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.

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.

Smoking Cessation, Version 3.2022, NCCN Clinical Practice Guidelines in Oncology.

Although the harmful effects of smoking after a cancer diagnosis have been clearly demonstrated, many patients continue to smoke cigarettes during treatment and beyond. The NCCN Guidelines for Smoking Cessation emphasize the importance of smoking cessation in all patients with cancer and seek to establish evidence-based recommendations tailored to the unique needs and concerns of patients with cancer. The recommendations contained herein describe interventions for cessation of all combustible tobacco products (eg, cigarettes, cigars, hookah), including smokeless tobacco products. However, recommendations are based on studies of cigarette smoking. The NCCN Smoking Cessation Panel recommends that treatment plans for all patients with cancer who smoke include the following 3 tenets that should be done concurrently: (1) evidence-based motivational strategies and behavior therapy (counseling), which can be brief; (2) evidence-based pharmacotherapy; and (3) close follow-up with retreatment as needed.

Electrophysiological normative responses to emotional, neutral, and cigarette-related images.

To create reproducible emotional probes, affective scientists rely on sets of standardized pictures that are normed using subjective ratings of valence and emotional arousal. However, when emotional responses are investigated using neurophysiological measures, it might be more appropriate to select pictures integrating information from normative subjective reports and normative neurophysiological responses. Here, we provide electrophysiological normative responses for 323 emotional pictures (215 from the IAPS) covering a wide range of categories (erotica, romantic, appetizing foods, landscapes, people engaged in mundane activities, household objects, disgusting objects, accidents, sad people, violence, mutilations, and cigarette-related contents). Event-related potentials (ERPs) and subjective ratings of pleasure and emotional arousal were collected from 763 individuals (52% females, 41% white) aged between 18 and 65 (mean = 43). For each image, the mean amplitude of the late positive potential (LPP, an electrophysiological index of motivational relevance) and the mean subjective ratings of valence and arousal were calculated. We validated our procedure by showing that the subjective ratings of valence and arousal from this sample were highly correlated to the IAPS' published norms (Pearson r = .97 for pleasure and r = .82 for emotional arousal). LPP responses and subjective ratings of emotional arousal also were correlated (Pearson r = .61), but some categories reported being significantly more arousing than neutral (i.e., food, landscapes, and unpleasant objects) did not evoke LPPs significantly different from those evoked by neutral pictures. Researchers interested in probing the brain's affective systems can use these electrophysiological normative responses to create emotional probes that evoke reliable neuroaffective responses.

Bayesian regularization to predict neuropsychiatric adverse events in smoking cessation with pharmacotherapy.

BACKGROUND: Research on risk factors for neuropsychiatric adverse events (NAEs) in smoking cessation with pharmacotherapy is scarce. We aimed to identify predictors and develop a prediction model for risk of NAEs in smoking cessation with medications using Bayesian regularization. METHODS: Bayesian regularization was implemented by applying two shrinkage priors, Horseshoe and Laplace, to generalized linear mixed models on data from 1203 patients treated with nicotine patch, varenicline or placebo. Two predictor models were considered to separate summary scores and item scores in the psychosocial instruments. The summary score model had 19 predictors or 26 dummy variables and the item score model 51 predictors or 58 dummy variables. A total of 18 models were investigated. RESULTS: An item score model with Horseshoe prior and 7 degrees of freedom was selected as the final model upon model comparison and assessment. At baseline, smokers reporting more abnormal dreams or nightmares had 16% greater odds of experiencing NAEs during treatment (regularized odds ratio (rOR) = 1.16, 95% credible interval (CrI) = 0.95 - 1.56, posterior probability P(rOR > 1) = 0.90) while those with more severe sleep problems had 9% greater odds (rOR = 1.09, 95% CrI = 0.95 - 1.37, P(rOR > 1) = 0.85). The prouder a person felt one week before baseline resulted in 13% smaller odds of having NAEs (rOR = 0.87, 95% CrI = 0.71 - 1.02, P(rOR < 1) = 0.94). Odds of NAEs were comparable across treatment groups. The final model did not perform well in the test set. CONCLUSIONS: Worse sleep-related symptoms reported at baseline resulted in 85%-90% probability of being more likely to experience NAEs during smoking cessation with pharmacotherapy. Treatment for sleep disturbance should be incorporated in smoking cessation program for smokers with sleep disturbance at baseline. Bayesian regularization with Horseshoe prior permits including more predictors in a regression model when there is a low number of events per variable.

A Comprehensive Program to Reduce Tobacco-related Cancers Through Actions by a National Cancer Institute-designated Cancer Center.

Tobacco use accounts for 30% of all cancer-related deaths worldwide and 20% in the US, despite effective, evidence-based interventions for reducing tobacco use and tobacco-related cancers and deaths. In 2012, to reduce the burden of tobacco-related cancer and associated population-level risks across Texas, The University of Texas MD Anderson Cancer Center initiated the EndTobacco® program to promote statewide cancer control activities. We created evidence-based initiatives, established selection criteria, and implemented actions involving policy, education, and tobacco treatment services. As a result, EndTobacco has supported, educated, and convened local and state coalitions in policymaking; provided tobacco treatment education to health professionals; implemented Texas' only certified tobacco treatment training program; and led an initiative to enhance the tobacco-free culture of the state's publicly funded university system. Supported by commitments from MD Anderson, we developed and implemented evidence-based actions for tobacco control tailored to the center's mission, values, expertise, resources, and partnerships. By 2021, the adult smoking rate in Texas dropped from 19.2% (2014) to 13.2%. Contributors to this drop include state tobacco control policies, programs and services from multiple agencies and associations, and EndTobacco activities that complement the statewide effort to prevent youth smoking initiation and increase quit attempts among youth and adults.

Topiramate decreases the salience of motivationally relevant visual cues among smokers with alcohol use disorder.

BACKGROUND: There is preliminary evidence that the anticonvulsant topiramate increases the likelihood of both smoking and alcohol abstinence among smokers with alcohol use disorder (AUD), but its therapeutic mechanism has not been determined. We used event-related potentials (ERPs) to evaluate topiramate's effect on the salience of drug-related, emotional, and neutral pictorial cues to identify whether one of its potential therapeutic mechanisms involves reduction of the salience of motivationally relevant cues. METHODS: Participants enrolled in a multisite clinical trial treating smokers with AUD were randomly assigned to receive placebo, low-dose topiramate (up to 125 mg/day), or high-dose topiramate (up to 250 mg/day), along with brief behavioral compliance enhancement treatment. A subsample (n = 101) completed ERP assessments at baseline (1 week pre-medication) and week 5 (5 weeks on medication; 1 week pre-quit). We assessed the salience of pleasant, unpleasant, cigarette-related, alcohol-related, and neutral pictorial cues using the late positive potential (LPP) ERP component and measured self-reported substance use, reinforcement, craving, and withdrawal. RESULTS: Five weeks of high-dose topiramate treatment decreased LPP amplitudes in response to both emotional (pleasant and unpleasant) and drug-related cues (alcohol and cigarette), but not to neutral cues. However, results showed that the LPPs were not significant mediators of the relationship between topiramate dose and post-quit measures of substance use, reinforcement, craving, or withdrawal. CONCLUSIONS: These findings suggest that high-dose topiramate (up to 250 mg/day) decreases the motivational salience of both drug-related and emotional cues among smokers with AUD. However, the nonsignificant mediation analyses preclude any firm conclusions about whether this effect represents one of topiramate's therapeutic mechanisms of action.

Smoking abstinence and cessation-related outcomes one month after an immediate versus gradual reduction in nicotine content of cigarettes.

The United States Food and Drug Administration has the authority to reduce the nicotine content in cigarettes to minimal or non-addictive levels and could do so immediately or gradually over time. A large clinical trial compared the two approaches. This secondary analysis assesses abstinence and cessation-related outcomes one month after the trial concluded, when participants no longer had access to very low nicotine content (VLNC) research cigarettes. Smokers not interested in quitting (N = 1250) were recruited for the parent trial from 2014 to 2016 across 10 sites throughout the US and randomized to a 20-week study period during which they immediately switched to VLNC cigarettes, gradually transitioned to VLNC cigarettes with five monthly dose reductions, or smoked normal nicotine research cigarettes (control). At the one-month follow-up, both immediate and gradual reduction resulted in greater mean cigarette-free days (4.7 and 4.6 respectively) than the control group (3.2, both p < .05). Immediate reduction resulted in fewer mean cigarettes per day (CPD = 10.3) and lower Fagerström Test for Cigarette Dependence (FTCD = 3.7) than the gradual (CPD = 11.7, p = .001; FTCD = 3.8, p = .039) and control (CPD = 13.5, p < .001; FTCD = 4.0, p < .001) groups. Compared to controls, gradual reduction resulted in reduced CPD (p = .012) but not FTCD (p = .13). Differences in CO-verified 7-day point-prevalence abstinence were not significant. Findings demonstrate that switching to VLNC cigarettes resulted in reduced smoking and nicotine dependence severity that was sustained for at least a month after the VLNC trial period in smokers who were not interested in cessation. The greatest harm reduction endpoints were observed in those who immediately transitioned to VLNC cigarettes.

The effects of varenicline, bupropion, nicotine patch, and placebo on smoking cessation among smokers with major depression: A randomized clinical trial.

IMPORTANCE: Improving treatment outcomes for smokers with major depressive disorder (MDD) can have significant public health implications. OBJECTIVE: To evaluate the safety and efficacy of smoking cessation pharmacotherapy among smokers with MDD. DESIGN: Secondary analysis of a randomized, double-blind, active- (nicotine patch) and placebo-controlled trial of 12 weeks of either varenicline or bupropion with a 12-week follow-up. PARTICIPANTS: Community volunteers 18-75 years of age; smoke 10+ cigarettes/day; with clinically stable MDD (N = 2635) or no psychiatric disorder (N = 4028), from 140 sites in 16 countries. INTERVENTION: Twelve weeks of pharmacotherapy (placebo [PLA], nicotine replacement therapy [NRT], bupropion [BUP], varenicline [VAR]) plus brief cessation counseling. MEASURE(S): Primary safety outcome: the occurrence of ≥1 treatment-emergent, moderate to severe neuropsychiatric adverse event (NPSAE). Primary efficacy outcome: biochemically confirmed continuous abstinence (CA) during the final 4 weeks of treatment (Weeks 9-12). RESULTS: A total of 6653 participants (56% female; 39% MDD) ~47 years old. Risk of NPSAEs did not differ by medication for MDD. MDD had higher risk (p < .0001) for NPSAEs than the NPC. Efficacy (6653; intent-to-treat): CA rates for MDD versus NPC respectively were 31.2% versus 38.0% VAR; 23.0% versus 26.1% BUP; 22.6% versus 26.4% NRT; and 13.4% versus 13.7% PLA but no differential treatment effect was noted within the cohorts. All active treatments differed from PLA but VAR showed the largest effect. CONCLUSIONS: Results suggest that for MDD smokers, inclusive of those with recurrent episode, varenicline plus counseling may be the best pharmacological option for the treatment of smoking given its greater efficacy effect size and similar risk of NPSAEs. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01456936. https://clinicaltrials.gov/ct2/show/NCT01456936.

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.

Evaluating Treatment Mechanisms of Varenicline: Mediation by Affect and Craving.

INTRODUCTION: Negative reinforcement models posit that relapse to cigarette smoking is driven in part by changes in affect and craving during the quit attempt. Varenicline may aid cessation by attenuating these changes; however, this mediational pathway has not been formally evaluated in placebo-controlled trials. Thus, trajectories of negative affect (NA), positive affect (PA), and craving were tested as mediators of the effect of varenicline on smoking cessation. AIMS AND METHODS: Secondary data analysis was conducted on 828 adults assigned to either varenicline or placebo in a randomized controlled trial for smoking cessation (NCT01314001). Self-reported NA, PA, and craving were assessed 1-week pre-quit, on the target quit day (TQD), and 1 and 4 weeks post-TQD. RESULTS: Across time, NA peaked 1-week post-quit, PA did not change, and craving declined. Less steep rises in NA (indirect effect 95% CI: .01 to .30) and lower mean craving at 1-week post-quit (CI: .06 to .50) were mediators of the relationship between varenicline and higher cessation rates at the end of treatment. PA was associated with cessation but was not a significant mediator. CONCLUSIONS: These results partially support the hypothesis that varenicline improves smoking cessation rates by attenuating changes in specific psychological processes and supported NA and craving as plausible treatment mechanisms of varenicline. IMPLICATIONS: The present research provides the first evidence from a placebo-controlled randomized clinical trial that varenicline's efficacy is due, in part, to post-quit attenuation of NA and craving. Reducing NA across the quit attempt and craving early into the attempt may be important treatment mechanisms for effective interventions. Furthermore, post-quit NA, PA, and craving were all associated with relapse and represent treatment targets for future intervention development.

Bupropion XL and SR have similar effectiveness and adverse event profiles when used to treat smoking among patients at a comprehensive cancer center.

BACKGROUND AND OBJECTIVES: Bupropion extended-release (XL; once-daily dosing) has equal efficacy with the sustained-release (SR) formulation (twice-daily dosing) for treating depression, but no studies have compared the two formulations for the treatment of smoking. In a naturalistic open-label study, we compared the effectiveness and the adverse event profiles of XL and SR in treating cancer patients for smoking. METHODS: Cancer patients (N = 648) were prescribed bupropion XL (n = 454) or SR (n = 194) alone or in combination with nicotine replacement therapy (NRT) for treating smoking from September 2006 to December 2017. We analyzed 7-day point prevalence abstinence at end-of-treatment (EOT; 3 months postmedication initiation) and evaluated for noninferiority. We also analyzed the adverse event profile differences between the medications. RESULTS: There were no significant differences in abstinent rates at EOT between bupropion XL and SR when using intent-to-treat models, regardless of concomitant NRT. XL demonstrated noninferiority in treatment efficacy compared to SR when excluding those on combined treatment with NRT. Further, there were no significant differences in spontaneously reported adverse events between XL and SR. CONCLUSIONS: Our data did not reveal a difference between bupropion XL and SR formulations in terms of effectiveness or adverse event profiles among cancer patients prescribed bupropion alone or in combination with NRTs to quit smoking. SCIENTIFIC SIGNIFICANCE: In this first published direct comparison of their effectiveness and adverse event profiles, we found that bupropion XL is likely therapeutically equivalent to bupropion SR when treating smoking among cancer patients, and produces similar side effects.

Tobacco use and cessation for cancer survivors: an overview for clinicians.

Approximately 30% of all cancer deaths in the United States are caused by tobacco use and smoking. Cancers of eighteen sites have been causally linked to smoking, the most common of which are the lung, head and neck, bladder, and esophagus. While quit rates and quit attempt rates are relatively high shortly after a cancer diagnosis, the recidivism rates are also high. Therefore, screening, treating, and preventing relapse to tobacco use is imperative among patients with and survivors of cancer. To date, research has consistently shown that a combination of pharmacologic and behavioral interventions is needed to achieve the highest smoking cessation rates, with a recent emphasis on individualized treatment as a most promising approach. Challenges in health care systems, including the lack of appropriate resources and provider training, have slowed the progress in addition to important clinical considerations relevant to the treatment of tobacco dependence (eg, a high degree of comorbidity with psychiatric disorders and other substance use disorders). However, continued tobacco use has been shown to limit the effectiveness of major cancer treatments and to increase the risk of complications and of developing secondary cancers. The authors recommend that oncology providers screen all patients for tobacco use and refer users to specialized treatment when available. Alternatively, oncology clinicians can provide basic advice on tobacco use cessation and pharmacotherapy and/or referral to outside resources (eg, quitlines). Herein, the authors summarize the current knowledge on tobacco use and its treatment, with a focus on the related available evidence for patients with and survivors of cancer.

Intersectionality and Smoking Cessation: Exploring Various Approaches for Understanding Health Inequities.

OBJECTIVE: Many marginalized groups smoke at higher rates and have greater difficulty quitting than less marginalized groups. Most research on smoking cessation inequities has focused on a single sociodemographic attribute (eg, race or socioeconomic status), yet individuals possess multiple attributes that may increase risk. The current study used an intersectionality framework to examine how the interplay between multiple marginalized attributes may impact smoking cessation outcomes. METHODS: A diverse sample of 344 adults enrolled in a smoking cessation program and reported on sociodemographic attributes (eg, race/ethnicity, gender, income) and continuous smoking abstinence on their quit date and at 1, 2, and 4 weeks postquit date. A Cox proportional hazard regression model was used to estimate whether intersectional links among race/ethnicity, gender, and income were related to smoking cessation outcomes. RESULTS: Lower household income may be related to higher risk of smoking cessation failure. There were no significant interactions among race/ethnicity, gender, and income in predicting relapse. Pairwise intersectional group differences suggested some groups may be at higher risk of relapse. Number of marginalized sociodemographic attributes did not predict relapse. CONCLUSIONS: Intersectionality may be a promising framework for addressing health inequities, and may help elucidate how to best design and target intervention efforts for individuals characterized by sociodemographic intersections that concur particularly high risk for poor tobacco cessation outcomes. IMPLICATIONS: Despite an overall decline in smoking rates, socioeconomic inequities in smoking prevalence and cancer mortality are widening. Efforts targeting tobacco cessation should incorporate new theory to capture the complex set of factors that may account for tobacco cessation inequities (eg, multiple aspects of identity that may influence access to tobacco cessation treatment and exposure to certain stressors that impede cessation efforts). Intersectionality may be a promising framework for addressing health inequities in tobacco use and cessation and may help elucidate how to best design and target intervention efforts for individuals that concur particularly high risk for poor tobacco cessation outcomes.

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.

Comparing the Rate of Nicotine Metabolism Among Smokers With Current or Past Major Depressive Disorder.

BACKGROUND AND OBJECTIVES: Persons with current or past major depressive disorder (MDD) vs those without have higher smoking rates. The nicotine metabolite ratio (NMR) represents variation in the rate of nicotine metabolism and has been associated with smoking behaviors and response to tobacco treatments. We compared NMR between smokers with current or past MDD (MDD+) vs smokers without MDD (MDD-). We also assessed correlates of NMR and compared withdrawal and craving between MDD+ and MDD- smokers. METHODS: Using baseline data from two clinical trials and propensity score weighting based on sex, race, body mass index, and smoking rate, we compared NMR between MDD+ (N = 279) and MDD- (N = 1575) smokers. We also compared groups on and nicotine withdrawal and craving. RESULTS: Mean NMR (ß = -.02, 95% confidence interval [CI]: -0.05 to 0.01, P = .13) and the distribution of smokers across NMR quartiles (odds ratio [OR] = 0.76, 95% CI: 0.50 to 1.16, P = .21) were similar between MDD+ and MDD- samples. This relationship was not affected by antidepressant medication. In the MDD+ sample, African Americans had significantly lower mean NMR, while older smokers and smokers with lower education had higher mean NMR (Ps < .05). MDD+ smokers had significantly higher withdrawal and craving than MDD- smokers (Ps < .05). DISCUSSION AND CONCLUSIONS: While variability in NMR may not explain differences in smoking rates between MDD+ and MDD- smokers, MDD+ smokers report increased withdrawal and craving. SCIENTIFIC SIGNIFICANCE: In this first study to assess NMR among MDD+ smokers, the findings underscore the need to address withdrawal and craving within smoking cessation treatments for those with MDD. (Am J Addict 2021;00:00-00).

Socioeconomic Status, Social Context, and Smoking Lapse During a Quit Attempt: An Ecological Momentary Assessment Study.

BACKGROUND: Low socioeconomic status (SES) is linked to failure to quit smoking. Health inequity models suggest that low SES smokers experience barriers to quitting in part due to greater exposure to pro-smoking social contexts. PURPOSE: The current study examined longitudinal associations among socioeconomic status, pro-smoking social context factors (i.e., exposure to other smokers, places where smoking was allowed), cigarette availability, and smoking lapse during a quit attempt. METHODS: Ecological momentary assessments (EMA) were gathered from a multiethnic sample of 365 smokers engaged in a quit attempt. A multilevel structural equation model estimated a latent variable for SES indicated by income, education, health insurance, and employment, associations among EMAs for pro-smoking social contexts and cigarette availability, and indirect effects of SES through, pro-smoking social contexts and cigarette availability to subsequent smoking lapse. RESULTS: Lower SES scores were associated with a higher likelihood of smoking lapse. Decomposition of the path from SES to smoking lapse into indirect effects showed significant paths through exposure to places where smoking is allowed and cigarette availability. Additionally, significant serial indirect paths from SES through both exposure to other smokers and places where smoking was allowed, in turn, through cigarette availability, and, ultimately, to smoking lapse were noted. CONCLUSIONS: Consistent with models positing that SES influences health behaviors via contextual factors, the current study demonstrated that low SES smokers attempting to quit experienced greater pro-smoking social contexts that affected subsequent risk for lapse.

Withdrawal Symptom, Treatment Mechanism, and/or Side Effect? Developing an Explicit Measurement Model for Smoking Cessation Research.

INTRODUCTION: Assessment of withdrawal symptoms, treatment mechanisms, and side effects is central to understanding and improving smoking cessation interventions. Though each domain is typically assessed separately with widely used questionnaires to separately assess each domain (eg, Minnesota Nicotine Withdrawal Scale = withdrawal; Questionnaire of Smoking Urges-Brief = craving; Positive and Negative Affect Schedule = affect; symptom checklist = side effects), there are substantial problems with this implicit "one questionnaire equals one construct" measurement model, including item overlap across questionnaires. This study sought to clarify the number and nature of constructs assessed during smoking cessation by developing an explicit measurement model. METHODS: Two subsamples were randomly created from 1246 smokers in a clinical trial. Exploratory and confirmatory factor analyses were conducted to identify and select a model that best represented the data. Measurement invariance was assessed to determine if the factors and their content were consistent prior to and during the quit. Improvement in construct overlap within this model was compared against the implicit measurement model using correlational analyses. RESULTS: A 5-factor measurement model composed of negative affect, somatic symptoms, sleep problems, positive affect, and craving fits the data well prior to and during quitting. All factor content except somatic symptoms was consistent over time. Correlational analyses indicated that the 5-factor model attenuated construct overlap compared to the implicit model. CONCLUSIONS: The models generated from data-driven approaches (eg, the 5-factor model) reduced overlap and better represented the constructs underlying these measures. This approach created distinct, stable constructs that span over measures of side effects and potential treatment mechanisms. IMPLICATIONS: This study demonstrated that measures assessing treatment mechanisms, withdrawal symptoms, and side effects contain problematic overlap that reduces the clarity of these key constructs. The use of data-driven approaches showed that these measures do not map on to their posited latent constructs (eg, the Minnesota Nicotine Withdrawal Scale does not yield a withdrawal factor). Rather, these measures form distinct, basic processes that may represent more meaningful constructs for future research on cessation and treatment. Assessments designed to individually examine these processes may improve the study of treatment mechanisms.

Toward Precision Medicine for Smoking Cessation: Developing a Neuroimaging-Based Classification Algorithm to Identify Smokers at Higher Risk for Relapse.

INTRODUCTION: By 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 METHOD: The 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. RESULTS: The 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. CONCLUSION: These 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. IMPLICATIONS: We 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.