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Aim: To compare effects of three post-relapse interventions on smoking abstinence., Design: Sequential three-phase multiple assignment randomized trial (SMART)., Setting: Eighteen Wisconsin, USA, primary care clinics., Participants: A total of 1154 primary care patients (53.6% women, 81.2% White) interested in quitting smoking enrolled from 2015 to 2019; 582 relapsed and were randomized to relapse recovery treatment., Interventions: In phase 1, patients received cessation counseling and 8 weeks nicotine patch. Those who relapsed and agreed were randomized to a phase 2 relapse recovery group: (1) reduction counseling + nicotine mini-lozenges + encouragement to quit starting 1 month post-randomization (preparation); (2) repeated encouragement to quit starting immediately post-randomization (recycling); or (3) advice to call the tobacco quitline (control). The first two groups could opt into phase 3 new quit treatment [8 weeks nicotine patch + mini-lozenges plus randomization to two treatment factors (skill training and supportive counseling) in a 2 × 2 design]. Phase 2 and 3 interventions lasted ≤ 15 months., Measurements: The study was powered to compare each active phase 2 treatment with the control on the primary outcome: biochemically confirmed 7-day point-prevalence abstinence 14 months post initiating phase 2 relapse recovery treatment. Exploratory analyses tested for phase 3 counseling factor effects., Findings: Neither skill training nor supportive counseling (each on versus off) increased 14-month abstinence rates; skills on versus off 9.3% (14/151) versus 5.2% (8/153), P = 0.19; support on versus off 6.6% (10/152) versus 7.9% (12/152), P = 0.73. Phase 2 preparation did not produce higher 14-month abstinence rates than quitline referral; 3.6% (8/220) versus 2.1% [3/145; risk difference = 1.5%, 95% confidence interval (CI) = -1.8-5.0%, odds ratio (OR) = 1.8, 95% CI = 0.5-6.9]. Recycling, however, produced higher abstinence rates than quitline referral; 6.9% (15/217) versus 2.1% (three of 145; risk difference, 4.8%, 95% CI = 0.7-8.9%, OR = 3.5, 95% CI = 1.0-12.4). Recycling produced greater entry into new quit treatment than preparation: 83.4% (181/217) versus 55.9% (123/220), P < 0.0001., Conclusions: Among people interested in quitting smoking, immediate encouragement post-relapse to enter a new round of smoking cessation treatment ('recycling') produced higher probability of abstinence than tobacco quitline referral. Recycling produced higher rates of cessation treatment re-engagement than did preparation/cutting down using more intensive counseling and pharmacotherapy., (© 2024 Society for the Study of Addiction.)

Importance: Smoking is the leading preventable cause of death and illness in the US. Identifying cost-effective smoking cessation treatment may increase the likelihood that health systems deliver such treatment to their patients who smoke., Objective: To evaluate the cost-effectiveness of standard vs enhanced varenicline use (extended varenicline treatment or varenicline in combination with nicotine replacement therapy) among individuals trying to quit smoking., Design, Setting, and Participants: This economic evaluation assesses the Quitting Using Intensive Treatments Study (QUITS), which randomized 1251 study participants who smoked into 4 conditions: (1) 12-week varenicline monotherapy (n = 315); (2) 24-week varenicline monotherapy (n = 311); (3) 12-week varenicline combination treatment with nicotine replacement therapy patch (n = 314); or (4) 24-week varenicline combination treatment with nicotine replacement therapy patch (n = 311). Study enrollment occurred in Madison and Milwaukee, Wisconsin, between November 11, 2017, and July 2, 2020. Statistical analysis took place from May to October 2023., Main Outcomes and Measures: The primary outcome was 7-day point prevalence abstinence (biochemically confirmed with exhaled carbon monoxide level ≤5 ppm) at 52 weeks. The incremental cost-effectiveness ratio (ICER), or cost per additional person who quit smoking, was calculated using decision tree analysis based on abstinence and cost for each arm of the trial., Results: Of the 1251 participants, mean (SD) age was 49.1 (11.9) years, 675 (54.0%) were women, and 881 (70.4%) completed the 52-week follow-up. Tobacco cessation at 52 weeks was 25.1% (79 of 315) for 12-week monotherapy, 24.4% (76 of 311) for 24-week monotherapy, 23.6% (74 of 314) for 12-week combination therapy, and 25.1% (78 of 311) for 24-week combination therapy, respectively. The total mean (SD) cost was $1175 ($365) for 12-week monotherapy, $1374 ($412) for 12-week combination therapy, $2022 ($813) for 24-week monotherapy, and $2118 ($1058) for 24-week combination therapy. The ICER for 12-week varenicline monotherapy was $4681 per individual who quit smoking and $4579 per quality-adjusted life-year (QALY) added. The ICER for 24-week varenicline combination therapy relative to 12-week monotherapy was $92 000 000 per additional individual who quit smoking and $90 000 000 (95% CI, $15 703 to dominated or more costly and less efficacious) per additional QALY., Conclusions and Relevance: This economic evaluation of standard vs enhanced varenicline treatment for smoking cessation suggests that 12-week varenicline monotherapy was the most cost-effective treatment option at the commonly cited threshold of $100 000/QALY. This study provides patients, health care professionals, and other stakeholders with increased understanding of the health and economic impact of more intensive varenicline treatment options.

Introduction: Smoking is the leading preventable cause of death and disease in the U.S. This study evaluates the cost-effectiveness from a healthcare system perspective of a comprehensive primary care intervention to reduce smoking rates., Methods: This pragmatic trial implemented electronic health record prompts during primary care visits and employed certified tobacco cessation specialists to offer proactive outreach and smoking cessation treatment to patients who smoke. The data, analyzed in 2022, included 10,683 patients in the smoking registry from 2017 to 2020. Pre-post analyses compared intervention costs to treatment engagement, successful self-reported smoking cessation, and acute health care utilization (urgent care, emergency department visits, and inpatient hospitalization). Cost per quality-adjusted life year was determined by applying conversion factors obtained from the tobacco research literature to the cost per patient who quit smoking., Results: Tobacco cessation outreach, medication, and counseling costs increased from $2.64 to $6.44 per patient per month, for a total post-implementation intervention cost of $500,216. Smoking cessation rates increased from 1.3% pre-implementation to 8.7% post-implementation, for an incremental effectiveness of 7.4%. The incremental cost-effectiveness ratio was $628 (95% CI: $568, $695) per person who quit smoking, and $905 (95% CI: $822, $1,001) per quality-adjusted life year gained. Acute health care costs decreased by an average of $42 (95% CI: -$59, $145) per patient per month for patients in the smoking registry., Conclusions: Implementation of a comprehensive and proactive smoking cessation outreach and treatment program for adult primary care patients who smoke meets typical cost-effectiveness thresholds for healthcare., (Copyright © 2023 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Introduction: Available evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown., Methods: Electronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission., Results: Current (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97)., Conclusions: Former but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers., Implications: Prior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Purpose: Quitting smoking improves patients' clinical outcomes, yet smoking is not commonly addressed as part of cancer care. The Cancer Center Cessation Initiative (C3I) supports National Cancer Institute-designated cancer centers to integrate tobacco treatment programs (TTPs) into routine cancer care. C3I centers vary in size, implementation strategies used, and treatment approaches. We examined associations of these contextual factors with treatment reach and smoking cessation effectiveness., Methods: This cross-sectional study used survey data from 28 C3I centers that reported tobacco treatment data during the first 6 months of 2021. Primary outcomes of interest were treatment reach (reach)-the proportion of patients identified as currently smoking who received at least one evidence-based tobacco treatment component (eg, counseling and pharmacotherapy)-and smoking cessation effectiveness (effectiveness)-the proportion of patients reporting 7-day point prevalence abstinence at 6-month follow-up. Center-level differences in reach and effectiveness were examined by center characteristics, implementation strategies, and tobacco treatment components., Results: Of the total 692,662 unique patients seen, 44,437 reported current smoking. Across centers, a median of 96% of patients were screened for tobacco use, median smoking prevalence was 7.4%, median reach was 15.4%, and median effectiveness was 18.4%. Center-level characteristics associated with higher reach included higher smoking prevalence, use of center-wide TTP, and lower patient-to-tobacco treatment specialist ratio. Higher effectiveness was observed at centers that served a larger overall population and population of patients who smoke, reported a higher smoking prevalence, and/or offered electronic health record referrals via a closed-loop system., Conclusion: Whole-center TTP implementation among inpatients and outpatients, and increasing staff-to-patient ratios may improve TTP reach. Designating personnel with tobacco treatment expertise and resources to increase tobacco treatment dose or intensity may improve smoking cessation effectiveness.

Effective treatments for smoking cessation exist but are underused. Proactive chronic care approaches may enhance the reach of cessation treatment and reduce the prevalence of smoking in healthcare systems. This pragmatic study evaluated a population-based Comprehensive Tobacco Intervention Program (CTIP) implemented in all (6) adult primary care clinics in a Madison, Wisconsin, USA healthcare cooperative, assessing treatment reach, reach equity, and effectiveness in promoting smoking cessation. CTIP launched in 3 waves of 2 clinics each in a multiple baseline design. Electronic health record (EHR) tools facilitated clinician-delivered pharmacotherapy and counseling; guiding tobacco care managers in phone outreach to all patients who smoke; and prompting multimethod bulk outreach to all patients on a smoking registry using an opt-out approach. EHR data were analyzed to assess CTIP reach and effectiveness among 6894 adult patients between January 2018 and February 2020. Cessation treatment reach increased significantly after CTIP launch in 5 of 6 clinics and was significantly higher when clinics were active vs. inactive in CTIP [Odds Ratio (OR) range = 2.0-3.0]. Rates of converting from current to former smoking status were also higher in active vs. inactive clinics (OR range = 2.2-10.5). Telephone treatment reach was particularly high in historically underserved groups, including African-American, Hispanic, and Medicaid-eligible patients. Implementation of a comprehensive, opt-out, chronic-care program aimed at all patients who smoke was associated with increases in the rates of pharmacotherapy and counseling delivery and quitting smoking. Proactive outreach may help reduce disparities in treatment access., Competing Interests: Declaration of Competing Interest Danielle E. McCarthy, Michael C. Fiore, and Timothy B. Baker have all received grant funding from NCI, the institute that sponsors SmokefreeTXT. Michael C. Fiore serves as a consultant to the National Cancer Institute (NCI) on tobacco cessation policy issues. Timothy B. Baker has served as a paid consultant to ICF to evaluate the portfolio of Smokefree resources via monies supplied by NCI. His consulting activities involved suggesting new research directions for digital health interventions and providing feedback to ICF and NCI on research products on such interventions. The research reported in this report was not part of his consulting work with ICF/NCI. Timothy B. Baker is Principal Investigator on a project funded by NHLBI for which Pfizer provided free active and placebo varenicline. Pfizer played no role in the design, implementation, or analysis of the project described in the present manuscript. All other authors have no conflicts to report. The electronic health record tools described in this manuscript are marketed by Epic Systems Corporation., (Copyright © 2022. Published by Elsevier Inc.)

Objective: Most individuals who try to quit smoking will not succeed even if they use evidence-based treatment. Qualitative methods can help identify cessation treatments' limitations and suggest adaptations to increase treatment success., Method: Rapid qualitative analysis was conducted on data from 125 adults who smoked daily (48% female; 44% White) and participated in a smoking cessation trial and completed qualitative interviews 2 weeks prequit, reporting on changes they needed to make to quit, and 100 adults (50% female; 49% White) who completed a second interview 2 weeks postquit, reporting changes they had made., Results: The anticipated changes reported prequit (in order of frequency) were as follows: identify smoking triggers (without a coping plan), focus on benefits of quitting, reduce exposure to others smoking, make other health changes, reduce exposure to nonsocial smoking cues, and reduce alcohol consumption. Many participants were unable to identify specific changes that would aid their cessation success. Changes reported postquit included the following: use the 4 D strategies (delay, drink water, deep breathing, distract), reduce exposure to nonsocial smoking cues, focus on benefits of quitting, change daily routine, make other health changes, reduce exposure to others smoking, and get support from loved ones. Most changes reported postquit were consistent with clinical practice guidelines; however, use of cessation medication was the least reported theme., Conclusion: Prior to quitting, over a third of participants were unable to identify changes to increase cessation success. Those who could focus on triggers and cues for smoking. Postquit, participants reported using cessation strategies encouraged during study cessation counseling. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Purpose: Continued smoking after the diagnosis of cancer can markedly worsen oncology treatment side effects, cancer outcomes, cancer mortality, and all-cause mortality. Conversely, mounting evidence demonstrates that smoking cessation by patients with cancer improves outcomes. A cancer diagnosis often serves as a teachable moment, characterized by high motivation to quit. However, too few patients with cancer who smoke are offered evidence-based smoking cessation treatment, and too few engage in such treatment., Methods and Materials: The National Cancer Institute commissioned Tobacco Control Monograph 23, Treating Smoking in Cancer Patients: An Essential Component of Cancer Care , to review and synthesize the evidence that clarifies the need to intervene with smoking in cancer care., Results: Although many patients with newly diagnosed cancer who smoke make quit attempts, many of these are unsuccessful, and among those who successfully quit, relapse is common. Indeed, an estimated 12.2% of adults ever diagnosed with cancer reported they currently smoked (National Health Interview Survey, 2020). Patients with cancer who smoke are likely to benefit from smoking cessation treatments, including counseling and US Food and Drug Administration-approved medications, and there are many effective strategies to increase delivery of smoking cessation treatment in cancer care settings., Conclusion: Smoking cessation is among the most effective treatment options for improving the likelihood of survival, quality of life, and overall health of patients with cancer who smoke. It is important for cancer care clinicians and patients to realize that it is never too late to quit smoking and that there are clear benefits to doing so, regardless of cancer type.

Introduction: Tobacco use disorder is a complex behavior with a strong genetic component. Genome-wide association studies (GWAS) on smoking behaviors allow for the creation of polygenic risk scores (PRSs) to approximate genetic vulnerability. However, the utility of smoking-related PRSs in predicting smoking cessation in clinical trials remains unknown., Aims and Methods: We evaluated the association between polygenic risk scores and bioverified smoking abstinence in a meta-analysis of two randomized, placebo-controlled smoking cessation trials. PRSs of smoking behaviors were created using the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN) consortium summary statistics. We evaluated the utility of using individual PRS of specific smoking behavior versus a combined genetic risk that combines PRS of all four smoking behaviors. Study participants came from the Transdisciplinary Tobacco Use Research Centers (TTURCs) Study (1091 smokers of European descent), and the Genetically Informed Smoking Cessation Trial (GISC) Study (501 smokers of European descent)., Results: PRS of later age of smoking initiation (OR [95% CI]: 1.20, [1.04-1.37], p = .0097) was significantly associated with bioverified smoking abstinence at end of treatment. In addition, the combined PRS of smoking behaviors also significantly predicted bioverified smoking abstinence (OR [95% CI] 0.71 [0.51-0.99], p = .045)., Conclusions: PRS of later age at smoking initiation may be useful in predicting smoking cessation at the end of treatment. A combined PRS may be a useful predictor for smoking abstinence by capturing the genetic propensity for multiple smoking behaviors., Implications: There is a potential for polygenic risk scores to inform future clinical medicine, and a great need for evidence on whether these scores predict clinically meaningful outcomes. Our meta-analysis provides early evidence for potential utility of using polygenic risk scores to predict smoking cessation amongst smokers undergoing quit attempts, informing further work to optimize the use of polygenic risk scores in clinical care., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

There are evidence-based treatments for tobacco dependence, but inequities exist in the access to and reach of these treatments. Traditional models of tobacco treatment delivery are "reactive" and typically provide treatment only to patients who are highly motivated to quit and seek out tobacco treatment. Newer models involve "proactive" outreach, with benefits that include increasing access to tobacco treatment, prompting quit attempts among patients with low motivation, addressing health disparities, and improving population-level quit rates. However, the definition of "proactive" is not clear, and adoption has been slow. This commentary introduces a comprehensive yet flexible model of proactive outreach and describes how proactive outreach can optimize clinical research and care delivery in these domains: (1) identifying the population, (2) offering treatment, and (3) delivering treatment. Dimensions relevant to each domain are the intensity of proactive outreach (low to high) and the extent to which proactive outreach activities rely on human interaction or are facilitated by information technology (IT). Adoption of the proposed proactive outreach model could improve the precision and rigor with which tobacco cessation research and tobacco treatment programs report data, which could have a positive effect on care delivery and patient outcomes., (© 2022. The Author(s).)

Purpose: Hospitalization affords an opportunity to reduce smoking, but fewer than half of patients who smoke receive evidence-based cessation treatment during inpatient stays. This study evaluated a pharmacist-led, electronic health record (EHR)-facilitated opt-out smoking cessation intervention designed to address this need., Methods: Analyses of EHR records for adult patients who smoked in the past 30 days admitted to an academic medical center in the upper Midwest were conducted using the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. The reach of a pharmacist-led, EHR-facilitated protocol for smoking cessation treatment was assessed by comparing patients' receipt of nicotine replacement therapy (NRT) and tobacco quitline referral before and after implementation. χ2 tests, t tests, and multiple logistic regression models were used to compare reach across patient demographic groups to assess treatment disparities and the representativeness of reach. Adoption of the program by hospital services was also assessed., Results: Of the 70 hospital services invited to implement the program, 88.6% adopted it and 78.6% had eligible admissions. Treatment reach increased as rates of delivering NRT rose from 43.6% of eligible patients before implementation to 50.4% after implementation (P < 0.0001) and quitline referral rates rose from 0.9% to 11.9% (P < 0.0001). Representativeness of reach by sex and ethnicity improved after implementation, although disparities by race and age persisted after adjustment for demographics, insurance, and primary diagnosis. Pharmacists addressed tobacco use for eligible patients in 62.5% of cases after protocol implementation., Conclusion: Smoking cessation treatment reach and representativeness of reach improved after implementation of a proactive, pharmacist-led, EHR-facilitated opt-out smoking cessation treatment protocol in adult inpatient services., (© American Society of Health-System Pharmacists 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Tobacco cessation treatment for cancer patients is essential to providing comprehensive oncologic care. We have implemented a point of care tobacco treatment care model enabled by electronic health record (EHR) modifications in a comprehensive cancer center. Data are needed on the sustainability of both reach of treatment and effectiveness over time, including the COVID-19 pandemic., Methods: Using EHR data from the pre-implementation (P: 5 months) and post-implementation periods (6 month-blocks, T1-T5 for a total of 30 months), we compared two primary outcomes: 1) reach of treatment among those smoking and 2) effectiveness assessed by smoking cessation among those smoking in the subsequent 6 month period. We analyzed the data using generalized estimation equation regression models., Results: With the point of care tobacco treatment care model, reach of treatment increased from pre to post T5 (3.2 % vs. 48.4 %, RR 15.50, 95 % CI 10.56-22.74, p < 0.0001). Reach of treatment in all post periods (T1-T5 including the COVID-19 pandemic time) remained significantly higher than the pre period. Effectiveness, defined by smoking cessation among those smoking, increased from pre to post T2 before the pandemic (12.4 % vs. 21.4 %, RR 1.57, 95 % CI 1.31-1.87, p < 0.0001). However, effectiveness, while higher in later post periods (T3, T4), was no longer significantly increased compared with the pre period., Conclusion: A point of care EHR-enabled tobacco treatment care model demonstrates sustained reach up to 30 months following implementation, even during the COVID-19 pandemic and changes in healthcare prioritization. Effectiveness was sustained for 12 months, but did not sustain through the subsequent 12 months., (Copyright © 2021. Published by Elsevier Ltd.)

Smoking cessation results in improved cancer treatment outcomes. However, the factors associated with successful implementation of cessation programs in cancer care settings are not well understood. This paper presents the reach the reach and effectiveness of cessation programs implemented in NCI-Designated Cancer Centers in the Cancer Center Cessation Initiative (C3I). An observational, cross-sectional study was conducted among C3I Cancer Centers from July 1, 2019 and December 31, 2019 (N = 38). Reach was calculated as the proportion of patients reporting current smoking that received cessation treatment and was analyzed overall and by organizational characteristics. Smoking abstinence rates were determined by the proportion of participants self-reporting smoking abstinence in the previous 7 and 30 days at 6 months after treatment. On average, nearly 30% of patients who smoked received any cessation treatment. In-person counseling was most implemented but reached an average of only 13.2% of patients who smoked. Although less frequently implemented, average reach was highest for counseling provided via an interactive voice response system (55.8%) and telephone-based counseling (18.7%). Reach was higher at centers with more established programs, electronic health record referral systems, and higher smoking prevalence. At 6-month follow-up, about a fifth of participants on average had not smoked in the past 7 days (21.7%) or past 30 days (18.6%). Variations in reach by organizational characteristics suggest that leadership engagement and investment in technology-facilitated programs may yield higher levels of reach. Understanding which implementation and intervention strategies facilitate greater cessation treatment reach and effectiveness could lead to improved outcomes among cancer patients who smoke., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Background: Tobacco cessation after a cancer diagnosis can extend patient survival by improving outcomes for primary cancer and preventing secondary cancers. However, smoking is often unaddressed in cancer care, highlighting the need for strategies to increase treatment reach and cessation. This study examined a low-burden, point-of-care tobacco treatment program (ELEVATE) featuring an electronic health record-enabled smoking module and decision support tools to increase the reach and effectiveness of evidence-based smoking cessation treatment., Methods: This study included adult outpatient tobacco smokers (n=13,651) in medical oncology, internal medicine, and surgical oncology clinics from a large midwestern healthcare system. We examined reach and effectiveness of ELEVATE with 2 comparisons: (1) preimplementation versus postimplementation of ELEVATE and (2) ELEVATE versus usual care. Data were evaluated during 2 time periods: preimplementation (January through May 2018) and postimplementation (June through December 2018), with smoking cessation assessed at the last follow-up outpatient encounter during the 6 months after these periods., Results: The proportion of current tobacco smokers receiving cessation treatment increased from pre-ELEVATE to post-ELEVATE (1.6%-27.9%; difference, 26.3%; relative risk, 16.9 [95% CI, 9.8-29.2]; P<.001). Compared with 27.9% treatment reach with ELEVATE in the postimplementation time period, reach within usual care clinics ranged from 11.8% to 12.0% during this same period. The proportion of tobacco smokers who subsequently achieved cessation increased significantly from pre-ELEVATE to post-ELEVATE (12.0% vs 17.2%; difference, 5.2%; relative risk, 1.3 [95% CI, 1.1-1.5]; P=.002). Compared with 17.2% smoking cessation with ELEVATE in the postimplementation time period, achievement of cessation within usual care clinics ranged from 8.2% to 9.9% during this same period., Conclusions: A low-burden, point-of-care tobacco treatment strategy increased tobacco treatment and cessation, thereby improving access to and the impact of evidence-based cessation treatment. Using implementation strategies to embed tobacco treatment in every healthcare encounter promises to engage more smokers in evidence-based treatment and facilitate smoking cessation, thereby improving care cancer for patients who smoke.

Aims: To understand dual users' cigarette and e-cigarette use patterns, including the contexts in which they vape versus smoke and to understand how environmental and internal contexts and smoking patterns differ between dual users and exclusive smokers., Design: Longitudinal observational trial., Setting: Research center in Wisconsin, USA., Participants: Adult dual users (n = 162) and adults who exclusively smoked (n = 143), with no plans to quit smoking or vaping in the next 30 days., Measurements: Participants carried smartphones for 2 weeks at baseline to record each use event for the two products and report on the context of their product use. The percentage of mornings where participants vaped first versus smoked were used to compute e-cigarette dependence., Findings: Hierarchical linear regression models with random slopes and intercepts examined the within- and between-subject effects of context on the likelihood of vaping (versus smoking); significant fixed effects were tested for moderation by e-cigarette dependence. Dual users reported significantly more puffs/cigarette [mean = 13.1, standard deviation (SD) = 10.2] than puffs/vape event (mean = 11.7, SD = 11.5; P = 0.01). E-cigarette dependence moderated the influence of social cues (t-ratio = 2.4, P = 0.02) and smoking restrictions (t-ratio = 3.1, P = 0.003) on the likelihood of vaping versus smoking [odds ratio (OR) = 2.30, P = 0.02]. Context was more related to which product was used in those of low versus higher e-cigarette dependence. Reports of strong cravings to smoke and positive expectancies for cigarettes were associated with a reduced likelihood of vaping, whereas strong cravings to vape and positive vaping expectancies were related to increased likelihood of vaping., Conclusions: Among dual users of cigarettes and e-cigarettes with no motivation to quit, vaping appears to be related to internal cues and more highly linked with social contexts and smoking restrictions (i.e. under stronger external stimulus control) among those with low to moderate e-cigarette dependence compared with high e-cigarette dependence. These findings illustrate the importance of contextual factors in tobacco product use among dual users with the influence of context being reduced at high levels of e-cigarette dependence., (© 2021 Society for the Study of Addiction.)

Aims: To assess the effectiveness of intervention components designed to increase quit attempts and promote abstinence in patients initially unwilling to quit smoking., Design: A four-factor, randomized factorial experiment., Setting: Sixteen primary care clinics in southern Wisconsin., Participants: A total of 577 adults who smoke (60% women, 80% White) recruited during primary care visits who were currently willing to reduce their smoking but unwilling to try to quit. Interventions Four factors contrasted intervention components administered over a 1-year period: (i) nicotine mini-lozenge versus none; (ii) reduction counseling versus none; (iii) behavioral activation (BA) counseling versus none; and (iv) motivational 5Rs counseling versus none. Participants could request cessation treatment at any time., Measurements: The primary outcome was 7-day point-prevalence abstinence at 52 weeks post enrollment; secondary outcomes were point-prevalence abstinence at 26 weeks and making a quit attempt by weeks 26 and 52., Findings: No abstinence main effects were found but a mini-lozenge × reduction counseling × BA interaction was found at 52 weeks; P = 0.03. Unpacking this interaction showed that the mini-lozenge alone produced the highest abstinence rate (16.7%); combining it with reduction counseling produced an especially low abstinence rate (4.1%). Reduction counseling decreased the likelihood of making a quit attempt by 52 weeks relative to no reduction counseling (P = 0.01)., Conclusions: Nicotine mini-lozenges may increase smoking abstinence in people initially unwilling to quit smoking, but their effectiveness declines when used with smoking reduction counseling or other behavioral interventions. Reduction counseling decreases the likelihood of making a quit attempt in people initially unwilling to quit smoking., (© 2021 Society for the Study of Addiction.)

Importance: Smoking cessation medications are routinely used in health care. Research suggests that combining varenicline with the nicotine patch, extending the duration of varenicline treatment, or both, may increase cessation effectiveness., Objective: To compare combinations of varenicline plus the nicotine or placebo patch vs combinations used for either 12 weeks (standard duration) or 24 weeks (extended duration)., Design, Settings, and Participants: Double-blind, 2 × 2 factorial randomized clinical trial conducted from November 11, 2017, to July 9, 2020, at 1 research clinic in Madison, Wisconsin, and at 1 clinic in Milwaukee, Wisconsin. Of the 5836 adults asked to participate in the study, 1251 who smoked 5 cigarettes/d or more were randomized., Interventions: All participants received cessation counseling and were randomized to 1 of 4 medication groups: varenicline monotherapy for 12 weeks (n = 315), varenicline plus nicotine patch for 12 weeks (n = 314), varenicline monotherapy for 24 weeks (n = 311), or varenicline plus nicotine patch for 24 weeks (n = 311)., Main Outcomes and Measures: The primary outcome was carbon monoxide-confirmed self-reported 7-day point prevalence abstinence at 52 weeks., Results: Among 1251 patients who were randomized (mean [SD] age, 49.1 [11.9] years; 675 [54.0%] women), 751 (60.0%) completed treatment and 881 (70.4%) provided final follow-up. For the primary outcome, there was no significant interaction between the 2 treatment factors of medication type and medication duration (odds ratio [OR], 1.03 [95% CI, 0.91 to 1.17]; P = .66). For patients randomized to 24-week vs 12-week treatment duration, the primary outcome occurred in 24.8% (154/622) vs 24.3% (153/629), respectively (risk difference, -0.4% [95% CI, -5.2% to 4.3%]; OR, 1.01 [95% CI, 0.89 to 1.15]). For patients randomized to varenicline combination therapy vs varenicline monotherapy, the primary outcome occurred in 24.3% (152/625) vs 24.8% (155/626), respectively (risk difference, 0.4% [95% CI, -4.3% to 5.2%]; OR, 0.99 [95% CI, 0.87 to 1.12]). Nausea occurrence ranged from 24.0% to 30.9% and insomnia occurrence ranged from 24.4% to 30.5% across the 4 groups., Conclusions and Relevance: Among adults smoking 5 cigarettes/d or more, there were no significant differences in 7-day point prevalence abstinence at 52 weeks among those treated with combined varenicline plus nicotine patch therapy vs varenicline monotherapy, or among those treated for 24 weeks vs 12 weeks. These findings do not support the use of combined therapy or of extended treatment duration., Trial Registration: ClinicalTrials.gov Identifier: NCT03176784.

The impact of tobacco smoking treatment is determined by its reach into the smoking population and the effectiveness of its interventions. This review evaluates the reach and effectiveness of pharmacotherapy and psychosocial interventions for smoking. Historically, the reach of smoking treatment has been low, and therefore its impact has been limited, but new reach strategies such as digital interventions and health care system changes offer great promise. Pharmacotherapy tends to be more effective than psychosocial intervention when used clinically, and newer pharmacotherapy strategies hold great promise of further enhancing effectiveness. However, new approaches are needed to advance psychosocial interventions; progress has stagnated because research and dissemination efforts have focused too narrowly on skill training despite evidence that its core content may be inconsequential and the fact that its mechanisms are either unknown or inconsistent with supporting theory. Identifying effective psychosocial content and its mechanisms of action could greatly enhance the effectiveness of counseling, digital, and web interventions.

Background and Aims: The phase-based model of smoking cessation treatment suggests that treatment needs may vary across phases (e.g. pre-cessation, cessation). This study tested the comparative effects of varenicline and combination nicotine replacement therapy (C-NRT) relative to nicotine patch monotherapy on pre-cessation and cessation phase candidate withdrawal, expectancy and motivation mediators; relations between mediators and abstinence; and indirect effects of enhanced treatments on abstinence via candidate mediators., Design: Secondary mediation analysis of data from the open-label, randomized Wisconsin Smokers' Health Study 2, a comparative effectiveness trial of varenicline or C-NRT, versus patch monotherapy, in adults who smoked, recruited via media and community outreach., Setting: Research clinics in Madison and Milwaukee, Wisconsin, USA., Participants: A total of 1051 daily smokers motivated to quit smoking (52.5% female; mean age = 48.1, standard deviation = 11.6)., Interventions: Twelve weeks of varenicline (n = 407) or 12 weeks of combination nicotine patch and nicotine lozenge therapy (n = 421), both compared with 12 weeks of patch control condition (n = 230), with individual smoking cessation counseling., Measurements: The primary abstinence outcome was biochemically verified 7-day point-prevalence abstinence 4 weeks post-target quit day (TQD). Candidate mediators (craving, positive smoking expectancies, withdrawal symptoms, and quitting motivation) were assessed via ecological momentary assessment from 1 week prior (pre-cessation phase) to 4 weeks after (cessation phase) the TQD., Findings: Pre-cessation and cessation mean levels and slopes of craving [adjusted odds ratio (aOR) = 0.34-0.79], smoking expectancies (aOR = 0.46-0.79) and quitting motivation (aOR = 1.35-7.21) significantly predicted 4-week post-TQD abstinence (P < 0.05). Significant varenicline mediation occurred via greater suppression in pre-cessation craving [mediated effect (ab) = 0.09, standard error (SE) = 0.03, 95% confidence interval (CI) = 0.04-0.14] and smoking expectancies (ab = 0.06, SE = 0.02, 95% CI = 0.02-0.12). C-NRT mediation occurred via greater reduction in pre-post-TQD changes in craving (ab = 0.04, SE = 0.02, 95% CI = 0.01-0.08) and expectancies (ab = 0.03, SE = 0.02, 95% CI = 0.001-0.07), relative to patch monotherapy., Conclusion: Among adult smokers seeking to quit, varenicline seems to work through its effects on suppression of craving and smoking expectancies pre-cessation while combination nicotine replacement therapy mediation seems to work through cessation-related reduction in craving and smoking expectancies changes., (© 2020 Society for the Study of Addiction.)

Aims: To identify when smoking cessation treatments affect craving, negative affect and anhedonia, and how these symptoms relate to abstinence, to help evaluate the effects of particular intervention components in multi-component treatments and accelerate treatment refinement., Design: Secondary analysis of data from a two-arm randomized controlled trial., Setting: Seven primary care clinics in Wisconsin, United States., Participants: Adult primary care patients who smoked daily (n = 574)., Intervention and Comparator: Intervention was abstinence-optimized treatment (A-OT, n = 276) comprising 3 weeks of nicotine mini-lozenges pre-target quit day (TQD), 26 weeks of combination nicotine patch and mini-lozenges post-TQD and extensive psychosocial support. The comparator was recommended usual care (RUC, n = 298), comprising brief counseling and 8 weeks of nicotine patch post-TQD., Measurements: Time-varying effect models examined dynamic effects of A-OT (versus RUC) on the primary outcomes of nightly cigarette craving, negative affect and anhedonia from 1 week pre- to 2 weeks post-TQD. Exploratory models examined within-person relations between nicotine medication use and same-day symptom ratings. Secondary logistic regression analyses examined associations between post-TQD craving, negative affect and anhedonia and 1-month post-TQD abstinence., Findings: A-OT significantly suppressed pre- and post-TQD craving (β = -0.27 to -0.46 across days) and post-TQD anhedonia (β = -0.24 to -0.38 across days), relative to RUC. Within individuals, using patches was associated with lower negative affect in RUC (β = -0.42 to -0.52), but not in A-OT. Using more mini-lozenges was associated with greater craving (β = 0.04-0.07) and negative affect (β = 0.03-0.05) early, and with lower anhedonia (β = -0.06 to -0.12) later. Greater post-TQD craving (OR = 0.68) and anhedonia (OR = 0.85) predicted lower odds of abstinence 1 month post-TQD., Conclusion: Time-varying effect models showed that a multi-component treatment intervention for smoking cessation suppressed significant withdrawal symptoms more effectively than recommended usual care among daily adult smokers motivated to quit. The intervention reduced craving pre- and post-target quit day (TQD) and anhedonia post-TQD., (© 2020 Society for the Study of Addiction.)

The assessment of tobacco withdrawal is important for both research and clinical purposes. This study describes the psychometric development of a revised version of the 28-item Wisconsin Smoking Withdrawal Scale (WSWS; Welsch et al., Experimental and Clinical Psychopharmacology , 1999, 7, p. 354). Because the different contexts of use sometimes permit only brief assessment, this revision has produced both a brief and longer form using an updated pool of candidate items. For the revised Wisconsin Smoking Withdrawal Scale 2 (WSWS2), a candidate pool of 37 items was developed to measure nine putative withdrawal constructs. The stem and wording of items were revised as was the response scale. Data for psychometric analyses were derived from three smoking cessation randomized clinical trials conducted at the University of Wisconsin Center for Tobacco Research and Intervention. Dimensionality, internal consistency, and item characteristic analyses of the candidate items were conducted in a derivation sample to ascertain the factor structure and to identify items that could be used in the WSWS2 scales. Confirmatory factor analyses (CFAs) of reduced item sets and factor structure were conducted in two validation samples along with reliability and validity analyses. Derivation and validation sample analyses yielded a longer version of the WSWS2 (WSWS2-L) with 19 items and six subscales (Craving, Negative Affect, Hunger, Sleep, Restlessness, and Concentration) and a brief 6-item version (WSWS2-B). In validation sample analyses, both the WSWS2-L and the WSWS2-B demonstrated good reliability and validity as well as good fit in CFAs. The WSWS2-L and WSWS2-B possess improved construct coverage, fewer items, and other enhancements relative to the WSWS. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Introduction: Patients who use tobacco are too rarely connected with tobacco use treatment during healthcare visits. Electronic health record enhancements may increase such referrals in primary care settings. This project used the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework to assess the implementation of a healthcare system change carried out in an externally valid manner (executed by the healthcare system)., Methods: The healthcare system used their standard, computer-based training approach to implement the electronic health record and clinic workflow changes for electronic referral in 30 primary care clinics that previously used faxed quitline referral. Electronic health record data captured rates of assessment of readiness to quit and quitline referral 4 months before implementation and 8 months (May-December 2017) after implementation. Data, analyzed from October 2018 to June 2019, also reflected intervention reach, adoption, and maintenance., Results: For reach and effectiveness, from before to after implementation for electronic referral, among adult patients who smoked, assessment of readiness to quit increased from 24.8% (2,126 of 8,569) to 93.2% (11,163 of 11,977), quitline referrals increased from 1.7% (143 of 8,569) to 11.3% (1,351 of 11,977), and 3.6% were connected with the quitline after implementation. For representativeness of reach, electronic referral rates were especially high for women, African Americans, and Medicaid patients. For adoption, 52.6% of staff who roomed at least 1 patient who smoked referred to the quitline. For maintenance, electronic referral rates fell by approximately 60% over 8 months but remained higher than pre-implementation rates., Conclusions: Real-world implementation of an electronic health record-based electronic referral system markedly increased readiness to quit assessment and quitline referral rates in primary care patients. Future research should focus on implementation methods that produce more consistent implementation and better maintenance of electronic referral., (Copyright © 2020 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Relatively little is known about the possible effects of personalized genetic risk information on smoking, the leading preventable cause of morbidity and mortality. We examined the acceptability and potential behavior change associated with a personalized genetically informed risk tool ( RiskProfile ) among current smokers. Current smokers ( n = 108) were enrolled in a pre-post study with three visits. At visit 1, participants completed a baseline assessment and genetic testing via 23andMe. Participants' raw genetic data ( CHRNA5 variants) and smoking heaviness were used to create a tailored RiskProfile tool that communicated personalized risks of smoking-related diseases and evidence-based recommendations to promote cessation. Participants received their personalized RiskProfile intervention at visit 2, approximately 6 weeks later. Visit 3 involved a telephone-based follow-up assessment 30 days after intervention. Of enrolled participants, 83% were retained across the three visits. Immediately following intervention, acceptability of RiskProfile was high (M = 4.4; SD = 0.6 on scale of 1 to 5); at 30-day follow-up, 89% of participants demonstrated accurate recall of key intervention messages. In the full analysis set of this single-arm trial, cigarettes smoked per day decreased from intervention to 30-day follow-up [11.3 vs. 9.8; difference = 1.5; 95% confidence interval (0.6-2.4); P = 0.001]. A personalized genetically informed risk tool was found to be highly acceptable and associated with a reduction in smoking, although the absence of a control group must be addressed in future research. This study demonstrates proof of concept for translating key basic science findings into a genetically informed risk tool that was used to promote progress toward smoking cessation. Prevention Relevance: This study demonstrates that personal genetic information can be incorporated into a risk feedback tool that was highly acceptable to current smokers and associated with reductions in smoking. These findings may pave the way for effectiveness and implementation research on genetically-informed behavior change interventions to enhance cancer prevention efforts., (©2020 American Association for Cancer Research.)

Too few smokers who present for outpatient healthcare receive evidence-based interventions to stop smoking. Referral to nationally available smoking cessation support may enhance tobacco intervention reach during healthcare visits. This study evaluated the feasibility of outpatient electronic health record (EHR)-enabled, closed-loop referral (eReferral) to SmokefreeTXT, a National Cancer Institute text message smoking cessation program. SmokefreeTXT eReferral for adult patients who smoke was implemented in a family medicine clinic and an allergy and asthma clinic in an integrated Midwestern healthcare system. Interoperable, HIPAA-compliant eReferral returned referral outcomes to the EHR. In Phase 1 of implementation, clinicians were responsible for eReferral; in Phase 2 this responsibility shifted to Medical Assistants and/or nurses. EHR data were extracted to compute eReferral rates among adult smokers and compare demographics among those eReferred versus not referred. SmokefreeTXT data were used to compute SmokefreeTXT enrollment rates among those eReferred. Descriptive analyses of clinic staff surveys assessed implementation context and staff attitudes toward and adaptations of eReferral processes. During clinician implementation, 43 of 299 adult smokers (14.4%) were eReferred. During medical assistant (MA) implementation, 36 of 401 adult smokers (9.0%) were eReferred. Overall, among those eReferred, 25.7% completed SmokefreeTXT enrollment (3.1% of patients eligible for eReferral). Staff survey responses indicated that eReferral was efficient and easy. eReferral rates and relevant attitudes varied meaningfully by clinic. Thus, interoperable eReferral via outpatient EHR to SmokefreeTXT is feasible and acceptable to clinic staff and enrolls roughly 3.0% of smokers. Clinic context and implementation approach may influence reach., (© Society of Behavioral Medicine 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Tobacco smoking is an important risk factor for cancer incidence, an effect modifier for cancer treatment, and a negative prognostic factor for disease outcomes. Inadequate implementation of evidence-based smoking cessation treatment in cancer centers, a consequence of numerous patient-, provider-, and system-level barriers, contributes to tobacco-related morbidity and mortality. This study provides data for a paradigm shift from a frequently used specialist referral model to a point-of-care treatment model for tobacco use assessment and cessation treatment for outpatients at a large cancer center. The point-of-care model is enabled by a low-burden strategy, the Electronic Health Record-Enabled Evidence-Based Smoking Cessation Treatment program, which was implemented in the cancer center clinics on June 2, 2018. Five-month pre- and post-implementation data from the electronic health record (EHR) were analyzed. The percentage of cancer patients assessed for tobacco use significantly increased from 48% to 90% (z = 126.57, p < .001), the percentage of smokers referred for cessation counseling increased from 0.72% to 1.91% (z = 3.81, p < .001), and the percentage of smokers with cessation medication significantly increased from 3% to 17% (z = 17.20, p < .001). EHR functionalities may significantly address barriers to point-of-care treatment delivery, improving its consistent implementation and thereby increasing access to and quality of smoking cessation care for cancer center patients., (© Society of Behavioral Medicine 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

It is unclear if genetic variants affect smoking cessation treatment response. This study tested whether variants in the cholinergic receptor nicotinic alpha 5 subunit (CHRNA5) predict response to smoking cessation medication by directly comparing the two most effective smoking cessation pharmacotherapies. In this genotype-stratified randomized, double-blind, placebo-controlled clinical trial (May 2015-August 2019 in St Louis, Missouri), smokers were randomized by genotype in blocks of six (1:1:1 ratio) to three conditions: 12 weeks of placebo (n = 273), combination nicotine patch and lozenge (combination nicotine replacement therapy, cNRT, n = 275), or varenicline (n = 274). All participants received counseling and were followed for 12 months. The primary end point was biochemically verified 7-day point prevalence abstinence at the end of treatment (EOT, week 12). Trial registration and eligibility criteria are on clinicaltrials.gov (https://clinicaltrials.gov/) (NCT02351167). We conducted the genetic analyses separately for 516 European ancestry (EA) smokers and 306 non-EA smokers (including 270 African American smokers). In African American smokers, there was a genotype-by-treatment interaction for EOT abstinence (χ 2  = 10.7, degrees of freedom = 2. P = 0.0049): specifically, cNRT was more effective in smokers with rs16969968 GG genotype than was placebo, while varenicline was more effective in smokers of GA/AA genotypes. In EA ancestry smokers, there was no significant genotype-by-treatment interaction. In the whole sample, although both were effective at EOT, only varenicline, and not cNRT, was significantly effective relative to placebo at 6-month follow-up. Importantly, this study suggests that genetic information can further enhance smoking cessation treatment effectiveness., (© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)

Background and Aims: We quantified the effects of smoking and smoking cessation on carotid artery atherosclerosis and wall thickness in two unique cohorts of smokers making a quit attempt., Methods: Our primary analysis included 726 smokers making a quit attempt in a randomized clinical trial with long-term follow-up. Our secondary analysis included 889 smokers making a quit attempt in a subsequent trial. Participants underwent carotid artery ultrasonography at baseline and up to 3 subsequent visits. Primary outcomes were changes in carotid plaque score and intima media-thickness (IMT). We calculated a smoking burden score (SBS) that reflected the number of visits in which participants reported smoking after the quit attempt. Multivariable regression examined relations between SBS and carotid artery outcomes with adjustments for cardiovascular disease risk factors., Results: In the primary analysis, participants were mean (standard deviation) 46.1 (10.3) years old (57.9% female) and smoked 21.1 (8.9) cigarettes per day (CPD). After a median of 7 years, lower SBS predicted less increase in carotid plaque score (Chi-squared = 13.0, p = 0.012). SBS independently predicted change in carotid plaque score (p = 0.007; SBS 0 vs 4) as did baseline CPD (p = 0.024) and age (p<0.0001). SBS did not affect carotid IMT change. In the secondary analysis, increasing SBS was associated with increased likelihood of new plaques over 3 years among participants that smoked ≥15 CPD, (Chi-squared = 6.51, p = 0.011)., Conclusions: Smoking cessation is associated with less progression of carotid plaque, but not IMT. Salutary associations of smoking cessation with carotid plaque progression are related to degree of abstinence., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Introduction: Greater use of nicotine replacement therapy (NRT) is related to smoking cessation success, but the causal direction is unclear. This study characterized the relationship between NRT use and smoking lapse and relapse., Methods: Participants (N = 416 smokers; 57% female, 85% White) were recruited from primary care for a smoking cessation factorial experiment and analyzed if abstaining ≥1 day in the first 2 weeks post-target quit day (TQD). Participants were randomized to counseling and 8 versus 26 weeks of nicotine patch plus nicotine gum post-TQD. Participants carried electronic dispensers that timestamped each gum use. Participants who lapsed (smoked after abstaining) within 6 weeks post-TQD were matched with nonlapsers (n = 146 pairs) on multiple variables. We compared lapsers' versus matched nonlapsers' gum use in the 5 days before and after the lapsers' first lapse., Results: By week 6 post-TQD, 63% of participants lapsed. Compared with nonlapsers, lapsers used less gum 1 and 2 days pre-"lapse" and on the 5 days post-lapse. Lapsers used less gum during the 5 days post-lapse than the 5 days pre-lapse. Univariate survival analyses with lapsers showed greater gum use during both pre- and post-lapse periods predicted longer latency to relapse in the first 6 weeks., Conclusions: In a smoking cessation attempt using nicotine patch plus gum, lapsers versus matched nonlapsers used less gum immediately preceding and following their first lapse. Lower mean gum use before and after lapses predicted a more rapid escalation to relapse. Decreased nicotine gum use both precedes and follows returns to smoking during cessation attempts., Implications: This research examined electronically monitored nicotine gum use collected in real time and found that among smokers engaged in a quit attempt, lapsers (vs. matched nonlapsers) tended to decrease their gum use 1-2 days prior to lapsing and to further decrease their gum use from pre- to post-lapse. Decreased gum use pre-lapse may signal heightened lapse risk in 1-2 days, with lower level of gum use predicting a more precipitous course of relapse. These results encourage further exploration of objective measures of smoking medication use patterns to examine their signaling properties and to inform understanding of cessation failure., Clinical Trial Registration: ClinicalTrials.gov NCT01120704., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.)

Smoking is a major contributor to lung cancer and chronic obstructive pulmonary disease (COPD). Two of the strongest genetic associations of smoking-related phenotypes are the chromosomal regions 15q25.1, encompassing the nicotinic acetylcholine receptor subunit genes CHRNA5-CHRNA3-CHRNB4, and 19q13.2, encompassing the nicotine metabolizing gene CYP2A6. In this study, we examined genetic relations between cigarettes smoked per day, smoking cessation, lung cancer, and COPD. Data consisted of genome-wide association study summary results. Genetic correlations were estimated using linkage disequilibrium score regression software. For each pair of outcomes, z-score-z-score (ZZ) plots were generated. Overall, heavier smoking and decreased smoking cessation showed positive genetic associations with increased lung cancer and COPD risk. The chromosomal region 19q13.2, however, showed a different correlational pattern. For example, the effect allele-C of the sentinel SNP (rs56113850) within CYP2A6 was associated with an increased risk of heavier smoking (z-score = 19.2; p = 1.10 × 10 -81 ), lung cancer (z-score = 8.91; p = 5.02 × 10 -19 ), and COPD (z-score = 4.04; p = 5.40 × 10 -5 ). Surprisingly, this allele-C (rs56113850) was associated with increased smoking cessation (z-score = -8.17; p = 2.52 × 10 -26 ). This inverse relationship highlights the need for additional investigation to determine how CYP2A6 variation could increase smoking cessation while also increasing the risk of lung cancer and COPD likely through increased cigarettes smoked per day., (© 2020 Wiley Periodicals LLC.)

Introduction: Most people who smoke cigarettes are not willing (ie, not ready) to make a quit attempt (QA) at any given time. Unfortunately, interventions intended to increase QAs and the success of QAs are only modestly effective. Identifying processes leading to QAs and quitting success could guide intervention development., Aims and Methods: This is a secondary analysis of a randomized factorial trial of 6 weeks of motivation-phase interventions among primary care patients (N = 517) who were initially unwilling to quit but were willing to reduce their smoking. Using logistic regression, we controlled for treatment condition and tested whether baseline or change in smoking-related constructs after 6 weeks of treatment predicted (1) making an at least 24 h QA between weeks 6 and 26 and (2) quitting success at week 26 (7-day point-prevalence abstinence among those who made a QA). Predictors included cigarettes/day, time to first cigarette, motivation to quit, quitting self-efficacy, anticipated urges to smoke if quit, positive affect, negative affect, and time spent around others who smoke., Results: In multivariable models that included all smoking-related constructs, changes in the following variables predicted initiating a QA above and beyond other variables: greater baseline time to first cigarette (odds ratio [OR] = 1.60), increases in time to first cigarette (OR = 1.27), and increases in quitting self-efficacy (OR = 1.14). Increased motivation to quit predicted conversion of a QA into quitting success at 26 weeks (OR = 1.36)., Conclusion: Predictors of making a QA differed from predictors of quitting success. Predictors of QAs and success could each serve as important treatment targets of motivation-phase interventions., Implications: Motivation-phase interventions for people initially unwilling to quit smoking cigarettes may be improved by striving to increase their (1) time to first cigarette and quitting self-efficacy to promote QAs and (2) motivation to quit to promote quit success. Future experimental tests of such interventions are needed to identify causal determinants of QAs and quitting success., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Heavy drinking is common among smokers and is associated with especially poor health outcomes. Varenicline may affect mechanisms and clinical outcomes that are relevant for both smoking cessation and alcohol use. The current study examines whether varenicline, relative to nicotine replacement therapy, yields better smoking cessation outcomes among binge drinking smokers., Method: Secondary data analyses of a comparative effectiveness randomized controlled trial of three smoking cessation pharmacotherapies (12 weeks of varenicline, nicotine patch, or nicotine patch and lozenge) paired with six counseling sessions were conducted. Adult daily cigarette smokers (N = 1,078, 52% female) reported patterns of alcohol use, cigarette craving, and alcohol-related cigarette craving at baseline and over 4 weeks after quitting. Smoking cessation outcome was 7-day biochemically confirmed point-prevalence abstinence., Results: Binge drinkers had higher relapse rates than moderate drinkers at 4-week post-target quit day but not at the end of treatment or long-term follow up (12 and 26 weeks). Varenicline did not yield superior smoking cessation outcomes among binge drinkers, nor did it affect alcohol use early in the quit attempt. Varenicline did produce relatively large reductions in alcohol-related cigarette craving and overall cigarette craving during the first 4 weeks after quitting., Conclusions: Varenicline did not yield higher smoking abstinence rates or reduce alcohol use among binge drinkers. Varenicline did reduce alcohol-related cigarette craving but this did not translate to meaningful differences in smoking abstinence. Varenicline's effects on smoking abstinence do not appear to vary significantly as a function of drinking status.

Tobacco cessation after cancer diagnosis leads to better patient outcomes. However, tobacco treatment services are frequently unavailable in cancer care settings, and multilevel implementation challenges can impede uptake of new programs. The National Cancer Institute (NCI) dedicated Cancer Moonshot funding through the Cancer Center Cessation Initiative (C3I) for NCI-Designated Cancer Centers to implement or enhance the implementation of tobacco treatment services. We examined a pragmatic application of the RE-AIM framework (reach, effectiveness, adoption, implementation, and maintenance) to evaluate tobacco treatment programs implemented within Cancer Centers funded through C3I. Using three C3I-funded Centers as examples, we describe how each RE-AIM construct was operationalized to evaluate the implementation of a wide range of cessation services (e.g., tobacco use screening, counseling, Quitline referral, pharmacotherapy) in this heterogeneous group of cancer care settings. We discuss the practical challenges encountered in assessing RE-AIM constructs in real world situations, including using the electronic health record (EHR) to aid in assessment. Reach and effectiveness evaluation required that Centers define the setting(s) where cessation services were implemented (to determine the "denominator"), enumerate the patient population, report current patient tobacco use, patient engagement in tobacco treatment, and 6-month cessation outcomes. To reduce site heterogeneity, increase data accuracy, and reduce burden, reach was frequently captured via standardized EHR enhancements that improved the identification of current smokers and tobacco treatment referrals. Effectiveness was determined by cessation outcomes (30-day point prevalence abstinence at 6-months post-engagement) assessed through a variety of data collection approaches. Adoption was measured by the characteristics and proportion of targeted cancer care settings and clinicians engaged in cessation service delivery. Implementation was assessed by examining the delivery of tobacco screening assessments and intervention components across sites, and provider-level implementation consistency. Maintenance assessments identified whether tobacco treatment services continued in the setting after implementation and documented the sustainability plan and organizational commitment to continued delivery. In sum, this paper demonstrates a pragmatic approach to using RE-AIM as an evaluation framework that yields relevant outcomes on common implementation metrics across widely differing tobacco treatment approaches and settings., (Copyright © 2020 D'Angelo, Ramsey, Rolland, Chen, Bernstein, Fucito, Webb Hooper, Adsit, Pauk, Rosenblum, Cinciripini, Joseph, Ostroff, Warren, Fiore and Baker.)

Background: Low-income smokers experience greater difficulty in quitting smoking than do other smokers. Providing financial incentives for treatment engagement increases smoking cessation success. This study models the cost-effectiveness of varying levels of financial incentives to maximise return on investment (ROI) for engaging low-income Medicaid recipients who smoke to take calls from a tobacco quit line., Methods: Participants (N=1900) were recruited from May 2013 to June 2015 through quit line-based (n=980), clinic-based (n=444) or community-based referrals (n=476) into the Wisconsin Medicaid Quit Line Incentive project. Incentive (n=948) and control group participants (n=952) received $30 versus $0 per call, respectively, for taking up to five Wisconsin Tobacco Quit Line (WTQL) calls. Cost-effectiveness analyses estimated the incremental cost-effectiveness ratio for alternative financial incentives for engagement with WTQL calls. Probabilistic sensitivity analysis was employed to determine an optimal strategy for financial incentives to minimise the cost per individual who quit smoking., Results: Using fixed payments, the incremental cost-effectiveness ratio of $2316 per smoker who quit in the randomised trial decreased to $2150 per smoker who quit when the incentives were modelled at $20 per each of five WTQL calls taken. Using variable payments, the minimal cost per additional smoker who quit was $2125 when incentives for the first four WTQL calls were set at $20, and the financial payment for the fifth WTQL call was set at $70., Conclusions: Modelling suggests that financial incentives in the amount of $20 per call for taking the first four quit line calls and $70 for taking a fifth quit line call maximise ROI to engage low-income smokers with evidence-based smoking cessation treatment., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Electronic cigarettes (e-cigarettes) have drastically changed the nicotine and tobacco product landscape. However, their potential public health impact is still unclear. A reliable and valid measure of e-cigarette dependence would likely advance assessment and prognostication of the public health impact of e-cigarettes. The aim of this research was to examine the internal consistency, structure, and validity of three e-cigarette dependence scales., Methods: Adult dual users (smokers who also vape, N = 256) enrolled in an observational cohort study (45.1% women, 70.7% white). At baseline, participants completed the e-cigarette Fagerström Test of Cigarette Dependence (e-FTCD), the e-cigarette Wisconsin Inventory of Smoking Dependence Motives (e-WISDM), and the Penn State Electronic Cigarette Dependence Index (PS-ECDI). All participants provided a urine sample for cotinine analysis and reported e-cigarette use at 1 year., Results: The e-WISDM subscales had the highest internal consistency (α = .81-.96), then the PS-ECDI (α = .74) and e-FTCD (α = .51). A single-factor structure for the e-FTCD and an 11-factor structure for the e-WISDM were supported, but the PS-ECDI did not have a single-factor structure. All three e-cigarette dependence scales were highly correlated with validation criteria including continued e-cigarette use at 1 year, but not with e-liquid nicotine concentration or cotinine., Conclusions: The e-WISDM and PS-ECDI had stronger internal consistency than did the e-FTCD, despite the e-FTCD's single-factor structure, but all 3 measures appear to be valid measures of e-cigarette dependence as suggested by their significant relations with self-perceived addiction, heavy use, early use after overnight deprivation, and continued use over time., Implications: This research provides empirical support for three e-cigarette dependence measures: the e-FTCD, the PS-ECDI, and the e-WISDM among dual users of e-cigarettes and combustible cigarettes. The PS-ECDI and e-WISDM are more reliable, but all three measures were strongly correlated with key dependence constructs such as heavy use and continued use over time., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Dual use of combustible and electronic cigarettes (e-cigarettes) is a growing use pattern; more than half of e-cigarette users are dual users. However, little is known regarding the course of dual use; for example, the likelihood of discontinuation of either combustible or e-cigarettes or both., Methods: Adult daily smokers and dual users (daily smokers who also vaped at least once per week) who did not intend to quit use of either product in the next 30 days participated in a longitudinal, observational study (N = 322, 51.2% women, 62.7% white, mean age = 42.27 [SD = 14.05]). At baseline, participants completed demographics and smoking and vaping history assessments. They also reported daily cigarette and e-cigarette use via timeline follow-back assessment and provided a breath sample for carbon monoxide assay at 4-month intervals for 1 year., Results: Of those who completed the year 1 follow-up, 1.9% baseline smokers and 8.0% dual users achieved biochemically confirmed seven-day point-prevalence abstinence from combustible cigarettes (χ2 = 4.57, p = .03). Of initial dual users, by 1 year 43.9% were smoking only, 48.8% continued dual use, 5.9% were vaping only, and 1.4% abstained from both products. Among baseline smokers, 92.3% continued as exclusive smokers. Baseline dual users who continued e-cigarette use were more likely to be white and report higher baseline e-cigarette dependence., Conclusions: In this community sample, the majority of dual users transitioned to exclusive smoking. A higher percentage of dual users quit smoking than smokers, but attrition and baseline differences between the groups compromise strong conclusions. Sustained e-cigarette use was related to baseline e-cigarette dependence., Implications: This research suggests that dual use of combustible and e-cigarettes is not a sustained pattern for the majority of dual users, but it is more likely to be a continued pattern if the user is more dependent on e-cigarettes. There was evidence that dual users were more likely to quit smoking than exclusive smokers, but this may be due to factors other than their dual use., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: Strong cravings to smoke are an obstacle to cessation success. Unfortunately, cessation medication and counseling only modestly quell craving. This pilot study was designed to examine the feasibility of mobile games as a response strategy to craving and whether a fully powered trial is warranted. Materials and Methods: Smokers interested in quitting ( N  = 30) were offered 4 weeks of nicotine patch plus counseling and randomized to quit with (games-on) versus without (games-off) access to 11 commercial mobile games. Outcomes included post-target quit day (TQD) game play, craving, smoking, and quitting. Almost all P' s were >0.05; outcomes should be interpreted with caution due to the small N . Results: Of games-on participants ( n  = 16), one played games ≥80% of days post-TQD (22/28 days); 38% played >1/3 of days; 25% did not play. Games-on participants reported games moderately helped them cope with cravings; M  = 3.22 on a scale from 1 ( not at all ) to 5 ( very much ). Also, games-on participants showed a slight decrease in craving from baseline to 1-week post-TQD (2.35-2.25 on a 0-5 point-scale), whereas games-off participants showed an increase (2.01-2.53). Games-on participants showed greater decreases in craving after playing a game than after the passage of time (when an app imposed a 2-minute wait period following their game request), but there was little evidence games-on versus games-off participants differed in mean post-TQD cigarettes/day. Games-on participants reported modestly but not significantly higher continuous abstinence through day 28 (31.3% vs. 21.4%). Conclusion: Feasibility results encourage a fully powered trial of this easily disseminable intervention. Clinical Trial Registration: ClinicalTrials.gov NCT02164383.

Introduction: This study examined relations of two affective vulnerabilities, high anxiety sensitivity (AS) and low distress tolerance (DT), with tobacco dependence, withdrawal, smoking cessation, and pharmacotherapy response., Methods: Smokers interested in quitting (N = 1067; 52.2% female, 28.1% African American) were randomized to 12 weeks of nicotine patch, nicotine patch plus nicotine lozenge, or varenicline. Baseline questionnaires assessed AS, DT, negative affect, anxiety, and dependence. Withdrawal was assessed the first-week post-quit via ecological momentary assessment., Results: DT, but not AS, predicted biochemically confirmed point-prevalence abstinence at multiple endpoints: weeks 4, 12, 26, and 52 post-quit (ps < .05); relations remained after controlling for pharmacotherapy treatment, AS, baseline negative affect, anxiety, and anxiety disorder history (ps < .05). Additional exploratory analyses examining week 4 abstinence showed DT predicted abstinence (p = .004) even after controlling for baseline dependence, post-quit withdrawal (craving and negative affect), and treatment. DT moderated treatment effects on abstinence in exploratory analyses (interaction p = .025); those with high DT were especially likely to be abstinent at week 4 with patch plus lozenge versus patch alone., Conclusions: DT, but not AS, predicted abstinence over 1 year post-quit (higher DT was associated with higher quit rates), with little overlap with other affective measures. DT also predicted early abstinence independent of dependence and withdrawal symptoms. Results suggest low DT may play a meaningful role in motivation to use tobacco and constitute an additional affective risk factor for tobacco cessation failure beyond negative affect or clinical affective disorders., Implications: People in a stop-smoking study who reported a greater ability to tolerate distress were more likely to quit smoking and remain smoke-free 1 year later. Smokers with high DT were more likely to be smoke-free 4 weeks after their target quit day if they received nicotine patch plus nicotine lozenge rather than nicotine patch alone., Trial Registration: NCT01553084., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.)

Background We evaluated the effects of smoking and smoking cessation on aortic wave reflections (augmentation index), aortic pulse wave velocity, and carotid artery distensibility and stiffness (distensibility coefficient, Young's elastic modulus). Methods and Results Current smokers underwent carotid, radial, and femoral artery tonometry and carotid ultrasound at baseline and 3 years after a quit attempt. Baseline associations of smoking heaviness markers (exhaled carbon monoxide and cigarettes smoked/d) and effects of smoking cessation at year 3 on changes in arterial measures were assessed using multivariable linear regression models. The 1417 smokers (54% female) were mean (SD) 49.3 (11.6) years old and smoked 17.2 (8.3) cigarettes/d (exhaled carbon monoxide 14.7 [8.2] parts per million). Arterial measures were associated more strongly with age, blood pressure (BP), and waist circumference than with smoking heaviness markers. Augmentation index was associated independently with carbon monoxide ( P =0.004). Pulse wave velocity, distensibility coefficient, and Young's elastic modulus had small, inconsistent associations with smoking heaviness markers. At year 3, augmentation index improved with smoking cessation ( P =0.006) despite more weight gain (2.54 vs 0.36 kg, P <0.001) and insulin resistance ( P =0.001) among abstainers, but distensibility coefficient decreased ( P =0.004). Changes in arterial measures were related more strongly to changes in BP than smoking cessation. Conclusions Arterial wave reflection and stiffness measures were associated more strongly with age, BP, and waist circumference than smoking heaviness. Smoking cessation was associated with weight gain and increased insulin resistance. Changes in arterial measures were predicted by changes in BP, highlighting the need to address weight gain and BP changes during a quit attempt.

Carotid artery grayscale ultrasound echogenicity and texture features predict cardiovascular disease events. We evaluated the longitudinal effects of smoking cessation on four grayscale ultrasound measures. This was a secondary analysis of data from 188 age, sex, and body mass index (BMI)-matched smokers (94 eventual abstainers [EA], 94 continued smokers [CS]) from a smoking cessation trial that had carotid ultrasound examinations at baseline and after 3 years. General linear models that included time, smoking group (EA or CS), and a time*smoking interaction term were used to examine the impact of smoking abstinence on carotid artery grayscale marker values at year 3. Participants were mean (SD) 50.3 (11.4) years old (57% female, 86% white). The baseline grayscale median value (GSM) was inversely correlated with age, BMI, insulin resistance, and smoking pack-years ( r = -0.20 to -0.30, p < 0.007 for all). There was a significant time*smoking status interaction for predicting GSM at year 3: GSM decreased significantly in the EA group compared to the CS group (-3.63 [13.00] vs CS 0.39 [12.06] units; p = 0.029). BMI increased more in the EA than the CS group (2.42 [3.00] vs CS 0.35 [2.57] kg/m 2 ; p < 0.001). After adjusting for changes in BMI, the time*smoking status interaction no longer was significant ( p = 0.138). From baseline to year 3, contrast increased similarly in both groups. Entropy and angular second moment did not change significantly in either group. Changes in carotid ultrasound echogenicity and grayscale texture features during a smoking cessation attempt are modest and mostly related to weight gain. Clinicaltrials.gov Identifier: NCT01553084.

Background: Nonadherence to smoking cessation medication is a frequent problem. Identifying pre-quit predictors of nonadherence may help explain nonadherence and suggest tailored interventions to address it., Aims: Identify and characterize subgroups of smokers based on adherence to nicotine replacement therapy (NRT)., Method: Secondary classification tree analyses of data from a 2-arm randomized controlled trial of Recommended Usual Care (R-UC, n = 315) versus Abstinence-Optimized Treatment (A-OT, n = 308) were conducted. R-UC comprised 8 weeks of nicotine patch plus brief counseling whereas A-OT comprised 3 weeks of pre-quit mini-lozenges, 26 weeks of nicotine patch plus mini-lozenges, 11 counseling contacts, and 7-11 automated reminders to use medication. Analyses identified subgroups of smokers highly adherent to nicotine patch use in both treatment conditions, and identified subgroups of A-OT participants highly adherent to mini-lozenges., Results: Varied facets of nicotine dependence predicted adherence across treatment conditions 4 weeks post-quit and between 4- and 16-weeks post-quit in A-OT, with greater baseline dependence and greater smoking trigger exposure and reactivity predicting greater medication use. Greater quitting motivation and confidence, and believing that stop smoking medication was safe and easy to use were associated with greater adherence., Conclusion: Adherence was especially high in those who were more dependent and more exposed to smoking triggers. Quitting motivation and confidence predicted greater adherence, while negative beliefs about medication safety and acceptability predicted worse adherence. Results suggest that adherent use of medication may reflect a rational appraisal of the likelihood that one will need medication and will benefit from it., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Quitting smoking leads to improved outcomes for patients with cancer, yet too few patients receive cessation services during their oncology healthcare visits. The National Cancer Institute (NCI) dedicated Cancer Moonshot funding for NCI-Designated Cancer Centers to develop a population-based approach to reach all patients who smoke with tobacco treatment services. As a result, the Cancer Center Cessation Initiative (C3I) offers an unparalleled opportunity to identify effective implementation strategies and barriers to delivering tobacco treatment services across multiple clinical oncology settings. Over one year after receiving funding, the first cohort of C3I funded Centers demonstrated progress in hiring tobacco treatment specialists, adding new tobacco treatment programs, and integrating EHR-based tobacco treatment referrals. However, tobacco treatment program reach remains low in some settings, even using a broad definition of patient engagement. Centers identified implementation challenges related to staff training needs, devising new clinical workflows, and engagement of IT leadership. Understanding implementation challenges may help other clinical oncology settings effectively implement tobacco treatment programs, leading to improved cancer outcomes by helping patients quit smoking., (©2019 American Association for Cancer Research.)

Introduction: We examined past-12-month quit attempts and smoking cessation from 2006 to 2016 while accounting for demographic shifts in the US population. In addition, we sought to understand whether the current use of electronic cigarettes was associated with a change in past-12-month quit attempts and successful smoking cessation at the population level., Methods: We analyzed data from 25- to 44-year-olds from the National Health Interview Survey (NHIS) from 2006 to 2016 (N = 26,354) and the Tobacco Use Supplement to the Current Population Survey (TUS-CPS) in 2006-2007, 2010-2011, and 2014-2015 (N = 33,627). Data on e-cigarette use were available in the 2014-2016 NHIS and 2014-2015 TUS-CPS surveys., Results: Past-12-month quit attempts and smoking cessation increased in recent years compared with 2006. Current e-cigarette use was associated with higher quit attempts (adjusted odds ratio [aOR] = 2.29, 95% confidence interval [CI] = 1.87 to 2.81, p < .001) and greater smoking cessation (aOR = 1.64, 95% CI = 1.21 to 2.21, p = .001) in the NHIS. Multivariable logistic regression of the TUS-CPS data showed that current e-cigarette use was similarly significantly associated with increased past-12-month quit attempts and smoking cessation. Significant interactions were found for smoking frequency (everyday and some-day smoking) and current e-cigarette use for both outcomes (p < .0001) with the strongest positive effects seen in everyday smokers., Conclusions: Compared with 2006, past-12-month quit attempts and smoking cessation increased among adults aged 25-44 in recent years. Current e-cigarette use was associated with increased past-12-month quit attempts and successful smoking cessation among established smokers. These findings are relevant to future tobacco policy decisions., Implications: E-cigarettes were introduced into the US market over the past decade. During this period, past-12-month quit attempts and smoking cessation have increased among US adults aged 25-44. These trends are inconsistent with the hypothesis that e-cigarette use is delaying quit attempts and leading to decreased smoking cessation. In contrast, current e-cigarette use was associated with significantly higher past-12-month quit attempts and past-12-month cessation. These findings suggest that e-cigarette use contributes to a reduction in combustible cigarette use among established smokers., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: The study sought to determine whether interoperable, electronic health record-based referral (eReferral) produces higher rates of referral and connection to a state tobacco quitline than does fax-based referral, thus addressing low rates of smoking treatment delivery in health care., Materials and Methods: Twenty-three primary care clinics from 2 healthcare systems (A and B) in Wisconsin were randomized, unblinded, over 2016-2017, to 2 smoking treatment referral methods: paper-based fax-to-quit (system A =6, system B = 6) or electronic (eReferral; system A = 5, system B = 6). Both methods referred adult patients who smoked to the Wisconsin Tobacco Quitline. A total of 14 636 smokers were seen in the 2 systems (system A: 54.5% women, mean age 48.2 years; system B: 53.8% women, mean age 50.2 years)., Results: Clinics with eReferral, vs fax-to-quit, referred a higher percentage of adult smokers to the quitline: system A clinic referral rate = 17.9% (95% confidence interval [CI], 17.2%-18.5%) vs 3.8% (95% CI, 3.5%-4.2%) (P < .001); system B clinic referral rate = 18.9% (95% CI, 18.3%-19.6%) vs 5.2% (95% CI, 4.9%-5.6%) (P < .001). Average rates of quitline connection were higher in eReferral than F2Q clinics: system A = 5.4% (95% CI, 5.0%-5.8%) vs 1.3% (95% CI, 1.1%-1.5%) (P < .001); system B = 5.3% (95% CI, 5.0%-5.7%) vs 2.0% (95% CI, 1.8%-2.2%) (P < .001)., Discussion: Electronic health record-based eReferral provided an effective, closed-loop, interoperable means of referring patients who smoke to telephone quitline services, producing referral rates 3-4 times higher than the current standard of care (fax referral), including especially high rates of referral of underserved individuals., Conclusions: eReferral may help address the challenge of providing smokers with treatment for tobacco use during busy primary care visits.ClinicalTrials.gov; No. NCT02735382., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: Effective smoking cessation medications are readily available but may be underutilized in hospital settings. In our large, tertiary care hospital, we aimed to (1) characterize patient tobacco use prevalence across medical specialties, (2) determine smoking cessation pharmacotherapy prescription variation across specialties, and (3) identify opportunities for improvement in practice., Methods: Using electronic health records at Barnes Jewish Hospital, we gathered demographic data, admitting service, admission route, length of stay, self-reported tobacco use, and smoking cessation prescriptions over a 6-year period, from 2010 to 2016. We then compared tobacco use prevalence and smoking cessation prescriptions across medical specialties using a cross-sectional, retrospective design., Results: Past 12-month tobacco use was reported by patients in 27.9% of inpatient admissions; prescriptions for smoking cessation pharmacotherapy were provided during 21.5% of these hospitalizations. The proportion of patients reporting tobacco use was highest in psychiatry (55.3%) and lowest in orthopedic surgery (17.1%). Psychiatric patients who reported tobacco use were most likely to receive pharmacotherapy (71.8% of admissions), and plastic surgery patients were least likely (4.7% of admissions). Compared with Caucasian tobacco users, African American patients who used tobacco products were less likely to receive smoking cessation medications (adjusted odds ratio [aOR] = 0.65; 95% confidence interval [CI] = 0.62 to 0.68)., Conclusions: Among hospitalized tobacco users, safe and cost-effective pharmacotherapies are under-prescribed. We identified substantial variation in prescribing practices across different medical specialties and demographic groups, suggesting the need for an electronic medical record protocol that facilitates consistent tobacco use cessation pharmacotherapy treatment., Implications: Tobacco use cessation pharmacotherapy is underutilized during hospitalization, and prescription rates vary greatly across medical specialties and patient characteristics. Hospitals may benefit from implementing policies and practices that standardize and automate the offer of smoking pharmacotherapy for all hospitalized patients who use tobacco., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)