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Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action.

ABSTRACT: BACKGROUND:Understanding how smoking cessation treatments exert their effects can inform treatment development and use. Factorial designs allow researchers to examine whether multiple intervention components affect hypothesized change mechanisms, and whether the affected mechanisms are related to cessation. METHODS:This is a secondary data analysis of smokers recruited during primary care visits (N=637, 55% women, 87% white) who were motivated to quit. Participants in this fractional factorial experiment were randomized to one level of each of six intervention factors: Prequit Nicotine Patch vs None, Prequit Nicotine Gum vs None, Preparation Counseling vs None, Intensive In-Person Counseling vs Minimal, Intensive Phone Counseling vs Minimal, and 16 vs 8 Weeks of Combination Nicotine Replacement (nicotine patch+nicotine gum). Data on putative mechanisms (e.g., medication use, withdrawal, self-efficacy) and smoking status were gathered using daily assessments and during follow-up assessment calls. RESULTS:Some intervention components influenced hypothesized mechanisms. Prequit Gum and Patch each reduced prequit smoking and enhanced prequit coping and self-efficacy. In-Person Counseling increased prequit motivation to quit, postquit self-efficacy, and postquit perceived intratreatment support. Withdrawal reduction and reduced prequit smoking produced the strongest effects on cessation. The significant effect of combining Prequit Gum and In-Person Counseling on 26-week abstinence was mediated by increased prequit self-efficacy. CONCLUSIONS:This factorial experiment identified which putative treatment mechanisms were influenced by discrete intervention components and which mechanisms influenced cessation. Such information supports the combined use of prequit nicotine gum and intensive in-person counseling as cessation interventions that operate via increased prequit self-efficacy.

SUBMITTER: Piper ME

PROVIDER: S-EPMC5262527 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action.

Piper Megan E ME Cook Jessica W JW Schlam Tanya R TR Smith Stevens S SS Bolt Daniel M DM Collins Linda M LM Mermelstein Robin R Fiore Michael C MC Baker Timothy B TB

Drug and alcohol dependence 20161124

<h4>Background</h4>Understanding how smoking cessation treatments exert their effects can inform treatment development and use. Factorial designs allow researchers to examine whether multiple intervention components affect hypothesized change mechanisms, and whether the affected mechanisms are related to cessation.<h4>Methods</h4>This is a secondary data analysis of smokers recruited during primary care visits (N=637, 55% women, 87% white) who were motivated to quit. Participants in this fractio ...[more]

PMID: 28013097

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Project description:The focus on acute care, time pressure, and lack of resources hamper the delivery of smoking cessation interventions in the emergency department (ED). The aim of this study was to 1) determine the effect of an emergency nurse-initiated intervention on delivery of smoking cessation counseling based on the 5As framework (ask-advise-assess-assist-arrange) and 2) assess ED nurses' and physicians' perceptions of smoking cessation counseling.The authors conducted a pre-post trial in 789 adult smokers (five or more cigarettes/day) who presented to two EDs. The intervention focused on improving delivery of the 5As by ED nurses and physicians and included face-to-face training and an online tutorial, use of a charting/reminder tool, fax referral of motivated smokers to the state tobacco quitline for proactive telephone counseling, and group feedback to ED staff. To assess ED performance of cessation counseling, a telephone interview of subjects was conducted shortly after the ED visit. Nurses' and physicians' self-efficacy, role satisfaction, and attitudes toward smoking cessation counseling were assessed by survey. Multivariable logistic regression was used to assess the effect of the intervention on performance of the 5As, while adjusting for key covariates.Of 650 smokers who completed the post-ED interview, a greater proportion had been asked about smoking by an ED nurse (68% vs. 53%, adjusted odds ratio [OR] = 2.0, 95% confidence interval [CI] = 1.3 to 2.9), assessed for willingness to quit (31% vs. 9%, adjusted OR= 4.9, 95% CI = 2.9 to 7.9), and assisted in quitting (23% vs. 6%, adjusted OR = 5.1, 95% CI = 2.7 to 9.5) and had arrangements for follow-up cessation counseling (7% vs. 1%, adjusted OR = 7.1, 95% CI = 2.3 to 21) during the intervention compared to the baseline period. A similar increase was observed for emergency physicians (EPs). ED nurses' self-efficacy and role satisfaction in cessation counseling significantly improved following the intervention; however, there was no change in "pros" and "cons" attitudes toward smoking cessation in either ED nurses or physicians.Emergency department nurses and physicians can effectively deliver smoking cessation counseling to smokers in a time-efficient manner. This trial also provides empirical support for expert recommendations that call for nursing staff to play a larger role in delivering public health interventions in the ED.

Project description:IntroductionBy improving our understanding of the neurobiological mechanisms underlying addiction, neuroimaging research is helping to identify new targets for personalized treatment interventions. When trying to quit, smokers with larger electrophysiological responses to cigarette-related, compared with pleasant, stimuli ("C > P") are more likely to relapse than smokers with the opposite brain reactivity profile ("P > C").Aim and methodThe goal was to (1) build a classification algorithm to identify smokers characterized by P > C or C > P neuroaffective profiles and (2) validate the algorithm's classification outcomes in an independent data set where we assessed both smokers' electrophysiological responses at baseline and smoking abstinence during a quit attempt. We built the classification algorithm applying discriminant function analysis on the event-related potentials evoked by emotional images in 180 smokers.ResultsThe predictive validity of the classifier showed promise in an independent data set that included new data from 177 smokers interested in quitting; the algorithm classified 111 smokers as P > C and 66 as C > P. The overall abstinence rate was low; 15 individuals (8.5% of the sample) achieved CO-verified 12-month abstinence. Although individuals classified as P > C were nearly 2.5 times more likely to be abstinent than smokers classified as C > P (12 vs. 3, or 11% vs. 4.5%), this result was nonsignificant, preliminary, and in need of confirmation in larger trials.ConclusionThese results suggest that psychophysiological techniques have the potential to advance our knowledge of the neurobiological underpinnings of nicotine addiction and improve clinical applications. However, larger sample sizes are necessary to reliably assess the predictive ability of our algorithm.ImplicationsWe assessed the clinical relevance of a neuroimaging-based classification algorithm on an independent sample of smokers enrolled in a smoking cessation trial and found those with the tendency to attribute more relevance to rewards than cues were nearly 2.5 times more likely to be abstinent than smokers with the opposite brain reactivity profile (11% vs. 4.5%). Although this result was not statistically significant, it suggests our neuroimaging-based classification algorithm can potentially contribute to the development of new precision medicine interventions aimed at treating substance use disorders. Regardless, these findings are still preliminary and in need of confirmation in larger trials.

Project description:The incorporation of genomic information into routine care settings is a burgeoning area for investigation in behavioral medicine. The past decade has witnessed rapid advancements in knowledge of genetic biomarkers associated with smoking behaviors and tobacco-related morbidity and mortality, providing the basis for promising genomic applications in clinical and community settings. We assessed the current state of readiness for implementing genomic applications involving variation in the α5 nicotinic cholinergic receptor subunit gene CHRNA5 and smoking outcomes (behaviors and related diseases) using a process that could be translatable to a wide range of genomic applications in behavioral medicine. We reviewed the scientific literature involving CHRNA5 genetic variation and smoking cessation, and then summarized and synthesized a chain of evidence according to analytic validity, clinical validity, clinical utility, and ethical, legal, and social implications (ACCE), a well-established set of criteria used to evaluate genomic applications. Our review identified at least three specific genomic applications for which implementation may be considered, including the use of CHRNA5 genetic test results for informing disease risk, optimizing smoking cessation treatment, and motivating smoking behavior change. For these genomic applications, we rated analytic validity as convincing, clinical validity as adequate, and clinical utility and ethical, legal, and social implications as inadequate. For clinical genomic applications involving CHRNA5 variation and smoking outcomes, research efforts now need to focus on establishing clinical utility. This approach is compatible with pre-implementation research, which is also needed to accelerate translation, improve innovation design, and understand and refine system processes involved in implementation. This study informs the readiness to incorporate smoking-related genomic applications in real-world settings and facilitates cross-disciplinary collaboration to accelerate the integration of evidence-based genomics in behavioral medicine.

Project description:Introduction:Varenicline doubles cessation over nicotine replacement therapy (NRT) patch for "normal," but not "slow," nicotine metabolizers, as assessed by the nicotine metabolite ratio (NMR). Metabolism-informed care (MIC) could improve outcomes by matching normal metabolizers with non-nicotine medication (e.g., varenicline) and slow metabolizers with NRT patch. Methods:We conducted a feasibility randomized controlled trial of MIC versus guideline based care (GBC) among 81 outpatient adult daily smokers with medical comorbidity. Participants reported perceptions of MIC, underwent blood draw for NMR, and received expert cessation counseling. For MIC participants, medication selection was informed by NMR result (normal (?0.31) vs. slow (< 0.31)). The primary outcome was MIC feasibility, reflected by attitudes toward MIC and by match rates between NMR and medication. Secondary endpoints (cessation confidence, medication use, smoking status) were assessed over 6 months to inform future studies. Results:Participants were median age 53 years, 46% female, 28% black, and ~90% endorsed MIC. Despite high varenicline prescription rates (~60%) in both arms, NMR-medication matching was higher in MIC (84%) versus GBC (58%) participants (p=0.02); unadjusted odds ratio (OR) 3.67, 95% confidence interval [1.33, 11.00; p-value=0.02]. Secondary endpoints were similar at 1, 3, and 6 months. Conclusions:MIC, an NMR-based precision approach to smoking cessation, was acceptable to 90% of smokers and improved NMR-medication match rates more than 3-fold compared to GBC, even with generally high use of varenicline. These data support the feasibility of MIC, which could maximize efficacy of smoking cessation medication while minimizing side effects and cost. Implications:Among treatment-seeking daily smokers with medical comorbidity, most viewed metabolism-informed care (MIC), guided by the nicotine metabolism ratio (NMR), favorably, and were willing to accept MIC-guided medication. Compared to GBC participants (58%), more MIC participants (84%) were prescribed NMR-matched medication (i.e., normal metabolizers received varenicline; slow metabolizers received NRT patch). MIC increased the odds of optimized matching between NMR and medication more than 3-fold over GBC. Because the number needed to treat (NNT) to help one normal metabolizer quit smoking is only 4.9 for varenicline versus 26 for patch, broad implementation of MIC will improve drug efficacy in normal metabolizers as well as minimize side effects in slow metabolizers.

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Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action.

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Toward precision smoking cessation treatment II: Proximal effects of smoking cessation intervention components on putative mechanisms of action.

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