Interventions for smoking cessation in hospitalised patients.

BACKGROUND: In 2020, 32.6% of the world's population used tobacco. Smoking contributes to many illnesses that require hospitalisation. A hospital admission may prompt a quit attempt. Initiating smoking cessation treatment, such as pharmacotherapy and/or counselling, in hospitals may be an effective preventive health strategy. Pharmacotherapies work to reduce withdrawal/craving and counselling provides behavioural skills for quitting smoking. This review updates the evidence on interventions for smoking cessation in hospitalised patients, to understand the most effective smoking cessation treatment methods for hospitalised smokers. OBJECTIVES: To assess the effects of any type of smoking cessation programme for patients admitted to an acute care hospital. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was 7 September 2022. SELECTION CRITERIA: We included randomised and quasi-randomised studies of behavioural, pharmacological or multicomponent interventions to help patients admitted to hospital quit. Interventions had to start in the hospital (including at discharge), and people had to have smoked within the last month. We excluded studies in psychiatric, substance and rehabilitation centres, as well as studies that did not measure abstinence at six months or longer. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcome was abstinence from smoking assessed at least six months after discharge or the start of the intervention. We used the most rigorous definition of abstinence, preferring biochemically-validated rates where reported. We used GRADE to assess the certainty of the evidence. MAIN RESULTS: We included 82 studies (74 RCTs) that included 42,273 participants in the review (71 studies, 37,237 participants included in the meta-analyses); 36 studies are new to this update. We rated 10 studies as being at low risk of bias overall (low risk in all domains assessed), 48 at high risk of bias overall (high risk in at least one domain), and the remaining 24 at unclear risk. Cessation counselling versus no counselling, grouped by intensity of intervention Hospitalised patients who received smoking cessation counselling that began in the hospital and continued for more than a month after discharge had higher quit rates than patients who received no counselling in the hospital or following hospitalisation (risk ratio (RR) 1.36, 95% confidence interval (CI) 1.24 to 1.49; 28 studies, 8234 participants; high-certainty evidence). In absolute terms, this might account for an additional 76 quitters in every 1000 participants (95% CI 51 to 103). The evidence was uncertain (very low-certainty) about the effects of counselling interventions of less intensity or shorter duration (in-hospital only counselling ≤ 15 minutes: RR 1.52, 95% CI 0.80 to 2.89; 2 studies, 1417 participants; and in-hospital contact plus follow-up counselling support for ≤ 1 month: RR 1.04, 95% CI 0.90 to 1.20; 7 studies, 4627 participants) versus no counselling. There was moderate-certainty evidence, limited by imprecision, that smoking cessation counselling for at least 15 minutes in the hospital without post-discharge support led to higher quit rates than no counselling in the hospital (RR 1.27, 95% CI 1.02 to 1.58; 12 studies, 4432 participants). Pharmacotherapy versus placebo or no pharmacotherapy Nicotine replacement therapy helped more patients to quit than placebo or no pharmacotherapy (RR 1.33, 95% CI 1.05 to 1.67; 8 studies, 3838 participants; high-certainty evidence). In absolute terms, this might equate to an additional 62 quitters per 1000 participants (95% CI 9 to 126). There was moderate-certainty evidence, limited by imprecision (as CI encompassed the possibility of no difference), that varenicline helped more hospitalised patients to quit than placebo or no pharmacotherapy (RR 1.29, 95% CI 0.96 to 1.75; 4 studies, 829 participants). Evidence for bupropion was low-certainty; the point estimate indicated a modest benefit at best, but CIs were wide and incorporated clinically significant harm and clinically significant benefit (RR 1.11, 95% CI 0.86 to 1.43, 4 studies, 872 participants). Hospital-only intervention versus intervention that continues after hospital discharge Patients offered both smoking cessation counselling and pharmacotherapy after discharge had higher quit rates than patients offered counselling in hospital but not offered post-discharge support (RR 1.23, 95% CI 1.09 to 1.38; 7 studies, 5610 participants; high-certainty evidence). In absolute terms, this might equate to an additional 34 quitters per 1000 participants (95% CI 13 to 55). Post-discharge interventions offering real-time counselling without pharmacotherapy (RR 1.23, 95% CI 0.95 to 1.60, 8 studies, 2299 participants; low certainty-evidence) and those offering unscheduled counselling without pharmacotherapy (RR 0.97, 95% CI 0.83 to 1.14; 2 studies, 1598 participants; very low-certainty evidence) may have little to no effect on quit rates compared to control. Telephone quitlines versus control To provide post-discharge support, hospitals may refer patients to community-based telephone quitlines. Both comparisons relating to these interventions had wide CIs encompassing both possible harm and possible benefit, and were judged to be of very low certainty due to imprecision, inconsistency, and risk of bias (post-discharge telephone counselling versus quitline referral: RR 1.23, 95% CI 1.00 to 1.51; 3 studies, 3260 participants; quitline referral versus control: RR 1.17, 95% CI 0.70 to 1.96; 2 studies, 1870 participants). AUTHORS' CONCLUSIONS: Offering hospitalised patients smoking cessation counselling beginning in hospital and continuing for over one month after discharge increases quit rates, compared to no hospital intervention. Counselling provided only in hospital, without post-discharge support, may have a modest impact on quit rates, but evidence is less certain. When all patients receive counselling in the hospital, high-certainty evidence indicates that providing both counselling and pharmacotherapy after discharge increases quit rates compared to no post-discharge intervention. Starting nicotine replacement or varenicline in hospitalised patients helps more patients to quit smoking than a placebo or no medication, though evidence for varenicline is only moderate-certainty due to imprecision. There is less evidence of benefit for bupropion in this setting. Some of our evidence was limited by imprecision (bupropion versus placebo and varenicline versus placebo), risk of bias, and inconsistency related to heterogeneity. Future research is needed to identify effective strategies to implement, disseminate, and sustain interventions, and to ensure cessation counselling and pharmacotherapy initiated in the hospital is sustained after discharge.

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.

Cessation of Smoking Trial in the Emergency Department (COSTED): a multicentre randomised controlled trial.

BACKGROUND: Supporting people to quit smoking is one of the most powerful interventions to improve health. The Emergency Department (ED) represents a potentially valuable opportunity to deliver a smoking cessation intervention if it is sufficiently resourced. The objective of this trial was to determine whether an opportunistic ED-based smoking cessation intervention can help people to quit smoking. METHODS: In this multicentre, parallel-group, randomised controlled superiority trial conducted between January and August 2022, adults who smoked daily and attended one of six UK EDs were randomised to intervention (brief advice, e-cigarette starter kit and referral to stop smoking services) or control (written information on stop smoking services). The primary outcome was biochemically validated abstinence at 6 months. RESULTS: An intention-to-treat analysis included 972 of 1443 people screened for inclusion (484 in the intervention group, 488 in the control group). Of 975 participants randomised, 3 were subsequently excluded, 17 withdrew and 287 were lost to follow-up. The 6-month biochemically-verified abstinence rate was 7.2% in the intervention group and 4.1% in the control group (relative risk 1.76; 95% CI 1.03 to 3.01; p=0.038). Self-reported 7-day abstinence at 6 months was 23.3% in the intervention group and 12.9% in the control group (relative risk 1.80; 95% CI 1.36 to 2.38; p<0.001). No serious adverse events related to taking part in the trial were reported. CONCLUSIONS: An opportunistic smoking cessation intervention comprising brief advice, an e-cigarette starter kit and referral to stop smoking services is effective for sustained smoking abstinence with few reported adverse events. TRIAL REGISTRATION NUMBER: NCT04854616.

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.

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.

Interventions for waterpipe smoking cessation.

BACKGROUND: While cigarette smoking has declined globally, waterpipe smoking is rising, especially among youth. The impact of this rise is amplified by mounting evidence of its addictive and harmful nature. Waterpipe smoking is influenced by multiple factors, including appealing flavors, marketing, use in social settings, and misperceptions that waterpipe is less harmful or addictive than cigarettes. People who use waterpipes are interested in quitting, but are often unsuccessful at doing so on their own. Therefore, developing and testing waterpipe cessation interventions to help people quit was identified as a priority for global tobacco control efforts.  OBJECTIVES: To evaluate the effectiveness of tobacco cessation interventions for people who smoke waterpipes. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Review Group Specialized Register from database inception to 29 July 2022, using variant terms and spellings ('waterpipe' or 'narghile' or 'arghile' or 'shisha' or 'goza' or 'narkeela' or 'hookah' or 'hubble bubble'). We searched for trials, published or unpublished, in any language. SELECTION CRITERIA: We sought randomized controlled trials (RCTs), quasi-RCTs, or cluster-RCTs of any smoking cessation interventions for people who use waterpipes, of any age or gender. In order to be included, studies had to measure waterpipe abstinence at a three-month follow-up or longer. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcome was abstinence from waterpipe use at least three months after baseline. We also collected data on adverse events. Individual study effects and pooled effects were summarized as risk ratios (RR) and 95% confidence intervals (95% CI), using Mantel-Haenszel random-effects models to combine studies, where appropriate. We assessed statistical heterogeneity with the I2 statistic. We summarized secondary outcomes narratively. We used the five GRADE considerations (risk of bias, inconsistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence for our primary outcome in four categories high, moderate, low, or very low. MAIN RESULTS: This review included nine studies, involving 2841 participants. All studies were conducted in adults, and were carried out in Iran, Vietnam, Syria, Lebanon, Egypt, Pakistan, and the USA. Studies were conducted in several settings, including colleges/universities, community healthcare centers, tuberculosis hospitals, and cancer treatment centers, while two studies tested e-health interventions (online web-based educational intervention, text message intervention). Overall, we judged three studies to be at low risk of bias, and six studies at high risk of bias. We pooled data from five studies (1030 participants) that tested intensive face-to-face behavioral interventions compared with brief behavioral intervention (e.g. one behavioral counseling session), usual care (e.g. self-help materials), or no intervention. In our meta-analysis, we included people who used waterpipe exclusively, or with another form of tobacco. Overall, we found low-certainty evidence of a benefit of behavioral support for waterpipe abstinence (RR 3.19 95% CI 2.17 to 4.69; I2 = 41%; 5 studies, N = 1030). We downgraded the evidence because of imprecision and risk of bias. We pooled data from two studies (N = 662 participants) that tested varenicline combined with behavioral intervention compared with placebo combined with behavioral intervention. Although the point estimate favored varenicline, 95% CIs were imprecise, and incorporated the potential for no difference and lower quit rates in the varenicline groups, as well as a benefit as large as that found in cigarette smoking cessation (RR 1.24, 95% CI 0.69 to 2.24; I2 = 0%; 2 studies, N = 662; low-certainty evidence). We downgraded the evidence because of imprecision. We found no clear evidence of a difference in the number of participants experiencing adverse events (RR 0.98, 95% CI 0.67 to 1.44; I2 = 31%; 2 studies, N = 662). The studies did not report serious adverse events.   One study tested the efficacy of seven weeks of bupropion therapy combined with behavioral intervention. There was no clear evidence of benefit for waterpipe cessation when compared with behavioral support alone (RR 0.77, 95% CI 0.42 to 1.41; 1 study, N = 121; very low-certainty evidence), or with self-help (RR 1.94, 95% CI 0.94 to 4.00; 1 study, N = 86; very low-certainty evidence).  Two studies tested e-health interventions. One study reported higher waterpipe quit rates among participants randomized to either a tailored mobile phone or untailored mobile phone intervention compared with those randomized to no intervention (RR 1.48, 95% CI 1.07 to 2.05; 2 studies, N = 319; very low-certainty evidence). Another study reported higher waterpipe abstinence rates following an intensive online educational intervention compared with a brief online educational intervention (RR 1.86, 95% CI 1.08 to 3.21; 1 study, N = 70; very low-certainty evidence).  AUTHORS' CONCLUSIONS: We found low-certainty evidence that behavioral waterpipe cessation interventions can increase waterpipe quit rates among waterpipe smokers. We found insufficient evidence to assess whether varenicline or bupropion increased waterpipe abstinence; available evidence is compatible with effect sizes similar to those seen for cigarette smoking cessation.  Given e-health interventions' potential reach and effectiveness for waterpipe cessation, trials with large samples and long follow-up periods are needed. Future studies should use biochemical validation of abstinence to prevent the risk of detection bias. Finally, there has been limited attention given to high-risk groups for waterpipe smoking, such as youth, young adults, pregnant women, and dual or poly tobacco users. These groups would benefit from targeted studies.

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.

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.

Treatment of Tobacco Smoking: A Review.

IMPORTANCE: More deaths in the US are attributed to cigarette smoking each year than to any other preventable cause. Approximately 34 million people and an estimated 14% of adults in the US smoke cigarettes. If they stopped smoking, they could reduce their risk of tobacco-related morbidity and mortality and potentially gain up to 10 years of life. OBSERVATIONS: Tobacco smoking is a chronic disorder maintained by physical nicotine dependence and learned behaviors. Approximately 70% of people who smoke cigarettes want to quit smoking. However, individuals who attempt to quit smoking make an average of approximately 6 quit attempts before achieving long-term abstinence. Both behavioral counseling and pharmacotherapy while using nicotine replacement therapy (NRT) products, varenicline, or bupropion are effective treatments when used individually, but they are most effective when combined. In a meta-analysis including 19 488 people who smoked cigarettes, the combination of medication and behavioral counseling was associated with a quit rate of 15.2% over 6 months compared with a quit rate of 8.6% with brief advice or usual care. The EAGLES trial, a randomized double-blind clinical trial of 8144 people who smoked, directly compared the efficacy and safety of varenicline, bupropion, nicotine patch, and placebo and found a significantly higher 6-month quit rate for varenicline (21.8%) than for bupropion (16.2%) and the nicotine patch (15.7%). Each therapy was more effective than placebo (9.4%). Combining a nicotine patch with other NRT products is more effective than use of a single NRT product. Combining drugs with different mechanisms of action, such as varenicline and NRT, has increased quit rates in some studies compared with use of a single product. Brief or intensive behavioral support can be delivered effectively in person or by telephone, text messages, or the internet. The combination of a clinician's brief advice to quit and assistance to obtain tobacco cessation treatment is effective when routinely administered to tobacco users in virtually all health care settings. CONCLUSIONS AND RELEVANCE: Approximately 34 million people in the US smoke cigarettes and could potentially gain up to a decade of life expectancy by stopping smoking. First-line therapy should include both pharmacotherapy and behavioral support, with varenicline or combination NRT as preferred initial interventions.

Interventions for tobacco cessation delivered by dental professionals.

BACKGROUND: Dental professionals are well placed to help their patients stop using tobacco products. Large proportions of the population visit the dentist regularly. In addition, the adverse effects of tobacco use on oral health provide a context that dental professionals can use to motivate a quit attempt. OBJECTIVES: To assess the effectiveness, adverse events and oral health effects of tobacco cessation interventions offered by dental professionals. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group's Specialised Register up to February 2020. SELECTION CRITERIA: We included randomised and quasi-randomised clinical trials assessing tobacco cessation interventions conducted by dental professionals in the dental practice or community setting, with at least six months of follow-up. DATA COLLECTION AND ANALYSIS: Two review authors independently reviewed abstracts for potential inclusion and extracted data from included trials. We resolved disagreements by consensus. The primary outcome was abstinence from all tobacco use (e.g. cigarettes, smokeless tobacco) at the longest follow-up, using the strictest definition of abstinence reported. Individual study effects and pooled effects were summarised as risk ratios (RR) and 95% confidence intervals (CI), using Mantel-Haenszel random-effects models to combine studies where appropriate. We assessed statistical heterogeneity with the I2 statistic. We summarised secondary outcomes narratively. MAIN RESULTS: Twenty clinical trials involving 14,897 participants met the criteria for inclusion in this review. Sixteen studies assessed the effectiveness of interventions for tobacco-use cessation in dental clinics and four assessed this in community (school or college) settings. Five studies included only smokeless tobacco users, and the remaining studies included either smoked tobacco users only, or a combination of both smoked and smokeless tobacco users. All studies employed behavioural interventions, with four offering nicotine treatment (nicotine replacement therapy (NRT) or e-cigarettes) as part of the intervention. We judged three studies to be at low risk of bias, one to be at unclear risk of bias, and the remaining 16 studies to be at high risk of bias. Compared with usual care, brief advice, very brief advice, or less active treatment, we found very low-certainty evidence of benefit from behavioural support provided by dental professionals, comprising either one session (RR 1.86, 95% CI 1.01 to 3.41; I2 = 66%; four studies, n = 6328), or more than one session (RR 1.90, 95% CI 1.17 to 3.11; I2 = 61%; seven studies, n = 2639), on abstinence from tobacco use at least six months from baseline. We found moderate-certainty evidence of benefit from behavioural interventions provided by dental professionals combined with the provision of NRT or e-cigarettes, compared with no intervention, usual care, brief, or very brief advice only (RR 2.76, 95% CI 1.58 to 4.82; I2 = 0%; four studies, n = 1221). We did not detect a benefit from multiple-session behavioural support provided by dental professionals delivered in a high school or college, instead of a dental setting (RR 1.51, 95% CI 0.86 to 2.65; I2 = 83%; three studies, n = 1020; very low-certainty evidence). Only one study reported adverse events or oral health outcomes, making it difficult to draw any conclusions. AUTHORS' CONCLUSIONS: There is very low-certainty evidence that quit rates increase when dental professionals offer behavioural support to promote tobacco cessation. There is moderate-certainty evidence that tobacco abstinence rates increase in cigarette smokers if dental professionals offer behavioural support combined with pharmacotherapy. Further evidence is required to be certain of the size of the benefit and whether adding pharmacological interventions is more effective than behavioural support alone. Future studies should use biochemical validation of abstinence so as to preclude the risk of detection bias. There is insufficient evidence on whether these interventions lead to adverse effects, but no reasons to suspect that these effects would be specific to interventions delivered by dental professionals. There was insufficient evidence that interventions affected oral health.

Behavioural interventions for smoking cessation: an overview and network meta-analysis.

BACKGROUND: Smoking is a leading cause of disease and death worldwide. In people who smoke, quitting smoking can reverse much of the damage. Many people use behavioural interventions to help them quit smoking; these interventions can vary substantially in their content and effectiveness. OBJECTIVES: To summarise the evidence from Cochrane Reviews that assessed the effect of behavioural interventions designed to support smoking cessation attempts and to conduct a network meta-analysis to determine how modes of delivery; person delivering the intervention; and the nature, focus, and intensity of behavioural interventions for smoking cessation influence the likelihood of achieving abstinence six months after attempting to stop smoking; and whether the effects of behavioural interventions depend upon other characteristics, including population, setting, and the provision of pharmacotherapy. To summarise the availability and principal findings of economic evaluations of behavioural interventions for smoking cessation, in terms of comparative costs and cost-effectiveness, in the form of a brief economic commentary. METHODS: This work comprises two main elements. 1. We conducted a Cochrane Overview of reviews following standard Cochrane methods. We identified Cochrane Reviews of behavioural interventions (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials) for smoking cessation by searching the Cochrane Library in July 2020. We evaluated the methodological quality of reviews using AMSTAR 2 and synthesised data from the reviews narratively. 2. We used the included reviews to identify randomised controlled trials of behavioural interventions for smoking cessation compared with other behavioural interventions or no intervention for smoking cessation. To be included, studies had to include adult smokers and measure smoking abstinence at six months or longer. Screening, data extraction, and risk of bias assessment followed standard Cochrane methods. We synthesised data using Bayesian component network meta-analysis (CNMA), examining the effects of 38 different components compared to minimal intervention. Components included behavioural and motivational elements, intervention providers, delivery modes, nature, focus, and intensity of the behavioural intervention. We used component network meta-regression (CNMR) to evaluate the influence of population characteristics, provision of pharmacotherapy, and intervention intensity on the component effects. We evaluated certainty of the evidence using GRADE domains. We assumed an additive effect for individual components. MAIN RESULTS: We included 33 Cochrane Reviews, from which 312 randomised controlled trials, representing 250,563 participants and 845 distinct study arms, met the criteria for inclusion in our component network meta-analysis. This represented 437 different combinations of components. Of the 33 reviews, confidence in review findings was high in four reviews and moderate in nine reviews, as measured by the AMSTAR 2 critical appraisal tool. The remaining 20 reviews were low or critically low due to one or more critical weaknesses, most commonly inadequate investigation or discussion (or both) of the impact of publication bias. Of note, the critical weaknesses identified did not affect the searching, screening, or data extraction elements of the review process, which have direct bearing on our CNMA. Of the included studies, 125/312 were at low risk of bias overall, 50 were at high risk of bias, and the remainder were at unclear risk. Analyses from the contributing reviews and from our CNMA showed behavioural interventions for smoking cessation can increase quit rates, but effectiveness varies on characteristics of the support provided. There was high-certainty evidence of benefit for the provision of counselling (odds ratio (OR) 1.44, 95% credibility interval (CrI) 1.22 to 1.70, 194 studies, n = 72,273) and guaranteed financial incentives (OR 1.46, 95% CrI 1.15 to 1.85, 19 studies, n = 8877). Evidence of benefit remained when removing studies at high risk of bias. These findings were consistent with pair-wise meta-analyses from contributing reviews. There was moderate-certainty evidence of benefit for interventions delivered via text message (downgraded due to unexplained statistical heterogeneity in pair-wise comparison), and for the following components where point estimates suggested benefit but CrIs incorporated no clinically significant difference: individual tailoring; intervention content including motivational components; intervention content focused on how to quit. The remaining intervention components had low-to very low-certainty evidence, with the main issues being imprecision and risk of bias. There was no evidence to suggest an increase in harms in groups receiving behavioural support for smoking cessation. Intervention effects were not changed by adjusting for population characteristics, but data were limited. Increasing intensity of behavioural support, as measured through the number of contacts, duration of each contact, and programme length, had point estimates associated with modestly increased chances of quitting, but CrIs included no difference. The effect of behavioural support for smoking cessation appeared slightly less pronounced when people were already receiving smoking cessation pharmacotherapies. AUTHORS' CONCLUSIONS: Behavioural support for smoking cessation can increase quit rates at six months or longer, with no evidence that support increases harms. This is the case whether or not smoking cessation pharmacotherapy is also provided, but the effect is slightly more pronounced in the absence of pharmacotherapy. Evidence of benefit is strongest for the provision of any form of counselling, and guaranteed financial incentives. Evidence suggested possible benefit but the need of further studies to evaluate: individual tailoring; delivery via text message, email, and audio recording; delivery by lay health advisor; and intervention content with motivational components and a focus on how to quit. We identified 23 economic evaluations; evidence did not consistently suggest one type of behavioural intervention for smoking cessation was more cost-effective than another. Future reviews should fully consider publication bias. Tools to investigate publication bias and to evaluate certainty in CNMA are needed.

ANTECEDENTES: El tabaquismo es una causa principal de enfermedad y muerte en todo el mundo. En las personas que fuman, dejar de fumar puede revertir gran parte del daño. Muchas personas utilizan intervenciones conductuales para ayudarles a dejar de fumar y estas intervenciones pueden variar considerablemente en contenido y efectividad. OBJETIVOS: Resumir la evidencia de las revisiones Cochrane que evaluaron el efecto de las intervenciones conductuales diseñadas para apoyar los intentos de abandono del hábito de fumar y realizar un metanálisis en red para determinar cómo las modalidades de prestación; la persona que administra la intervención; y la naturaleza, el enfoque y la intensidad de las intervenciones conductuales para el abandono del hábito de fumar influyen en la probabilidad de lograr la abstinencia seis meses después de intentar dejar de fumar; y si los efectos de las intervenciones conductuales dependen de otras características, como la población, el contexto y la administración de farmacoterapia. Resumir la disponibilidad y los hallazgos principales de las evaluaciones económicas de intervenciones conductuales para dejar de fumar, en términos de costes y coste­efectividad, mediante un breve comentario económico. MÉTODOS: Este artículo comprende dos elementos principales. 1. Se realizó una revisión global Cochrane de revisiones según los métodos estándar de Cochrane. Mediante una búsqueda en la Biblioteca Cochrane en julio de 2020 se identificaron las revisiones Cochrane de intervenciones conductuales (incluidas todas las intervenciones no farmacológicas, p.ej., orientación, ejercicio, hipnoterapia, materiales de autoayuda) para el abandono del hábito de fumar. La calidad metodológica de las revisiones se evaluó mediante AMSTAR 2 y los datos de las revisiones se resumieron de manera narrativa. 2. Las revisiones incluidas se utilizaron para identificar los ensayos controlados aleatorizados de intervenciones conductuales para el abandono del hábito de fumar en comparación con otras intervenciones conductuales o ninguna intervención para el abandono del hábito de fumar. Para ser incluidos, los estudios debían incluir a fumadores adultos y medir la abstinencia de fumar a los seis meses o más. La selección, la extracción de los datos y la evaluación del riesgo de sesgo siguieron los métodos Cochrane estándar. Los datos se resumieron mediante un metanálisis en red de componentes (MARC) bayesiano, y se examinaron los efectos de 38 componentes diferentes en comparación con una intervención mínima. Los componentes incluyeron elementos conductuales y motivacionales, proveedores de la intervención, modos de administración, naturaleza, enfoque e intensidad de la intervención conductual. Se utilizó la metarregresión en red de componentes (MRRC) para evaluar la influencia de las características de la población, la administración de farmacoterapia y la intensidad de la intervención sobre los efectos de los componentes. La certeza de la evidencia se evaluó mediante los dominios de GRADE. Se presupuso un efecto aditivo para los componentes individuales. RESULTADOS PRINCIPALES: Se incluyeron 33 revisiones Cochrane, de las cuales 312 ensayos controlados aleatorizados, que representaban a 250 563 participantes y 845 grupos de estudio distintos, cumplieron los criterios para su inclusión en el metanálisis en red de componentes. Esto representó 437 combinaciones diferentes de componentes. De las 33 revisiones, la confianza en los hallazgos de la revisión fue alta en cuatro y moderada en nueve, medida con la herramienta de lectura crítica AMSTAR 2. Las 20 revisiones restantes tuvieron una confianza baja o críticamente baja debido a una o más deficiencias graves, las más habituales fueron una investigación o discusión (o ambas) insuficiente acerca del impacto del sesgo de publicación. Cabe señalar que las debilidades críticas identificadas no afectaron los elementos de la búsqueda, la selección o la extracción de los datos del proceso de revisión, que mantienen una relación directa en este MARC. Entre los estudios incluidos, 125/312 tuvieron un riesgo general de sesgo bajo, 50 un riesgo de sesgo alto y el resto un riesgo de sesgo poco claro. Los análisis de las revisiones contribuyentes y de este MARC mostraron que las intervenciones conductuales para dejar de fumar pueden aumentar las tasas de abandono del hábito, pero la efectividad varía según las características del apoyo proporcionado. Hubo evidencia de certeza alta de un efecto beneficioso de la prestación de orientación (odds ratio [OR] 1,44; intervalo de credibilidad [ICr] del 95%: 1,22 a 1,70, 194 estudios, n = 72 273) y de los incentivos económicos garantizados (OR 1,46; ICr del 95% 1,15 a 1,85, 19 estudios, n = 8877). La evidencia de un efecto beneficioso se mantuvo cuando se eliminaron los estudios con alto riesgo de sesgo. Estos hallazgos fueron concordantes con los metanálisis pareados de las revisiones contribuyentes. Hubo evidencia de certeza moderada de un efecto beneficioso de las intervenciones administradas a través de mensajes de texto (la certeza se disminuyó debido a una heterogeneidad estadística inexplicada en la comparación pareada), y de los siguientes componentes en los que las estimaciones puntuales indicaron un efecto beneficioso pero los ICr no incorporaron una diferencia clínicamente significativa: personalización; contenido de la intervención con componentes motivacionales; contenido de la intervención centrado en cómo dejar de fumar. Los otros componentes de la intervención tuvieron evidencia de certeza muy baja a baja, y sus problemas principales fueron la imprecisión y el riesgo de sesgo. No hubo evidencia que indicara un aumento de los efectos perjudiciales en los grupos que recibieron apoyo conductual para dejar de fumar. Los efectos de la intervención no cambiaron al ajustar las características de la población, pero los datos fueron limitados. El aumento de la intensidad del apoyo conductual, medido a través del número de contactos, la duración de cada contacto y la duración del programa, tuvo estimaciones puntuales asociadas con un modesto aumento de las posibilidades de dejar de fumar, pero los ICr no incluyeron una diferencia. El efecto del apoyo conductual para dejar de fumar pareció ser ligeramente menos pronunciado cuando las personas ya recibían farmacoterapias para dejar de fumar. CONCLUSIONES DE LOS AUTORES: El apoyo conductual para dejar de fumar puede aumentar las tasas de abandono a los seis meses o más, sin evidencia de que este apoyo aumente los efectos perjudiciales. Esto es así tanto si se proporciona una farmacoterapia para dejar de fumar como si no, pero el efecto es ligeramente más pronunciado sin farmacoterapia. La evidencia de un efecto beneficioso es más sólida para la prestación de cualquier tipo de orientación y de incentivos económicos garantizados. La evidencia indicó un posible efecto beneficioso, pero la necesidad de realizar más estudios para evaluar: la personalización; la administración mediante mensajes de texto, correos electrónicos y grabaciones de audio; la administración por parte de un asesor de salud no profesional; y el contenido de la intervención con componentes motivacionales y centrada en cómo dejar de fumar. Se identificaron 23 evaluaciones económicas; la evidencia no indicó de manera homogénea que un tipo de intervención conductual para el abandono del hábito de fumar fuera más coste­efectiva que otra. Las revisiones futuras deberían examinar a fondo el sesgo de publicación. Se necesitan herramientas para investigar el sesgo de publicación y evaluar la certeza en MARC.

Antidepressants for smoking cessation.

BACKGROUND: Whilst the pharmacological profiles and mechanisms of antidepressants are varied, there are common reasons why they might help people to stop smoking tobacco. Firstly, nicotine withdrawal may produce depressive symptoms and antidepressants may relieve these. Additionally, some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction. OBJECTIVES: To assess the evidence for the efficacy, safety 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 Specialized Register, which includes reports of trials indexed in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO, clinicaltrials.gov, the ICTRP, and other reviews and meeting abstracts, in May 2019. SELECTION CRITERIA: We included randomized controlled trials (RCTs) that recruited smokers, and compared antidepressant medications with placebo or no treatment, an alternative pharmacotherapy, or the same medication used in a different way. We excluded trials with less than six months follow-up from efficacy analyses. We included trials with any follow-up length in safety analyses. DATA COLLECTION AND ANALYSIS: We extracted data and assessed risk of bias using standard Cochrane methods. We also used GRADE to assess the certainty of the evidence. The primary outcome measure was smoking cessation after at least six months follow-up, expressed as a risk ratio (RR) and 95% confidence intervals (CIs). We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Where appropriate, we performed meta-analysis using a fixed-effect model. Similarly, we presented incidence of safety 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 dropout due to drug, as RRs (95% CIs). MAIN RESULTS: We included 115 studies (33 new to this update) in this review; most recruited adult participants from the community or from smoking cessation clinics. We judged 28 of the studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk did not change clinical interpretation of the results. There was high-certainty evidence that bupropion increased long-term smoking cessation rates (RR 1.64, 95% CI 1.52 to 1.77; I2 = 15%; 45 studies, 17,866 participants). There was insufficient evidence to establish whether participants taking bupropion were more likely to report SAEs compared to those taking placebo. Results were imprecise and CIs encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I2 = 0%; 21 studies, 10,625 participants; moderate-certainty evidence, downgraded one level due to imprecision). We found high-certainty evidence that use of bupropion resulted in more trial dropouts due to adverse events of the drug than placebo (RR 1.37, 95% CI 1.21 to 1.56; I2 = 19%; 25 studies, 12,340 participants). Participants randomized to bupropion were also more likely to report psychiatric AEs compared with those randomized to placebo (RR 1.25, 95% CI 1.15 to 1.37; I2 = 15%; 6 studies, 4439 participants). We also looked at the safety and efficacy of bupropion when combined with other non-antidepressant smoking cessation therapies. There was insufficient evidence to establish whether combination bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.19, 95% CI 0.94 to 1.51; I2 = 52%; 12 studies, 3487 participants), or whether combination bupropion and varenicline resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I2 = 15%; 3 studies, 1057 participants). We judged the certainty of evidence to be low and moderate, respectively; in both cases due to imprecision, and also due to inconsistency in the former. Safety data were sparse for these comparisons, making it difficult to draw clear conclusions. A meta-analysis of six studies provided evidence that bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.71, 95% CI 0.64 to 0.79; I2 = 0%; 6 studies, 6286 participants), whilst there was no evidence of a difference in efficacy between bupropion and NRT (RR 0.99, 95% CI 0.91 to 1.09; I2 = 18%; 10 studies, 8230 participants). We also found some 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), whilst there was insufficient evidence to determine whether bupropion or nortriptyline were more effective when compared with one another (RR 1.30 (favouring bupropion), 95% CI 0.93 to 1.82; I2 = 0%; 3 studies, 417 participants). There was no evidence that any of the other antidepressants tested (including St John's Wort, selective serotonin reuptake inhibitors (SSRIs), monoamine oxidase inhibitors (MAOIs)) had a beneficial effect on smoking cessation. 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 also increases the number of adverse events, including psychiatric AEs, and there is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with placebo. However, there is no clear evidence to suggest whether people taking bupropion experience more or fewer SAEs than those taking placebo (moderate certainty). Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo. Evidence suggests that bupropion may be as successful as NRT and nortriptyline in helping people to quit smoking, but that it is less effective than varenicline. There is insufficient evidence to determine whether the other antidepressants tested, such as SSRIs, aid smoking cessation, and when looking at safety and tolerance outcomes, in most cases, paucity of data made it difficult to draw conclusions. Due to the high-certainty evidence, 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 front-line smoking cessation aids already available. However, it is important that where studies of antidepressants for smoking cessation are carried out they measure and report safety and tolerability clearly.

Print-based self-help interventions for smoking cessation.

BACKGROUND: Many smokers give up smoking on their own, but materials that provide a structured programme for smokers to follow may increase the number who quit successfully. OBJECTIVES: The aims of this review were to determine the effectiveness of different forms of print-based self-help materials that provide a structured programme for smokers to follow, compared with no treatment and with other minimal contact strategies, and to determine the comparative effectiveness of different components and characteristics of print-based self-help, such as computer-generated feedback, additional materials, tailoring of materials to individuals, and targeting of materials at specific groups. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Trials Register, ClinicalTrials.gov, and the International Clinical Trials Registry Platform (ICTRP). The date of the most recent search was March 2018. SELECTION CRITERIA: We included randomised trials of smoking cessation with follow-up of at least six months, where at least one arm tested print-based materials providing self-help compared with minimal print-based self-help (such as a short leaflet) or a lower-intensity control. We defined 'self-help' as structured programming for smokers trying to quit without intensive contact with a therapist. DATA COLLECTION AND ANALYSIS: We extracted data in accordance with standard methodological procedures set out by Cochrane. The main outcome measure was abstinence from smoking after at least six months' follow-up in people smoking at baseline. We used the most rigorous definition of abstinence in each study and biochemically validated rates when available. Where appropriate, we performed meta-analysis using a random-effects model. MAIN RESULTS: We identified 75 studies that met our inclusion criteria. Many study reports did not include sufficient detail to allow judgement of risk of bias for some domains. We judged 30 studies (40%) to be at high risk of bias for one or more domains.Thirty-five studies evaluated the effects of standard, non-tailored self-help materials. Eleven studies compared self-help materials alone with no intervention and found a small effect in favour of the intervention (n = 13,241; risk ratio (RR) 1.19, 95% confidence interval (CI) 1.03 to 1.37; I² = 0%). We judged the evidence to be of moderate certainty in accordance with GRADE, downgraded for indirect relevance to populations in low- and middle-income countries because evidence for this comparison came from studies conducted solely in high-income countries and there is reason to believe the intervention might work differently in low- and middle-income countries. This analysis excluded two studies by the same author team with strongly positive outcomes that were clear outliers and introduced significant heterogeneity. Six further studies of structured self-help compared with brief leaflets did not show evidence of an effect of self-help materials on smoking cessation (n = 7023; RR 0.87, 95% CI 0.71 to 1.07; I² = 21%). We found evidence of benefit from standard self-help materials when there was brief contact that did not include smoking cessation advice (4 studies; n = 2822; RR 1.39, 95% CI 1.03 to 1.88; I² = 0%), but not when self-help was provided as an adjunct to face-to-face smoking cessation advice for all participants (11 studies; n = 5365; RR 0.99, 95% CI 0.76 to 1.28; I² = 32%).Thirty-two studies tested materials tailored for the characteristics of individual smokers, with controls receiving no materials, or stage-matched or non-tailored materials. Most of these studies used more than one mailing. Pooling studies that compared tailored self-help with no self-help, either on its own or compared with advice, or as an adjunct to advice, showed a benefit of providing tailored self-help interventions (12 studies; n = 19,190; RR 1.34, 95% CI 1.20 to 1.49; I² = 0%) with little evidence of difference between subgroups (10 studies compared tailored with no materials, n = 14,359; RR 1.34, 95% CI 1.19 to 1.51; I² = 0%; two studies compared tailored materials with brief advice, n = 2992; RR 1.13, 95% CI 0.86 to 1.49; I² = 0%; and two studies evaluated tailored materials as an adjunct to brief advice, n = 1839; RR 1.72, 95% CI 1.17 to 2.53; I² = 10%). When studies compared tailored self-help with non-tailored self-help, results favoured tailored interventions when the tailored interventions involved more mailings than the non-tailored interventions (9 studies; n = 14,166; RR 1.42, 95% CI 1.20 to 1.68; I² = 0%), but not when the two conditions were contact-matched (10 studies; n = 11,024; RR 1.07, 95% CI 0.89 to 1.30; I² = 50%). We judged the evidence to be of moderate certainty in accordance with GRADE, downgraded for risk of bias.Five studies evaluated self-help materials as an adjunct to nicotine replacement therapy; pooling three of these provided no evidence of additional benefit (n = 1769; RR 1.05, 95% CI 0.86 to 1.30; I² = 0%). Four studies evaluating additional written materials favoured the intervention, but the lower confidence interval crossed the line of no effect (RR 1.20, 95% CI 0.91 to 1.58; I² = 73%). A small number of other studies did not detect benefit from using targeted materials, or find differences between different self-help programmes. AUTHORS' CONCLUSIONS: Moderate-certainty evidence shows that when no other support is available, written self-help materials help more people to stop smoking than no intervention. When people receive advice from a health professional or are using nicotine replacement therapy, there is no evidence that self-help materials add to their effect. However, small benefits cannot be excluded. Moderate-certainty evidence shows that self-help materials that use data from participants to tailor the nature of the advice or support given are more effective than no intervention. However, when tailored self-help materials, which typically involve repeated assessment and mailing, were compared with untailored materials delivered similarly, there was no evidence of benefit.Available evidence tested self-help interventions in high-income countries, where more intensive support is often available. Further research is needed to investigate effects of these interventions in low- and middle-income countries, where more intensive support may not be available.

Incentives for smoking cessation.

BACKGROUND: Financial incentives, monetary or vouchers, are widely used in an attempt to precipitate, reinforce and sustain behaviour change, including smoking cessation. They have been used in workplaces, in clinics and hospitals, and within community programmes. OBJECTIVES: To determine the long-term effect of incentives and contingency management programmes for smoking cessation. SEARCH METHODS: For this update, we searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the International Clinical Trials Registry Platform (ICTRP). The most recent searches were conducted in July 2018. SELECTION CRITERIA: We considered only randomised controlled trials, allocating individuals, workplaces, groups within workplaces, or communities to smoking cessation incentive schemes or control conditions. We included studies in a mixed-population setting (e.g. community, work-, clinic- or institution-based), and also studies in pregnant smokers. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. The primary outcome measure in the mixed-population studies was abstinence from smoking at longest follow-up (at least six months from the start of the intervention). In the trials of pregnant women we used abstinence measured at the longest follow-up, and at least to the end of the pregnancy. Where available, we pooled outcome data using a Mantel-Haenzel random-effects model, with results reported as risk ratios (RRs) and 95% confidence intervals (CIs), using adjusted estimates for cluster-randomised trials. We analysed studies carried out in mixed populations separately from those carried out in pregnant populations. MAIN RESULTS: Thirty-three mixed-population studies met our inclusion criteria, covering more than 21,600 participants; 16 of these are new to this version of the review. Studies were set in varying locations, including community settings, clinics or health centres, workplaces, and outpatient drug clinics. We judged eight studies to be at low risk of bias, and 10 to be at high risk of bias, with the rest at unclear risk. Twenty-four of the trials were run in the USA, two in Thailand and one in the Phillipines. The rest were European. Incentives offered included cash payments or vouchers for goods and groceries, offered directly or collected and redeemable online. The pooled RR for quitting with incentives at longest follow-up (six months or more) compared with controls was 1.49 (95% CI 1.28 to 1.73; 31 RCTs, adjusted N = 20,097; I2 = 33%). Results were not sensitive to the exclusion of six studies where an incentive for cessation was offered at long-term follow up (result excluding those studies: RR 1.40, 95% CI 1.16 to 1.69; 25 RCTs; adjusted N = 17,058; I2 = 36%), suggesting the impact of incentives continues for at least some time after incentives cease.Although not always clearly reported, the total financial amount of incentives varied considerably between trials, from zero (self-deposits), to a range of between USD 45 and USD 1185. There was no clear direction of effect between trials offering low or high total value of incentives, nor those encouraging redeemable self-deposits.We included 10 studies of 2571 pregnant women. We judged two studies to be at low risk of bias, one at high risk of bias, and seven at unclear risk. When pooled, the nine trials with usable data (eight conducted in the USA and one in the UK), delivered an RR at longest follow-up (up to 24 weeks post-partum) of 2.38 (95% CI 1.54 to 3.69; N = 2273; I2 = 41%), in favour of incentives. AUTHORS' CONCLUSIONS: Overall there is high-certainty evidence that incentives improve smoking cessation rates at long-term follow-up in mixed population studies. The effectiveness of incentives appears to be sustained even when the last follow-up occurs after the withdrawal of incentives. There is also moderate-certainty evidence, limited by some concerns about risks of bias, that incentive schemes conducted among pregnant smokers improve smoking cessation rates, both at the end of pregnancy and post-partum. Current and future research might explore more precisely differences between trials offering low or high cash incentives and self-incentives (deposits), within a variety of smoking populations.

Relapse prevention interventions for smoking cessation.

BACKGROUND: A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse. OBJECTIVES: To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group trials register, clinicaltrials.gov, and the ICTRP in February 2018 for studies mentioning relapse prevention or maintenance in their title, abstracts, or keywords. SELECTION CRITERIA: Randomised or quasi-randomised controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included studies that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. MAIN RESULTS: We included 77 studies (67,285 participants), 15 of which are new to this update. We judged 21 studies to be at high risk of bias, 51 to be at unclear risk of bias, and five studies to be at low risk of bias. Forty-eight studies included abstainers, and 29 studies helped people to quit and then tested treatments to prevent relapse. Twenty-six studies focused on special populations who were abstinent because of pregnancy (18 studies), hospital admission (five studies), or military service (three studies). Most studies used behavioural interventions that tried to teach people skills to cope with the urge to smoke, or followed up with additional support. Some studies tested extended pharmacotherapy.We focused on results from those studies that randomised abstainers, as these are the best test of relapse prevention interventions. Of the 12 analyses we conducted in abstainers, three pharmacotherapy analyses showed benefits of the intervention: extended varenicline in assisted abstainers (2 studies, n = 1297, risk ratio (RR) 1.23, 95% confidence interval (CI) 1.08 to 1.41, I² = 82%; moderate certainty evidence), rimonabant in assisted abstainers (1 study, RR 1.29, 95% CI 1.08 to 1.55), and nicotine replacement therapy (NRT) in unaided abstainers (2 studies, n = 2261, RR 1.24, 95% Cl 1.04 to 1.47, I² = 56%). The remainder of analyses of pharmacotherapies in abstainers had wide confidence intervals consistent with both no effect and a statistically significant effect in favour of the intervention. These included NRT in hospital inpatients (2 studies, n = 1078, RR 1.23, 95% CI 0.94 to 1.60, I² = 0%), NRT in assisted abstainers (2 studies, n = 553, RR 1.04, 95% CI 0.77 to 1.40, I² = 0%; low certainty evidence), extended bupropion in assisted abstainers (6 studies, n = 1697, RR 1.15, 95% CI 0.98 to 1.35, I² = 0%; moderate certainty evidence), and bupropion plus NRT (2 studies, n = 243, RR 1.18, 95% CI 0.75 to 1.87, I² = 66%; low certainty evidence). Analyses of behavioural interventions in abstainers did not detect an effect. These included studies in abstinent pregnant and postpartum women at end of pregnancy (8 studies, n = 1523, RR 1.05, 95% CI 0.99 to 1.11, I² = 0%) and at postpartum follow-up (15 studies, n = 4606, RR 1.02, 95% CI 0.94 to 1.09, I² = 3%), studies in hospital inpatients (4 studies, n = 1300, RR 0.95, 95% CI 0.81 to 1.11, I² = 0%), and studies in assisted abstainers (10 studies, n = 5408, RR 0.99, 95% CI 0.87 to 1.13, I² = 56%; moderate certainty evidence) and unaided abstainers (5 studies, n = 3561, RR 1.06, 95% CI 0.96 to 1.16, I² = 1%) from the general population. AUTHORS' CONCLUSIONS: Behavioural interventions that teach people to recognise situations that are high risk for relapse along with strategies to cope with them provided no worthwhile benefit in preventing relapse in assisted abstainers, although unexplained statistical heterogeneity means we are only moderately certain of this. In people who have successfully quit smoking using pharmacotherapy, there were mixed results regarding extending pharmacotherapy for longer than is standard. Extended treatment with varenicline helped to prevent relapse; evidence for the effect estimate was of moderate certainty, limited by unexplained statistical heterogeneity. Moderate-certainty evidence, limited by imprecision, did not detect a benefit from extended treatment with bupropion, though confidence intervals mean we could not rule out a clinically important benefit at this stage. Low-certainty evidence, limited by imprecision, did not show a benefit of extended treatment with nicotine replacement therapy in preventing relapse in assisted abstainers. More research is needed in this area, especially as the evidence for extended nicotine replacement therapy in unassisted abstainers did suggest a benefit.

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation.

BACKGROUND: Pharmacotherapies for smoking cessation increase the likelihood of achieving abstinence in a quit attempt. It is plausible that providing support, or, if support is offered, offering more intensive support or support including particular components may increase abstinence further. OBJECTIVES: To evaluate the effect of adding or increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition. We also looked at studies which directly compare behavioural interventions matched for contact time, where pharmacotherapy is provided to both groups (e.g. tests of different components or approaches to behavioural support as an adjunct to pharmacotherapy). SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the ICTRP in June 2018 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline, that evaluated the addition of personal support or compared two or more intensities of behavioural support. SELECTION CRITERIA: Randomised or quasi-randomised controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount or type of behavioural support. The intervention condition had to involve person-to-person contact (defined as face-to-face or telephone). The control condition could receive less intensive personal contact, a different type of personal contact, written information, or no behavioural support at all. We excluded trials recruiting only pregnant women and trials which did not set out to assess smoking cessation at six months or longer. DATA COLLECTION AND ANALYSIS: For this update, screening and data extraction followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates, if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a random-effects model. MAIN RESULTS: Eighty-three studies, 36 of which were new to this update, met the inclusion criteria, representing 29,536 participants. Overall, we judged 16 studies to be at low risk of bias and 21 studies to be at high risk of bias. All other studies were judged to be at unclear risk of bias. Results were not sensitive to the exclusion of studies at high risk of bias. We pooled all studies comparing more versus less support in the main analysis. Findings demonstrated a benefit of behavioural support in addition to pharmacotherapy. When all studies of additional behavioural therapy were pooled, there was evidence of a statistically significant benefit from additional support (RR 1.15, 95% CI 1.08 to 1.22, I² = 8%, 65 studies, n = 23,331) for abstinence at longest follow-up, and this effect was not different when we compared subgroups by type of pharmacotherapy or intensity of contact. This effect was similar in the subgroup of eight studies in which the control group received no behavioural support (RR 1.20, 95% CI 1.02 to 1.43, I² = 20%, n = 4,018). Seventeen studies compared interventions matched for contact time but that differed in terms of the behavioural components or approaches employed. Of the 15 comparisons, all had small numbers of participants and events. Only one detected a statistically significant effect, favouring a health education approach (which the authors described as standard counselling containing information and advice) over motivational interviewing approach (RR 0.56, 95% CI 0.33 to 0.94, n = 378). AUTHORS' CONCLUSIONS: There is high-certainty evidence that providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking increases quit rates. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 20%, based on a pooled estimate from 65 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support. More research is needed to assess the effectiveness of specific components that comprise behavioural support.

Relapse prevention interventions for smoking cessation.

BACKGROUND: A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse. OBJECTIVES: To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group trials register, clinicaltrials.gov, and the ICTRP in May 2019 for studies mentioning relapse prevention or maintenance in their title, abstracts, or keywords. SELECTION CRITERIA: Randomised or quasi-randomised controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included studies that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. MAIN RESULTS: We included 81 studies (69,094 participants), five of which are new to this update. We judged 22 studies to be at high risk of bias, 53 to be at unclear risk of bias, and six studies to be at low risk of bias. Fifty studies included abstainers, and 30 studies helped people to quit and then tested treatments to prevent relapse. Twenty-eight studies focused on special populations who were abstinent because of pregnancy (19 studies), hospital admission (six studies), or military service (three studies). Most studies used behavioural interventions that tried to teach people skills to cope with the urge to smoke, or followed up with additional support. Some studies tested extended pharmacotherapy. We focused on results from those studies that randomised abstainers, as these are the best test of relapse prevention interventions. Of the 12 analyses we conducted in abstainers, three pharmacotherapy analyses showed benefits of the intervention: extended varenicline in assisted abstainers (2 studies, n = 1297, risk ratio (RR) 1.23, 95% confidence interval (CI) 1.08 to 1.41, I2 = 82%; moderate-certainty evidence), rimonabant in assisted abstainers (1 study, RR 1.29, 95% CI 1.08 to 1.55), and nicotine replacement therapy (NRT) in unaided abstainers (2 studies, n = 2261, RR 1.24, 95% Cl 1.04 to 1.47, I2 = 56%). The remainder of analyses of pharmacotherapies in abstainers had wide confidence intervals consistent with both no effect and a statistically significant effect in favour of the intervention. These included NRT in hospital inpatients (2 studies, n = 1078, RR 1.23, 95% CI 0.94 to 1.60, I2 = 0%), NRT in assisted abstainers (2 studies, n = 553, RR 1.04, 95% CI 0.77 to 1.40, I2 = 0%; low-certainty evidence), extended bupropion in assisted abstainers (6 studies, n = 1697, RR 1.15, 95% CI 0.98 to 1.35, I2 = 0%; moderate-certainty evidence), and bupropion plus NRT (2 studies, n = 243, RR 1.18, 95% CI 0.75 to 1.87, I2 = 66%; low-certainty evidence). Analyses of behavioural interventions in abstainers did not detect an effect. These included studies in abstinent pregnant and postpartum women at the end of pregnancy (8 studies, n = 1523, RR 1.05, 95% CI 0.99 to 1.11, I2 = 0%) and at postpartum follow-up (15 studies, n = 4606, RR 1.02, 95% CI 0.94 to 1.09, I2 = 3%), studies in hospital inpatients (5 studies, n = 1385, RR 1.10, 95% CI 0.82 to 1.47, I2 = 58%), and studies in assisted abstainers (11 studies, n = 5523, RR 0.98, 95% CI 0.87 to 1.11, I2 = 52%; moderate-certainty evidence) and unaided abstainers (5 studies, n = 3561, RR 1.06, 95% CI 0.96 to 1.16, I2 = 1%) from the general population. AUTHORS' CONCLUSIONS: Behavioural interventions that teach people to recognise situations that are high risk for relapse along with strategies to cope with them provided no worthwhile benefit in preventing relapse in assisted abstainers, although unexplained statistical heterogeneity means we are only moderately certain of this. In people who have successfully quit smoking using pharmacotherapy, there were mixed results regarding extending pharmacotherapy for longer than is standard. Extended treatment with varenicline helped to prevent relapse; evidence for the effect estimate was of moderate certainty, limited by unexplained statistical heterogeneity. Moderate-certainty evidence, limited by imprecision, did not detect a benefit from extended treatment with bupropion, though confidence intervals mean we could not rule out a clinically important benefit at this stage. Low-certainty evidence, limited by imprecision, did not show a benefit of extended treatment with nicotine replacement therapy in preventing relapse in assisted abstainers. More research is needed in this area, especially as the evidence for extended nicotine replacement therapy in unassisted abstainers did suggest a benefit.

Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers with feedback on the current or potential future biomedical effects of smoking using, for example, measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer or other diseases. OBJECTIVES: The main objective was to determine the efficacy of providing smokers with feedback on their exhaled CO measurement, spirometry results, atherosclerotic plaque imaging, and genetic susceptibility to smoking-related diseases in helping them to quit smoking. SEARCH METHODS: For the most recent update, we searched the Cochrane Tobacco Addiction Group Specialized Register in March 2018 and ClinicalTrials.gov and the WHO ICTRP in September 2018 for studies added since the last update in 2012. SELECTION CRITERIA: Inclusion criteria for the review were: a randomised controlled trial design; participants being current smokers; interventions based on a biomedical test to increase smoking cessation rates; control groups receiving all other components of intervention; and an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. We expressed results as a risk ratio (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate, we pooled studies using a Mantel-Haenszel random-effects method. MAIN RESULTS: We included 20 trials using a variety of biomedical tests interventions; one trial included two interventions, for a total of 21 interventions. We included a total of 9262 participants, all of whom were adult smokers. All studies included both men and women adult smokers at different stages of change and motivation for smoking cessation. We judged all but three studies to be at high or unclear risk of bias in at least one domain. We pooled trials in three categories according to the type of biofeedback provided: feedback on risk exposure (five studies); feedback on smoking-related disease risk (five studies); and feedback on smoking-related harm (11 studies). There was no evidence of increased cessation rates from feedback on risk exposure, consisting mainly of feedback on CO measurement, in five pooled trials (RR 1.00, 95% CI 0.83 to 1.21; I2 = 0%; n = 2368). Feedback on smoking-related disease risk, including four studies testing feedback on genetic markers for cancer risk and one study with feedback on genetic markers for risk of Crohn's disease, did not show a benefit in smoking cessation (RR 0.80, 95% CI 0.63 to 1.01; I2 = 0%; n = 2064). Feedback on smoking-related harm, including nine studies testing spirometry with or without feedback on lung age and two studies on feedback on carotid ultrasound, also did not show a benefit (RR 1.26, 95% CI 0.99 to 1.61; I2 = 34%; n = 3314). Only one study directly compared multiple forms of measurement with a single form of measurement, and did not detect a significant difference in effect between measurement of CO plus genetic susceptibility to lung cancer and measurement of CO only (RR 0.82, 95% CI 0.43 to 1.56; n = 189). AUTHORS' CONCLUSIONS: There is little evidence about the effects of biomedical risk assessment as an aid for smoking cessation. The most promising results relate to spirometry and carotid ultrasound, where moderate-certainty evidence, limited by imprecision and risk of bias, did not detect a statistically significant benefit, but confidence intervals very narrowly missed one, and the point estimate favoured the intervention. A sensitivity analysis removing those studies at high risk of bias did detect a benefit. Moderate-certainty evidence limited by risk of bias did not detect an effect of feedback on smoking exposure by CO monitoring. Low-certainty evidence, limited by risk of bias and imprecision, did not detect a benefit from feedback on smoking-related risk by genetic marker testing. There is insufficient evidence with which to evaluate the hypothesis that multiple types of assessment are more effective than single forms of assessment.

Community pharmacy personnel interventions for smoking cessation.

BACKGROUND: Community pharmacists could provide effective smoking cessation treatment because they offer easy access to members of the community. They are well placed to provide both advice on the correct use of smoking cessation products and behavioural support to aid smoking cessation. OBJECTIVES: To assess the effectiveness of interventions delivered by community pharmacy personnel to assist people to stop smoking, with or without concurrent use of pharmacotherapy. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Specialised Register, along with clinicaltrials.gov and the ICTRP, for smoking cessation studies conducted in a community pharmacy setting, using the search terms pharmacist* or pharmacy or pharmacies. Date of the most recent search: January 2019. SELECTION CRITERIA: Randomised controlled trials of interventions delivered by community pharmacy personnel to promote smoking cessation amongst their clients who were smokers, compared with usual pharmacy support or any less intensive programme. The main outcome measure was smoking cessation rates at six months or more after the start of the intervention. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane for study screening, data extraction and management. We conducted a meta-analysis using a Mantel-Haenszel random-effects model to generate risk ratios (RRs) and 95% confidence intervals (CIs). MAIN RESULTS: We identified seven studies including 1774 participants. We judged three studies to be at high risk of bias and four to be at unclear risk. Each study provided face-to-face behavioural support delivered by pharmacy staff, and required pharmacy personnel training. Typically such programmes comprised support starting before quit day and continuing with weekly appointments for several weeks afterwards. Comparators were either minimal or less intensive behavioural support for smoking cessation, typically comprising a few minutes of one-off advice on how to quit. Participants in both intervention and control arms received equivalent smoking cessation pharmacotherapy in all but one study. All studies took place in high-income countries, and recruited participants visiting pharmacies. We pooled six studies of 1614 participants and detected a benefit of more intensive behavioural smoking cessation interventions delivered by community pharmacy personnel compared with less intensive cessation interventions at longest follow-up (RR 2.30, 95% CI 1.33 to 3.97; I2 = 54%; low-certainty evidence). AUTHORS' CONCLUSIONS: Community pharmacists can provide effective behavioural support to people trying to stop smoking. However, this conclusion is based on low-certainty evidence, limited by risk of bias and imprecision. Further research could change this conclusion.