic review and component network meta-analysis of randomised controlled trials identified from Cochrane reviews. Interventions included behavioural interventions for smoking cessation (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials), compared with another behavioural intervention or no support. Building on a 2021 review (CD013229), we conducted three analyses, investigating: comparative effectiveness of the components, whether models that allowed interactions between components gave different results to models assuming additivity, and predicted effect estimates for combined effects of components that had showed promise but where there were few trials. SETTING: Community and health-care settings. PARTICIPANTS: Adults who smoke tobacco. MEASUREMENTS: Smoking cessation at ≥6 months, preferring sustained, biochemically validated outcomes where available. FINDINGS: Three hundred and twelve trials (250 563 participants) were included. Fifty were at high risk of bias using Cochrane risk of bias tool, V1 (ROB1); excluding these studies did not change findings. Head-to-head comparisons of components suggested that support via text message (SMS) compared with telephone (OR 1.48, 95% CrI 1.13-1.94) or print materials (OR 1.44, 95% CrI 1.14-1.83) was more effective, and individual delivery was less effective than delivery as part of a group (OR 0.78, 95% CrI 0.64-0.95). There was no conclusive evidence of synergistic or antagonistic interactions when combining components that were commonly used together. Adding multiple components that are commonly used in behavioural counselling suggested clinically relevant and statistically conclusive evidence of benefit. Components with the largest effects that could be combined, but rarely have been, were estimated to increase the odds of quitting between two and threefold. For example, financial incentives delivered via SMS, with tailoring and a focus on how to quit, had an estimated OR of 2.94 (95% CrI 1.91-4.52). CONCLUSIONS: Among the components of behavioural support for smoking cessation, behavioural counselling and guaranteed financial incentives are associated with the greatest success. Incorporating additional components associated with effectiveness may further increase benefit, with delivery via text message showing particular promise.