Smoking cessation medicines and e-cigarettes: a systematic review, network meta-analysis and cost-effectiveness analysis

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Chapter 1 Background

Chapter 2 Research questions

Chapter 3 Review methods: assessment of clinical effectiveness and safety

Chapter 4 Economic evaluation methods: assessment of cost-effectiveness

Methods

Model description

The model structure is based on the ‘Sheffield model’ used in a recent Health Technology Assessment report58 on the clinical effectiveness and cost-effectiveness of cytisine compared with varenicline for smoking cessation. This in turn was based on the Benefits of Smoking Cessation on Outcomes (BENESCO) model, which was adapted from the Health Economic Consequences of Smoking (HECOS) model used by the World Health Organization European Partnership Project to reduce tobacco dependence. 95 The BENESCO model is an existing and widely used economic model that has previously been applied to model the effects of smoking cessation interventions in the UK, the USA, Germany, France, Belgium, the Netherlands, Finland, Sweden and the Republic of Korea. 96–105

A cohort simulation model is used for smokers making a one-time smoking cessation attempt. Smoking status, morbidity and mortality are simulated over a lifetime (until the age of 100 years) to calculate the costs and benefits of smoking cessation strategies from the perspective of the health-care payer. The model uses an annual cycle length. UK estimates are used to determine the percentage of the initial cohort that are male or female, their age (18–34, 35–64 or 65–100 years) and their underlying health conditions [lung cancer, COPD, coronary heart disease (CHD) and stroke].

Every cohort member begins in the smoker state and at the end of the first year a percentage of the cohort will have quit smoking, with this proportion dependent on the efficacy of the cessation aid treatment they receive. No further quit attempts are modelled. It is, therefore, assumed that those who fail to quit will remain smokers until death.

There is a possibility that quitters may relapse and start smoking again in future years. This possibility decreases as time since cessation increases, with the risk of relapse being highest in the four model cycles following cessation (recent quitters). After four cycles without relapse, recent quitters become long-run quitters and the annual relapse rate is lower in the next five cycles, and lower still in subsequent cycles, with this underlying relapse rate continuing for the duration of the model. It is assumed that the probability of relapse at any stage is the same regardless of which treatment is used to aid cessation.

At the end of each year, the cohort is distributed into smokers, quitters and relapsed smokers (Figure 1). Within these broad smoking states, cohort members can have no current morbidity or one of the following smoking-related morbidities: lung cancer, COPD, CHD, stroke or an asthma exacerbation. These health states correspond to the smoking-related diseases that cause the greatest morbidity, mortality and cost. It is assumed that a person can be in one of these health states at a time only. When a person dies, they are removed from the model. The probability of moving to a new health state at the end of each cycle depends on current health state, smoking status, age and sex.

FIGURE 1.

Transitions between smoking states. Note that death can occur from any state.

It is assumed that a restricted hierarchy exists in which subjects can enter the CHD or stroke health state and subsequently transit to the COPD or lung cancer state. However, because of the irreversible nature of COPD and lung cancer, once subjects enter these health states, they stay there until they transition to death. An asthma exacerbation or exacerbations can occur from the no current morbidity health state only and are assumed to resolve within 1 year.

The original BENESCO model did not consider the AEs of treatment, but we have incorporated these as a probability of experiencing depression or fatal/non-fatal self-harm in the first year of treatment. We included these aspects of MANEs because we were able to identify cohort data sources for these outcomes with which to estimate the baseline probability of event on NRT standard. Depression and non-fatal self-harm are represented by a one-off disutility and cost, whereas fatal self-harm results in death. These are applied in the first year only because it is assumed that depression or self-harm would lead to discontinuation of treatment. We did not include cardiovascular treatment-related AEs in our model. This is because cardiovascular events are already included in the model as a consequence of smoking. Any differences observed between treatment groups in the RCTs in terms of cardiovascular events are more likely to be a result of having successfully quit or not (and subsequent reduction in risk), which is already captured in the model, or a side effect of the treatment. It is not possible to distinguish between these two causes from the RCT evidence, and we, therefore, could not estimate treatment-related adverse cardiovascular events.

All other health states are associated with utility and cost values, as detailed later. Therefore, cohort members accumulate costs and health outcomes each cycle until death. Future costs and benefits were discounted at a rate of 3.5% per annum. 94

Model inputs

In this section, we describe the evidence sources used for each parameter in the model. Evidence sources were identified as follows. First, we looked for updates to the evidence sources used in the Sheffield model58 by searching for studies that cited these sources and carrying out targeted searches on PubMed and EMBASE. Where alternative or more recent evidence sources were available, we considered these and made a decision about which evidence sources to use based on sample size and relevance to a contemporary UK population.

When searching for data on prevalence, we concentrated on large routine data sources such as the Health Survey for England. For incidence and relative risks (RRs), we searched for prospective cohorts (if RCT evidence was not available/not possible). Where no preferable evidence sources could be identified, we used the same data as used in the Sheffield model.

The assumed characteristics of the initial cohort

The distribution of the cohort across sex and age categories at the start of the model was designed to reflect the distribution of smokers in the UK. The proportion of male and female adults, and the mortality risk in each of the three age categories was determined from general population data. 106,107 Smoking prevalence data108 were applied to these data to calculate the distribution across age and sex groups for a representative sample of 10,000 UK smokers (see Appendix 2, Table 18).

The prevalence of smoking-related diseases in the smoking cohort was estimated from various literature sources on the prevalence of each disease in the general UK population and risk ratios of these diseases in smokers (see Table 19). The most recent data source identified on the prevalence of COPD and asthma in the UK was an online report from the British Lung Foundation109 based on data from 12.6 million patients in The Health Improvement Network (THIN) database, a UK general practice database that contains anonymised longitudinal patient records from over 500 practices (about 6% of the population). It reports the number of people ever diagnosed with COPD and asthma per 100,000 people, by age group, in 2012. This is updated from the estimate used in the Sheffield model, which was taken from a 2000 paper by Soriano et al. ,110 who used the General Practice Research Database to calculate the prevalence of COPD in the UK from January 1990 to December 1997. The British Lung Foundation reports an increased prevalence of COPD compared with Soriano et al. (e.g. new estimate of 7% in females aged > 65 years as opposed to 2%). This may be because of a difference in the number of elderly people included in the studies, although the British Lung Foundation estimate was thought to be a more representative estimate of COPD in the current population of those aged ≥ 65 years. 109,110

The prevalence of lung cancer was taken from a paper by Maddams et al. ,111 who used data from cancer registries in the UK to provide prevalence estimates by sex and age for 2008. This was updated from a 2003 paper by Forman et al. ,112 who used UK cancer registries to provide estimates for 1992. The estimates were relatively similar (e.g. new estimate of 0.3% in females aged ≥ 65 years compared with 0.24%).

History of CHD prevalence was taken from the 2016 Health Survey for England,113 which is one in a series of annual surveys designed to measure health and health-related behaviours in adults and children living in private households in England. In 2016, interviews were completed with 8011 adults. This was updated from an estimate taken from the 2005 Office for National Statistics (ONS) General Household Survey and was, again, higher (12% in females aged ≥ 65 years compared with 5.9%).

The source for prevalence of stroke history was Bhatnagar et al. ,114 who obtained 2013 prevalence data from the Clinical Practice Research Datalink Global Initiative for Chronic Obstructive Lung Disease (GOLD) database, which collates records from a widely used general practice software system and covers approximately 8.8% of the UK population. This was updated from a 2004 report from Asthma UK and was, again, higher (11% in females aged ≥ 65 years compared with 5.3%).

Relative risks for the prevalence of each disease in smokers relative to never-smokers were taken from the Statistics on Smoking, England – 2017115 report for COPD, lung cancer, CHD and stroke (see Table 37), and from Cassino et al. 116 for asthma. These estimates were used to calculate the expected number of cases in the cohort of smokers using the formulae shown in Appendix 3. The data are reproduced in Appendix 2, Table 20.

Transition probabilities

The annual incidence of disease was estimated by age and sex categories for smokers, recent quitters and long-run quitters. These values relied on estimates used in the Sheffield model58 (which, in turn, used estimates from a previous manufacturer’s single technology assessment submission to NICE117) as no preferable evidence could be identified for COPD, CHD, stroke or asthma. For lung cancer, the 2016 ONS release (updating the 2005 release used in the Sheffield model) was identified,118 which reports directly age-standardised rates per 100,000 population of newly diagnosed cases of cancer in England. These estimates showed that the incidence of lung cancer did not greatly increase between 2003 and 2016 (see Table 21). For simplicity, we, therefore, assumed that all incidence estimates were the same as those reported in the Sheffield model.

Appendix 2, Tables 22–25 show the estimates of the annual incidences of diseases for the general population, smokers, recent quitters and long-run quitters, respectively. These were obtained using the same method as for prevalence (see Appendix 3), assuming that the RRs of incidence in smokers, short-run and recent quitters relative to never-smokers were the same as the RRs of prevalence (see Table 37). 115,116

In accordance with previous BENESCO models, the RRs in recent quitters relative to never-smokers were assumed to be equal to the RRs for current smokers at year 1 for each disease. The RRs for COPD, stroke and asthma exacerbations are reduced when the smoker has quit for at least 1 year. The RRs in long-term quitters compared with never-smokers are assumed to be equal to the RRs in never-smokers after the smoker has quit smoking for > 5 years. Lung cancer has been approached differently: lung cancer risk for long-term quitters is kept equal to the risk in recent quitters. Although there is evidence that quitting smoking does reduce the risk of developing lung cancer, the risk does not return to that of non-smokers. 119

Mortality

Annual mortality probability by condition, excluding asthma, was estimated using the British Heart Foundation’s published total numbers of deaths in the UK in 2016 in each age group,120 which are based on general population data. These numbers were used as the numerator, with the denominator as the number of prevalent cases in the UK calculated using the population and prevalence estimates for 2016 (see Tables 18 and 19).

It was assumed that no additional mortality was associated with asthma exacerbation. Mortality for chronic diseases, COPD and lung cancer is the probability of death from these diseases given the disease is present. Mortality from acute events, CHD and stroke is the probability of a fatal event that differs by smoking status, age and sex.

Appendix 2, Tables 26–29 show the disease-specific mortality estimates for the general population, smokers, recent quitters and long-run quitters. The same RRs for smokers, short-run and recent quitters relative to never-smokers that were used for prevalence and incidence of diseases were also used to generate absolute probabilities of mortality. The probability of smoking-related mortality is equivalent or lower for recent quitters compared with smokers, and for long-run quitters relative to recent quitters. The exception is lung cancer, for which the mortality risk is the same regardless of smoking status.

Relapse rates

Hawkins et al. 121 used British Household Panel Survey data to look at smokers who quit, but then relapsed. These data were used to calculate the annual relapse probability for short-run quitters (people for whom it had been < 5 years since they quit) and long-run quitters (people who had quit smoking for > 5 years but < 10 years). The annual relapse probability ≥ 10 years post cessation was based on a study by Krall et al. ,122 which followed 483 men for up to 35 years.

The probabilities of relapse that were used in the model are shown in Appendix 2, Table 30. Uncertainty around relapse rates is modelled as a beta distribution using event data from the original studies.

Costs

Costs included in the model related to health states and intervention costs. Owing to a lack of recent or relevant UK data, the mean costs of COPD and lung cancer estimated by the Irish Health Information and Quality Authority (HIQA) in its 2017 report on interventions for smoking cessation123 were used in the model. This report used Irish data on the total annual spending divided by the total number of people with a diagnosis of each disease. The total direct costs to the Irish health service of inpatient and day-case treatment were estimated from the Hospital Inpatient Enquiry database for 2015, which is based on 2014 prices. The annual primary care and medication costs of COPD were estimated using 2014 Primary Care Reimbursement Service data from Ireland on the total costs of adrenergic and other drugs for obstructive airway diseases. The primary care and medication costs of lung cancer were estimated from a report on European cardiovascular disease statistics published by the European Society of Cardiology in 2012. 124 These costs were converted from euros to Great British pounds and inflated to 2019 prices using HM Revenue & Customs monthly exchange rates for February 2019. 125

This resulted in a total annual cost of COPD of £1468, an increase from the £971 used in the Sheffield model based on a paper by Britton. 126 The annual cost of lung cancer (£5429) is lower than the estimate used in the Sheffield model (£6524), which was based on Flack et al. 127

The cost of CHD was estimated from the British Heart Foundation’s cardiovascular disease statistics reported in 2014. 128 These data are taken from analysis of commissioning expenditure in the UK (the programme budgeting data return). These estimates are based on the price paid for specific activities and services purchased from health-care providers for each region. The annual cost of CHD estimated (£1460) is higher than the £1163 used in the Sheffield model based on McMurray et al. 129

The source used for the cost of stroke was Xu et al. ,130 who developed an individual patient simulation model to estimate health and social care costs at 1 and 5 years after stroke. The results were estimated using data on all patients with stroke included in Sentinel Stroke National Audit Programme (the national stroke register of England, Wales and Northern Ireland) from April 2015 to March 2016 (n = 84,184). The annual cost of stroke estimated (£1460) is lower than the £5484 used in the Sheffield model based on Simpson et al. ,131 who calculated the cost of a dependent/independent state due to stroke using NHS reference costs for ‘non-transient stroke or cerebrovascular accident, nervous system infections of encephalopathy’ long-stay/short-stay non-elective inpatients.

Tan et al. 132 documented asthma costs over time for asthma patients who were enrolled in an asthma care programme in Singapore, using a 10-year longitudinal data set. The study population comprised different cohorts of 939 asthma patients entering the programme at different times during 2004–13. Ten-year average annual asthma costs were estimated as £341 per patient. The main drivers of costs were asthma medications and consultation fees. This is lower than the £1162 used in the Sheffield model based on Hoskins et al. ,133 which was a retrospective cohort analysis of a representative data set of 12,203 patients with asthma in the UK over a 1-year period. The estimate from Tan et al. was preferred as it was thought to be more reflective of mild asthma, which is what the majority of adults will have.

The cost associated with depression (£340) was taken from a paper by Hunter et al. 134 Here, a weighted average annual cost per UK patient to treat depression was calculated by multiplying the proportion of patients who access each type of treatment by the average annual cost of the treatment. The cost associated with self-harm was taken from a paper by Tsiachristas et al. ,135 who estimated hospital resource use and care costs for all patients presenting with self-harm to the John Radcliffe Hospital (Oxford, UK) between 1 April 2013 and 31 March 2014.

Uncertainty around cost estimates was incorporated into the probabilistic analysis. In the absence of data, the SDs for COPD and lung cancer were assumed to be 10% of the mean estimate, and the standard errors were calculated using this figure, along with the number of people on which the mean estimate was based. As it was not possible to identify the number of people on whom the depression and CHD cost estimates were based, the standard error in this case was assumed to be 10% of the mean. These data were assumed to follow a gamma distribution. 136 All costs have been inflated to 2019 prices using HM Revenue & Customs monthly exchange rates for February 2019. 125

Appendix 2, Table 31 details the source, summary estimates and distributions used for the health state costs employed in the model.

Intervention costs comprised the cost of the interventions alone. It was assumed that, although counselling and other health professional support are likely to occur, the cost of these is likely to be the same or very similar across interventions, thus not having an impact on the relative cost–utility. These costs were, therefore, excluded from the economic analysis.

Data from the BNF on dosage and pricing are used to calculate the costs of varenicline, bupropion and NRT. 137 For varenicline, the cost of treatment is the cost of a starter pack covering the first 2 weeks of tapered treatment (£27.30) plus the cost of 10 weeks at full dose (5 × £27.30), giving £163.80 in total. The cost of low-dose varenicline is assumed to be the same, as the BNF states the same price for both 1 mg and 0.5 mg (500 µg) tablets.

Bupropion was costed as 150 mg daily for 6 days and then 150 mg twice daily for 7–9 weeks at a cost of £83.52. 137 The cost of low-dose bupropion is assumed to be £62.54 based on a dose of one tablet per day for an average of 13 weeks.

Similarly, for NRT, standard treatment is assumed to be a high-strength patch daily for 6–8 weeks, followed by the medium-strength patch for 2 weeks and then the low-strength patch for the final 2 weeks, at a cost of £105.65. 137 The cost of NRT low is assumed to be £83.84, based on 4 weeks of 10-mg/16-hour patches and 4 weeks of 5-mg/16-hour patches. The cost of NRT high is estimated as £77.46, based on a 4-week supply of 21 mg NicoDerm CQ (GlaxoSmithKline plc, Brentford, UK) transdermal patches followed by 2 weeks at 14 mg and 2 weeks at 7 mg.

E-cigarettes are not medically licensed in the UK. 138 The HIQA report123 costed a 12-week supply of e-cigarettes (e-cigarette + 3.55 ml liquid per day, including a replacement atomiser in months 2 and 3) as €93.80, based on Liber et al. 139 This is equivalent to approximately £82. 125

The costs of all interventions including combinations of interventions are shown in Appendix 2, Table 32.

Utilities associated with health states

Baseline utility for smokers with no current comorbidity was taken from the general population utility profile estimated by Ara and Brazier140 using 2003 and 2006 Health Survey for England data (see Table 33). These data are a function of age and sex and are based on random samples of the population living in private households in England. A total of 26,679 participants were asked to complete the EuroQol-5 Dimensions (EQ-5D) questionnaire (a commonly used questionnaire to describe and value health), and preference-based health state utility values were estimated from the weights obtained using time trade-off valuations. Health state utility was determined by multiplying baseline utility by age by an estimate of the impact of the disease.

Disease-specific utility values for smoking-related diseases were estimated from the literature. For lung cancer utility, two sources were identified. Jang et al. 141 measured EQ-5D scores in 172 consecutive outpatients with non-small-cell lung cancer attending a major Canadian cancer centre outpatient clinic and estimated a mean utility of 0.76 (95% CI –0.7 to 0.78). A more recent paper by Bertranou et al. 142 derived a similar utility value for progressed non-small-cell lung cancer from EQ-5D patient-level data collected in two lung cancer treatment trials, AURA2 (n = 199) and IMPRESS (n = 265) (0.72, SD 0.029). The progressed disease utility was given by the mid-point of the two studies. The source used in our model is that estimated by Bertranou et al. 142 (0.72) owing to the larger sample size. This is higher than the estimate used in the Sheffield model (0.5), which was taken from Trippoli et al. ,143 who measured quality of life in 95 patients with non-small-cell lung cancer from 15 Italian hospitals.

For utility associated with COPD, the source was Pickard et al. ,144 who synthesised the literature on the validity and reliability of EQ-5D use in studies of asthma and COPD, and estimated EQ-5D utility scores associated with stage of disease. The authors found eight studies that recorded EQ-5D scores ranging from 0.52 (SD 0.16) to 0.84 (SD 0.15) for patients with COPD. Sufficient studies in COPD were available to calculate pooled mean utility scores according to GOLD stage, which categorises COPD severity in four stages, from very mild to very severe. The utilities estimated were 0.74 for stage I (95% CI 0.62 to 0.87), 0.74 for stage II (95% CI 0.66 to 0.83), 0.69 for stage III (95% CI 0.60 to 0.78) and 0.61 for stage IV (95% CI 0.44 to 0.77) (most severe). The utility used was that for stage II (moderate disease) as this should capture the mid-point of severities. This could have been estimated by calculating a weighted average based on patient numbers in each stage, but it was assumed that the utility for moderate disease would adequately reflect a mix of mild to severe. This is higher than the estimate used in the Sheffield model (0.63), which was based on Spencer et al. ,145 who derived utility values from 283 patients with COPD who took part in the 1996 Health Survey for England.

The source used for utility associated with CHD was Stevanović et al. 146 This estimate (0.76) was based on a multivariate meta-analysis of preference-based quality-of-life values from 40 studies representing over 30,575 patients with CHD. For this utility, the Sheffield model cited Hay and Sterling,147 who sourced their utilities from the Beaver Dam Health Outcomes Study (a longitudinal cohort study of health status and health-related quality of life in a random sample of 1356 US adults). The average CHD utility (0.77) was a weighted average of myocardial infarction and angina utilities and was similar to that found in Stevanović et al.

Utility associated with stroke was estimated from Haacke et al. ,148 who assessed health-related quality of life (HRQoL) in 77 patients who had experienced an ischaemic stroke, a transient ischaemic attack or a haemorrhagic stroke. The mean EQ-5D value was 0.73 (SD 0.32). This replaces the estimate used in the Sheffield model (0.62), which was taken from Tengs and Lin,149 who carried out a systematic search to identify 20 articles reporting 53 unique quality-of-life weights for stroke and pooled these using a hierarchical linear model. The estimate from Haacke et al. 148 was preferred as it was from a more recent study and was thought to more accurately reflect the specific disutility associated with stroke. 148

For utility associated with second stroke, an estimate (0.48) was sourced from Ara and Brazier,140 who looked at EQ-5D data collected in Health Survey for England from individuals who reported a history of more than one cardiovascular condition. For utility associated with second stroke, the Sheffield model cited Gage et al. ,150 who elicited preferences from 69 volunteers at the Veterans Affairs Palo Alto Health Care System and Stanford University who had atrial fibrillation. Twenty of the volunteers had previously had a stroke. This paper estimated a utility value of 0.12.

Lloyd et al. 151 reported the impact of asthma exacerbations on health-related quality of life and health utility in patients with moderate to severe asthma in the UK. Prospective data regarding health-related quality of life were collected from 112 patients at four asthma centres across the UK using the EQ-5D at two time points. The EQ-5D utility estimated was 0.57 (SD 0.27) for patients with an exacerbation that required oral steroids. For utility associated with asthma, the Sheffield model cited Szende et al. 152 In this study, 228 consecutive adult outpatients and inpatients at four sites in Hungary completed the EQ-5D questionnaire. Patients had to have been diagnosed and already treated for asthma, and were involved in the study at their outpatient visit or during their hospital stay. The utility value estimated for poorly controlled asthma is 0.52.

The utility associated with depression [0.58, standard error (SE) 0.015] was taken from a paper by Hunter et al. ,134 who calculated a score for depressed patients using a weighted average from four UK trials. 153–156 The utility associated with self-harm came from a paper by Byford et al. ,157 in which baseline EQ-5D was collected in 480 patients with a history of recurrent deliberate self-harm.

Intervention effectiveness

The absolute probabilities of cessation at 1 year for interventions were generated by combining the results of the NMA (see Chapter 5) on sustained abstinence with an estimate of response on NRT estimated from Taylor et al. 158 This was a prospective cohort study of electronic medical records from 654 general practices in England in the UK’s Clinical Practice Research Datalink, including 287,079 patients who were prescribed smoking cessation medications during the study period. Of these, 149,526 patients prescribed NRT were eligible for analysis. At 1 year, 21.2% (31,695/149,526) of those prescribed NRT had quit smoking.

The mean probability of 1-year sustained abstinence with all treatments, and 95% credible intervals (CrIs), are shown in Appendix 2, Table 34. The results of the NMA suggested that varenicline low plus NRT standard and varenicline standard plus NRT standard have the highest absolute probability of sustained abstinence, followed by e-cigarette low/varenicline plus bupropion standard/e-cigarette high. Note that the absolute probabilities are derived from the NMA estimates, which are correlated because they are jointly estimated from a single model.

The absolute probabilities of depression at 1 year for interventions were generated by combining the results of the NMA on MANE (see Chapter 6) with an estimate of depression on NRT standard estimated from Kotz et al. 57 This was a retrospective cohort study using data from patients included in the validated QResearch database (www.qresearch.org), which holds data from 753 NHS general practices across England. Patients who were prescribed smoking cessation medications during the study period were identified and followed for 6 months. Of these, 106,759 patients prescribed NRT were eligible for analysis and 8274 reported suffering from depression. This gave a probability of 7%. The mean probabilities of depression for all treatments and 95% CrIs are shown in Appendix 2, Table 35. As no data were available on the other interventions, assumptions had to be made about their relative level of harm. It was, therefore, assumed that NRT low and e-cigarette low have the same level of harm as NRT standard, e-cigarette high has the same level of harm as NRT high, bupropion low has the same level of harm as bupropion standard, and varenicline low plus NRT standard has the same level of harm as varenicline standard plus NRT standard.

The absolute probabilities of self-harm at 1 year for interventions were also generated by combining the results of the NMA on MANE with an estimate of self-harm on NRT estimated from Kotz et al. 57 A total of 540 of the patients in this study reported self-harm, giving a probability of 0.5%. The mean probability of self-harm for all treatments for which data were available is shown in Appendix 2, Table 36.

Cost-effectiveness analysis methods

We conduct a probabilistic analysis in which uncertainty in the model inputs is captured by simulating 5000 times from the assumed distributions described in the previous section, using Monte Carlo simulation performed in Microsoft Excel^® version 1908 (Microsoft Corporation, Redmond, WA, USA). The absolute probabilities of abstinence, depression and self-harm were estimated using Bayesian inference, computed using Markov chain Monte Carlo simulation in OpenBUGS (URL: www.openbugs.net). Simulated samples for the model were drawn from 60,000 Markov chain Monte Carlo samples from the posterior distributions, taken from OpenBUGS and read into Microsoft Excel. Care was taken to preserve correlations from the Markov chain Monte Carlo.

We report mean lifetime costs and quality-adjusted life-years (QALYs) for each treatment option. Incremental cost-effectiveness ratios (ICERs), interpreted as the additional expected cost per additional unit gain in QALY for one treatment compared with another, are computed by first ordering treatments by increasing expected cost and then removing treatments that are dominated or extendedly dominated (i.e. have a higher expected cost and lower expected utility than another intervention). ICERs are then calculated for each non-dominated treatment relative to the previous (lower expected cost) non-dominated treatment, where:

⁽¹⁾ ICER = additional expected cost / additional expected utility .

For each treatment we also computed net benefit for a given willingness to pay per additional QALY, λ (cost per QALY gained ratio), where net benefit is defined as:

⁽²⁾ net benefit = utility × λ – cost .

‘Net benefit’ represents the value of a treatment in monetary terms by scaling both QALYs and use of resources to costs. 159 Averaging the net benefit over the probabilistic simulation samples gives the expected net benefit. The intervention with the highest expected net benefit (the optimal intervention) at any willingness-to-pay threshold, λ, can be calculated. We present the expected net benefit for λ  = £20,000.

We also plot cost-effectiveness acceptability curves (CEACs), which present the uncertainty in the optimal treatment by plotting the probability that each treatment is the most cost-effective (has the highest net benefit) against the willingness to pay per QALY.

We also present uncertainty between these interventions using rank-o-grams that show the distribution of the probabilities that each treatment is optimal, second, third and so on for each of the 14 treatments, at a willingness-to-pay threshold of £20,000 per QALY. The x-axis reports each of the possible ranks, for which position 1 means that the intervention is optimal. The y-axis shows the probability that each treatment has been ranked at each of the possible positions and, therefore, fully encapsulates the uncertainty in the intervention rankings. The peaks in the rank-o-gram plots show the most likely rank of a given treatment. Flat lines indicate a high degree of uncertainty for the ranking of that treatment type. We also explore how uncertainty in the model inputs impacts on the treatment considered to be optimal using value-of-information methods. 160 This method is also useful in guiding research recommendations as it can estimate the value of a future trial. The expected value of perfect information (EVPI) measures the value (in terms of net benefit) of eliminating all uncertainty in model inputs. The expected value of partial perfect information (EVPPI) measures the value (in terms of net benefit) of eliminating uncertainty in some of the model inputs. This allows us to identify which model inputs are the key drivers of decision uncertainty. Therefore, it follows that it is these areas in which further research might be most beneficial. EVPI and EVPPI are computed per person for the threshold of willingness to pay per QALY of £20,000. Population-level EVPI and EVPPI are also calculated, given an estimated number of smokers attempting to quit in England of 274,021. 3 The lifetime of a treatment represents the time until it becomes obsolete or goes out of use, for example by being superseded by a new intervention. We assume a lifetime of T = 1 year and 5 years, respectively, discounted at 3.5%. The Sheffield Accelerated Value of Information web application161 was used to compute EVPPI for subsets of parameters. 162

We also a present one sensitivity analysis in which the impact of depression and self-harm in the model is removed, so the results are driven by abstinence from smoking alone, and another limiting the analysis to UK-licensed treatments.

Chapter 5 Clinical results: effectiveness

Included studies

Study selection

The results of our search strategy are summarised in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram in Figure 2. Our original searches identified 345 studies for inclusion and our update searches identified an additional 18 studies for inclusion, resulting in a total of 363 studies reported on one or more effectiveness outcomes that are described below. 19,33,69,70,163–511 For the purpose of our analyses, the EAGLES study33 was treated as two studies, where Anthenelli 2016a33 included the four study arms from the non-psychiatric cohort and Athenelli 2016b33 included the four arms from the psychiatric cohort. A list of records excluded at full-text screening (those that did not meet randomised or non-randomised inclusion criteria for effectiveness or safety analyses) and their reasons for exclusion are presented in Report Supplementary Material 1.

FIGURE 2.

The PRISMA flow diagram for effectiveness study records. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Study characteristics

The number of participants randomised across the 363 trials ranged from 15 to 7354, with a total of 201,045 participants. Trials were conducted across six continents, with 208 trials in the USA, 29 trials in the UK, and 27 multicountry trials. Trials were conducted in several settings, including medical centres and facilities, academic and research centres, universities, community centres, low-income or subsidised housing neighbourhoods, hospitals, pharmacies, clinics (e.g. smoking cessation, dental, urology, methadone, surgical), primary care (general, family and private practices), over the counter, dispensaries, schools, companies and workplaces, Navy ships and over the telephone, by mail or online.

Study duration ranged from 24 to 754 weeks, with the duration of drug treatment ranging from 2 to 104 weeks. One hundred and twenty-one trials were industry sponsored and 122 trials were publicly registered online. We included 24 trials in which smokers were unwilling or not necessarily motivated to quit and 15 trials of smokeless-tobacco users. Twenty-six trials recruited smokers with comorbidities as specified by the Charlson Comorbidity Index,90 16 trials recruited smokers with current or a history of psychiatric conditions and 17 trials recruited smokers with current or a history of drug- or alcohol-related conditions.

The mean age of trial participants ranged from 27.1 to 62 years and the percentage of female participants (in studies that did not exclusively recruit male or female participants) ranged from 0.3% to 81%. Study populations ranged between ethnicities (e.g. white/Caucasian, African American, Latino/Hispanic, Asian, Indigenous Maori), types of tobacco use (e.g. smokeless tobacco, spit tobacco, cigars, waterpipes) and heaviness of smoking. Studies included smokers who were hospital inpatients or outpatients (including smokers scheduled for surgery), smokers with human immunodeficiency virus (HIV), smokers under criminal justice supervision, smokers with substance misuse, smokers with psychiatric conditions, smokers who were health-care professionals, smokers who were active or former armed forces and their family members (e.g. veterans, Navy, National Guard), smokers with prior quit attempts or who had recently relapsed, smokers who were cancer patients or prone to cancer or cancer survivors, female smokers concerned about weight, smokers from low-income or subsidised housing neighbourhoods, smokers with tuberculosis and smokers with asthma. Study-level characteristics of included trials can be found in tables in Report Supplementary Material 2.

Results on clinical effectiveness

We performed NMA on four bioverified effectiveness outcomes: sustained (or continuous) abstinence, prolonged abstinence, any abstinence at 6 months, and 7-day PPA. We fitted a standard (full interaction) NMA model as well as fixed- and random-class NMA models for each outcome. Based on the model fit indices (see Appendix 5), we focused on fixed-class NMA models. A list of treatments delivered in the trials included in effectiveness analyses and their frequency is reported in Appendix 3, Table 38. In this chapter, we present results for each outcome based on a fixed-class NMA model, with additional results for other models provided in Appendix 5. The results are presented as median odds ratios (ORs) alongside 95% CrIs. A summary of results across outcomes is provided at the end of the effectiveness results in the form of a rank-o-gram.

Sustained abstinence

Our primary effectiveness outcome, sustained abstinence at a follow-up of at least 24 weeks, was reported in 171 studies with a total of 90,443 patients, of which 161 (86,884 patients) studies compared two or more of the treatment classes of interest. The network of treatments for this outcome is displayed in Figure 3, where thicker edges represent comparisons with a larger number of randomised patients. Similarly, interventions with a larger number of randomised patients have larger circles. Most interventions were compared with placebo in the primary studies, although arms with no drug treatment or with usual care were also used as comparators in some studies, and some direct comparisons between different drug types are also available. One study comparing varenicline standard plus NRT gum standard (114/245 patients quit) with varenicline low plus NRT gum standard (111/240 patients quit) was disconnected from the network at the treatment level (see Figure 37) but not at the class level (see Figure 3); hence, we excluded that study when comparing the different models (see Table 39) but were able to include it in the analyses discussed in this section (which report results at the class level).

FIGURE 3.

Network plot for sustained abstinence at class level. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Figure 4 displays the results for the fixed-class NMA model based on 161 studies with placebo as a comparator. There was evidence that smokers randomised to usual care were less likely to quit than those who received placebo (OR 0.49, 95% CrI 0.33 to 0.71), whereas smokers randomised to no drug treatment were more likely to quit than those who received placebo (OR 1.28, 95% CrI 1.01 to 1.83). Moreover, there was evidence that smokers receiving NRT standard (OR 2.01, 95% CrI 1.68 to 2.41) and NRT high (OR 2.32, 95% CrI 1.88 to 2.86) were more likely to quit than those randomised to placebo. Most interventions were more effective than placebo, including bupropion low (OR 1.75, 95% CrI 1.03 to 3.00), bupropion standard (OR 1.73, 95% CrI 1.43 to 2.10), varenicline low (OR 1.79, 95% CrI 1.07 to 2.97), varenicline standard (OR 2.83, 95% CrI 2.34 to 3.39), e-cigarette high (OR 3.22, 95% CrI 1.63 to 6.36), varenicline low plus NRT standard (OR 5.70, 95% CrI 1.57 to 21.12), varenicline standard plus NRT standard (OR 5.75, 95% CrI 2.27 to 14.88), varenicline standard plus NRT high (OR 2.34, 95% CrI 1.12 to 4.90) and varenicline standard plus bupropion standard (OR 3.25, 95% CrI 1.35 to 7.92). There was weak evidence for the effectiveness of e-cigarette low compared with placebo (OR 3.22, 95% CrI 0.97 to 12.55).

FIGURE 4.

Forest plot with results of the fixed-class NMA model for sustained abstinence. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Table 2 presents the class effect estimates with placebo as comparator obtained from the NMA (last column) alongside the estimates obtained from direct and indirect evidence. Direct evidence was available for most monotherapies, whereas comparisons of combinations of interventions with placebo largely relied on indirect evidence only. Most effect estimates are above 1, suggesting that the interventions helped smokers to reach sustained abstinence more frequently than placebo. Where there was enough information to back-calculate indirect evidence and compare it with direct evidence, the results show some potentially inconsistent results, with examples where direct evidence shows a less beneficial effect for the experimental drug than the indirect evidence (e.g. bupropion low vs. placebo) and also the opposite (e.g. varenicline standard plus bupropion standard vs. placebo).

TABLE 2 - Results for sustained abstinence: comparisons with placebo

	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
No drug treatment	0.70 (0.08 to 4.01)	1.30 (1.02 to 1.64)	1.28 (1.01 to 1.63)
Usual care	0.81 (0.38 to 1.72)	0.41 (0.27 to 0.63)	0.49 (0.33 to 0.71)
NRT not specified	1.86 (1.55 to 2.25)	–	1.86 (1.55 to 2.25)
NRT low	–	0.58 (0.10 to 2.36)	0.58 (0.10 to 2.36)
NRT standard	2.01 (1.68 to 2.41)	–	2.01 (1.68 to 2.41)
NRT high	2.32 (1.88 to 2.86)	–	2.32 (1.88 to 2.86)
Bupropion not specified	–	0.17 (0.01 to 1.27)	0.17 (0.01 to 1.27)
Bupropion low	0.96 (0.44 to 2.05)	3.04 (1.46 to 6.33)	1.75 (1.03 to 3.00)
Bupropion standard	1.73 (1.43 to 2.10)	–	1.73 (1.43 to 2.10)
Varenicline not specified	3.56 (1.22 to 10.7)	–	3.56 (1.22 to 10.7)
Varenicline low	1.79 (1.07 to 2.97)	–	1.79 (1.07 to 2.97)
Varenicline standard	2.83 (2.34 to 3.39)	–	2.83 (2.34 to 3.39)
E-cigarette low	3.22 (0.97 to 12.6)	–	3.22 (0.97 to 12.6)
E-cigarette high	2.46 (0.86 to 7.03)	3.89 (1.63 to 9.28)	3.22 (1.63 to 6.36)
Bupropion not specified plus NRT not specified	–	1.04 (0.22 to 4.10)	1.04 (0.22 to 4.10)
Bupropion standard plus NRT not specified	–	1.62 (0.73 to 3.56)	1.62 (0.73 to 3.56)
Bupropion standard plus NRT high	–	1.99 (0.70 to 5.47)	1.99 (0.70 to 5.47)
Varenicline low plus NRT standard	–	5.70 (1.57 to 21.1)	5.70 (1.57 to 21.1)
Varenicline standard plus NRT standard	–	5.75 (2.27 to 14.9)	5.75 (2.27 to 14.9)
Varenicline standard plus NRT high	–	2.34 (1.12 to 4.90)	2.34 (1.12 to 4.90)
Varenicline standard plus bupropion standard	3.42 (1.39 to 8.67)	1.88 (0.09 to 39.9)	3.25 (1.35 to 7.92)

There was no statistical evidence of inconsistency based on model fit statistics (see Appendix 5, Table 39). The pairwise comparisons between interventions for this outcome are presented in Table 3. Most of the effect estimates were informed by indirect evidence only, and the results were consistent when both direct and indirect evidence were available. There was evidence that smokers randomised to varenicline standard plus NRT standard were more likely to achieve sustained abstinence than those receiving NRT standard (OR 2.87, 95% CrI 1.11 to 7.49) or bupropion standard (OR 3.34, 95% CrI 1.28 to 8.65). The results also suggest higher odds of abstinence with varenicline standard compared with NRT standard (OR 1.40, 95% CrI 1.10 to 1.78) or bupropion standard (OR 1.63, 95% CrI 1.27 to 2.07). Furthermore, there was weak evidence that e-cigarette high might increase the odds of sustained abstinence compared with bupropion standard (OR 1.86, 95% CrI 0.92 to 3.73).

TABLE 3 - Results for sustained abstinence: pairwise comparisons of interventions

	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
Bupropion standard vs. NRT standard	0.70 (0.17 to 2.83)	0.87 (0.67 to 1.12)	0.86 (0.67 to 1.11)
Varenicline standard vs. NRT standard	–	1.40 (1.10 to 1.78)	1.40 (1.10 to 1.78)
E-cigarette low vs. NRT standard	–	1.60 (0.48 to 6.30)	1.60 (0.48 to 6.30)
E-cigarette high vs. NRT standard	–	1.60 (0.80 to 3.20)	1.60 (0.80 to 3.20)
Varenicline standard plus NRT standard vs. NRT standard	–	2.87 (1.11 to 7.49)	2.87 (1.11 to 7.49)
Varenicline standard plus bupropion standard vs. NRT standard	–	1.61 (0.66 to 3.98)	1.61 (0.66 to 3.98)
Varenicline standard vs. bupropion standard	–	1.63 (1.27 to 2.07)	1.63 (1.27 to 2.07)
E-cigarette low vs. bupropion standard	–	1.85 (0.55 to 7.29)	1.85 (0.55 to 7.29)
E-cigarette high vs. bupropion standard	–	1.86 (0.92 to 3.73)	1.86 (0.92 to 3.73)
Varenicline standard plus NRT standard vs. bupropion standard	–	3.34 (1.28 to 8.65)	3.34 (1.28 to 8.65)
Varenicline standard plus bupropion standard vs. bupropion standard	–	1.87 (0.76 to 4.59)	1.87 (0.76 to 4.59)
E-cigarette low vs. varenicline standard	–	1.14 (0.34 to 4.47)	1.14 (0.34 to 4.47)
E-cigarette high vs. varenicline standard	–	1.14 (0.57 to 2.30)	1.14 (0.57 to 2.30)
Varenicline standard plus NRT standard vs. varenicline standard	2.05 (0.82 to 5.17)	–	2.05 (0.82 to 5.17)
Varenicline standard plus bupropion standard vs. varenicline standard	–	1.15 (0.48 to 2.76)	1.15 (0.48 to 2.76)
E-cigarette high vs. e-cigarette low	–	1.00 (0.22 to 4.03)	1.00 (0.22 to 4.03)
Varenicline standard plus NRT standard vs. e-cigarette low	–	1.80 (0.34 to 8.39)	1.80 (0.34 to 8.39)
Varenicline standard plus bupropion standard vs. e-cigarette low	–	1.01 (0.20 to 4.41)	1.01 (0.20 to 4.41)
Varenicline standard plus NRT standard vs. e-cigarette high	–	1.79 (0.57 to 5.71)	1.79 (0.57 to 5.71)
Varenicline standard plus bupropion standard vs. e-cigarette high	–	1.00 (0.33 to 3.08)	1.00 (0.33 to 3.08)
Varenicline standard plus bupropion standard vs. varenicline standard plus NRT standard	–	0.56 (0.16 to 1.98)	0.56 (0.16 to 1.98)

Estimates of absolute probabilities of sustained abstinence for each intervention can be obtained by applying the relative effects in Table 3 to an assumed cessation rate on NRT standard (estimates shown in Appendix 2, Table 34).

With regard to effect modifiers, there was evidence of effect modification as a function of counselling, with interventions that included counselling being associated with a higher proportion of smokers achieving sustained abstinence (additional log-OR was 0.86, 95% CrI 0.45 to 1.27; see Figure 45). We also found evidence of effect modification as a function of dependence, with higher odds of sustained abstinence among participants with higher average dependence scores (additional log-OR 0.23, 95% CrI 0.02 to 0.43; see Figure 47). We found inconclusive evidence of effect modification according to industry sponsorship, type of placebo, treatment duration, comorbidities, willingness to quit, smokeless tobacco, smoking level or publication year (see Figures 42, 44, 48 and 53). A sensitivity analysis excluding studies at high risk of bias yielded the same findings reported in this section for active interventions, although with wider intervals for most effect estimates, and particularly for e-cigarettes and treatment combinations (see Appendix 5, Figure 40). However, the results from this analysis suggested no difference between usual care and placebo (OR 1.16, 95% CrI 0.64 to 2.12). We observed the same trends in a further sensitivity analysis where we excluded studies comparing pharmacological with non-pharmacological interventions (the estimate of the OR comparing usual care with placebo was 1.03, 95% CrI 0.57 to 1.86; see Figure 41). Within this sensitivity analysis, we found inconclusive evidence of effect modification when pharmacological interventions were given with counselling, with a trend towards a synergistic effect (more effective than would be expected based on the sum of the pharmacological and counselling effects alone) (additional log-OR of 0.16, 95% CrI –0.05 to 0.37; see Figure 46).

Threshold analysis

Varenicline standard plus NRT standard had the highest estimated odds of sustained abstinence and was the first-ranked treatment in our analyses. Figure 5 shows the results of the threshold analysis for sustained abstinence, focusing on a selection of the eight treatment classes considered most relevant (and examined in the rank-o-grams presented later in this chapter). Threshold analysis determines how much the evidence could change before the first-ranked treatment changes. Each row in Figure 5 corresponds to a single study estimate, and displays the estimate (log-OR) and 95% CI from that study, along with the invariant interval (shaded bar). Any changes to the study estimate that lie within the invariant interval will not affect the first-ranked treatment. Changes that pass the thresholds at either end of the invariant interval will result in a new first-ranked treatment, which are shown as numeric treatment codes at either side of the invariant interval.

FIGURE 5.

Threshold analysis results for sustained abstinence, sorted by size of threshold (smallest to largest). Only studies with thresholds of < 10 log-OR are shown, for brevity. Treatment codes are (1) placebo, (7) NRT standard, (11) bupropion standard, (14) varenicline standard, (17) e-cigarette low, (18) e-cigarette high, (26) varenicline standard plus NRT Standard and (28) varenicline plus bupropion standard. For a full list, see Appendix 6. Bold study labels and red shaded invariant intervals show where a 95% CI crosses the corresponding threshold, indicating sensitivity to the level of uncertainty in this estimate. AC, allocation concealment; BOA, blinding of outcome assessment; BPP, blinding of participants and personnel; IOD, incomplete outcome data; NT, no threshold; OB, other bias; RSG, random sequence generation; SR, selective reporting. ‘+’, low risk of bias; ‘?’, unclear risk of bias; ‘–’, high risk of bias. 19,33,69,172,173,192,198,202,207,239,252,294,306,351,392,454,473,476 This figure is reproduced with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure is reproduced with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Figure 5 also shows the risk-of-bias judgements (see Report Supplementary Material 3). The smallest threshold is 0.44 (on the log-odds scale) for the Cinciripini et al. 207 study estimate of varenicline standard plus bupropion standard versus placebo; if the log-OR of this estimate changed from 1.63 to 2.07 (= 1.63 + 0.44) or higher in favour of varenicline standard plus bupropion standard, then varenicline standard plus bupropion standard would become the first-ranked treatment. This study was rated as being at low risk of bias; however, the upper end of the 95% CI for the study estimate crosses this threshold, meaning that the first-place ranking is sensitive to the level of uncertainty in this study estimate. The second smallest threshold is –0.47 (on the log-odds scale) for the Koegelenberg et al. 351 estimate of varenicline standard plus NRT standard versus varenicline standard; if the log-OR of this estimate changes from 0.71 to 0.24 (= 0.71 – 0.47) or lower, in favour of varenicline standard, then e-cigarette low would become the first-ranked treatment. This study was rated as being at unclear risk of bias, and it may be judged whether or not any bias due to inadequate random sequence generation or allocation concealment would lead to such an overestimation of treatment effects. There is no threshold in the other direction for this study estimate, indicated by ‘NT’ in the invariant interval; no amount of change to this estimate in favour of varenicline standard plus NRT would change the first-ranked treatment. Only one other study (Caponnetto et al. ;202 e-cigarette low vs. placebo) has a threshold < 0.7 log-OR (equivalent to a factor of 2 on the OR scale); the threshold is 0.61 in the direction favouring e-cigarette low, at which point e-cigarette low would be the first-ranked treatment. The upper end of the 95% CI for the study estimate crosses this threshold, meaning that the first-place ranking is sensitive to the level of uncertainty in this study estimate. Only another two studies19,192 have thresholds < 3 log-OR (equivalent to a factor of 20 on the OR scale). Bullen et al. 192 is rated as being at low risk of bias, but Hajek et al. 19 is rated as being at high or unclear risk of bias for blinding. To change the first-ranked treatment (to e-cigarette high), the Hajek et al. 19 estimate of e-cigarette high versus NRT not specified would have to underestimate the true OR by a factor of 2.6. The remaining 212 study estimates have even larger thresholds, and it is unlikely that any potential biases could plausibly change these estimates by such an amount to affect the first-place ranking.

Overall, the first-place ranking of varenicline standard plus NRT standard appears relatively robust. However, there is some sensitivity to the level of uncertainty and potential biases in the evidence, which could lead to varenicline plus bupropion standard, e-cigarette low or e-cigarette high being ranked first for sustained abstinence.

Prolonged abstinence

Prolonged abstinence was also restricted to measurements with a follow-up of at least 24 weeks. It was reported in 19 studies (4434 patients), with 17 studies (3512 patients) including at least one relevant comparison. Appendix 5, Figure 54 presents the structure of this network, sparser than the previous one but still connected both at (a) the treatment and (b) the class level. Placebo was, again, the main comparator across studies, although some direct comparisons between different drug types are also available. We excluded one study comparing NRT gum standard (8/79 patients quit) with no drug treatment (2/82 patients quit), which was disconnected from the main network both at the treatment and at the class levels, and one study comparing bupropion low (1/9 patients quit) with placebo (0/9 patients quit) because of small numbers that caused convergence problems in the models.

Therefore, the NMA for this outcome was based on 15 studies. Results with placebo as a comparator are presented in Appendix 5, Figure 55. There was evidence that smokers treated with bupropion standard (OR 2.34, 95% CrI 1.46 to 3.86), varenicline standard (OR 3.63, 95% CrI 2.23 to 6.36) and varenicline standard plus bupropion standard (OR 4.76, 95% CrI 2.48 to 10.10) were more likely to achieve prolonged abstinence than those who received placebo.

Appendix 5, Table 40 gives the NMA results with placebo as comparator alongside effect estimates from direct and/or indirect evidence, where available. Most estimates are above 1, which suggests that smokers assigned to each of the drugs examined were more likely to achieve prolonged abstinence than those receiving placebo. As would be expected, CrIs around the NMA effect estimates are typically narrower than those obtained using either direct or indirect evidence in isolation.

There was no statistical evidence of inconsistency based on model fit statistics (see Appendix 5, Table 42 and Figures 55 and 56). Pairwise comparisons between active interventions, mostly obtained through indirect evidence, are displayed in Appendix 5, Table 41. There was inconclusive evidence that bupropion standard, varenicline standard, and varenicline standard plus bupropion standard differed from each other in the odds of achieving prolonged abstinence.

Any abstinence

Any abstinence was restricted to measurements with a follow-up of at least 22 weeks. A total of 216 studies (99,630 smokers) reported on it, with 196 (91,667 smokers) including at least one relevant comparison. The structure of the network at the treatment level is displayed in Appendix 5, Figure 58 and at the class level in Figure 6.

FIGURE 6.

Network plot for any abstinence at class level. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Results for the fixed-class random-effects NMA with placebo as a comparator are presented in Figure 7. Compared with placebo, there was evidence that smokers randomised to no drug treatment were more likely to achieve any abstinence (OR 1.48, 95% CrI 1.19 to 1.86), whereas smokers receiving usual care were less likely to do so (OR 0.66, 95% CrI 0.46 to 0.96). With regard to active interventions, smokers allocated to NRT not specified (OR 1.86, 95% CrI 1.57 to 2.20), NRT standard (OR 2.03, 95% CrI 1.72 to 2.44), NRT high (OR 2.46, 95% CrI 2.03 to 2.94), bupropion low (OR 2.89, 95% CrI 1.34 to 6.23), bupropion standard (OR 1.84, 95% CrI 1.57 to 2.16), varenicline not specified (OR 4.06, 95% CrI 1.04 to 11.90), varenicline standard (OR 2.69, 95% CrI 2.27 to 3.19), e-cigarette low (OR 3.29, 95% CrI 1.13 to 10.80), e-cigarette high (OR 2.77, 95% CrI 1.01 to 7.69), bupropion low plus NRT high (OR 5.75, 95% CrI 1.79 to 19.10), bupropion standard plus NRT not specified (OR 2.10, 95% CrI 1.22 to 3.60), bupropion standard plus NRT high (OR 2.56, 95% CrI 1.60 to 4.14), varenicline standard plus NRT standard (OR 5.53, 95% CrI 2.12 to 14.40), varenicline standard plus NRT high (OR 2.36, 95% CrI 1.12 to 4.90), and varenicline standard plus bupropion standard (OR 3.56, 95% CrI 1.84 to 6.89) had higher odds of any abstinence than those receiving placebo.

FIGURE 7.

Forest plot with results of the fixed-class NMA model for any abstinence. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Appendix 5, Table 43 presents the class effect estimates with placebo as comparator obtained from the NMA and direct and indirect evidence. Direct evidence was available for most monotherapies, whereas comparisons of combinations of interventions compared with placebo largely relied on indirect evidence only. Most effect estimates are above 1, suggesting that the interventions helped smokers to reach sustained abstinence more frequently than placebo.

There was no statistical evidence of inconsistency based on model fit statistics (see Appendix 5, Table 45 and Figures 59 and 60). Where there was enough information to back-calculate indirect evidence and compare it with direct evidence, the results were largely consistent, although there were instances when direct evidence showed a less beneficial effect for the experimental drug than the indirect evidence (e.g. e-cigarette low vs. placebo).

The pairwise comparisons between experimental interventions for this outcome are presented in Appendix 5, Table 44. Most effect estimates were informed by indirect evidence only, and the results were consistent when both direct and indirect evidence were available. There was evidence that smokers randomised to varenicline standard were more likely to achieve any abstinence than those allocated to NRT standard (OR 1.32, 95% CrI 1.05 to 1.65) and bupropion standard (OR 1.46, 95% CrI 1.18 to 1.81). Furthermore, varenicline standard plus NRT standard led to higher odds of abstinence than NRT standard alone (OR 2.70, 95% CrI 1.02 to 7.13), bupropion standard (OR 2.99, 95% CrI 1.13 to 7.88) and standard doses of bupropion and NRT combined (OR 3.83, 95% CrI 1.05 to 14.00). Last, there was weak evidence that the combination of varenicline standard plus bupropion standard was more effective than bupropion standard alone (OR 1.93, 95% CrI 0.98 to 3.79).

Seven-day point prevalence abstinence

Point prevalence abstinence at 1 week was reported in 139 studies (55,724 patients), with 122 studies (48,110 patients) including at least one relevant comparison. Appendix 5, Figure 61 presents the structure of this network at the treatment level and Figure 8 presents the structure of this network at the class level.

FIGURE 8.

Network plot for 7-day PPA at class level. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

The NMA for this outcome was based on 122 studies. Results with placebo as a comparator are presented in Figure 9. There was evidence that smokers randomised to NRT not specified (OR 1.75, 95% CrI 1.48 to 2.08), NRT standard (OR 1.58, 95% CrI 1.21 to 2.12) and NRT high (OR 1.99, 95% CrI 1.67 to 2.39) were more likely to remain abstinent for a full week than those receiving placebo. Similarly, smokers treated with bupropion standard (OR 1.67, 95% CrI 1.48 to 1.88), varenicline not specified (OR 2.56, 95% CrI 1.21 to 5.42), varenicline standard (OR 2.14, 95% CrI 1.86 to 2.46), bupropion low plus NRT high (OR 4.76, 95% CrI 1.82 to 12.70), bupropion standard plus NRT high (OR 2.16, 95% CrI 1.57 to 2.97), varenicline standard plus NRT standard (OR 4.01, 95% CrI 2.16 to 7.54) and varenicline standard plus bupropion standard (OR 2.29, 95% CrI 1.48 to 3.56) reached 7-day PPA more often than those taking placebo. There was weak evidence that varenicline low was more effective than placebo (OR 1.75, 95% CrI 0.97 to 3.13).

FIGURE 9.

Forest plot with results of the fixed-class NMA model for PPA. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Appendix 5, Table 46 presents the NMA results with placebo as comparator alongside effect estimates from direct and/or indirect evidence, where available. Most estimates are above 1, which suggests that smokers assigned to each of the drugs examined were more likely to remain abstinent for a full week than those receiving placebo. Nonetheless, intervals around effect estimates obtained from direct and indirect evidence tend to be wider than those obtained when integrating both in the NMA, which reflects the gain in precision when using the latter approach. A comparison between direct and indirect evidence reveals largely consistent results, although examples can be found where direct evidence suggests a less beneficial effect of the experimental intervention (e.g. varenicline low vs. placebo) and also the opposite (NRT high vs. placebo).

There was no statistical evidence of inconsistency based on model fit statistics (see Appendix 5, Table 48 and Figures 62 and 63). Pairwise comparisons between active interventions, mostly obtained through indirect evidence, are displayed in Appendix 5, Table 47. Smokers allocated to varenicline standard achieved the target more often than those treated with NRT standard (OR 1.35, 95% CrI 0.99 to 1.82) or bupropion standard (OR 1.28, 95% CrI 1.08 to 1.53). Furthermore, there was strong evidence that the combination of varenicline standard plus NRT standard led to higher odds of abstinence than NRT standard alone (OR 2.54, 95% CrI 1.28 to 4.98), bupropion standard (OR 2.42, 95% CrI 1.28 to 4.57) and varenicline standard alone (OR 1.88, 95% CrI 1.02 to 3.46).

Ranking of interventions

Table 4 presents ranks for a selection of classes according to the primary effectiveness outcome, namely sustained abstinence. Varenicline standard plus NRT standard yielded the highest probability of being the most effective intervention (0.61, mean rank 1.67), followed by e-cigarette low (0.19, mean rank 3.61), varenicline standard plus bupropion standard (0.12, mean rank 3.42) and e-cigarette high (0.08, mean rank 3.32). Conversely, there was strong evidence that placebo had the lowest rank among the eight shortlisted interventions, with a mean rank of 7.97.

TABLE 4 - Mean ranking of interventions for sustained abstinence

Intervention	Pr(best)	Mean rank
Placebo	0	7.97
NRT standard	0	5.64
Bupropion standard	0	6.57
Varenicline standard	0	3.80
E-cigarette low	0.19	3.61
E-cigarette high	0.08	3.32
Varenicline standard plus NRT standard	0.61	1.67
Varenicline standard plus bupropion standard	0.12	3.42

Figure 10 is a rank-o-gram displaying the ranking of the same interventions across the four effectiveness outcomes examined in our NMA models. Varenicline standard plus NRT standard showed a high probability to be ranked best or second-best intervention for all of them (note that there was no information for the effect of this drug combination on prolonged abstinence). Furthermore, varenicline standard plus bupropion standard yielded the highest probability to be ranked as the best intervention for prolonged abstinence, although there was higher uncertainty about its ranking for the other outcomes. Moreover, varenicline standard showed highest probabilities of being ranked second to fourth best for the different outcomes, whereas e-cigarettes presented a more uncertain ranking profile. Last, placebo was ranked as the least effective intervention for all outcomes.

FIGURE 10.

Rank-o-gram of interventions across effectiveness outcomes. Rank of (a) placebo; (b) NRT standard; (c) bupropion standard; (d) varenicline standard; (e) e-cigarette low; (f) e-cigarette high; (g) bupropion standard plus NRT standard; (h) varenicline standard plus NRT standard; and (i) varenicline standard plus bupropion standard. Std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Chapter 6 Clinical results: safety

Included studies

Randomised evidence

Study selection

The results of our search strategy are summarised in Figure 11. Our original searches identified 335 studies for inclusion and our update searches identified an additional 20 studies for inclusion, resulting in a total of 355 studies19,33,40,69,70,164–166,169–171,173–180,184–186,190,192,193,196–198,200–203,205–208,212,216–218,220,221,223–226,228–231,233–252,255,257–259,261–263,265–268,271–275,277–279,281–283,286–288,295–297,300–303,307–311,313,315,318–331,336–340,343–345,347,349–352,354,356,357,359,361–366,371,373–378,380,381,385–387,390,391,393,395–397,399,401,403,404,406,408,410,411,413–416,418–422,424–427,429–436,438–440,442–450,453–458,460,463–476,478–482,484,487,488,490–495,497–506,509,511–604 that reported on one or more safety outcomes; these are described in the following sections. For the purpose of our analyses, the EAGLES study33 was treated as two studies, where Anthenelli 2016a33 included the four study arms from the non-psychiatric cohort and Anthenelli 2016b33 included the four arms from the psychiatric cohort. A list of records excluded at full-text screening (that did not meet randomised or non-randomised inclusion criteria for effectiveness or safety analyses) and the reasons for their exclusion are presented in Report Supplementary Material 1.

FIGURE 11.

The PRISMA flow diagram for randomised safety study records. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Study characteristics

The number of participants randomised across the 355 trials ranged from 5 to 5887, with a total of 159,101 participants. Trials were conducted across six continents, with 211 trials in the USA, 34 trials in the UK, and 31 multicountry trials. Trials were conducted in several settings, including medical centres and facilities, academic and research centres, universities, community centres, subsidised housing neighbourhoods, hospitals, pharmacies, clinics (e.g. smoking cessation, dental, substance misuse, HIV), primary care (general, family and private practices), over-the-counter, companies and workplaces, over the telephone and by mail.

Trial duration ranged from 0.14 (1 day/single session) to 754 weeks and duration of drug treatment ranged from 0.07 (half a day) to 104 weeks. One hundred and forty trials were industry sponsored and 154 trials were publicly registered online. We included 48 trials in which smokers were unwilling or not necessarily motivated to quit and 13 trials of smokeless-tobacco users. Twenty-three trials recruited smokers with comorbidities as specified by the Charlson Comorbidity Index,90 29 trials recruited smokers with current or a history of psychiatric conditions and 25 trials recruited smokers with current or a history of drug- or alcohol-related conditions.

The mean age of trial participants ranged from 28.4 to 62.8 years and the percentage of female participants (in studies that did not exclusively recruit male or female participants) ranged from 0.3% to 79%. Study populations ranged between ethnicities (e.g. white/Caucasian, African American, Asian, Indigenous Maori), types of tobacco use (e.g. smokeless tobacco, spit tobacco, cigars, waterpipes) and heaviness of smoking. Studies included smokers who were hospital inpatients or outpatients (including smokers scheduled for surgery), smokers with HIV, smokers with substance misuse, smokers with psychiatric conditions, smokers who were health-care professionals, smokers who were active or former armed forces and their family members (e.g. veterans, National Guard), smokers with previous quit attempts or who had recently relapsed, smokers who were cancer patients or survivors, female smokers concerned about weight, smokers from low-income or subsidised housing neighbourhoods, smokers with tuberculosis and smokers with asthma. Study-level characteristics can be found in tables in Report Supplementary Material 4.

Non-randomised evidence

Study selection

The results of our search strategy are summarised in Figure 12. Our original searches identified 48 studies for inclusion and our update searches identified an additional five studies for inclusion, resulting in a total of 53 studies53–55,57,605–653 that reported on one or more safety outcomes; these are described in the following sections. A list of records excluded at full-text screening (i.e. they did not meet randomised or non-randomised inclusion criteria for effectiveness or safety analyses) and the reasons for their exclusion are presented in Report Supplementary Material 1.

FIGURE 12.

The PRISMA flow diagram for non-randomised safety study records.

Study characteristics

The number of participants randomised across the 53 studies ranged from 32 to 7,917,436, with a total of 8,783,403 participants. Study designs included case–control, population cohort, retrospective cohort, prospective cohort and quasi-randomised. Studies were conducted across five continents, with 19 studies in the USA, seven studies in the UK, and no multicountry studies. Studies were conducted in several settings, including hospitals, primary care (e.g. GP practices), clinics (e.g. community, smoking cessation, tobacco dependence, surgical preoperative), academic, drug monitoring and medical centres. Observational studies used a range of databases, including the Clinical Practice Research Datalink (CPRD) (formerly the General Practice Research Database), New York City Fire Department, Bureau of Medical Services, Medicaid, Military Health System Data Repository, nationwide registries (National Prescription Registry, National Patient Registry), and were conducted over the telephone and online.

Study duration ranged from 4 to 208 weeks and the duration of drug treatment ranged from 1.26 to 208 weeks. Three studies were industry sponsored and three studies were publicly registered online. We included two studies in which smokers were not necessarily motivated to quit and no studies of smokeless-tobacco users. Five studies recruited smokers with comorbidities as specified by the Charlson Comorbidity Index,90 five studies recruited smokers with current or a history of psychiatric conditions and two studies recruited smokers with current or a history of drug- or alcohol-related conditions.

The mean age of study participants ranged from 37.9 to 58.3 years and the percentage of female participants (in studies that did not exclusively recruit male or female participants) ranged from 1% to 61.6%. Studies included smokers who were hospital inpatients or outpatients (including smokers scheduled for surgery), smokers with HIV, smokers with substance misuse, smokers with psychiatric conditions, smokers who were veterans, New York City Fire Department employees and their household family members who smoked, smokers with previous quit attempts, smokers who were critically ill and smokers who were Medicare patients. Study-level characteristics can be found in tables in Report Supplementary Material 6.

Results on safety

We performed NMA on three safety outcomes: SAEs, MACEs and MANEs. We fitted a standard (full interaction) NMA model as well as fixed- and random-class NMA models for each outcome. Based on the model fit indices (see Appendix 7), we focused on fixed-class NMA models. Appendix 7, Tables 49 and 50 provide a list of the treatments delivered in the randomised trials and non-randomised studies included in safety analyses and their frequency, respectively. In this chapter we present results for each outcome based on a fixed-class NMA model; for additional results using other models, see Appendix 7. Results are presented as median ORs alongside 95% CrIs. A summary of results across outcomes is provided at the end of this chapter in the form of a rank-o-gram.

Serious adverse events

Randomised evidence only

Our primary safety outcome, SAEs, was reported in 111 studies with a total of 63,927 patients, of which 101 studies (58,318 patients) compared two or more of the treatment classes of interest. We excluded one study from all analyses [varenicline not specified (3/160 patients with event) vs. placebo (0/160 patients with event)] because of small event numbers causing convergence problems. Furthermore, two studies (bupropion standard plus NRT inhalator vs. usual care, and varenicline standard plus NRT gum standard vs. varenicline low plus NRT gum standard) were disconnected at the treatment level (see Figure 64), but connected to the main network at the class level (Figure 13). We excluded both studies when comparing the different models (see Table 51), but we were able to include them in the analyses discussed in this section (which report results at the class level).

FIGURE 13.

Network plot for SAEs at class level. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Figure 14 displays results for the fixed-class NMA model based on 100 studies with placebo as a comparator. There was evidence that bupropion standard (OR 1.27, 95% CrI 1.04 to 1.58) increased the odds of SAEs compared with placebo.

FIGURE 14.

Forest plot with results of the fixed-class NMA model for SAEs. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Table 5 presents the class effect estimates with placebo as comparator obtained from the NMA (final column) alongside the estimates obtained from direct and indirect evidence. Direct evidence was available for most monotherapies, whereas comparisons of most combinations of interventions with placebo were obtained largely through indirect evidence only. Evidence for some of the main interventions (e.g. bupropion standard and varenicline standard) was informed by large trials that compared these drugs against placebo, so that indirect evidence did not add anything to the NMA results. When both direct and indirect evidence was available, results were mostly consistent, although there were some instances in which direct evidence suggested a larger increase in the odds of a SAE for the experimental drug (e.g. e-cigarette high vs. placebo).

TABLE 5 - Results for SAEs: comparisons with placebo

Comparison	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
No drug treatment	–	1.11 (0.56 to 2.29)	1.11 (0.56 to 2.29)
Usual care	–	0.28 (0.02 to 2.20)	0.28 (0.02 to 2.20)
NRT not specified	1.19 (0.86 to 1.62)	0.72 (0.31 to 1.68)	1.12 (0.79 to 1.49)
NRT standard	1.11 (0.74 to 1.68)	1.37 (0.38 to 4.96)	1.13 (0.76 to 1.67)
NRT high	1.11 (0.77 to 1.58)	1.40 (0.87 to 2.27)	1.21 (0.89 to 1.63)
Bupropion low	0.26 (0.03 to 1.52)	0.37 (0.01 to 9.36)	0.21 (0.01 to 1.57)
Bupropion standard	1.27 (1.04 to 1.58)	–	1.27 (1.04 to 1.58)
Varenicline low	1.12 (0.54 to 2.29)	1.62 (0.15 to 17.6)	1.07 (0.40 to 2.29)
Varenicline standard	1.09 (0.91 to 1.34)	–	1.09 (0.91 to 1.34)
E-cigarette low	–	7.24 (0.46 to 3262)	7.24 (0.46 to 3262)
E-cigarette high	1.99 (0.90 to 4.44)	1.44 (0.61 to 3.42)	1.72 (0.77 to 2.89)
Bupropion low plus NRT high	–	1.19 (0.24 to 7.46)	1.19 (0.24 to 7.46)
Bupropion standard plus NRT not specified	–	0.49 (0.03 to 3.35)	0.49 (0.03 to 3.35)
Bupropion standard plus NRT high	0.73 (0.05 to 4.18)	1.57 (0.47 to 5.28)	1.31 (0.49 to 3.67)
Varenicline low plus NRT standard	–	6.62 (0.09 to 4964)	6.62 (0.09 to 4964)
Varenicline standard plus NRT standard	–	1.38 (0.33 to 9.78)	1.38 (0.33 to 9.78)
Varenicline standard plus NRT high	–	1.11 (0.29 to 3.49)	1.11 (0.29 to 3.49)
Varenicline standard plus bupropion standard	2.51 (0.73 to 9.49)	1.48 (0.57 to 3.84)	1.79 (0.86 to 4.06)

There was no statistical evidence of inconsistency based on model fit statistics (see Appendix 7, Table 51 and Figures 66 and 67). The pairwise comparisons between active interventions for this outcome are presented in Table 6. Most effect estimates were informed by indirect evidence only. As a consequence of this, and also the small event rates reported, effects were imprecisely estimated and all intervals included the null.

TABLE 6 - Results for SAEs: pairwise comparisons of interventions

Comparison	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
Bupropion standard vs. NRT standard	–	1.12 (0.72 to 1.80)	1.12 (0.72 to 1.80)
Varenicline standard vs. NRT standard	–	0.98 (0.62 to 1.50)	0.98 (0.62 to 1.50)
E-cigarette low vs. NRT standard	–	6.48 (0.39 to 3087)	6.48 (0.39 to 3087)
E-cigarette high vs. NRT standard	–	1.54 (0.58 to 2.90)	1.54 (0.58 to 2.90)
Varenicline standard plus NRT standard vs. NRT standard	–	1.23 (0.28 to 8.39)	1.23 (0.28 to 8.39)
Varenicline standard plus bupropion standard vs. NRT standard	–	1.60 (0.69 to 3.82)	1.60 (0.69 to 3.82)
Varenicline standard vs. bupropion standard	–	0.86 (0.67 to 1.11)	0.86 (0.67 to 1.11)
E-cigarette low vs. bupropion standard	–	5.75 (0.37 to 2419)	5.75 (0.37 to 2419)
E-cigarette high vs. bupropion standard	–	1.34 (0.69 to 2.28)	1.34 (0.69 to 2.28)
Varenicline standard plus NRT standard vs. bupropion standard	–	1.10 (0.25 to 8.09)	1.10 (0.25 to 8.09)
Varenicline standard plus bupropion standard vs. bupropion standard	–	1.39 (0.67 to 3.20)	1.39 (0.67 to 3.20)
E-cigarette low vs. varenicline standard	–	6.36 (0.42 to 2879)	6.36 (0.42 to 2879)
E-cigarette high vs. varenicline standard	–	1.56 (0.74 to 2.67)	1.56 (0.74 to 2.67)
Varenicline standard plus NRT standard vs. varenicline standard	1.28 (0.30 to 7.77)	–	1.28 (0.30 to 7.77)
Varenicline standard plus bupropion standard vs. varenicline standard	1.24 (0.49 to 3.34)	2.55 (0.78 to 8.31)	1.64 (0.80 to 3.59)
E-cigarette high vs. e-cigarette low	–	0.23 (0.00 to 3.47)	0.23 (0.00 to 3.47)
Varenicline standard plus NRT standard vs. e-cigarette low	–	0.21 (0.00 to 5.40)	0.21 (0.00 to 5.40)
Varenicline standard plus bupropion standard vs. e-cigarette low	–	0.27 (0.00 to 4.28)	0.27 (0.00 to 4.28)
Varenicline standard plus NRT standard vs. e-cigarette high	–	0.83 (0.17 to 5.52)	0.83 (0.17 to 5.52)
Varenicline standard plus bupropion standard vs. e-cigarette high	–	1.07 (0.42 to 3.31)	1.07 (0.42 to 3.31)
Varenicline standard plus bupropion standard vs. varenicline standard plus NRT standard	–	1.33 (0.19 to 6.31)	1.33 (0.19 to 6.31)

With regard to effect modifiers, there was inconclusive evidence of effect modification according to industry sponsorship, type of placebo, treatment duration, counselling, dependence score, comorbid samples, studies in which patients were not required to be willing to quit, smokeless-tobacco users, analyses restricted to samples of heavy smokers, and publication year (see Figures 69–80); sensitivity analysis excluding studies at high risk of bias yielded the same findings reported in this section, although with wider intervals for most effect estimates (see Figure 68; full results provided in Appendix 7). A sensitivity analysis excluding studies that compared pharmacological interventions with psychological interventions (that were not given on all arms of the study) was very similar to that in the main analysis (see Appendix 7).

Threshold analysis

The results of the threshold analyses for the first- and last-ranked treatments for SAEs are shown in Figures 15 and 16. The first-ranked treatment is placebo and the last-ranked is e-cigarette low. Both figures also include the risk-of-bias judgements from Report Supplementary Material 5.

FIGURE 15.

Threshold analysis results for SAEs (first-ranked treatment), sorted by size of threshold (smallest to largest). Only studies with thresholds < 3 log-OR are shown, for brevity. Treatment codes are (1) placebo, (7) NRT standard, (11) bupropion standard, (14) varenicline standard, (17) e-cigarette low, (18) e-cigarette high, (26) varenicline standard plus NRT standard and (28) varenicline plus bupropion standard (for a full list, see Appendix 6). Bold study labels and red shaded invariant intervals show where a 95% CI crosses the corresponding threshold, indicating sensitivity to the level of uncertainty in this estimate. AC, allocation concealment; BOA, blinding of outcome assessment; BPP, blinding of participants and personnel; IOD, incomplete outcome data; OB, other bias; RSG, random sequence generation; SR, selective reporting. ‘+’, low risk of bias; ‘–’, high risk of bias; ‘?’, unclear risk of bias. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

FIGURE 16.

Threshold analysis results for SAEs (last-ranked treatment), sorted by size of threshold (smallest to largest). Only studies with thresholds < 3 log-OR are shown, for brevity. Treatment codes are (1) placebo, (7) NRT standard, (11) bupropion standard, (14) varenicline standard, (17) e-cigarette low, (18) e-cigarette high, (26) varenicline standard plus NRT standard and (28) varenicline plus bupropion standard (for a full list, see Appendix 6). Bold study labels and red shaded invariant intervals show where a 95% CI crosses the corresponding threshold, indicating sensitivity to the level of uncertainty in this estimate. AC, allocation concealment; BOA, blinding of outcome assessment; BPP, blinding of participants and personnel; IOD, incomplete outcome data; OB, other bias; NT, no threshold; RSG, random sequence generation; SR, selective reporting. ‘+’, low risk of bias; ‘–’, high risk of bias; ‘?’, unclear risk of bias. This figure is reproduced with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure is reproduced with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

The first-place ranking (of placebo) is very sensitive to the level of uncertainty in the evidence, as shown by the number of study estimates with 95% CIs that cross the corresponding threshold. At each of these thresholds, the new first-ranked treatment is NRT standard, varenicline standard plus NRT standard, e-cigarette high, e-cigarette low, or varenicline plus bupropion standard. Five studies351,386,415,444,468 have thresholds < 0.7 log-OR (equivalent to a factor of 2 on the OR scale), and, of these, only one468 is rated as being at low risk of bias.

The last-place ranking (of e-cigarette low) is sensitive to the level of uncertainty from only one study525 (e-cigarette low vs. no drug treatment). The first-place ranking is also sensitive to the level of uncertainty in this study estimate. If the estimate were to change by –0.80 log-OR from 1.32 to 0.52 in favour of e-cigarette low, then e-cigarette low would no longer be ranked last (replaced by varenicline plus bupropion standard), and if the estimate were to change only a little more to 0.24, then e-cigarette low would be ranked first for SAEs. Owing to the high level of uncertainty in this study estimate and the resulting wide CI, both of these are plausible owing to sampling error. Cravo et al. 525 has the smallest threshold for the last-place ranking (–0.80 log-OR, equivalent to a factor of 2.2 on the OR scale) and was judged to be at high risk of bias owing to inadequate blinding and other bias. The remaining thresholds for the other 122 study estimates are equivalent to a factor of ≥ 8 on the OR scale, which may be larger than any plausible biases.

Overall, the first- and last-place rankings for SAEs are not very robust: both are sensitive to the level of uncertainty in the data, and there may be plausible biases in studies at high or unclear risk of bias that could result in a change of first- or last-place ranking. The Cravo et al. 525 study is notably influential for both first- and last-place rankings, displays high levels of uncertainty and is rated as being at high risk of bias. The last-place ranking is likely to be robust to plausible biases in all other studies.

Incorporating non-randomised evidence

Only one non-randomised study632 reported one or more SAEs. This was a three-arm study comparing e-cigarette standard (14 events in 343 patients), dual smoking (10 events in 319 patients) and no drug treatment (14 events in 693 patients). The network plots at the treatment level and at the class level, combining randomised and non-randomised evidence for this outcome, are presented in Appendix 7, Figure 65 and Figure 17, respectively.

FIGURE 17.

Network plot for SAEs, incorporating non-randomised evidence at class level. Ns, not specified; std, standard.

The statistical integration was identical to that restricted to randomised evidence, except for the addition of the non-randomised study. The results for the fixed-class random-effects NMA, based on 102 studies and 59,673 smokers, are displayed in Figure 18. Comparison with Figure 14 suggests that, although only one study was added, the effect estimates changed substantially, now suggesting that varenicline standard (OR 0.63, 95% CrI 0.45 to 0.64) and e-cigarette low (OR 0.01, 95% CrI 0.00 to 0.15) might lead to lower odds of SAEs than placebo. The notable influence of the study added might be because of its contribution of 38 events to a network focused on a rare outcome. Furthermore, the non-randomised study, conducted by Manzoli et al. ,632 found that no drug treatment might be the safest of the three interventions compared. Given that no drug treatment is one of the main comparators in the network, this finding from a single study is likely to have an impact on the effect estimates for many interventions. In summary, this analysis illustrates the difficulties of drawing solid conclusions about the relative safety of different smoking interventions from the currently available evidence on SAEs.

FIGURE 18.

Forest plot displaying the NMA results for SAEs, combining randomised and non-randomised evidence. Ns, not specified; std, standard.

Major adverse cardiovascular events

Randomised evidence only

A total of 49 studies (38,329 patients) reported MACEs, with 44 studies (36,231 patients) including at least one relevant comparison. The structure of this network is presented at the treatment (see Figure 81) and at the class (Figure 19) level. We discarded three studies from all analyses owing to small numbers causing convergence problems, namely one study comparing varenicline not specified (1/160 patients with event) with placebo (0/160 patients with event), one study comparing bupropion standard plus NRT inhalator not specified (0/267 patients with event) with usual care (1/271 patients with event) and one study comparing NRT not specified (0/61 patients with event) with usual care (5/61 patients with event). Furthermore, one further study comparing NRT gum standard (25/3923 patients with event) with usual care (12/1964 patients with event) was disconnected from the network and, hence, was excluded from any further analyses.

FIGURE 19.

Network plot for major adverse cardiovascular events at class level. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Therefore, the NMA for this outcome was based on 41 studies. The results with placebo as a comparator are presented in Figure 20. Owing to the small numbers of events reported across studies, all effect estimates show very wide intervals and, hence, it was not possible to identify differences among any pair of interventions.

FIGURE 20.

Forest plot with results of the fixed-class NMA model for MACEs. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Table 7 presents the NMA results with placebo as comparator alongside effect estimates from direct and/or indirect evidence, where available. Although intervals were wide and always included the null, NMA estimates were generally more precise when both direct and indirect evidence were available.

TABLE 7 - Results for MACEs: comparisons with placebo

Comparison	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
No drug treatment	–	1.08 (0.24 to 5.26)	1.08 (0.24 to 5.26)
NRT not specified	0.82 (0.30 to 2.03)	0.61 (0.15 to 2.52)	0.75 (0.31 to 1.57)
NRT standard	1.28 (0.21 to 8.67)	0.57 (0.03 to 9.47)	1.01 (0.22 to 4.66)
NRT high	0.44 (0.11 to 1.75)	2.98 (0.71 to 12.5)	1.12 (0.42 to 3.03)
Bupropion low	0.15 (0.00 to 3.25)	–	0.15 (0.00 to 3.25)
Bupropion standard	1.31 (0.68 to 2.48)	0.95 (0.08 to 11.0)	1.28 (0.71 to 2.36)
Varenicline standard	0.76 (0.41 to 1.25)	–	0.76 (0.41 to 1.25)
E-cigarette high	2.61 (0.44 to 28.22)	26.8 (0.39 to 1860)	4.01 (0.79 to 29.7)
Bupropion standard plus NRT standard	0.33 (0.00 to 7.24)	–	0.33 (0.00 to 7.24)
Bupropion standard plus NRT high	–	0.08 (0.00 to 1.73)	0.08 (0.00 to 1.73)
Varenicline standard plus NRT high	–	0.47 (0.04 to 3.82)	0.47 (0.04 to 3.82)
Varenicline standard plus bupropion standard	0.08 (0.00 to 1.34)	–	0.08 (0.00 to 1.34)

There was no statistical evidence of inconsistency based on model fit statistics (see Appendix 7, Table 52 and Figures 83 and 84). The pairwise comparisons between active interventions presented in Table 8 were almost entirely obtained through indirect evidence only. All effect estimates had wide intervals including the null, and some effects were very imprecisely estimated. There was inconclusive evidence of effect modification based on comorbidities (see Figure 85) and smoking level (see Figure 86).

TABLE 8 - Results for MACEs: pairwise comparisons of interventions

Comparison	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
Bupropion standard vs. NRT standard	–	1.26 (0.26 to 6.15)	1.26 (0.26 to 6.15)
Varenicline standard vs. NRT standard	0.99 (0.03 to 49.3)	0.68 (0.12 to 3.84)	0.73 (0.15 to 3.39)
E-cigarette high vs. NRT standard	–	4.35 (0.42 to 43.1)	4.35 (0.42 to 43.1)
Bupropion standard plus NRT standard vs. NRT standard	–	0.33 (0.00 to 9.83)	0.33 (0.00 to 9.83)
Varenicline standard plus bupropion standard vs. NRT standard	–	0.07 (0.00 to 1.96)	0.07 (0.00 to 1.96)
Varenicline standard vs. bupropion standard	–	0.58 (0.27 to 1.19)	0.58 (0.27 to 1.19)
E-cigarette high vs. bupropion standard	–	3.17 (0.57 to 25.3)	3.17 (0.57 to 25.3)
Bupropion standard plus NRT standard vs. bupropion standard	–	0.26 (0.00 to 5.50)	0.26 (0.00 to 5.50)
Varenicline standard plus bupropion standard vs. bupropion standard	–	0.06 (0.00 to 1.14)	0.06 (0.00 to 1.14)
E-cigarette high vs. varenicline standard	–	5.51 (1.05 to 40.1)	5.51 (1.05 to 40.1)
Bupropion standard plus NRT standard vs. varenicline standard	–	0.44 (0.00 to 10.4)	0.44 (0.00 to 10.4)
Varenicline standard plus bupropion standard vs. varenicline standard	–	0.11 (0.00 to 1.88)	0.11 (0.00 to 1.88)
Bupropion standard plus NRT standard vs. e-cigarette high	–	0.07 (0.00 to 2.97)	0.07 (0.00 to 2.97)
Varenicline standard plus bupropion standard vs. e-cigarette high	–	0.02 (0.00 to 0.55)	0.02 (0.00 to 0.55)
Varenicline standard plus bupropion standard vs. bupropion standard plus NRT standard	–	0.20 (0.00 to 567)	0.20 (0.00 to 567)

Incorporating non-randomised evidence

A total of 10 non-randomised studies reported at least one major adverse cardiovascular event. The treatments examined in these studies, alongside the arm sizes and events per arm, are listed in Table 9. Furthermore, the network plots resulting from combining randomised and non-randomised evidence for this outcome are displayed in Appendix 7, Figure 82 (treatment level) and Figure 21 (class level). The disparity between sizes of the nodes for different treatments and classes stems from the very large numbers of smokers enrolled in some non-randomised studies (see Table 9).

TABLE 9 - Non-randomised studies reporting major cardiovascular AEs

Study (first author and year)	Treatment	Arm size	Number of events
Manzoli 2015632	Dual smoking	319	2
Manzoli 2015632	E-cigarette standard	343	4
Manzoli 2015632	No drug treatment	693	2
Davies 2015609	Varenicline not specified	41,742	531
Davies 2015609	NRT choice not specified	84,976	160
Ferketich 2013615	NRT combination high	110	1
Ferketich 2013615	Varenicline standard	118	0
Kotz 2017629	Bupropion not specified	350	155
Kotz 2017629	Varenicline not specified	3574	3
Kotz 2017629	NRT not specified	10,426	34
Kotz 201557	Bupropion not specified	6557	2148
Kotz 201557	Varenicline not specified	51,450	52
Kotz 201557	NRT not specified	106,759	594
Woolf 2012651	NRT choice not specified	184	8
Woolf 2012651	No drug treatment	479	23
Svanström 2012648	Varenicline not specified	17,926	16
Svanström 2012648	Bupropion not specified	17,926	21
Graham 2014618	Bupropion standard	14,133	216
Graham 2014618	Varenicline not specified	74,824	44
Panos 2010637	No drug treatment	113	3
Panos 2010637	NRT patch (24 hours) not specified	114	6
Deniz 2016611	Bupropion not specified	47	1
Deniz 2016611	Varenicline not specified	94	0

FIGURE 21.

Network plot for major adverse cardiovascular events (including randomised and non-randomised studies) at class level. Ns, not specified; std, standard.

The combination of both types of evidence enabled the inclusion of 54 studies in the NMA, as the incorporation of 10 non-randomised studies also made it possible to include some randomised trials that had been excluded from the main analyses owing to small numbers causing convergence problems. The results of this combined analysis, based on a fixed-class random-effects model, are presented in Figure 22 and suggest that, even with the additional studies, substantial uncertainty remains about the relative safety of the different treatment classes for this outcome.

FIGURE 22.

Forest plot with results for major adverse cardiovascular events (combining randomised and non-randomised evidence). Ns, not specified; std, standard.

Major adverse neuropsychiatric events

Randomised evidence only

Major adverse neuropsychiatric events were reported in 75 studies (42,088 patients), with 73 studies (41,483 patients) including at least one relevant comparison. The structure of this network is presented at the treatment (see Figure 87) and the class (Figure 23) levels, which show that placebo (main comparator), NRT not specified, bupropion standard, and varenicline standard were the best represented interventions. One study comparing bupropion standard plus NRT inhalator not specified (1/267 patients with event) with usual care (1/271 patients with event) was disconnected from the treatment network and, hence, we excluded it from the model comparisons (see Table 53), although we were able to include it in the analyses reported in this section. Moreover, we excluded two studies from all analyses owing to small numbers causing convergence problems. One of these excluded studies compared NRT nasal spray standard (1/506 patients with event) with placebo (0/255 patients with event), while the other one compared e-cigarette high (2/440 patients with event) with NRT choice not specified (0/448 patients with event).

FIGURE 23.

Network plot for major adverse neuropsychiatric events at class level. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

The NMA for this outcome was based on 71 studies. The results with placebo as a comparator are presented in Figure 24 and show wide intervals around the effect estimates owing to small numbers. There was weak evidence that patients randomised to no drug treatment (OR 0.27, 95% CrI 0.05 to 1.05) and strong evidence that those randomised to waitlist (OR 0.03, 95% CrI 0.00 to 0.44) were less likely to report MANEs than those allocated to placebo. Regarding active treatments, there was evidence that patients who received NRT not specified (OR 0.60, 95% CrI 0.36 to 0.89), bupropion standard (OR 0.67, 95% CrI 0.47 to 0.91), bupropion standard plus NRT high (OR 0.21, 95% CrI 0.03 to 0.92) were less likely to report MANEs than those treated with placebo. There was weak evidence for patients randomised to varenicline standard plus bupropion standard (OR 0.15, 95% CrI 0.01 to 1.12) compared with placebo.

FIGURE 24.

Forest plot with results of the fixed-class NMA model for major adverse neuropsychiatric events. Ns, not specified; std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Table 10 presents the NMA results with placebo as comparator alongside effect estimates from direct and/or indirect evidence where available. Most comparisons were informed by direct or indirect evidence only, and, where back-calculation of indirect evidence was possible, this led to very imprecise and uninformative estimates.

TABLE 10 - Results for major adverse neuropsychiatric events: comparisons with placebo

Comparison	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
No drug treatment	–	0.27 (0.05 to 1.05)	0.27 (0.05 to 1.05)
Waitlist	0.03 (0.00 to 0.42)	–	0.03 (0.00 to 0.42)
Usual care	–	0.48 (0.04 to 4.18)	0.48 (0.04 to 4.18)
NRT not specified	0.73 (0.49 to 1.09)	5.16 (1.43 to 18.7)	0.60 (0.38 to 0.89)
NRT standard	0.12 (0.00 to 1.93)	0.04 (0.00 to 5506)	0.10 (0.00 to 2.20)
NRT high	0.73 (0.38 to 1.38)	0.80 (0.14 to 4.70)	0.74 (0.40 to 1.35)
Bupropion standard	0.62 (0.44 to 0.82)	0.47 (0.25 to 0.87)	0.67 (0.47 to 0.91)
Varenicline not specified	1.60 (0.21 to 15.2)	–	1.60 (0.21 to 15.2)
Varenicline low	0.99 (0.06 to 11.1)	–	0.99 (0.06 to 11.1)
Varenicline standard	0.96 (0.76 to 1.21)	–	0.96 (0.76 to 1.21)
Bupropion standard plus NRT not specified	2.39 (0.17 to 22.7)	0.94 (0.31 to 2.83)	1.11 (0.39 to 2.97)
Bupropion standard plus NRT high	–	0.21 (0.03 to 0.92)	0.21 (0.03 to 0.92)
Varenicline standard plus NRT standard	–	1.72 (0.34 to 10.9)	1.72 (0.34 to 10.9)
Varenicline standard plus NRT high	–	0.64 (0.17 to 2.10)	0.64 (0.17 to 2.10)
Varenicline standard plus bupropion standard	0.06 (0.00 to 1.05)	0.23 (0.01 to 5.97)	0.15 (0.01 to 1.12)

There was no statistical evidence of inconsistency based on model fit statistics (see Appendix 7, Table 53 and Figures 89 and 90). Pairwise comparisons between active interventions are displayed in Table 11. Although most effect estimates were imprecisely estimated owing to small numbers, there was evidence of increased odds of MANEs for smokers randomised to varenicline standard compared with those allocated to bupropion standard (OR 1.43, 95% CrI 1.02 to 2.09). There was inconclusive evidence of effect modification based on psychiatric comorbidities (see Figure 91).

TABLE 11 - Results for major adverse neuropsychiatric events: pairwise comparisons of interventions

Comparison	Direct evidence, OR (95% CrI)	Indirect evidence, OR (95% CrI)	NMA, OR (95% CrI)
Bupropion standard vs. NRT standard	–	6.55 (0.29 to 3523)	6.55 (0.29 to 3523)
Varenicline standard vs. NRT standard	–	9.43 (0.43 to 4989)	9.43 (0.43 to 4989)
Varenicline standard plus NRT standard vs. NRT standard	–	18.52 (0.49 to 10,312)	18.52 (0.49 to 10,312)
Varenicline standard plus bupropion standard vs. NRT standard	–	1.45 (0.02 to 950)	1.45 (0.02 to 950)
Varenicline standard vs. bupropion standard	–	1.43 (1.02 to 2.09)	1.43 (1.02 to 2.09)
Varenicline standard plus NRT standard vs. bupropion standard	–	2.58 (0.49 to 16.6)	2.58 (0.49 to 16.6)
Varenicline standard plus bupropion standard vs. bupropion standard	–	0.22 (0.01 to 1.73)	0.22 (0.01 to 1.73)
Varenicline standard plus NRT standard vs. varenicline standard	1.80 (0.35 to 11.2)	–	1.80 (0.35 to 11.2)
Varenicline standard plus bupropion standard vs. varenicline standard	0.22 (0.00 to 5.43)	0.12 (0.00 to 3.20)	0.15 (0.01 to 1.16)
Varenicline standard plus bupropion standard vs. varenicline standard plus NRT standard	–	0.08 (0.00 to 1.19)	0.08 (0.00 to 1.19)

Incorporating non-randomised evidence

A total of 16 non-randomised studies reported one or more major adverse neuropsychiatric events. The treatments compared in those studies, the arm sizes and the event counts are presented in Table 12, whereas the network plots combining both types of evidence at the treatment level and class level are displayed in Appendix 7, Figure 88 and Figure 25, respectively.

TABLE 12 - Non-randomised studies reporting major adverse neuropsychiatric events

Study (first author and year)	Treatment	Arm size	Number of events
Cunningham 2016608	Varenicline not specified	11,774	6
Cunningham 2016608	NRT patch (24 hours) not specified	23,548	12
Dhelaria 2012612	Varenicline not specified	171	2
Dhelaria 2012612	NRT not specified	200	0
Ferketich 2013615	NRT combination high	110	0
Ferketich 2013615	Varenicline standard	118	1
Kotz 2017629	NRT not specified	10,426	722
Kotz 2017629	Bupropion not specified	350	18
Kotz 2017629	Varenicline not specified	3574	176
Jiménez-Ruiz 2017624	NRT combination high	215	0
Jiménez-Ruiz 2017624	Varenicline standard	134	1
Hodgkin 2013619	NRT choice not specified	236	0
Hodgkin 2013619	Bupropion not specified plus NRT choice not specified	162	3
Hodgkin 2013619	Varenicline not specified plus NRT choice not specified	16	2
Jiménez Ruiz 2012623	NRT choice not specified	233	5
Jiménez Ruiz 2012623	Bupropion standard plus NRT choice not specified	45	1
Jiménez Ruiz 2012623	Varenicline standard plus NRT choice not specified	190	6
Kaduri 2015625	Varenicline not specified	98	10
Kaduri 2015625	NRT choice not specified	98	8
Kotz 201557	NRT not specified	106,759	8814
Kotz 201557	Bupropion not specified	6557	377
Kotz 201557	Varenicline not specified	51,450	2514
Thomas 201353	NRT not specified	81,545	874
Thomas 201353	Bupropion not specified	6741	44
Thomas 201353	Varenicline not specified	31,260	276
Gunnell 200954	NRT choice not specified	63,265	1824
Gunnell 200954	Bupropion not specified	6422	162
Gunnell 200954	Varenicline not specified	10,973	297
Garcia-Portilla 2016616	NRT patch (24 hours) not specified	36	0
Garcia-Portilla 2016616	Varenicline standard	39	1
Koçak 2015627	Varenicline not specified	206	4
Koçak 2015627	Bupropion not specified	137	2
Koçak 2015627	NRT patch (24 hours) not specified	112	0
Stapleton 2008646	NRT choice not specified	204	2
Stapleton 2008646	Varenicline not specified	208	10
Pasternak 2013638	Varenicline not specified	59,790	4
Pasternak 2013638	Bupropion not specified	17,936	1
Shiltz 2012645	Bupropion standard plus NRT patch (24 hours) standard	121	18
Shiltz 2012645	Varenicline standard plus bupropion standard	204	12
Shiltz 2012645	Varenicline standard	164	19

FIGURE 25.

Network plot for major adverse neuropsychiatric events (combining randomised and non-randomised evidence) at class level. Ns, not specified; std, standard.

We fitted a fixed-class random-effects NMA model combining randomised and non-randomised evidence for this outcome, which led to the inclusion of 89 studies in total. The results displayed in Figure 26 suggest that bupropion standard (OR 0.68, 95% CrI 0.50 to 0.91), bupropion standard plus NRT high (OR 0.23, 95% CrI 0.04 to 0.93) and varenicline standard plus bupropion standard (OR 0.36, 95% CrI 0.15 to 0.89) are associated with lower odds of events than placebo. Some of the effect estimates were imprecisely estimated (e.g. e-cigarette high vs. placebo), and there was also one extreme result for varenicline not specified plus NRT not specified, stemming from a single small study in which 2 out of 16 smokers treated with this combination reported an event (see Table 12).

FIGURE 26.

Forest plot of NMA results for major adverse neuropsychiatric events (combining randomised and non-randomised evidence). Ns, not specified; std, standard.

Ranking of interventions

Table 13 presents ranks for a selection of classes according to the primary safety outcome, SAEs. Placebo yielded the largest probability of being ranked as the best intervention for reducing the odds of SAEs (0.33) and also showed the lowest mean rank (1.97). Varenicline standard plus NRT standard showed the next largest probability to be ranked best (0.31), but the mean rank for this intervention (4.41) suggests substantial uncertainty about its ranking. On the other hand, the highest mean ranks were obtained by e-cigarette low (6.97), varenicline standard plus bupropion standard (5.94), and e-cigarette high (5.73), suggesting that these interventions were least likely to be ranked highly for reducing the occurrence of SAEs.

TABLE 13 - Mean ranking of interventions for SAEs

Pr, probability.

Intervention	Pr(best)	Mean rank
Placebo	0.33	1.97
NRT standard	0.17	3.4
Bupropion standard	0	4.5
Varenicline standard	0.06	3.08
E-cigarette low	0.07	6.97
E-cigarette high	0.04	5.73
Varenicline standard plus NRT standard	0.31	4.41
Varenicline standard plus bupropion standard	0.03	5.94

Figure 27 is a rank-o-gram displaying the ranking of eight selected intervention classes across the three safety outcomes examined in our NMA models. Placebo was most likely to be ranked best or second best out of eight interventions for SAEs, with lower rankings for MACEs (4/7) and MANEs (5/7). NRT standard was also most likely to be ranked among the best two interventions to reduce the odds of SAEs, with uncertain rankings for the other adverse outcomes. However, these findings may not be robust because of the uncertainty associated with SAE estimates. The rankings for MACEs suggest that bupropion standard plus NRT standard, and varenicline standard plus bupropion standard might be the safest interventions, although we note that these rankings are based on rather imprecise effect estimates (see Figure 20). The latter statement also applies to MANEs (see Figure 24).

FIGURE 27.

Rank-o-gram of interventions across safety outcomes. Std, standard. This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

This figure has been adapted with permission from Thomas et al. 67 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The figure includes minor additions and formatting changes to the original figure.

Chapter 7 Results: cost-effectiveness

Table 14 shows the primary results of the probabilistic analysis. The expected (average) total discounted costs and QALYs for all interventions are reported, which represent the estimated average costs and benefits (allowing for length and quality of life) per smoker, having accounted for uncertainty in the inputs to the economic model. This analysis includes disutilities and costs related to depression and self-harm. Interventions are ordered by increasing expected total cost, with NRT low having the lowest expected total cost and varenicline standard plus NRT standard having the highest expected total cost. E-cigarette low has the highest expected QALYs, followed by varenicline standard plus bupropion standard, and varenicline standard plus NRT standard. NRT low has the lowest expected QALYs.

We prefer interventions with lower costs and higher QALYs. Any intervention that has a higher expected cost and lower expected QALYs than another intervention is said to be dominated. As can be seen in Table 14, all treatments apart from NRT low are dominated by e-cigarette low, which is more effective, in terms of increased utility, and less expensive than the other interventions. If the funder is not willing to pay £56 per QALY, then NRT low is estimated to be most cost-effective. If the funder is willing to pay ≥ £56 per QALY, then e-cigarette low is estimated to be most cost-effective.

If the payer is willing to pay up to £20,000 per QALY, e-cigarette low has the highest expected net benefit (£7085), followed by varenicline standard plus bupropion standard (£6756), and varenicline standard plus NRT standard (£6591).

We present the uncertainty surrounding the cost-effectiveness of the various interventions using a CEAC (Figure 28), which plots the probability that each intervention is the most cost-effective at a given willingness-to-pay threshold. Only interventions with a probability of being the optimal treatment of > 10% at any willingness-to-pay value are plotted.

FIGURE 28.

Cost-effectiveness acceptability curve. Probability that treatment is optimal plotted against different willingness-to-pay per unit increase in utility (ceiling ratio). Based on 5000 Monte Carlo simulations. Std, standard.

Figure 28 shows that, at any willingness-to-pay value, e-cigarette low has the highest probability of being cost-effective, followed by varenicline low plus NRT standard. At any threshold above £20,000, the probability of e-cigarette low being the most cost-effective intervention is never > 30%, indicating a high degree of uncertainty about the optimal intervention.

The rank-o-grams presented in Figure 29 further demonstrate the uncertainty in the results. The lines are relatively flat for most interventions, showing that there is no strong probability that they will be the most or least cost-effective at a willingness-to-pay threshold of £20,000 per QALY. The exception is NRT low, which shows a clear probability that it is among the least cost-effective interventions if the payer is willing to pay £20,000 per QALY. There is a similar trend for bupropion low, bupropion standard and varenicline low, which have higher probabilities of being among the worst interventions than being among the best. The reverse trend is seen for e-cigarette low, e-cigarette high, varenicline low plus NRT standard, varenicline standard plus NRT standard and varenicline plus bupropion standard.

FIGURE 29.

Rank-o-grams showing the probability that each intervention is ranked first, second, etc. based on net benefit at a willingness-to-pay threshold of £20,000 per QALY. Std, standard.

Sensitivity analysis with results based on abstinence alone

Table 16 shows the primary results of the sensitivity analysis when the impact of depression and self-harm is removed from the model. In this case, bupropion low has the lowest expected total cost. Varenicline standard plus NRT standard, again, has the highest expected total cost. Varenicline standard plus NRT standard has the highest expected QALYs, followed by varenicline low plus NRT standard. NRT low has the lowest expected QALYs.

TABLE 16 - Expected total costs, expected total utilities, ICERs and expected net benefit at a £20,000 willingness-to-pay threshold, based on abstinence alone

ENB, expected net benefit.

Treatment	Total costs (£)	Total QALYs	ICER (£)	ENB (£)
Bupropion low	10,219	11.135		3159
NRT low	10,231	10.977	Dominated	0
NRT high	10,238	11.198	Extendedly dominated	4400
Bupropion standard	10,240	11.130	Dominated	3041
E-cigarette high	10,248	11.295	Extendedly dominated	6335
E-cigarette low	10,250	11.332	159	7072
NRT standard	10,264	11.162	Dominated	3657
Bupropion standard plus NRT high	10,319	11.168	Dominated	3721
Varenicline low	10,320	11.138	Dominated	3120
Varenicline standard	10,327	11.254	Dominated	5434
Varenicline standard plus NRT high	10,402	11.214	Dominated	4556
Varenicline plus bupropion standard	10,415	11.314	Dominated	6558
Varenicline low plus NRT standard	10,446	11.476	Extendedly dominated	9759
Varenicline standard plus NRT standard	10,447	11.483	1302	9895

An intervention is said to be ‘extendedly dominated’ if a mix of two interventions can provide the same QALYs at a lower cost. As can be seen in Table 16, all treatments apart from NRT high, e-cigarette high, e-cigarette low, varenicline low plus NRT standard and varenicline standard plus NRT standard are dominated by bupropion low, which is more effective, in terms of increased utility, and less expensive than the other interventions.

The interventions on the efficiency frontier (i.e. those that are not dominated or extendedly dominated) are NRT low, e-cigarette low and varenicline standard plus NRT standard. If the payer is not willing to pay £159 per QALY, then bupropion low is estimated to be most cost-effective. If the payer is willing to pay between £159 and £1302 per QALY, then e-cigarette low is estimated to be most cost-effective, and if the willingness to pay per QALY is above £1302, then varenicline standard plus NRT standard is estimated to be most cost-effective.

At a willingness-to-pay threshold of £20,000, varenicline standard plus NRT standard has the highest expected net benefit (£9895), followed by varenicline low plus NRT standard (£9759).

We present the uncertainty surrounding the cost-effectiveness of the various interventions, using a CEAC (Figure 30). Only those interventions with a probability of being the optimal treatment of more than 10% at any willingness-to-pay value are plotted. Figure 30 shows that, at any willingness-to-pay value, varenicline low plus NRT standard has the highest probability of being cost-effective, followed by varenicline standard plus NRT standard. At any threshold above £20,000, the probability of any intervention being the most cost-effective intervention is never > 40%, again, indicating a degree of uncertainty in the optimal intervention.

FIGURE 30.

Cost-effectiveness acceptability curve. Probability that treatment is optimal plotted against different willingness-to-pay per unit increase in utility (ceiling ratio). Based on 5000 Monte Carlo simulations. Sensitivity analysis based on abstinence alone. Std, standard.

The rank-o-grams are presented in Figure 31.

FIGURE 31.

Rank-o-grams showing the probability that each intervention is ranked first, second, etc. based on net benefit at a willingness-to-pay threshold of £20,000 per QALY. Sensitivity analysis based on abstinence alone. Std, standard.

Sensitivity analysis with only UK-licensed interventions included

Table 17 shows the primary results of the sensitivity analysis including only interventions that are licensed in the UK (NRT low, standard and high, bupropion low and standard, and varenicline low and standard). In this case, NRT low has the lowest expected total cost and varenicline low has the highest expected total cost. Varenicline standard has the highest expected QALYs, followed by NRT standard. NRT low has the lowest expected QALYs.

TABLE 17 - Expected total costs, expected total utilities, ICERs and expected net benefit at a £20,000 willingness-to-pay threshold, based on licensed interventions only

ENB, expected net benefit.

Treatment	Total costs (£)	Total QALYs	ICER (£)	ENB (£)
NRT low	10,259	10.934		0
Bupropion low	10,283	11.038	Extendedly dominated	2056
NRT standard	10,292	11.119	32	3663
Bupropion standard	10,304	11.033	Dominated	1937
NRT high	10,309	11.092	Dominated	3092
Varenicline standard	10,413	11.127	15,665	3697
Varenicline low	10,440	10.959	Dominated	308

As can be seen in Table 17, all treatments apart from NRT low, bupropion low and NRT standard are dominated by varenicline standard, which is more effective, in terms of increased utility, and less expensive than the other interventions. Bupropion low is extendedly dominated by NRT standard.

The interventions on the efficiency frontier are NRT low, NRT standard and varenicline standard. If the payer is not willing to pay £32 per QALY, then NRT low is estimated to be most cost-effective. At a willingness to pay per QALY above £32, but below £15,665, NRT standard is estimated to be most cost-effective. At a willingness to pay per QALY above £15,665, varenicline standard is estimated to be most cost-effective.

At a willingness-to-pay threshold of £20,000, varenicline standard has the highest expected net benefit (£3697), followed by NRT standard (£3663).

We present the uncertainty surrounding the cost-effectiveness of the various interventions using a CEAC (Figure 32). Only those interventions with a probability of being the optimal treatment of more than 10% at any willingness-to-pay value are plotted. Figure 32 shows that, at any willingness-to-pay value above £5000, NRT standard has the highest probability of being cost-effective, followed by varenicline standard.

FIGURE 32.

Probability treatment is optimal plotted against different willingness-to-pay per unit increase in utility (ceiling ratio). Based on 5000 Monte Carlo simulations. Sensitivity analysis based on licensed interventions. Std, standard.

The rank-o-grams are presented in Figure 33. These show that, at a willingness-to-pay value of £20,000, NRT standard and varenicline standard have the highest probabilities of being the most cost-effective treatment. NRT low and varenicline low have very low probabilities of being the most cost-effective.

FIGURE 33.

Rank-o-grams showing the probability that each intervention is ranked first, second, etc. based on net benefit at a willingness-to-pay threshold of £20,000 per QALY. Sensitivity analysis based on licensed interventions only. Std, standard.

Chapter 8 Discussion and conclusions

Chapter 9 Patient and public involvement

A lay summary of this project was reviewed by participants of the UK Centre for Tobacco and Alcohol Studies (UKCTAS) smokers’ panel and was presented to members of the Elizabeth Blackwell Institute’s Public Advisory Group. Originally set up in 2008, the UKCTAS smokers’ panel consists of active smokers and recent quitters who meet two or three times per year in Nottingham. The panel meets regularly to discuss tobacco, tobacco policy, approaches to smoking cessation and new developments in tobacco harm reduction. Panel members also serve as lay advisers on research applications submitted from UKCTAS universities, which involves commenting on study information sheets, consent forms and data collection instruments (literature review protocols, data management plans and other key documents); commenting on press releases and communication plans; participating in bespoke meetings to develop or advise on new studies; and other forms of engagement as appropriate. The Elizabeth Blackwell Institute’s Public Advisory Group comprises key stakeholders in public engagement and health and social care as well as representatives of patient and public involvement groups linked to research projects at the University of Bristol. The Public Advisory Group works with the Elizabeth Blackwell Institute to ensure excellent engagement across the research life cycle. The group meets a few times per year, and researchers across the University of Bristol are invited to share their research with the group and receive feedback. During the course of the project, we interviewed vapers from the UKCTAS smokers’ panel for input on our outcomes and planned analyses. We also presented preliminary findings based on data from studies identified in our original searches to the Elizabeth Blackwell Institute’s Patient Advisory Panel for feedback and suggestions for further analyses.

Acknowledgements

We are grateful to Professor David Gunnell for help with preparing the original project proposal and grant submission, and to Sarah Dawson and Cath Borwick for help with designing and running search strategies.

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Appendix 1 MEDLINE search strategies

Appendix 2 Inputs into the economic model