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Numerous randomized, placebo-controlled clinical trials have demonstrated that nicotine replacement therapy [1, 2], bupropion  and varenicline  are efficacious in increasing the odds of smoking cessation, and clinical practice guidelines recommend the use of pharmacotherapy as a first-line agent for treating nicotine dependence [5, 6]. Despite the recommendations, the majority of smokers who attempt to quit do so without the aid of stop-smoking medications (SSMs) [7-9], although the use of SSMs has been increasing over time [10-13].
It is important to assess the ‘real-world’ effectiveness of SSMs in the contexts in which they are being used, because compliance with medication use instructions in the controlled trial setting is probably higher than it is in the population setting, and because subjects who are selected to participate in clinical trials may not be representative of the self-selected smokers who ultimately use the medications . The real-world effectiveness of varenicline and bupropion as quitting smoking treatments has not yet been assessed widely in population studies, and studies of the effectiveness of nicotine replacement therapies (NRT) have produced mixed results [15-26]. For example, Pierce & Gilpin reported that NRT is ineffective since becoming available over-the-counter (OTC) , Hyland et al. found nicotine patch quit rates to be lower after becoming available OTC , but Thorndike et al. found quit rates among those using NRT to be nearly identical during the period before and after the medication became available OTC . Studies evaluating the effectiveness of NRT without focusing on the impact of OTC availability have also produced mixed results [20-26]. For example, Shiffman et al. reported that use of NRT was associated with decreased rates of smoking cessation, and pointed to bias inherent in retrospective surveys to account for this finding . Similarly, Alberg et al. found that NRT users were less likely to quit smoking than were those who never used NRT . Recently, Alpert et al. concluded, surprisingly, that NRT is not effective for long-term smoking cessation because they found relapse rates between those who quit with and without NRT to be equivalent in a period of a year or more after use ceased , which does not relate to the question of medication effectiveness. Others have found positive effects [23-26]. West & Zhou, using data collected every 3 months, reported that cessation rates were two to three times higher among NRT users compared to nonusers . Similarly, a prospective evaluation of the New York State Smokers' Quitline program to give away free nicotine patches showed quit rates among those who received the patches to be nearly two times higher than rates observed prior to the implementation of the program [24, 25]. Additionally, Gilpin et al. found a cessation advantage among NRT users living in smoke-free homes, and suggested that medication may be more effective among those who are more motivated to quit .
Within the context of the widespread observation that population level quit rates have not increased over time despite increases in usage of stop-smoking medications [10, 11, 27, 28], some have taken the failure to consistently find positive effects of NRT as evidence that it is not effective in the real world [17, 29]. However, others have pointed to confounders inherent in population-based survey designs that might explain the lack of compelling real-world evidence for effectiveness [15, 16, 20, 30-36]. First, medication users in the general population are systematically different from non-users in important characteristics, such as being more heavily addicted to nicotine, which predisposes medication users to be unsuccessful in quitting [7, 20, 30-32]. Secondly, retrospective survey designs may be subject to biased recall of failed quit attempts [20, 33-36]. It has been shown that the likelihood of recalling a quit attempt decreases with increasing time since the quit attempt . In addition, Borland et al. found that, compared to those who attempted to quit with medication, those who attempted to quit without medication recalled their last unsuccessful quit attempts as starting more recently, with a significantly greater proportion of unaided attempts being reported in the previous month . Adjusted for nicotine dependence to equate groups on the likelihood of making a recent quit attempt, this association demonstrates that failed quit attempts occurring longer ago are more likely to be forgotten by those who did not use medication.
The presence of these confounders requires that population-based evaluations of SSM effectiveness control for systematic differences between self-selected medication users and non-users, as is carried out routinely in population studies, and be limited to respondents for whom systematic recall bias is minimal (i.e. those who recalled their last quit attempts as occurring recently relative to survey date), which has not yet been carried out methodically in population studies. The purpose of this study was to evaluate the real-world effectiveness of SSMs while accounting for previously considered confounders, as well as recall bias. We also describe the characteristics of medication users, such that the comparability of our sample to previous population-based samples can be considered.
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The odds of 1-month and 6-month continuous abstinence from smoking as a function of medication use are presented in Table 1, both overall (i.e. since the previous wave—around 1 year), and stratified by quit attempt recency (i.e. within 3, 2 and 1 month of interview). In the analyses using the full interwave interval, there was only a small and inconsistent positive effect for NRT, effectively replicating previous findings of no or smaller effects. However, among those who recalled their last quit attempts as occurring within 1 month of interview (i.e. the stratum that excluded the most recall bias), varenicline users were nearly six times more likely to be quit for 6 months (adjusted OR = 5.84, 95% CI = 2.12–16.12), bupropion users were nearly four times more likely to be quit for 6 months (adjusted OR = 3.94, (95% CI = 0.87–17.80) and nicotine patch users were four times more likely to be quit for 6 months (adjusted OR = 4.09, 95% CI = 1.72–9.74), compared to those who attempted to quit without medication. Indeed, as increasing amounts of recall bias were removed, the odds ratios for these medications increased to be higher than those found from meta-analyses of randomized controlled trials. However, there were only non-significant associations for oral NRT users, regardless of the recall time-frame.
Table 1. Odds of smoking cessation as a function of medication use, stratified by recalled recency of last quit attempt.
|Recency of quit attempt (QA)|| ||Type of medication|
|No medication (ref)||Any medication a ||Nicotine gum/other oral NRT||Nicotine patch||Bupropion||Varenicline|
|nIndiv ||nQA ||% quit||nIndiv ||nQA ||% quit||OR||(95% CI)||nIndiv ||nQA ||% quit||OR||(95% CI)||nIndiv ||nQA ||% quit||OR||(95% CI)||nIndiv ||nQA ||% quit||OR||(95% CI)||nIndiv ||nQA ||% quit||OR||(95% CI)|
|1-month abstinence|| || || || || || || || || || || || || || || || || || || || || || || || || || || || |
|QA since last wave b ||2956||3706||21||2201||2798||24||1.21** ||(1.07–1.36)||423||477||22||1.06||(0.83–1.34)||1260||1523||24||1.19* ||(1.02–1.38)||313||357||23||1.21||(0.93–1.57)||286||291||33||1.88*** ||(1.41–2.52)|
|QA within the last 3 months c ||652||720||16||525||560||22||1.47** ||(1.10–1.96)||89||91||15||0.96||(0.52–1.76)||236||247||21||1.26||(0.87–1.83)||41||41||29||2.08||(0.97–4.48)||125||127||30||2.61*** ||(1.64–4.14)|
|QA within the last 2 months c ||405||446||14||326||340||23||1.96** ||(1.33–2.89)||55||56||16||1.27||(0.59–2.77)||157||163||23||1.96** ||(1.22–3.15)||27||27||26||2.14||(0.76–6.04)||67||67||30||3.34*** ||(1.71–6.54)|
|QA within the last month c ||292||313||12||219||227||23||2.56*** ||(1.56–4.19)||39||40||18||1.84||(0.73–4.61)||98||101||25||2.53** ||(1.31–4.90)||20||20||25||3.35* ||(1.02–11.07)||47||47||27||3.76** ||(1.60–8.79)|
|6-month abstinence|| || || || || || || || || || || || || || || || || || || || || || || || || || || || |
|QA since last wave b ||2750||3473||14||2042||2609||16||1.17* ||(1.01–1.35)||393||444||14||1.02||(0.76–1.36)||1151||1405||15||1.15||(0.96–1.38)||289||332||14||1.09||(0.77–1.53)||276||281||26||1.76** ||(1.28–2.41)|
|QA within the last 3 months c ||624||690||8||503||538||12||1.57* ||(1.07–2.31)||86||88||7||0.90||(0.37–2.20)||226||237||11||1.37||(0.82–2.29)||41||41||15||2.06||(0.78–5.45)||117||119||17||2.73** ||(1.51–4.94)|
|QA within the last 2 months c ||393||434||6||316||330||13||2.47** ||(1.45–4.20)||53||54||6||0.89||(0.25–3.13)||151||157||13||2.65** ||(1.38–5.09)||27||27||15||3.42||(0.93–12.54)||65||65||18||4.48** ||(1.91–10.53)|
|QA within the last month c ||287||308||5||217||225||14||3.59*** ||(1.79–7.19)||39||40||8||1.42||(0.36–5.56)||98||101||16||4.09** ||(1.72–9.74)||20||20||15||3.94||(0.87–17.80)||47||47||19||5.84** ||(2.12–16.12)|
As shown in Table 2, those who attempted to quit without medication were generally more likely to be male, to be younger, to be minorities, to have lower incomes, to be less heavily addicted to nicotine and to have higher self-efficacy compared to those who attempted to quit with medication. Those who agreed that SSMs make it easier to quit were approximately two to three times more likely to use medication.
Table 2. Predictors of using medication when attempting to quit smoking.
|Predictors||Nicotine gum||Nicotine patch||Bupropion||Varenicline|
|n = 5447 (10% use overall)||n = 6432 (27% use overall)||n = 5394 (8% use overall)||n = 2683 (13% use overall)|
|n||% used||OR||n||% used||OR||n||% used||OR||n||% used||OR|
|Country|| || || || || || || || || || || || |
|Canada||1415||10||0.68** ||1660||26||0.64*** ||1434||10||2.66*** ||662||12||1.95** |
|Australia||1492||9||0.60*** ||1779||26||0.72*** ||1492||8||2.22*** ||784||9||1.77** |
|United States||1292||9||0.54*** ||1430||19||0.45*** ||1303||9||2.26*** ||723||24||4.46*** |
|Sex|| || || || || || || || || || || || |
|Male||2378||9||0.87||2750||25||0.76*** ||2358||7||0.74** ||1150||11||0.64*** |
|Age group (years)|| || || || || || || || || || || || |
|25–39||1662||9||1.33||2000||26||2.02*** ||1655||7||2.16** ||664||10||4.90** |
|40–54||1887||11||1.38||2305||31||2.13*** ||1876||10||2.39*** ||987||15||5.70*** |
|55+||1449||11||1.37||1701||27||1.73*** ||1409||8||2.09** ||901||16||6.16*** |
|Majority/minority group|| || || || || || || || || || || || |
|Minority||709||8||0.85||756||16||0.59*** ||695||5||0.57** ||312||7||0.41*** |
|Education|| || || || || || || || || || || || |
|Income|| || || || || || || || || || || || |
|High||1649||11||1.12||1982||28||1.23** ||1634||9||1.57*** ||844||15||1.93*** |
|HSI|| || || || || || || || || || || || |
|High||2652||13||1.54*** ||3422||35||1.84*** ||2637||11||1.84*** ||1342||20||2.40*** |
|Self-efficacy|| || || || || || || || || || || || |
|High||1507||7||0.73** ||1729||20||0.85* ||1486||5||0.80||672||8||0.57** |
|Medications make quitting easier|| || || || || || || || || || || || |
|Disagree/neither agree nor disagree||2177||5||Referent||2370||13||Referent||2139||3||Referent||953||7||Referent|
|Agree||3699||13||1.92*** ||4590||34||2.49*** ||3658||11||3.08*** ||1822||17||2.48*** |
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Generally consistent with results from clinical trials, findings from this study show that use of varenicline, bupropion or the nicotine patch is associated with increased quit rates compared to quit rates among those attempting to quit without medication. Among those for whom systematic recall bias was largely minimized, those who used any of these medications exhibited a threefold or greater increase in 6-month continuous abstinence, with varenicline users experiencing a nearly sixfold increase. Given the limited power, no clear conclusions can be drawn about oral NRT use, but any effects appear smaller than those found for the other products. Results also suggest that failure to control for differential recall of unsuccessful quit attempts between medication users and non-users may explain the inconsistent results of previous population-based studies; as we tightened control over recall effects, the size of the positive effects for medications increased and the effect for NRT patches became significant. Lastly, our sample resembles samples from previous population studies, in that many smokers did not use medication when attempting to quit, and this was particularly true of younger smokers, minorities, those with low incomes and those, understandably, who did not believe medications make quitting easier.
These findings should be interpreted in light of the following study limitations: reliance on self-reported smoking status (although it is unlikely that successful quitters in the real world, who were neither compelled nor compensated to use medication, would misrepresent how they achieved cessation), no control over potential differences in motivation to quit or differences in relevant policy changes (e.g. increases in cigarette prices), the possibility that some subgroups of the population may have been under-represented, absence of an assessment of medication side effects and reduced sample sizes when analyses were restricted to recent quit attempters (which left insufficient power to detect cross-country differences in effectiveness, P > 0.05 for all country interaction terms).
Also, prior to wave 6, we could not ascertain whether medication was used specifically during a respondent's last quit attempt, meaning that results presented in Table 1 indicate estimated effect sizes for those known to have used medication at some point during the preceding year. However, beginning in wave 6, an additional item was added to the survey allowing for smoking cessation to be assessed as a direct function of medication use/non-use during the last quit attempt in particular, and analyses based on this subset of respondents (n = 1731) indicate that all recall bias-reduced estimates of medication effectiveness are higher when assessed as a direct function of respondents' last quit attempts. We also further restricted these analyses to respondents whose quit attempt lasted for at least 1 day, in an effort to exclude short quit attempts that some might not consider to be serious, and found that although effectiveness estimates were somewhat attenuated, the conclusions drawn from these results were the same as those drawn from Table 1.
We carried out several additional analyses to address the representativeness of our effectiveness findings, including: (i) performing analyses using longitudinally weighted data, which produced the same conclusions as those drawn from Table 1; (ii) statistically comparing those who were lost to follow-up (∼30%) with those who were retained in the sample in terms of demographic, smoking-related and medication usage variables, and found these groups to be statistically indistinguishable on all variables; and (iii) performing sensitivity analyses in which we supposed that all those who were lost to follow-up did not quit smoking, and though the effect sizes for nicotine patch effectiveness and varenicline effectiveness were somewhat attenuated, the conclusions drawn from these results were the same as those drawn from Table 1.
Balanced against the above study limitations are several strengths, including: (i) the large sample of smokers compared to some other studies; (ii) the breadth of the sample (representative from four countries); (iii) the cohort design, which allowed for longer term outcomes to be evaluated at subsequent survey waves; (iv) use of GEEs, which allowed for repeat longitudinal analyses to be performed while accounting for repeated measurements within individuals over time; and (v) measurement of time to recalled events and adjustment for numerous potential confounders of medication effectiveness.
The association between medication use and recall of failed quit attempts requires that population-based evaluations of medication effectiveness account for quit attempt recency . Indeed, results reported in the present study show that the estimated magnitude of effectiveness decreases with decreasing quit attempt recency. Reduction of recall bias can be achieved by using prospective cohorts and timely assessments, or by controlling, statistically, for time elapsed between events and measurement of events. Failure to address this bias may account for some of the previous inconsistencies observed in the literature; retrospective studies evaluating quit attempts occurring within 1 year of interview generally found NRT to be ineffective [17-21], while a study using assessments occurring every 3 months and a fully prospective study found NRT to be effective [23, 24]. Gilpin et al., using a retrospective design, did find a cessation benefit of NRT for smokers living in smoke-free homes, and suggested that NRT is more effective among those who are more motivated to quit .
Although there was a suggestion that oral NRT users may experience higher continuous abstinence rates than non-users, these rates were statistically indistinguishable from those of non-users. Although our power to detect a significant effect was limited, it remains possible that there is no long-term benefit of oral NRT when used in the population setting. We found that more than 80% of nicotine gum users reported using fewer than the recommended eight pieces per day , as have other studies [47, 48], and it remains plausible that insufficient use contributed to reduced effectiveness.
The bias-reduced estimates of varenicline, bupropion and nicotine patch effectiveness shown in our study are somewhat higher than the clinical trial estimates of medication efficacy [1-4]. This could be due to chance effects but could, plausibly, be real; in real-life settings we are testing the combined effect of the drug and non-specific effects. To the extent that non-specific effects accompany the drug (e.g. the belief that it will help), success rates should be greater than those estimated from randomized controlled trials. Thus, if our estimates are representative, more medication users are helped than many conventional studies suggest.
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Consistent with the findings of clinical trials, results from this study indicate that smoking cessation rates are higher among those using varenicline, bupropion or the nicotine patch compared to those attempting to quit without medication; however, no clear effects for oral NRT use were found. Despite the cessation advantage gained by using varenicline, bupropion or the nicotine patch, however, many of those making quit attempts do so without the aid of any medication. Thus, in theory, population quit rates could be increased by promoting use of demonstrably effective stop-smoking medications. However, even among those using these medications to help them stop smoking, relapse to smoking remains the norm, thus reinforcing the need for efforts to develop and deliver more effective treatments to help smokers to quit.
Declarations of interest
K. Michael Cummings has served as a paid consultant on smoking cessation to Pfizer and Novartis, has received payment from Pfizer and GlaxoSmithKline for lectures on smoking cessation to health professionals, and has served as a paid expert witness in litigation against the tobacco industry. All other authors declare no conflicts of interest.
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We would like to thank Timea Partos and Hua-Hie Yong of The Cancer Council Victoria for their input regarding evaluation of quit attempt recall. We are also grateful to the anonymous reviewers who provided insightful feedback on a previous version of this paper. The major funders of the ITC Four Country Survey are: US National Cancer Institute (P50 CA111326, P01 CA138389, R01 CA100362), Canadian Institutes of Health Research (57897, 79551, and 115016), National Health and Medical Research Council of Australia (265903, 450110, and 1005922), Cancer Research UK (C312/A3726, C312/A6465 and C312/A11039), the Robert Wood Johnson Foundation (045734) and the Canadian Tobacco Control Research Initiative (014578), with additional support from the Propel Centre for Population Health Impact, the Ontario Institute for Cancer Research and the Canadian Cancer Society Research Institute. None of the sponsors played any direct role in the design or conduct of the study, in the collection, management, analysis or interpretation of the data, in the preparation of the manuscript, or in the decision to submit the manuscript for publication.