Steven Bernstein

Conceptualizing tobacco dependence as a chronic relapsing condition suggests the need to use analytic strategies that reflect that premise. However, clinical trials for smoking cessation typically define the primary endpoint as a measure of abstinence at a single timepoint distal to the intervention, typically 3–12 months. This reinforces the concept of tobacco outcomes as a dichotomous state—one is, or is not, abstinent. Fortunately, there are several approaches available to handle longitudinal data that reflect the relapsing and remitting nature of tobacco use during treatment studies. In this paper, sponsored by the Society for Research on Nicotine and Tobacco’s Treatment Research Network, we present an introductory overview of these techniques and their application in smoking cessation clinical trials. Topics discussed include models to examine abstinence outcomes (eg, trajectory models of abstinence, models for transitions in smoking behavior, models for time to event), models that examine reductions in tobacco use, and models to examine joint outcomes (eg, examining changes in the use of more than one tobacco product). Finally, we discuss three additional relevant topics (ie, heterogeneity of effects, handling missing data, and power and sample size) and provide summary information about the type of model that can be used based on the type of data collected and the focus of the study. We encourage investigators to familiarize themselves with these techniques and use them in the analysis of data from clinical trials of smoking cessation treatment. Implications: Clinical trials of tobacco dependence treatment typically measure abstinence 3–12 months after participant enrollment. However, because smoking is a chronic relapsing condition, these measures of intervention success may not accurately reflect the common trajectories of tobacco abstinence and relapse. Several analytical techniques facilitate this type of outcome modeling. This paper is meant to be an introduction to these concepts and techniques to the global nicotine and tobacco research community including which techniques can be used for different research questions with visual summaries of which types of models can be used for different types of data and research questions.

Introduction Contingency management (CM) interventions deliver monetary reinforcers contingent upon biochemically verified abstinence from smoking. CM has been found to be effective, however, individual participant, analyses are warranted to further elucidate how individual-level behavior patterns vary during the intervention period, both within and across treatment groups. Aims and Methods This is a secondary analysis of a randomized controlled pilot trial of presurgical cancer patients who smoke (RCT N = 40). All participants were current everyday smokers and were enrolled in cessation counseling, offered nicotine replacement therapy, and submitted breath CO testing 3 times per week for 2–5 weeks. Participants randomized to CM received monetary reinforcers for breath CO ≤6 ppm on an escalating schedule of reinforcement with a reset for positive samples. Sufficient breath CO data exist for 28 participants (CM = 14; monitoring only [MO] = 14). Effect size was calculated for differences in negative CO tests. Time to first negative test was tested using survival analysis. Fisher’s exact test was used to assess relapse. Results The CM group achieved abstinence more quickly (p < .05), had a lower percentage of positive tests (h = 0.80), and experienced fewer lapses following abstinence (p = .00). While 11 of 14 participants in the CM group achieved and sustained abstinence by their third breath test, this was only true for 2 of the 14 MO participants. Conclusions Those in CM achieved abstinence quicker and with fewer lapses than those engaged in MO speaking to the efficacy of the schedule of financial reinforcement. This is particularly important within presurgical populations given the potential benefits to postoperative cardiovascular and wound infection risk. Implications While the efficacy of CM as an intervention is well established, this secondary analysis provides insight into the individual behavior patterns underlying successful abstinence. Those assigned to CM were not only more likely to achieve abstinence, but did so more quickly and with fewer instances of relapse. This is of particular importance to those scheduled for surgery where achieving abstinence as early as possible impacts on the risk of postoperative complications. CM interventions may be particularly well suited for critical windows in which timely and sustained abstinence is advantageous.