Smoking Cessation After Initial Treatment Failure With Varenicline or Nicotine Replacement: A Randomized Clinical Trial.

Importance: Most people who smoke do not quit on their initial attempt. Objective: To determine the best subsequent strategy for nonabstinence following initial treatment with varenicline or combined nicotine replacement therapy (CNRT). Design, Setting, and Participants: Using a double-blind, placebo-controlled, sequential multiple assignment randomized trial, 490 volunteers were randomized to receive 6 weeks of varenicline or CNRT. After 6 weeks, nonabstainers were rerandomized to continue, switch, or increase medication dosage for 6 additional weeks. The study was conducted from June 2015 through October 2019 in a Texas tobacco treatment clinic. Interventions: The initial treatment was 2 mg/d of varenicline or the combined replacement therapy of a 21-mg patch plus 2-mg lozenge. The rerandomized participants either continued with their initial therapies, switched between varenicline and CNRT, or increased dosages either to 3-mg or more of varenicline or to a 42-mg patch and lozenges. All received weekly brief counseling. Main Outcomes and Measures: Biochemically verified 7-day point prevalence abstinence at the end of treatment at 12 weeks. Results: The 490 randomized participants (210 female [43%], 287 non-Hispanic White [58%], mean age, 48.1 years) smoked an average of 20 cigarettes per day. After the first phase, 54 participants in the CNRT group were abstinent and continued their therapy; of the 191 who were not abstinent, 151 were rerandomized, and the 40 who did not return for rerandomization were assigned to continue their initial CNRT condition in phase 2. The end-of-treatment abstinence rate for the 191 phase 1 nonabstainers was 8% (95% credible interval [CrI], 6% to 10%) for the 90 (47%) who continued at the dosage condition, 14% (CrI, 10% to 18%) for the 50 (33%) who increased their dosage, and 14% (95% CrI, 10% to 18%) for the 51 (34%) who switched to varenicline (absolute risk difference [RD], 6%; 95% CrI, 6% to 11%) with more than 99% posterior probability that either strategy conferred benefit over continuing the initial dosage. After the first phase, 88 participants in the varenicline group were abstinent and continued their therapy; of the 157 who were not abstinent, 122 were rerandomized and 35 who did not return for rerandomization were assigned to continue with the varenicline condition. The end-of-treatment abstinence rate for the 157 phase 1 nonabstainers was 20% (95% CrI, 16% to 26%) for the 39 (32%) who increased their varenicline dosage, 0 (95% CrI, 0 to 0) for the 41 (34%) who switched CNRT, and 3% (95% CrI, 1% to 4%) for the 77 (49%) who were assigned to the continued varenicline condition (absolute RD, -3%; 95% CrI, -4% to -1%) with more than 99% posterior probability that continuing varenicline at the initial dosage was worse than switching to a higher dosage. Furthermore, increasing the varenicline dosage had an absolute RD of 18% (95% CrI, 13% to 24%) and a more than 99% posterior probability of conferring benefit. The secondary outcome of continuous abstinence at 6 months indicated that only increased dosages of the CNRT and varenicline provided benefit over continuation of the initial treatment dosages. Conclusions and Relevance: For individuals who smoked but did not achieve abstinence after treatment with varenicline, increasing the dosage enhanced abstinence vs continuing, whereas for nonabstainers initially treated with CNRT, a dosage increase or switch to varenicline enhanced abstinence and may be viable rescue strategies. Trial Registration: ClinicalTrials.gov Identifier: NCT02271919.

Comparing the Fagerström Test and Heaviness of Smoking Index in Predicting Smoking Abstinence in Cancer Patients.

INTRODUCTION: People with cancer who smoke exhibit greater cigarette dependence than people without cancer who smoke, a crucial factor in smoking cessation. Research is limited on the predictive potential of the Fagerström Test for Cigarette Dependence (FTCD) and the Heaviness of Smoking Index (HSI) on smoking abstinence in cancer patients undergoing smoking cessation treatment. METHODS: We analyzed data from 5,934 cancer patients seeking smoking cessation treatment at The University of Texas MD Anderson Cancer Center (female 52.08%; Mean age = 55.52, SD = 11.17). We evaluated the predictive accuracy of FTCD and HSI on abstinence at 3-, 6-, and 9-months from first consultation, and assessed the concordance between these tools in measuring cigarette dependence using Cohen's kappa test and different correlation and regression models. We also analyzed variations across sex at birth and race/ethnicity. RESULTS: Both the FTCD and the HSI demonstrated comparable predictive accuracy for smoking cessation at all follow-ups, with neither showing high accuracy (Areas Under the Curve scores around 0.6). Concordance analysis revealed substantial agreement between FTCD and HSI scores (Cohen's kappa ~ 0.7), particularly at lower levels of dependence. However, this agreement varied by race, with reduced concordance observed in Non-Hispanic Blacks. CONCLUSIONS: Our results indicate that both the FTCD and HSI are effective tools for predicting smoking cessation in cancer patients, with the HSI offering a less burdensome assessment option. Nevertheless, the findings suggest the need for tailored approaches in assessing cigarette dependence that could predict smoking cessation more accurately, considering racial differences. IMPLICATIONS: The burden of assessing cigarette dependence in cancer care settings can be reduced by using the HSI instead of the FTCD. In addition, both instruments could be substantially interchanged and used for meta-analytic studies examining dependence and abstinence, but race/ethnicity should be considered.

Brief report: Characterization of electronic cigarette use among patients of a comprehensive cancer center.

BACKGROUND AND OBJECTIVES: We provide an initial characterization of e-cigarette use among adult cancer patients. METHODS: Data were collected between November 2020 and August 2022 at a comprehensive cancer center. RESULTS: Relatively few (4.59%) of the assessed patients (n = 47,117) reported ever using e-cigarettes. Over one-third of current e-cigarette users reported being current combustible cigarette users. DISCUSSION AND CONCLUSIONS: These data suggest that e-cigarette use is uncommon but associated with other tobacco use among adult cancer patients. SCIENTIFIC SIGNIFICANCE: This is among the first comprehensive surveys of adult cancer patient e-cigarette use that details the types of e-cigarette and other tobacco products used by this population.

Examining the Association between Abstinence from Smoking and Healthcare Costs Among Patients with Cancer.

Continuous tobacco use in cancer patients is linked to substantial healthcare costs due to increased risks and complications, whereas quitting smoking leads to improved treatment outcomes and cost reductions. Addressing the need for empirical evidence on the economic impact of smoking cessation, this study examined the association between smoking cessation and healthcare cost utilization among a sample of 930 cancer patients treated at The University of Texas MD Anderson Cancer Center's Tobacco Research and Treatment Program (TRTP). Applying conditional quantile regression and propensity scores to address confounding, our findings revealed that abstinence achieved through the TRTP significantly reduced the median cost during a 3-month period post-quitting by $1,095 (ß=-$1,095, p=0.007, 95%CI=[-$1,886, -$304]). Sensitivity analysis corroborated these conclusions, showing a pronounced cost reduction when outlier data were excluded. The long-term accrued cost savings from smoking cessation could potentially offset the cost of participation in the TRTP program, underscoring its cost-effectiveness. An important implication of this study is that by reducing smoking rates, healthcare systems can more efficiently allocate resources, enhance patient health outcomes, and lessen the overall cancer burden.

Comparable cigarette consumption data collected using timeline follow-back and digital diary among treatment-seeking smokers.

OBJECTIVE: The timeline follow-back interview is a common method of collecting daily cigarette consumption (cigarettes per day [CPD]) in smoking research. However, it may be subject to recall bias due to its reliance on retrospective reports. The increasing ownership of smartphones allows researchers to administer app-based digital diaries (DD) to collect CPD, which is expected to have less recall bias. Several studies have compared these two methods and found a noticeable discrepancy between them. However, these studies have mainly focused on the time window when smokers were smoking ad libitum. In this study, we wanted to determine the comparability of these two methods when treatment-seeking smokers are attempting to quit smoking. METHOD: In a cessation trial, treatment-seeking smokers (n = 251) reported their CPD using the timeline follow-back and DD methods over a 12-week treatment period. To evaluate the comparability, we used the Bland-Altman comparison approach for agreement, correlational analysis between CPD and biochemical measures, digit bias, and logistic regression for predicting abstinence. RESULTS: We found that the two methods exhibited good agreement, and the agreement did not vary as a function of consumption levels. Consistent with this agreement, CPD data from both methods showed similar correlations with biochemical measures of smoking and predicted 6-month abstinence in a comparable fashion. Despite the agreement, the DD method appeared to be more precise by having a lower digit bias than the timeline follow-back method. CONCLUSIONS: Capturing smoking behavior using either TLFB or DD approaches yields similar data while smokers are attempting to quit smoking. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Effects of Scheduled Smoking Reduction and Precessation Nicotine Replacement Therapy on Smoking Cessation: Randomized Controlled Trial With Compliance.

BACKGROUND: Smoking remains a major public health problem, and it is important to provide a variety of efficacious and appealing options to encourage smokers to quit smoking. Scheduled smoking is a method of gradual reduction, preparing smokers to quit by systematically reducing cigarette consumption according to a predetermined schedule that increases the time between cigarette consumption. Gradual reduction may be preferred to abrupt quitting, but the efficacy of this cessation approach is unclear. OBJECTIVE: This study aims, first, to evaluate the overall effectiveness of scheduled smoking alone, or in combination with precessation nicotine replacement therapy (NRT), versus standard NRT starting on the quit date with no prior smoking reduction and, second, to evaluate the impact of schedule compliance on the effectiveness of the intervention. METHODS: A total of 916 participants recruited from the Houston metropolitan area were randomly assigned to 1 of the following 3 groups: scheduled smoking plus a precessation nicotine patch (n=306, 33.4%), scheduled smoking only with no precessation patch (n=309, 33.7%), and enhanced usual care (n=301, 32.9%) control. The primary abstinence outcomes were carbon monoxide-verified, self-reported, 7-day point prevalence abstinence at 2 and 4 weeks after the quit date. Unadjusted and adjusted logistic regression analyses were performed to evaluate the intervention effect. Scheduled smoking was implemented using a handheld device for 3 weeks before quitting. This trial was not registered because data collection began before July 1, 2005. RESULTS: Results for the first aim showed no overall differences in abstinence among the 3 groups in both the unadjusted and adjusted models. However, the results for the second aim showed a clear effect on abstinence by schedule compliance at 2 and 4 weeks and 6 months after quitting (odds ratio [OR] 2.01, 95% CI 1.31-3.07), 4 weeks (OR 1.58, 95% CI 1.05-2.38), and 6 months (OR 1.68, 95% CI 1.04-2.64), with the differences at 2 and 4 weeks after quitting being the most robust. We also found that scheduled smoking was related to a reduction in nicotine withdrawal, negative affect, and craving when compared with the controls. CONCLUSIONS: Scheduled smoking, when combined with precessation use of NRT, can result in significantly higher abstinence rates than usual care (abrupt quitting with NRT), particularly in the early postquit phase (2 and 4 weeks after cessation) when smokers are compliant with the procedure. Scheduled smoking also produced a better overall quitting experience by reducing symptoms of nicotine withdrawal and craving, in comparison with usual care, which could encourage future quit attempts. Studies in this area should focus on the use of counseling or other methods to improve adherence.

Reporting Treatment Fidelity in Behavioral Tobacco Treatment Clinical Trials: Scoping Review and Measurement Recommendations.

INTRODUCTION: Adoption of rigorous standards for reporting treatment fidelity is essential for advancing discovery, validation, and implementation of behavioral treatments. Whereas the NIH Behavior Change Consortium (BCC) developed an assessment tool to assess the quality of reporting and monitoring of treatment fidelity across health behavior change interventions, it has not yet been applied specifically to treatment fidelity in behavioral tobacco treatment trials. AIMS AND METHODS: We conducted a scoping review of peer-reviewed, clinical trials of behavioral adult tobacco treatment interventions published in English between 2006 and 2018. Using the BCC treatment fidelity checklist, articles were coded for the presence or absence of various treatment fidelity strategies within each of 5 domains: Design, Training, Delivery, Receipt, and Enactment. Eligible articles (N = 755) were coded by two independent coders. RESULTS: The proportion of reporting strategies varied within the fidelity domains, ranging from 5.2% to 96.3% in Design, 1.9% to 24.9% in Training, 2.6% to 32.3% in Delivery, 5.2% to 44.3% in Receipt, and 6.7% to 43.2% in Enactment. The mean proportion of adherence to treatment fidelity strategies within each domain was: Design (68%), Training (14%), Delivery (15%), Receipt (16%), and Enactment (25%). Only 11 studies achieved ≥80% reporting across >1 fidelity domain. There was no evidence for improvement in fidelity reporting across the 13-year time frame from the initial BCC publication to the present. CONCLUSIONS: These findings illustrate the lack of consistency in fidelity reporting in tobacco treatment trials and underscore the challenges faced in evaluating rigor and reproducibility, as well as interpretation and dissemination of findings. Recommendations are made for improving fidelity reporting in tobacco treatment trials. IMPLICATIONS: The SRNT Treatment Research Network sponsored a scoping review to summarize the current state of reporting treatment fidelity and make recommendations for best practices in reporting fidelity in tobacco treatment trials. The review identified a lack of consistency in fidelity reporting, illustrating the challenges faced in evaluating rigor, and reproducibility, as well as interpretation and dissemination of findings.

Python Package abstcal: An Open-Source Tool for Calculating Abstinence From Timeline Followback Data.

INTRODUCTION: In smoking cessation clinical trials, timeline followback (TLFB) interviews are widely used to track daily cigarette consumption. However, there are no standard tools for calculating abstinence based on TLFB data. Individual research groups have to develop their own calculation tools, which is not only time- and resource-consuming but might also lead to variability in the data processing and calculation procedures. AIMS AND METHODS: To address these issues, we developed a novel open-source Python package named abstcal to calculate abstinence using TLFB data. This package provides data verification, duplicate and outlier detection, missing-data imputation, integration of biochemical verification data, and calculation of a variety of definitions of abstinence, including continuous, point-prevalence, and prolonged abstinence. RESULTS: We verified the accuracy of the calculator using data derived from a clinical smoking cessation study. To improve the package's accessibility, we have made it available as a free web app. CONCLUSIONS: The abstcal package is a reliable abstinence calculator with open-source access, providing a shared validated online tool to the addiction research field. We expect that this open-source abstinence calculation tool will improve the rigor and reproducibility of smoking and addiction research by standardizing TLFB-based abstinence calculation. IMPLICATIONS: Abstinence calculation is an essential task in any smoking intervention study. However, there have not been standard open-source tools available to the researchers. This commentary describes a Python-based package called abstcal that can calculate abstinence from TLFB data, a common methodology to collect smoking consumption data in research settings. The package supports the calculation of point-prevalence, prolonged, and continuous abstinence. Importantly, the package has a web app interface that allows researchers to use the tool without any coding experience. This tool will facilitate smoking research by providing a standardized and easy-to-use abstinence calculation tool.

Engaging smokers in research: Utility of Facebook in facilitating recruitment to a smoking cessation study.

INTRODUCTION: Social media, including Facebook outreach, is increasingly being used as a participant recruitment tool, and may be particularly useful in tobacco and smoking cessation studies. The Recruitment Innovation Center at Vanderbilt University Medical Center partnered with Project LUNA, a smoking cessation study, to conduct a pilot social media campaign aimed at increasing study recruitment. METHODS: Two posts encouraging study participation were developed and promoted on Facebook to users with an interest in smoking-related topics, with a link to a study-specific webpage. Facebook and website analytics were collected, including impressions, clicks, click-through rates, website traffic, and clicks to the study screening form. Study screening and enrollment data were also collected. RESULTS: The Facebook campaign ran in June 2019 in the greater Houston area. In total, the Facebook posts logged 1,179,844 impressions, 6490 clicks, and an overall click-through rate of 0.55%. There were no differences in response to the two different promotional posts. Approximately 3812 unique individuals visited an intermediary study page, with 473 expressing interest in the study. Forty-three potential participants contacted the study team, resulting in study enrollment and randomization of 23 participants, with an estimated cost per enrolled participant of $441. CONCLUSIONS: The social media campaign was successful at increasing outreach and interest in the LUNA study. However, the price-per-participant enrolled was higher than in comparable tobacco cessation studies. These results and lessons learned may be beneficial to others considering social media as a recruitment method for their clinical research trial.

Predictors of Enrollment of Older Smokers in Six Smoking Cessation Trials in the Lung Cancer Screening Setting: The Smoking Cessation at Lung Examination (SCALE) Collaboration.

SIGNIFICANCE: Increased rates of smoking cessation will be essential to maximize the population benefit of low-dose CT screening for lung cancer. The NCI's Smoking Cessation at Lung Examination (SCALE) Collaboration includes eight randomized trials, each assessing evidence-based interventions among smokers undergoing lung cancer screening (LCS). We examined predictors of trial enrollment to improve future outreach efforts for cessation interventions offered to older smokers in this and other clinical settings. METHODS: We included the six SCALE trials that randomized individual participants. We assessed demographics, intervention modalities, LCS site and trial administration characteristics, and reasons for declining. RESULTS: Of 6285 trial- and LCS-eligible individuals, 3897 (62%) declined and 2388 (38%) enrolled. In multivariable logistic regression analyses, Blacks had higher enrollment rates (OR 1.5, 95% CI 1.2,1.8) compared to Whites. Compared to "NRT Only" trials, those approached for "NRT + prescription medication" trials had higher odds of enrollment (OR 6.1, 95% CI 4.7,7.9). Regarding enrollment methods, trials using "Phone + In Person" methods had higher odds of enrollment (OR 1.6, 95% CI 1.2,1.9) compared to trials using "Phone Only" methods. Some of the reasons for declining enrollment included "too busy" (36.6%), "not ready to quit" (8.2%), "not interested in research" (7.7%), and "not interested in the intervention offered" (6.2%). CONCLUSION: Enrolling smokers in cessation interventions in the LCS setting is a major priority that requires multiple enrollment and intervention modalities. Barriers to enrollment provide insights that can be addressed and applied to future cessation interventions to improve implementation in LCS and other clinical settings with older smokers. IMPLICATIONS: We explored enrollment rates and reasons for declining across six smoking cessation trials in the lung cancer screening setting. Offering multiple accrual methods and pharmacotherapy options predicted increased enrollment across trials. Enrollment rates were also greater among Blacks compared to Whites. The findings offer practical information for the implementation of cessation trials and interventions in the lung cancer screening context and other clinical settings, regarding intervention modalities that may be most appealing to older, long-term smokers.

Cost-Effectiveness of Smoking Cessation Interventions in the Lung Cancer Screening Setting: A Simulation Study.

BACKGROUND: Guidelines recommend offering cessation interventions to smokers eligible for lung cancer screening, but there is little data comparing specific cessation approaches in this setting. We compared the benefits and costs of different smoking cessation interventions to help screening programs select specific cessation approaches. METHODS: We conducted a societal-perspective cost-effectiveness analysis using a Cancer Intervention and Surveillance Modeling Network model simulating individuals born in 1960 over their lifetimes. Model inputs were derived from Medicare, national cancer registries, published studies, and micro-costing of cessation interventions. We modeled annual lung cancer screening following 2014 US Preventive Services Task Force guidelines plus cessation interventions offered to current smokers at first screen, including pharmacotherapy only or pharmacotherapy with electronic and/or web-based, telephone, individual, or group counseling. Outcomes included lung cancer cases and deaths, life-years saved, quality-adjusted life-years (QALYs) saved, costs, and incremental cost-effectiveness ratios. RESULTS: Compared with screening alone, all cessation interventions decreased cases of and deaths from lung cancer. Compared incrementally, efficient cessation strategies included pharmacotherapy with either web-based cessation ($555 per QALY), telephone counseling ($7562 per QALY), or individual counseling ($35 531 per QALY). Cessation interventions continued to have costs per QALY well below accepted willingness to pay thresholds even with the lowest intervention effects and was more cost-effective in cohorts with higher smoking prevalence. CONCLUSION: All smoking cessation interventions delivered with lung cancer screening are likely to provide benefits at reasonable costs. Because the differences between approaches were small, the choice of intervention should be guided by practical concerns such as staff training and availability.

Smoking cessation and shared decision-making practices about lung cancer screening among primary care providers.

OBJECTIVE: We describe primary care providers' current practice patterns related to smoking cessation counseling and lung cancer screening (LCS). METHODS: Family, internal medicine, and pulmonary medicine providers from two medical centers were asked to complete an electronic survey to report their practice patterns. RESULTS: Of 52 participating providers, most reported initiating three major components of a smoking cessation intervention often or very often: advise to quit (50, 96%), assess willingness to quit (47, 90%), and assist with counseling or pharmacotherapy (49, 94%). However, other components were less commonly initiated such as arranging follow-ups (only 11 providers indicated recommending them often or very often, 21%) and less than half of providers reported that they often or very often recommend cessation counseling or pharmacotherapy of any type (except varenicline), though family medicine providers were more likely to recommend pharmacotherapy compared to the other specialists (p < 0.01). The majority of providers (47, 92%) reported that they engage in informed/shared decision-making about LCS, although only about one-third (17, 33%) indicated using a patient decision aid. Pulmonary medicine providers were more likely to use decision aids than providers from internal or family medicine (p < 0.04). CONCLUSIONS: Within the context of LCS, primary care providers report often having conversations about smoking cessation with their patients who smoke, have no clear preference for type of treatment, and rarely use follow-up calls or visits pertaining to quitting smoking. While many providers report engaging in shared decision-making about LCS, few use a decision aid for this conversation.

You Don't Need an App-Conducting Mobile Smoking Research Using a Qualtrics-Based Approach.

With the increasing availability of smartphones, many tobacco researchers are exploring smartphone-delivered mobile smoking interventions as a disseminable means of treatment. Most effort has been focused on the development of smartphone applications (apps) to conduct mobile smoking research to implement and validate these interventions. However, developing project-specific smartphone apps that work across multiple mobile platforms (e.g., iOS and Android) can be costly and time-consuming. Here, using a hypothetical study, we present an alternate approach to demonstrate how mobile smoking cessation and outcome evaluation can be conducted without the need of a dedicated app. Our approach uses the Qualtrics platform, a popular online survey host that is used under license by many academic institutions. This platform allows researchers to conduct device-agnostic screening, consenting, and administration of questionnaires through Qualtrics's native survey engine. Researchers can also collect ecological momentary assessment data using text messaging prompts with the incorporation of Amazon Web Services' Pinpoint. Besides these assessment capabilities, Qualtrics has the potential for delivering personalized behavioral interventions through the use of JavaScript code. By customizing the question's web elements in Qualtrics (e.g., using texts, images, videos, and buttons), researchers can integrate interactive web-based interventions and complicated behavioral and cognitive tasks into the survey. In conclusion, this Qualtrics-based methodology represents a novel and cost-effective approach for conducting mobile smoking cessation and assessment research.

Estimating statistical power for event-related potential studies using the late positive potential.

The late positive potential (LPP) is a common measurement used to study emotional processes of subjects in ERP paradigms. Despite its extensive use in affective neuroscience, there is presently no gold standard for how to appropriately power ERP studies using the LPP. The present study investigates how the number of trials, number of subjects, and magnitude of the effect size affect statistical power in analyses of the LPP. Using Monte Carlo simulations of ERP experiments with varying numbers of trials, subjects, and synthetic effects of known magnitude, we measured the probability of obtaining a statistically significant effect in 1,489 experiments repeated 1,000 times each. Predictably, our results showed that statistical power increases with increasing numbers of trials and subjects and at larger effect sizes. We also found that higher levels of statistical power can be achieved with lower numbers of subjects and trials and at lower effect sizes in within-subject than in between-subjects designs. Furthermore, we found that, as subjects are added to an experiment, the slope of the relationship between effect size and statistical power increased and shifted to the left until the power asymptoted to nearly 100% at higher effect sizes. This suggests that adding more subjects greatly increases statistical power at lower effect sizes (<1 µV) compared with more robust (>1.5 µV) effect sizes. We confirmed the results from the simulations based on the synthetic effects by running a new series of simulated experiments based on real data collected while participants looked at emotional images.

Association of a Comprehensive Smoking Cessation Program With Smoking Abstinence Among Patients With Cancer.

Importance: Patients with cancer who smoke after diagnosis risk experiencing reductions in treatment effectiveness, survival rates, and quality of life, and increases in complications, cancer recurrence, and second primary cancers. Smoking cessation can significantly affect these outcomes, but to date comprehensive treatment is not widely implemented in the oncologic setting. Objectives: To describe a potential model tobacco treatment program (TTP) implemented in a cancer setting, report on its long-term outcomes, and highlight its importance to quality patient care. Design, Setting, and Participants: A prospective cohort of smokers was treated in the TTP at a comprehensive cancer center from January 1, 2006, to August 31, 2015. Data analysis was performed from November 2017 to December 2018. Participants included 3245 patients (2343 with current cancer; 309 with previous cancer; 593 with no cancer history) drawn from a population of 5061 smokers referred for treatment in the TTP. Reasons for exclusion included follow-up for a noncancerous disease, no medical consultation, smoked less than 1 cigarette per day; or died before the 9-month follow-up. Exposures: Treatment consisted of an in-person medical consultation, 6 to 8 in-person and telephone follow-up counseling sessions, and 10 to 12 weeks of pharmacotherapy. Main Outcomes and Measures: Primary outcome was 9-month 7-day point-prevalence abstinence evaluated using time-specific (3-, 6-, and 9-month follow-ups) and longitudinal covariate-adjusted and unadjusted regression models with multiple imputation, intention-to-treat, and respondent-only approaches to missing data. The Fagerström Test for Cigarette Dependence was used as a measure of dependence (possible range, 0-10; higher numbers indicate greater dependence). Results: Of the 3245 smokers, 1588 (48.9%) were men, 322 (9.9%) were of black race/ethnicity, 172 (5.3%) were of Hispanic race/ethnicity, and 2498 (76.0%) were of white race/ethnicity. Mean (SD) age was 54 (11.4) years; Fagerström Test for Cigarette Dependence score, 4.41 (2.2), number of cigarettes smoked per day, 17.1 (10.7); years smoked, 33 (13.2); and 1393 patients (42.9%) had at least 1 psychiatric comorbidity. Overall self-reported abstinence was 45.1% at 3 months, 45.8% at 6 months, and 43.7% at 9 months in the multiply imputed sample. Results across all models were consistent, suggesting that, in comparison with smokers with no cancer history, abstinence rates within this TTP program did not differ appreciably whether smokers had current cancer, were a cancer survivor, or had smoking-related cancers, with the exception of patients with head and neck cancer; the rates were higher at 9 months (relative risk, 1.31; 95% CI, 1.11-1.56; P = .001) and in longitudinal models (relative risk, 1.24; 95% CI, 1.08-1.42; P = .002). Conclusions and Relevance: In this study, mean smoking abstinence rates did not differ significantly between patients with cancer and those without cancer. These findings suggest that providing comprehensive tobacco treatment in the oncologic setting can result in sustained high abstinence rates for all patients with cancer and survivors and should be included as standard of care to ensure the best possible cancer treatment outcomes.

The Late Positive Potentials Evoked by Cigarette-Related and Emotional Images Show no Gender Differences in Smokers.

When trying to quit, women are less likely than men to achieve long-term smoking abstinence. Identifying the neuropsychological mechanisms underlying women's higher relapse vulnerability will help clinicians to develop effective tailored smoking cessation interventions. Here we used event-related potentials (ERPs), a direct measure of brain activity, to evaluate the extent to which neurophysiological responses to cigarette-related and other emotional stimuli differ between female and male smokers. Both women and men showed similar patterns of brain reactivity across all picture categories; pleasant and unpleasant images prompted larger Late Positive Potentials (LPPs, a robust measure of motivational relevance) than neutral images in both groups, and cigarette-related images prompted lower LPPs than high arousing emotional images in both groups. Unlike previous studies, there were no differences between male and female smokers with regard to LPP responses to cigarette-related images. This suggests that the LPP may not be ideally suited to discriminate neurophysiological gender differences or that there are simply no gender differences in the neurophysiological responses to cigarette-related stimuli. We collected ERPs from 222 non-nicotine-deprived smokers (101 women) while they watched a slideshow that included high and low emotionally arousing pleasant and unpleasant pictures, cigarette-related, and neutral pictures. We used the mean amplitude of the LPP to assess the affective significance that participants attributed to these pictures.

Brain Responses to Cigarette-Related and Emotional Images in Smokers During Smoking Cessation: No Effect of Varenicline or Bupropion on the Late Positive Potential.

Introduction: Varenicline and bupropion are two effective smoking cessation pharmacotherapies. Researchers have hypothesized that they might be effective, in part, because they reduce cue reactivity and cue-induced cravings. Here, we used event-related potentials (ERPs) to directly measure brain responses to cigarette-related and other motivationally relevant images during a pharmacologically aided quit attempt. Methods: Smokers involved in a 12-week placebo-controlled double-blind clinical trial of smoking cessation medications (varenicline, bupropion, placebo) took part in the study. We assessed participants at two time points: 24 h (n = 140) and 4 weeks (n = 176) after the quit date. At both sessions, we measured the amplitude of the late positive potential (LPP), an ERP component reliably associated with motivational relevance, and self-reported tonic craving using the brief version of the Questionnaire of Smoking Urges (QSU-Brief). Results: At both sessions, emotional and cigarette-related images evoked significantly larger LPPs than neutral images. Neither drug type nor smoking abstinence altered this effect at either session. At both sessions, varenicline and bupropion significantly reduced self-reported tonic craving relative to the placebo condition. Conclusions: While both varenicline and bupropion reduced self-reported tonic craving, neither medication altered the amplitude of the LPP to cigarette-related or emotional pictures in smokers attempting to quit. These medications may influence abstinence by means other than by reducing neuroaffective responses to cigarette-related cues. Smokers should be prepared for the likelihood that even after several weeks of successful abstinence, once treatment ends, cigarette-related cues may remain motivationally relevant and trigger cravings that might lead to relapse. Implications: Bupropion and varenicline do not alter electrophysiological responses, as measured by the LPP, to cigarette-related and emotional images. These findings help explain why cigarette-related cues can trigger relapse when smoking cessation medication treatments end.

An RCT with the combination of varenicline and bupropion for smoking cessation: clinical implications for front line use.

BACKGROUND AND AIMS: Despite the availability of several efficacious smoking cessation treatments, fewer than 25% of smokers who quit remain abstinent 1 year post-treatment. This study aimed to determine if varenicline and bupropion combination treatment would result in higher abstinence rates than varenicline alone. DESIGN: A double-blind, randomized, parallel-group smoking cessation clinical trial in which participants were exposed to 12 weeks of treatment and followed for 12 months. SETTING: Hospital-based out-patient clinic in Texas, USA specializing in cancer prevention. PARTICIPANTS: A total of 385 community smokers (58.44% male) who smoked 1 pack of cigarettes/day [mean = 19.66 cigarettes/day, standard deviation (SD) = 9.45]; had average carbon monoxide (CO) of 26.43 parts per million (SD = 13.74); and were moderately dependent (Fagerström Test for Cigarette Dependence = 4.79; SD = 2.07). INTERVENTIONS AND COMPARATOR: Smokers were randomized in a 3 : 1 (active: Placebo) ratio to 12 weeks of treatment as follows: placebo (n = 56), varenicline (Var; n = 166), and varenicline + bupropion (Combo; n = 163). MEASUREMENTS: A priori primary outcome: prolonged abstinence at 12 months. SECONDARY OUTCOMES: 7-day point prevalence abstinence and continuous abstinence; all abstinence measures at end of treatment and 6-month follow-ups. FINDINGS: Intention-to-treat analysis: the Combo group (n = 163) failed to demonstrate superiority to the Var group (n = 166) for prolonged abstinence at 12 months [odds ratio (OR) = 0.91, 95% confidence interval (CI) = 0.50-1.64], supported by Bayes factor = 0.06. Both the Var (OR = 6.66, 95% CI = 1.61-59.27) and Combo groups (OR = 6.06, 95% CI = 1.45-54.09) demonstrated superiority to the Placebo group (n = 56; score = 8.38, P < 0.016). CONCLUSIONS: The addition of bupropion to varenicline treatment does not appear to increase smoking abstinence rates above that of varenicline alone. The findings support previous research showing a consistently favorable effect of both varenicline and the combination of varenicline and bupropion on smoking cessation compared with placebo.

Exenatide once weekly for smoking cessation: study protocol for a randomized clinical trial.

BACKGROUND: Cigarette smoking is the greatest preventable cause of morbidity and premature mortality in the United States. Approved pharmacological treatments for smoking cessation are marginally effective, underscoring the need for improved pharmacotherapies. A novel approach might use glucagon-like peptide-1 (GLP-1) agonists, which reduce alcohol and drug use in preclinical studies. GLP-1 is produced in the intestinal L-cells and in the hindbrain. The peptide maintains glucose homeostasis and reduces food intake. Several GLP-1 agonists are used clinically to treat type 2 diabetes and obesity, but none have been tested in humans to reduce smoking. AIMS: We will examine whether extended-release exenatide reduces smoking, craving, and withdrawal symptoms, as well as cue-induced craving for cigarettes. METHODS: We will enroll prediabetic and/or overweight treatment seeking smokers (n = 90) into a double-blind, placebo-controlled, randomized clinical trial. Participants will be randomized in a 1:1 ratio to receive exenatide or placebo. All participants will receive transdermal nicotine replacement therapy (NRT) and behavioral counseling. Abstinence from smoking (verified via expired CO level of ≤5 ppm), craving (Questionnaire of Smoking Urges score), and withdrawal symptoms (Wisconsin Scale of Withdrawal Symptoms score) will be assessed weekly during 6 weeks of treatment and at 1 and 4 weeks posttreatment. Cue-induced craving for cigarettes will be assessed at baseline and at 3 weeks of treatment following virtual reality exposure. EXPECTED OUTCOMES: We hypothesize that exenatide will increase the number of participants able to achieve complete smoking abstinence above that achieved via standard NRT and that exenatide will reduce craving and withdrawal symptoms, as well as cue-induced craving for cigarettes.

Pharmacological intervention and abstinence in smokers undergoing cessation treatment: A psychophysiological study.

As a composite concept, negative affect comprises various aversive emotional experiences, such as irritability and nervousness. It is a critical motivational factor that helps maintain smoking behavior, and contributes significantly to smoking cessation failure as a core withdrawal symptom. Prior research has indicated an important role of nicotinic mechanisms in negative affect processing. The most effective smoking cessation medication, varenicline, targets nicotinic acetylcholine receptors (nAChRs) as a partial agonist, while another first-line cessation medication, bupropion, has shown antagonistic effects on nAChRs. Therefore, it is possible that both medications work to reduce smoking behavior through modulating negative affect processing. To evaluate this hypothesis, we examined the impact of varenicline tartrate and bupropion hydrochloride sustained-release on electrophysiological responses to affective, cigarette-related, and neutral cues before and during smoking cessation treatment in a randomized placebo-controlled clinical trial. The participants were 206 smokers, a subset of 294 participants that were enrolled in a larger smoking cessation clinical trial who were randomly assigned to one medication group for 12weeks. Orbicularis oculi (startle eyeblink response) and corrugator supercilii facial electromyographic (EMG) reactivity toward emotional pictures (i.e., pleasant and unpleasant) in a picture-viewing task were measured before treatment and 2 and 6weeks after treatment was started. The startle and corrugator EMG activities increase with the exposure to unpleasant cues, and served as indices for negative emotional reactivity (NER). We found that after 6weeks, drug reduced startle-related NER in the varenicline group, but not in the bupropion or placebo group. Independent of medication treatment, lower baseline NER, as measured by the corrugator EMG activity, predicted a higher likelihood of smoking abstinence 1 and 3months after quitting smoking. These findings indicate the important roles of varenicline in negative affect processing and negative emotional reactivity in the course of smoking cessation.