Why Two Smoking Cessation Agents Work Better than One: Role of Craving Suppression

Smoking cessation intervention is a key means of reducing the human and economic costs of tobacco use. Mounting evidence suggests that combining smoking cessation pharmacotherapies (i.e., using combination pharmacotherapy) improves cessation rates over those achieved by use of individual smoking cessation medications (i.e., monotherapy). For instance, both the 2008 PHS Guideline: Treating Tobacco Use and Dependence (Fiore et al., 2008) and a Cochrane report (Stead, Perera, Bullen, Mant, & Lancaster, 2008) presented meta-analyses showing that combinations of nicotine replacement therapies (NRT’s) produce higher long-term abstinence rates than do single NRT’s (also see Shah, Wilken, Winkler, & Lin, 2008). In addition, two recent, large comparative effectiveness trials demonstrated that combination pharmacotherapy interventions tended to produce higher success rates than did monotherapies (Piper et al., 2009; Smith et al., 2009; also see Blondal, Gudmundsson, Olafsdottir, Gustavsson, & Westin, 1999; Cooney et al., 2009; Kornitzer, Boutsen, Dramaix, Thijs, & Gustavsson, 1995; Puska et al., 1995; Sweeney, Fant, Fagerstrom, McGovern, & Henningfield, 2001); although cf. (Ingersoll & Cohen, 2005). There is some evidence that the type of medication involved in the combination treatment makes a difference. Specifically, evidence suggests that combinations of NRT’s (e.g., the nicotine patch + nicotine gum or lozenge) increase cessation rates beyond combinations comprising a non-NRT medication (e.g., NRT + bupropion). In analyses reported in the 2008 PHS Guideline (see Fiore, et al., 2008); also cf. (Jorenby et al., 1999) only the combination of NRT agents, and not NRT+bupropion, produced significantly higher success rates than did the nicotine patch by itself. However, there is evidence that the combination of NRT + bupropion is also efficacious relative to monotherapy. For instance, in one of the large, recent comparative effectiveness trials (Smith, et al., 2009) a combination of bupropion + nicotine lozenge produced significantly higher 6-month abstinence rates (29.9%) than did any of the tested monotherapies (the nicotine patch, nicotine lozenge, bupropion: 16.8 – 19.9%). The abstinence rate of the bupropion + NRT combination was also modestly higher than the combination of the nicotine patch + nicotine lozenge in that study (29.9% vs. 26.9%) but not significantly so. In the second major, recent comparative effectiveness trial, both the bupropion + nicotine lozenge and the nicotine patch + nicotine lozenge combinations produced significantly higher abstinence rates at end-of-treatment than did the monotherapies (Piper, et al., 2009). In sum, there is evidence that both combination NRT and the NRT+bupropion combination produce greater success than monotherapies, although the evidence is somewhat stronger with regard to the former. It is unknown why combination pharmacotherapies produce greater benefit than monotherapies (i.e., what therapeutic mechanisms account for their superior effects on abstinence). This issue can be addressed through formal mediation analysis. Such analyses can reveal whether the relation between a treatment (an independent variable) and a clinically important outcome (the dependent variable), is partly or wholly due to treatment effects on potentially mediating variables. Such information can shed light on the determinants of success and failure, reveal what treatments do and do not do, and may be used for purposes such as the development of treatment algorithms and the determination of treatment “dosing” (ascertaining when a person has had a sufficient dose of treatment, based on mediator status (McCarthy, Bolt, & Baker, 2007). The study of mediation demands that investigators hypothesize a causal path leading from treatment to a clinically important outcome, identifying variables that should index intermediate change in that path. Such variables, or mediators, should be substantively and/or empirically linked with inferred causal processes. Very little research exists on the mediation of smoking cessation pharmacotherapy, and virtually all that does exist concerns monotherapies (i.e., single medications1). The extant research reveals a relatively small group of variables that has been implicated, albeit inconsistently, in mediating pharmacotherapy effects on long-term abstinence. McCarthy et al., (McCarthy et al., 2008) reported that bupropion’s impact on abstinence was partially mediated by its effects on craving and positive affect, but not by its effects on overall withdrawal2, negative affect, or effects associated with smoking a lapse cigarette. McCarthy et al., also found that some of the effects of pharmacotherapy may be related to effects on self-efficacy and motivation, which themselves could reflect changes in multiple individual symptoms and diverse appraisal processes (McCarthy, et al., 2008). Another study using bupropion implicated negative affect as a mediator, but not withdrawal or positive affect (Lerman et al., 2002), and a third study reported bupropion mediation via withdrawal and craving suppression, but not via effects on negative or positive affect (Piper, Federman, et al., 2008). Only two studies have addressed NRT mediation. One study (Ferguson, Shiffman, & Gwaltney, 2006) reported that the increased time to first lapse caused by NRT was mediated by reductions in withdrawal and craving, especially the latter. While NRT produced other effects, such as reducing negative affect and attention disturbance and increasing positive affect, these did not mediate treatment effects on lapse latency. A second study with smokers with HIV/AIDS (Stanton, Lloyd-Richardson, Papandonatos, de Dios, & Niaura, 2009) reported that self-efficacy and decisional balance (a motivational measure), significantly mediated NRT effects on cessation outcomes. In sum, research has most consistently implicated craving as mediating the clinical effects of single agents (monotherapy); it less consistently implicates other variables such as positive affect, negative affect, withdrawal and motivation. However, it is important to note that this characterization is based on only a few studies, these studies used different methods (e.g., different outcomes, different dosings, different analytic strategies), and in all cases the mediator accounted for only a portion of the agent’s therapeutic effects – often a modest portion. The current study sought to yield additional insight into the mediation of smoking cessation pharmacotherapy effects by identifying the proximal actions of combination therapy that account for its superior clinical outcomes. The mediators examined in this research were craving, withdrawal, negative affect, positive affect, and expectation of smoking reward. The first four variables were chosen because: (1) there is some prior evidence that these mediated the effects of monotherapies, and (2) empirical evidence and theory suggest that they should be affected by nicotine abstinence and should affect the likelihood of remaining abstinent (Baker, Piper, McCarthy, Majeskie, & Fiore, 2004; D’Souza & Markou, 2010; Hughes, 2007; McCarthy, et al., 2008). The fifth potential mediator, expectancy of smoking reward, was selected for analysis because it has been shown to be related to relapse and smoking motivation (Gwaltney, Shiffman, Balabanis, & Paty, 2005; Herd & Borland, 2009; Kirchner & Sayette, 2007), and because prior research (McCarthy, et al., 2008; Stanton, et al., 2009) suggested that such motivational factors might mediate pharmacotherapy effects. This study used data generated by one of the large recent comparative effectiveness studies cited earlier (Piper, et al., 2009); the other comparative effectiveness study by Smith et al., (Smith, et al., 2009) did not comprise measures of potential mediators. The advantages of the former study are that it had a large sample size, involved several types of pharmacotherapy, including two different types of combination pharmacotherapy, and offered measures of diverse potential mediators assessed in real time. The current work uses a Bayesian approach to mediation analysis (Yuan & MacKinnon, 2009) that has not previously been used to characterize the effects of smoking cessation interventions. The complexity of mediational modeling, especially in the use of repeated measures, can make model estimation a challenge. Fortunately such complexity can be handled in a straightforward fashion through the use of Bayesian estimation techniques. A Bayesian approach to mediation has many advantages, including the ability to incorporate prior information into the analysis, the capacity to construct credible confidence intervals for mediation effects, as well as the potential to accommodate multilevel data structures (Yuan & MacKinnon, 2009). The latter two advantages are of particular relevance in the current analysis. Further, the use of a Bayesian approach facilitated our testing multiple mediator models, which allowed the estimation of the magnitude of orthogonal mediational paths. In sum, this research uses real-time measures of multiple potential mediators, which were selected on theoretical and empirical grounds, and which were modeled as latent variables in a discontinuous piecewise model that allowed for estimation of quit day increases as well as post-quit symptom trajectories. These data were analyzed using a novel, Bayesian mediation approach, which permitted the estimation of multiple mediator models. This research was intended to provide insight into why combination therapy results in superior cessation outcome relative to monotherapy; insight that can be used to develop new treatments or use existing treatments more efficiently.