Aim
The aim of this work was to systematically scope the evidence on opportunistic tobacco smoking cessation interventions for people accessing financial support settings.
Methods
We searched ...MEDLINE, Embase, PsycINFO and the Cochrane Tobacco Addiction Group specialized register to 21 March 2023. We duplicate screened 20% of titles/s and all full texts. We included primary studies investigating smoking cessation interventions delivered opportunistically to people who smoked tobacco, within settings offering support for problems caused by financial hardship, for example homeless support services, social housing and food banks. Data were charted by one reviewer, checked by another and narratively synthesized.
Results
We included 25 studies conducted in a range of financial support settings using qualitative (e.g. interviews and focus groups) and quantitative (e.g. randomized controlled trials, surveys and single arm intervention studies) methodologies. Evidence on the acceptability and feasibility of opportunistic smoking cessation advice was investigated among both clients and providers. Approximately 90% of service providers supported such interventions; however, lack of resources, staff training and a belief that tobacco smoking reduced illicit substance use were perceived barriers. Clients welcomed being asked about smoking and offered assistance to quit and expressed interest in interventions including the provision of nicotine replacement therapy, e‐cigarettes and incentives to quit smoking. Six studies investigated the comparative effectiveness of opportunistic smoking cessation interventions on quitting success, with five comparing more to less intensive interventions, with mixed results.
Conclusions
Most studies investigating opportunistic smoking cessation interventions in financial support settings have not measured their effectiveness. Where they have, settings, populations, interventions and findings have varied. There is more evidence investigating acceptability, with promising results.
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
The primary objectives are to summarise the evidence from Cochrane Reviews that assessed the effect of ...behavioural interventions designed to support smoking cessation attempts, and address the following two questions:
How do modes of delivery, person delivering the intervention, and the behavioural and motivational components of behavioural interventions for smoking cessation compare with each other in achieving abstinence at follow‐up of six months or longer?
Do the effects of behavioural interventions vary by other characteristics, including population, setting, and length of intervention?
The secondary objective of this review is 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.
Electronic cigarettes for smoking cessation Hartmann-Boyce, Jamie; Lindson, Nicola; Butler, Ailsa R ...
Cochrane database of systematic reviews,
01/2024, Letnik:
2024, Številka:
1
Journal Article
Recenzirano
Odprti dostop
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.
Type 1 diabetes has historically been associated with a significant reduction in life expectancy. Major advances in treatment of type 1 diabetes have occurred in the past 3 decades. Contemporary ...estimates of the effect of type 1 diabetes on life expectancy are needed.
To examine current life expectancy in people with and without type 1 diabetes in Scotland. We also examined whether any loss of life expectancy in patients with type 1 diabetes is confined to those who develop kidney disease.
Prospective cohort of all individuals alive in Scotland with type 1 diabetes who were aged 20 years or older from 2008 through 2010 and were in a nationwide register (n=24,691 contributing 67,712 person-years and 1043 deaths).
Differences in life expectancy between those with and those without type 1 diabetes and the percentage of the difference due to various causes.
Life expectancy at an attained age of 20 years was an additional 46.2 years among men with type 1 diabetes and 57.3 years among men without it, an estimated loss in life expectancy with diabetes of 11.1 years (95% CI, 10.1-12.1). Life expectancy from age 20 years was an additional 48.1 years among women with type 1 diabetes and 61.0 years among women without it, an estimated loss with diabetes of 12.9 years (95% CI, 11.7-14.1). Even among those with type 1 diabetes with an estimated glomerular filtration rate of 90 mL/min/1.73 m2 or higher, life expectancy was reduced (49.0 years in men, 53.1 years in women) giving an estimated loss from age 20 years of 8.3 years (95% CI, 6.5-10.1) for men and 7.9 years (95% CI, 5.5-10.3) for women. Overall, the largest percentage of the estimated loss in life expectancy was related to ischemic heart disease (36% in men, 31% in women) but death from diabetic coma or ketoacidosis was associated with the largest percentage of the estimated loss occurring before age 50 years (29.4% in men, 21.7% in women).
Estimated life expectancy for patients with type 1 diabetes in Scotland based on data from 2008 through 2010 indicated an estimated loss of life expectancy at age 20 years of approximately 11 years for men and 13 years for women compared with the general population without type 1 diabetes.
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.
Aims/hypothesis
We selected the most informative protein biomarkers for the prediction of incident cardiovascular disease (CVD) in people with type 2 diabetes.
Methods
In this nested case–control ...study we measured 42 candidate CVD biomarkers in 1,123 incident CVD cases and 1,187 controls with type 2 diabetes selected from five European centres. Combinations of biomarkers were selected using cross-validated logistic regression models. Model prediction was assessed using the area under the receiver operating characteristic curve (AUROC).
Results
Sixteen biomarkers showed univariate associations with incident CVD. The most predictive subset selected by forward selection methods contained six biomarkers: N-terminal pro-B-type natriuretic peptide (OR 1.69 per 1 SD, 95% CI 1.47, 1.95), high-sensitivity troponin T (OR 1.29, 95% CI 1.11, 1.51), IL-6 (OR 1.13, 95% CI 1.02, 1.25), IL-15 (OR 1.15, 95% CI 1.01, 1.31), apolipoprotein C-III (OR 0.79, 95% CI 0.70, 0.88) and soluble receptor for AGE (OR 0.84, 95% CI 0.76, 0.94). The prediction of CVD beyond clinical covariates improved from an AUROC of 0.66 to 0.72 (AUROC for Framingham Risk Score covariates 0.59). In addition to the biomarkers, the most important clinical covariates for improving prediction beyond the Framingham covariates were estimated GFR, insulin therapy and HbA
1c
.
Conclusions/interpretation
We identified six protein biomarkers that in combination with clinical covariates improved the prediction of our model beyond the Framingham Score covariates. Biomarkers can contribute to improved prediction of CVD in diabetes but clinical data including measures of renal function and diabetes-specific factors not included in the Framingham Risk Score are also needed.
Aims
To investigate the comparative and combined effectiveness of four types of components of behavioural interventions for cigarette smoking cessation: behavioural (e.g. counselling), motivational ...(e.g. focus on reasons to quit), delivery mode (e.g. phone) and provider (e.g. nurse).
Design
Systematic review and component network meta‐analysis of randomised controlled trials identified from Cochrane reviews. Interventions included behavioural interventions for smoking cessation (including all non‐pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self‐help materials), compared with another behavioural intervention or no support. Building on a 2021 review (CD013229), we conducted three analyses, investigating: comparative effectiveness of the components, whether models that allowed interactions between components gave different results to models assuming additivity, and predicted effect estimates for combined effects of components that had showed promise but where there were few trials.
Setting
Community and health‐care settings.
Participants
Adults who smoke tobacco.
Measurements
Smoking cessation at ≥6 months, preferring sustained, biochemically validated outcomes where available.
Findings
Three hundred and twelve trials (250 563 participants) were included. Fifty were at high risk of bias using Cochrane risk of bias tool, V1 (ROB1); excluding these studies did not change findings. Head‐to‐head comparisons of components suggested that support via text message (SMS) compared with telephone (OR 1.48, 95% CrI 1.13–1.94) or print materials (OR 1.44, 95% CrI 1.14–1.83) was more effective, and individual delivery was less effective than delivery as part of a group (OR 0.78, 95% CrI 0.64–0.95). There was no conclusive evidence of synergistic or antagonistic interactions when combining components that were commonly used together. Adding multiple components that are commonly used in behavioural counselling suggested clinically relevant and statistically conclusive evidence of benefit. Components with the largest effects that could be combined, but rarely have been, were estimated to increase the odds of quitting between two and threefold. For example, financial incentives delivered via SMS, with tailoring and a focus on how to quit, had an estimated OR of 2.94 (95% CrI 1.91–4.52).
Conclusions
Among the components of behavioural support for smoking cessation, behavioural counselling and guaranteed financial incentives are associated with the greatest success. Incorporating additional components associated with effectiveness may further increase benefit, with delivery via text message showing particular promise.
Nicotine receptor partial agonists for smoking cessation Livingstone-Banks, Jonathan; Livingstone-Banks, Jonathan; Fanshawe, Thomas R ...
Cochrane database of systematic reviews,
05/2023, Letnik:
2023, Številka:
5
Journal Article
Recenzirano
Odprti dostop
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 , 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.
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.
To describe the living systematic review (LSR) process and to share experience of planning, searches, screening, extraction, publishing and dissemination to inform and assist authors planning their ...own LSR. Many LSR do not publish more than one update, we hope this paper helps to increase this.
A Cochrane LSR with an international author team that has been ‘living’ for two years, with monthly search updates and three full updates published in this time. LSRs are regularly updated systematic reviews that allow new evidence to be incorporated as it becomes available. LSR are ideally suited to policy-relevant topics where there is uncertainty and new evidence will likely impact the interpretation and/or certainty of outcomes.
The key features of the process that require consideration are: specifying the frequency of searches and triggers for full updates in the protocol; stakeholder input; publishing and disseminating monthly search findings. A strong team, incorporating methodological and topic expertise, with core members that meet regularly is essential. Regular search updates make it important to have a clear cyclical schedule of activity. To achieve timely updates this process should be streamlined, for example, using automated monthly searches, and systematic reviewing software for screening. LSR provide a unique opportunity to incorporate stakeholder feedback.
We recommend that LSRs should be: justified; carefully planned including the timing of search updates, triggers for publication and termination; published in a timely manner; have a clear dissemination plan; and a strong core team of authors.
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