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.

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.

Long-Term Effect of Weight Regain Following Behavioral Weight Management Programs on Cardiometabolic Disease Incidence and Risk: Systematic Review and Meta-Analysis.

BACKGROUND: Behavioral weight management programs (BWMPs) enhance weight loss in the short term, but longer term cardiometabolic effects are uncertain as weight is commonly regained. We assessed the impact of weight regain after BWMPs on cardiovascular risk factors, diabetes, and cardiovascular disease. METHODS: Trial registries, 11 databases, and forward-citation searching (latest search, December 19) were used to identify articles published in English, from any geographical region. Randomized trials of BWMPs in adults with overweight/obesity reporting cardiometabolic outcomes at ≥12 months at and after program end were included. Differences between more intensive interventions and comparator groups were synthesized using mixed-effects, meta-regression, and time-to-event models to assess the impact of weight regain on cardiovascular disease incidence and risk. RESULTS: One hundred twenty-four trials reporting on ≥1 cardiometabolic outcomes with a median follow-up of 28 (range, 11-360) months after program end were included. Median baseline participant body mass index was 33 kg/m2; median age was 51 years. Eight and 15 study arms (7889 and 4202 participants, respectively) examined the incidence of cardiovascular disease and type 2 diabetes, respectively, with imprecise evidence of a lower incidence for at least 5 years. Weight regain in BWMPs relative to comparators reduced these differences. One and 5 years after program end, total cholesterol/HDL (high-density lipoprotein) ratio was 1.5 points lower at both times (82 studies; 19 003 participants), systolic blood pressure was 1.5 mm mercury and 0.4 mm lower (84 studies; 30 836 participants), and HbA1c (%) 0.38 lower at both times (94 studies; 28 083 participants). Of the included studies, 22% were judged at high risk of bias; removing these did not meaningfully change results. CONCLUSIONS: Despite weight regain, BWMPs reduce cardiometabolic risk factors with effects lasting at least 5 years after program end and dwindling with weight regain. Evidence that they reduce the incidence of cardiovascular disease or diabetes is less certain. Few studies followed participants for ≥5 years. REGISTRATION: URL: https://www.crd.york.ac.uk/PROSPERO/; Unique identifier: CRD42018105744.

Weight regain and mental health outcomes following behavioural weight management programmes: A systematic review with meta-analyses.

Behavioural weight management programmes (BWMPs) lead to weight loss but subsequent weight regain may harm mental health outcomes. We searched for randomised trials of BWMPs in adults with overweight/obesity with follow-up ≥12 months from baseline that measured weight change both at and after programme-end. We included only studies reporting mental health at or after programme-end. We meta-analysed changes in various mental health outcomes using a random-effects model by nature of the comparator group and by time since programme end. Subgroup analysis explored heterogeneity. We used mixed models and meta-regression to analyse the association between change in weight and change in depression and/or anxiety over time, with higher scores indicating greater depression and/or anxiety. We included 47 studies. When comparing BWMPs (diet and/or exercise) to control, most estimates included the possibility of no difference, but pooled estimates for psychological wellbeing, self-esteem and mental-health composite scores at programme-end, anxiety at 1-6 months, and depression at 7-12 months after programme-end suggested improvements in intervention arms relative to control, with 95% CIs excluding no difference. Pooled estimates found no evidence that BWMPs harmed mental health at programme end or beyond. Mental health composite scores at programme-end favoured diet and exercise interventions over diet alone, with 95% CIs excluding no difference. All other measures and timepoints included the possibility of no difference or could not be meta-analysed due to high heterogeneity or a paucity of data. Mixed models and meta-regression of the association between change in depression and/or anxiety scores over time, and change in weight, were inconclusive. Despite weight regain after BWMPs, our meta-analyses found no evidence of mental health harm and some evidence that BWMPs may improve some dimensions of mental health at and after programme-end.

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.

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.

Weight regain after behavioural weight management programmes and its impact on quality of life and cost effectiveness: Evidence synthesis and health economic analyses.

AIMS: We used data from a recent systematic review to investigate weight regain after behavioural weight management programmes (BWMPs, sometimes referred to as lifestyle modification programmes) and its impact on quality-of-life and cost-effectiveness. MATERIALS AND METHODS: Trial registries, databases and forward-citation searching (latest search December 2019) were used to identify randomized trials of BWMPs in adults with overweight/obesity reporting outcomes at ≥12 months, and after programme end. Two independent reviewers screened records. One reviewer extracted data and a second checked them. The differences between intervention and control groups were synthesized using mixed-effect, meta-regression and time-to-event models. We examined associations between weight difference and difference in quality-of-life. Cost-effectiveness was estimated from a health sector perspective. RESULTS: In total, 155 trials (n > 150 000) contributed to analyses. The longest follow-up was 23 years post-programme. At programme end, intervention groups achieved -2.8 kg (95%CI -3.2 to -2.4) greater weight loss than controls. Weight regain after programme end was 0.12-0.32 kg/year greater in intervention relative to control groups, with a between-group difference evident for at least 5 years. Quality-of-life increased in intervention groups relative to control at programme end and thereafter returned to control as the difference in weight between groups diminished. BWMPs with this initial weight loss and subsequent regain would be cost-effective if delivered for under £560 (£8.80-£3900) per person. CONCLUSIONS: Modest rates of weight regain, with persistent benefits for several years, should encourage health care practitioners and policymakers to offer obesity treatments that cost less than our suggested thresholds as a cost-effective intervention to improve long-term weight management. REGISTRATION: The review is registered on PROSPERO, CRD42018105744.

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.

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.

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.

Impact of program characteristics on weight loss in adult behavioral weight management interventions: systematic review and component network meta-analysis.

OBJECTIVE: Behavioral weight management programs (BWMPs) for adults lead to greater weight loss at 12 months than minimal-intervention control treatments. However, there is considerable heterogeneity in the content of BWMPs and outcomes of treatment. This study assessed the contribution of individual components of BWMPs, using Bayesian component network meta-analysis. METHODS: Randomized controlled trials of BWMPs in adults were identified (latest search: December 2019) and arms coded for presence or absence of 29 intervention components grouped by type, content, provider, mode of delivery, and intensity. RESULTS: A total of 169 studies (41 judged at high risk of bias) were included in the main analysis. Six components had effect estimates indicating clinically significant benefit and credible intervals (CrIs) excluding no difference: change in diet (mean difference [MD] = -1.84 kg, 95% CrI: -2.91 to -0.80); offering partial (MD = -2.12 kg, 95% CrI: -3.39 to -0.89) or total meal replacements (MD = -2.63 kg, 95% CrI: -4.58 to -0.73); delivery by a psychologist/counselor (MD = -1.45 kg, 95% CrI: -2.81 to -0.06) or dietitian (MD = -1.31 kg, 95% CrI: -2.40 to -0.24); and home setting (MD = -1.05 kg, 95% CrI: -2.02 to -0.09). CONCLUSIONS: Future program development should consider including these components; other approaches continue to warrant evaluation of effectiveness.

Effectiveness of Motivational Interviewing in Managing Overweight and Obesity : A Systematic Review and Meta-analysis.

BACKGROUND: Motivational interviewing (MI) is potentially useful in management of overweight and obesity, but staff training and increased delivery time are barriers, and its effectiveness independent of other behavioral components is unclear. PURPOSE: To assess the independent contribution of MI as part of a behavioral weight management program (BWMP) in controlling weight and improving psychological well-being. DATA SOURCES: 6 electronic databases and 2 trial registries, searched from database inception through 24 September 2021. STUDY SELECTION: Randomized controlled trials in adults or adolescents aimed at weight loss or maintenance and comparing programs incorporating MI versus interventions without MI. DATA EXTRACTION: Two reviewers independently screened studies, extracted data, and assessed risk of bias. Outcomes included weight, anxiety, depression, quality of life, and other aspects of psychological well-being. Pooled mean differences or standardized mean differences were obtained using random- and fixed-effects meta-analyses. DATA SYNTHESIS: Forty-six studies involving 11 077 participants, predominantly with obesity, were included. At 6 months, BWMPs using MI were more effective than no/minimal intervention (-0.88 [95% CI, -1.27 to -0.48] kg; I 2 = 0%) but were not statistically significantly more effective than lower-intensity (-0.88 [CI, -2.39 to 0.62] kg; I 2 = 55.8%) or similar-intensity (-1.36 [CI, -2.80 to 0.07] kg; I 2 = 18.8%) BWMPs. At 1 year, data were too sparse to pool comparisons with no/minimal intervention, but MI did not produce statistically significantly greater weight change compared with lower-intensity (-1.16 [CI, -2.49 to 0.17] kg; I 2 = 88.7%) or similar-intensity (-0.18 [CI, -2.40 to 2.04] kg; I 2 = 72.7%) BWMPs without MI. Studies with 18-month follow-up were also sparse; MI did not produce statistically significant benefit in any of the comparator categories. There was no evidence of subgroup differences based on study, participant, or intervention characteristics. Too few studies assessed effects on psychological well-being to pool, but data did not suggest that MI was independently effective. LIMITATIONS: High statistical heterogeneity among studies, largely unexplained by sensitivity and subgroup analyses; stratification by comparator intensity and follow-up duration resulted in pooling of few studies. CONCLUSION: There is no evidence that MI increases effectiveness of BWMPs in controlling weight. Given the intensive training required for its delivery, MI may not be a worthwhile addition to BWMPs. PRIMARY FUNDING SOURCE: National Institute for Health Research Biomedical Research Centre. (PROSPERO: CRD42020177259).

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.

Interventions for preventing weight gain after smoking cessation.

BACKGROUND: Most people who stop smoking gain weight. This can discourage some people from making a quit attempt and risks offsetting some, but not all, of the health advantages of quitting. Interventions to prevent weight gain could improve health outcomes, but there is a concern that they may undermine quitting. OBJECTIVES: To systematically review the effects of: (1) interventions targeting post-cessation weight gain on weight change and smoking cessation (referred to as 'Part 1') and (2) interventions designed to aid smoking cessation that plausibly affect post-cessation weight gain (referred to as 'Part 2'). SEARCH METHODS: Part 1 - We searched the Cochrane Tobacco Addiction Group's Specialized Register and CENTRAL; latest search 16 October 2020. Part 2 - We searched included studies in the following 'parent' Cochrane reviews: nicotine replacement therapy (NRT), antidepressants, nicotine receptor partial agonists, e-cigarettes, and exercise interventions for smoking cessation published in Issue 10, 2020 of the Cochrane Library. We updated register searches for the review of nicotine receptor partial agonists. SELECTION CRITERIA: Part 1 - trials of interventions that targeted post-cessation weight gain and had measured weight at any follow-up point or smoking cessation, or both, six or more months after quit day. Part 2 - trials included in the selected parent Cochrane reviews reporting weight change at any time point. DATA COLLECTION AND ANALYSIS: Screening and data extraction followed standard Cochrane methods. Change in weight was expressed as difference in weight change from baseline to follow-up between trial arms and was reported only in people abstinent from smoking. Abstinence from smoking was expressed as a risk ratio (RR). Where appropriate, we performed meta-analysis using the inverse variance method for weight, and Mantel-Haenszel method for smoking. MAIN RESULTS: Part 1: We include 37 completed studies; 21 are new to this update. We judged five studies to be at low risk of bias, 17 to be at unclear risk and the remainder at high risk.  An intermittent very low calorie diet (VLCD) comprising full meal replacement provided free of charge and accompanied by intensive dietitian support significantly reduced weight gain at end of treatment compared with education on how to avoid weight gain (mean difference (MD) -3.70 kg, 95% confidence interval (CI) -4.82 to -2.58; 1 study, 121 participants), but there was no evidence of benefit at 12 months (MD -1.30 kg, 95% CI -3.49 to 0.89; 1 study, 62 participants). The VLCD increased the chances of abstinence at 12 months (RR 1.73, 95% CI 1.10 to 2.73; 1 study, 287 participants). However, a second study  found that no-one completed the VLCD intervention or achieved abstinence. Interventions aimed at increasing acceptance of weight gain reported mixed effects at end of treatment, 6 months and 12 months with confidence intervals including both increases and decreases in weight gain compared with no advice or health education. Due to high heterogeneity, we did not combine the data. These interventions increased quit rates at 6 months (RR 1.42, 95% CI 1.03 to 1.96; 4 studies, 619 participants; I2 = 21%), but there was no evidence at 12 months (RR 1.25, 95% CI 0.76 to 2.06; 2 studies, 496 participants; I2 = 26%). Some pharmacological interventions tested for limiting post-cessation weight gain (PCWG) reduced weight gain at the end of treatment (dexfenfluramine, phenylpropanolamine, naltrexone). The effects of ephedrine and caffeine combined, lorcaserin, and chromium were too imprecise to give useful estimates of treatment effects. There was very low-certainty evidence that personalized weight management support reduced weight gain at end of treatment (MD -1.11 kg, 95% CI -1.93 to -0.29; 3 studies, 121 participants; I2 = 0%), but no evidence in the longer-term 12 months (MD -0.44 kg, 95% CI -2.34 to 1.46; 4 studies, 530 participants; I2 = 41%). There was low to very low-certainty evidence that detailed weight management education without personalized assessment, planning and feedback did not reduce weight gain and may have reduced smoking cessation rates (12 months: MD -0.21 kg, 95% CI -2.28 to 1.86; 2 studies, 61 participants; I2 = 0%; RR for smoking cessation 0.66, 95% CI 0.48 to 0.90; 2 studies, 522 participants; I2 = 0%). Part 2: We include 83 completed studies, 27 of which are new to this update. There was low certainty that exercise interventions led to minimal or no weight reduction compared with standard care at end of treatment (MD -0.25 kg, 95% CI -0.78 to 0.29; 4 studies, 404 participants; I2 = 0%). However, weight was reduced at 12 months (MD -2.07 kg, 95% CI -3.78 to -0.36; 3 studies, 182 participants; I2 = 0%). Both bupropion and fluoxetine limited weight gain at end of treatment (bupropion MD -1.01 kg, 95% CI -1.35 to -0.67; 10 studies, 1098 participants; I2 = 3%); (fluoxetine MD -1.01 kg, 95% CI -1.49 to -0.53; 2 studies, 144 participants; I2 = 38%; low- and very low-certainty evidence, respectively). There was no evidence of benefit at 12 months for bupropion, but estimates were imprecise (bupropion MD -0.26 kg, 95% CI -1.31 to 0.78; 7 studies, 471 participants; I2 = 0%). No studies of fluoxetine provided data at 12 months. There was moderate-certainty that NRT reduced weight at end of treatment (MD -0.52 kg, 95% CI -0.99 to -0.05; 21 studies, 2784 participants; I2 = 81%) and moderate-certainty that the effect may be similar at 12 months (MD -0.37 kg, 95% CI -0.86 to 0.11; 17 studies, 1463 participants; I2 = 0%), although the estimates are too imprecise to assess long-term benefit. There was mixed evidence of the effect of varenicline on weight, with high-certainty evidence that weight change was very modestly lower at the end of treatment (MD -0.23 kg, 95% CI -0.53 to 0.06; 14 studies, 2566 participants; I2 = 32%); a low-certainty estimate gave an imprecise estimate of higher weight at 12 months (MD 1.05 kg, 95% CI -0.58 to 2.69; 3 studies, 237 participants; I2 = 0%). AUTHORS' CONCLUSIONS: Overall, there is no intervention for which there is moderate certainty of a clinically useful effect on long-term weight gain. There is also no moderate- or high-certainty evidence that interventions designed to limit weight gain reduce the chances of people achieving abstinence from smoking.

Electronic cigarettes for smoking cessation.

BACKGROUND: Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, but 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 and if they are safe to use for this purpose. This is an 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 May 2021, and reference-checked and contacted study authors. We screened abstracts from the Society for Research on Nicotine and Tobacco (SRNT) 2021 Annual Meeting.   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 61 completed studies, representing 16,759 participants, of which 34 were RCTs. Five of the 61 included studies were new to this review update. Of the included studies, we rated seven (all contributing to our main comparisons) at low risk of bias overall, 42 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.53, 95% confidence interval (CI) 1.21 to 1.93; I2 = 0%; 4 studies, 1924 participants). In absolute terms, this might translate to an additional three quitters per 100 (95% CI 1 to 6). There was low-certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.30, 95% CI 0.89 to 1.90: I2 = 0; 4 studies, 1424 participants). There was moderate-certainty evidence, again 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%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 1.06, 95% CI 0.47 to 2.38; I2 = 0; 5 studies, 792 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.61, 95% CI 1.44 to 4.74; I2 = 0%; 6 studies, 2886 participants). In absolute terms this represents an additional six quitters per 100 (95% CI 2 to 15). 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 1.51, 95% CI 0.70 to 3.24; I2 = 0%; 7 studies, 1303 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 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 moderate-certainty evidence that ECs with nicotine increase quit rates compared to NRT and 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. Overall incidence of SAEs was low across all study arms. We did not detect  evidence of 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 now 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.

Association between characteristics of behavioural weight loss programmes and weight change after programme end: systematic review and meta-analysis.

OBJECTIVE: To determine if the characteristics of behavioural weight loss programmes influence the rate of change in weight after the end of the programme. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Trial registries, 11 electronic databases, and forward citation searching (from database inception; latest search December 2019). Randomised trials of behavioural weight loss programmes in adults with overweight or obesity, reporting outcomes at ≥12 months, including at the end of the programme and after the end of the programme. REVIEW METHODS: Studies were screened by two independent reviewers with discrepancies resolved by discussion. 5% of the studies identified in the searches met the inclusion criteria. One reviewer extracted the data and a second reviewer checked the data. Risk of bias was assessed with Cochrane's risk of bias tool (version 1). The rate of change in weight was calculated (kg/month; converted to kg/year for interpretability) after the end of the programme in the intervention versus control groups by a mixed model with a random intercept. Associations between the rate of change in weight and prespecified variables were tested. RESULTS: Data were analysed from 249 trials (n=59 081) with a mean length of follow-up of two years (longest 30 years). 56% of studies (n=140) had an unclear risk of bias, 21% (n=52) a low risk, and 23% (n=57) a high risk of bias. Regain in weight was faster in the intervention versus the no intervention control groups (0.12-0.32 kg/year) but the difference between groups was maintained for at least five years. Each kilogram of weight lost at the end of the programme was associated with faster regain in weight at a rate of 0.13-0.19 kg/year. Financial incentives for weight loss were associated with faster regain in weight at a rate of 1-1.5 kg/year. Compared with programmes with no meal replacements, interventions involving partial meal replacements were associated with faster regain in weight but not after adjustment for weight loss during the programme. Access to the programme outside of the study was associated with slower regain in weight. Programmes where the intensity of the interaction reduced gradually were also associated with slower regain in weight in the multivariable analysis, although the point estimate suggested that the association was small. Other characteristics did not explain the heterogeneity in regain in weight. CONCLUSION: Faster regain in weight after weight loss was associated with greater initial weight loss, but greater initial weight loss was still associated with reduced weight for at least five years after the end of the programme, after which data were limited. Continued availability of the programme to participants outside of the study predicted a slower regain in weight, and provision of financial incentives predicted faster regain in weight; no other clear associations were found. STUDY REGISTRATION: PROSPERO CRD42018105744.