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Women physicians are promoted less often, more likely to experience harassment and bias, and paid less than their male peers. Although many institutions have developed initiatives to help women physicians overcome these professional hurdles, few are specifically geared toward physicians-in-training. The Women in Medicine Trainees’ Council (WIMTC) was created in 2015 to support the professional advancement of women physicians-in-training in the Massachusetts General Hospital Department of Medicine (MGH-DOM). In a 2021 survey, the majority of respondents agreed that the WIMTC ameliorated the challenges of being a woman physician-in-training and contributed positively to overall wellness. Nearly all agreed that they would advise other training programs to implement a similar program. We present our model for women-trainee support to further the collective advancement of women physicians.

Introduction The COVID-19 pandemic disrupted cancer screening and treatment delivery, but COVID-19’s impact on tobacco cessation treatment for cancer patients who smoke has not been widely explored. Aims and Methods We conducted a sequential cross-sectional analysis of data collected from 34 National Cancer Institute (NCI)-designated cancer centers participating in NCI’s Cancer Center Cessation Initiative (C3I), across three reporting periods: one prior to COVID-19 (January–June 2019) and two during the pandemic (January–June 2020, January–June 2021). Using McNemar’s Test of Homogeneity, we assessed changes in services offered and implementation activities over time. Results The proportion of centers offering remote treatment services increased each year for Quitline referrals (56%, 68%, and 91%; p = .000), telephone counseling (59%, 79%, and 94%; p = .002), and referrals to Smokefree TXT (27%, 47%, and 56%; p = .006). Centers offering video-based counseling increased from 2020 to 2021 (18% to 59%; p = .006), Fewer than 10% of centers reported laying off tobacco treatment staff. Compared to early 2020, in 2021 C3I centers reported improvements in their ability to maintain staff and clinician morale, refer to external treatment services, train providers to deliver tobacco treatment, and modify clinical workflows. Conclusions The COVID-19 pandemic necessitated a rapid transition to new telehealth program delivery of tobacco treatment for patients with cancer. C3I cancer centers adjusted rapidly to challenges presented by the pandemic, with improvements reported in staff morale and ability to train providers, refer patients to tobacco treatment, and modify clinical workflows. These factors enabled C3I centers to sustain evidence-based tobacco treatment implementation during and beyond the COVID-19 pandemic. Implications This work describes how NCI-designated cancer centers participating in the Cancer Center Cessation Initiative (C3I) adapted to challenges to sustain evidence-based tobacco use treatment programs during the COVID-19 pandemic. This work offers a model for resilience and rapid transition to remote tobacco treatment services delivery and proposes a policy and research agenda for telehealth services as an approach to sustaining evidence-based tobacco treatment programs.

Introduction The nicotine metabolite ratio (NMR), a biomarker of CYP2A6-mediated nicotine metabolism, predicts efficacy of nicotine replacement therapy (NRT), with fast metabolizers benefiting less than slow metabolizers. Whether treatment support to optimize NRT use (henceforth “treatment support”) modifies this pharmacogenetic relationship is unknown. Methods Hospitalized adult daily smokers were assigned to one of two post-discharge smoking cessation interventions offering NRT and counseling: (1) Transitional Tobacco Care Management, which delivered enhanced treatment support via free combination NRT at discharge and automated counseling, and (2) a quitline-based approach representing usual care (UC). The primary outcome was biochemically verified 7-day point prevalence abstinence 6 months after discharge. Secondary outcomes were use of NRT and counseling during the 3-month intervention period. Logistic regression models tested for interactions between NMR and intervention, controlling for sex, race, alcohol use, and BMI. Results Participants (N=321) were classified as slow (n=80) or fast (n=241) metabolizers relative to the first quartile of NMR (0.012-0.219 vs. 0.221-3.45, respectively). Under UC, fast (vs. slow) metabolizers had lower odds of abstinence at 6 months (aOR 0.35, 95% CI 0.13-0.95) and similar odds of NRT and counseling use. Compared to UC, enhanced treatment support increased abstinence (aOR 2.13, 95% CI 0.98-4.64) and use of combination NRT (aOR 4.62, 95% CI 2.57-8.31) in fast metabolizers, while reducing abstinence in slow metabolizers (aOR 0.21, 95% CI 0.05-0.87; NMR-by-intervention interaction p=0.004). Conclusions Treatment support increased abstinence and optimal use of NRT among fast nicotine metabolizers, thereby mitigating the gap in abstinence between fast and slow metabolizers. Implications In this secondary analysis of two smoking cessation interventions for recently hospitalized smokers, fast nicotine metabolizers quit at lower rates than slow metabolizers, but providing fast metabolizers with enhanced treatment support doubled quit rates in this group and mitigated the disparity in abstinence between fast and slow metabolizers. If validated, these findings could lead to personalized approaches to smoking cessation treatment that improve outcomes by targeting treatment support to those who need it most.

Background South Africa is facing a convergence of communicable diseases (CDs) and non-communicable diseases (NCDs). The contribution of tobacco use to the burden of these conditions is unknown. Methods We analyzed the associations between current tobacco smoking and four important CDs and NCDs in Vukuzazi, a cross-sectional study of individuals aged 15 years and older conducted between 2018–2020 in a demographic surveillance area in KwaZulu-Natal, South Africa. Data on HIV, active tuberculosis (TB), hypertension and diabetes mellitus were collected via direct measurement from participants. Results Of 18,024 participants (68% female, median age 37 years [interquartile rage 23–56 years]), 1,301 (7.2%) reported current smoking. Prevalence of HIV infection was similarly high among people who currently smoked (34.6%) and people who had never smoked (33.9%). However, among people living with HIV (PLWH), there was a higher prevalence of detectable viremia in people reporting current smoking compared to people who reported never smoking (28.8% vs. 16.6%; p-value

BACKGROUND: Recent prevalence estimates of cannabis use among individuals receiving medication treatment for OUD (MOUD) are lacking, and no study has characterized cannabis route of administration (cROA) in this population. These knowledge gaps are relevant because cannabis’ effects and health outcomes vary by cROA and the availability and perceptions of cROA (e.g., vaping devices) are changing. METHODS: The Vaping In Buprenorphine-treated patients Evaluation (VIBE) cross-sectional survey assessed the prevalence and correlates of cannabis use and cROA among adults receiving buprenorphine MOUD from 02/20 to 07/20 at five community health centers in Massachusetts, a state with legal recreational and medical cannabis use. RESULTS: Among the 92/222 (41%) respondents reporting past 30-day cannabis use, smoking was the most common cROA (75%), followed by vaping (38%), and eating (26%). Smoking was more often used as a single cROA vs. in combination others (p=0.01), whereas vaping, eating, and dabbing were more often used in combination with another cROA (all p

Introduction With concerns about tobacco use being a risk factor for severe disease from COVID-19, understanding nicotine- and tobacco-use patterns is important for preventive efforts. This study aims to understand changes in combustible cigarette and E-cigarette use among U.S. adults. Methods In August 2020, a cross-sectional survey of a nationally representative sample of adults aged ≥18 years in the National Opinion Research Center's AmeriSpeak Panel who reported past 6–month use of combustible cigarettes or E-cigarettes was conducted. Multivariable logistic regression assessed the factors associated with increased product use and quit attempts since hearing about COVID-19. Results A total of 1,024 past 6–month cigarette smokers/E-cigarette users were surveyed. Among cigarette smokers, 45% reported no change in cigarette smoking, and 33% reported increased cigarette smoking since hearing about COVID-19. Higher stress was associated with increased cigarette smoking. Among E-cigarette users, 41% reported no change in E-cigarette use, and 23% reported increasing E-cigarette use. A total of 26% of cigarette smokers and 41% of E-cigarette users tried to quit because of COVID-19. Higher perceived risk of COVID-19 was associated with attempts to quit combustible cigarettes (AOR=2.37, 95% CI=1.59, 3.55) and E-cigarettes (AOR=3.14, 95% CI=1.73, 5.70). Conclusions Cigarette and E-cigarette use patterns varied in response to the COVID-19 pandemic. Most cigarette smokers and E-cigarette users perceived product use as increasing COVID-19‒related health risks, and this was associated with attempts to quit. Some cigarette smokers, especially those reporting higher stress, increased product use. Proactive provision of cessation support to smokers and E-cigarette users may help mitigate the stress-related increases in product use during the COVID-19 pandemic.

Introduction Many cancer patients who smoke report concurrent e-cigarette use. Using a mixed-methods approach, we aimed to (1) describe longitudinal e-cigarette use over 6 months after a cancer diagnosis and (2) assess the association between e-cigarette use and smoking cessation, among cancer patients in a smoking cessation trial. Aims and Methods Data were from a 2-site randomized controlled trial of Standard (brief counseling) versus Intensive treatment (sustained counseling plus smoking cessation medication) in individuals who smoke recently diagnosed with cancer. Participants (n = 303) reported e-cigarette use at baseline, 3 months, and 6 months. Biochemically-verified past 7-day cigarette abstinence was collected at 6 months. Qualitative interviews at 6 months explored factors related to e-cigarette use. Results E-cigarette use prevalence was highest between baseline and 3 months (16%) and declined over time. Participants using e-cigarettes at follow-up had higher baseline cigarette dependence and smoked more heavily. Multivariable analyses found no significant association between follow-up e-cigarette use and 6-month cigarette abstinence. E-cigarette use at follow-up was higher in the Standard versus Intensive treatment group (p = .003 and .001 at 3 and 6 mo, respectively). Smoking cessation and health concerns were primary reasons for using e-cigarettes. Conclusions Among individuals who smoke recently diagnosed with cancer and enrolled in a smoking cessation intervention trial, e-cigarette use during trial participation was not associated with smoking abstinence. Individuals who chose to use e-cigarettes were less likely to be receiving intensive cessation support as part of the trial. Further studies are needed to evaluate the association between e-cigarette use and smoking cessation in cancer patients. Implications E-cigarette use was not associated with cigarette abstinence at 6 months among adults who smoke recently diagnosed with cancer enrolled in a smoking cessation trial. Individuals with easier access to evidence-based smoking cessation treatment may be less likely to use e-cigarettes.

More than 40% of people with human immunodeficiency virus (PWH) in the United States smoke tobacco cigarettes. Among those on antiretroviral therapy, smoking decreases life expectancy more than human immunodeficiency virus (HIV) itself. Most PWH who smoke want to quit, but tobacco dependence treatment has not been widely integrated into HIV care. This article summarizes the epidemiology of tobacco use among PWH, health consequences of tobacco use and benefits of cessation in PWH, and studies of treatment for tobacco dependence among the general population and among PWH. We provide practical guidance for providers to treat tobacco dependence among PWH. A 3-step Ask-Advise-Connect framework includes asking about tobacco use routinely during clinical encounters, advising about tobacco cessation with emphasis on the benefits of cessation, and actively connecting patients to cessation treatments, including prescription of pharmacotherapy (preferably varenicline) and direct connection to behavioral interventions via telephone quitline or other means to increase the likelihood of a successful quit attempt.

There is strong evidence that cigarette smoking causes adverse outcomes in people with cancer. However, more research is needed regarding those effects and the effects of alternative tobacco products and of secondhand smoke, the effects of cessation (before diagnosis, during treatment, or during survivorship), the biologic mechanisms, and optimal strategies for tobacco dependence treatment in oncology. Fundamentally, tobacco is an important source of variation in clinical treatment trials. Nevertheless, tobacco use assessment has not been uniform in clinical trials. Progress has been impeded by a lack of consensus regarding tobacco use assessment suitable for cancer patients. The NCI-AACR Cancer Patient Tobacco Use Assessment Task Force identified priority research areas and developed recommendations for assessment items and timing of assessment in cancer research. A cognitive interview study was conducted with 30 cancer patients at the NIH Clinical Center to evaluate and improve the measurement items. The resulting Cancer Patient Tobacco Use Questionnaire (C-TUQ) includes “Core” items for minimal assessment of tobacco use at initial and follow-up time points, and an “Extension” set. Domains include the following: cigarette and other tobacco use status, intensity, and past use; use relative to cancer diagnosis and treatment; cessation approaches and history; and secondhand smoke exposure. The Task Force recommends that assessment occur at study entry and, at a minimum, at the end of protocol therapy in clinical trials. Broad adoption of the recommended measures and timing protocol, and pursuit of the recommended research priorities, will help us to achieve a clearer understanding of the significance of tobacco use and cessation for cancer patients. Clin Cancer Res; 22(8); 1907–13. ©2016 AACR.

This file contains the NCI-AACR tobacco use questionnaire and notes about its use.

This file contains detailed information about the methodology.

Aims This study aims to compare biomarkers of potential harm between people switching from smoking combustible cigarettes (CC) completely to electronic cigarettes (EC), continuing to smoke CC, using both EC and CC (dual users) and using neither (abstainers), based on behaviour during EC intervention studies. Design Secondary analysis following systematic review, incorporating inverse variance random-effects meta-analysis and effect direction plots. Setting This study was conducted in Greece, Italy, Poland, the United Kingdom and the United States. Participants A total of 1299 adults smoking CC (nine studies) and provided EC. Measurements Measuremens were conducted using carbon monoxide (CO) and 26 other biomarkers. Findings In pooled analyses, exhaled CO (eCO) was lower in EC versus EC + CC [mean difference (MD) = −4.40 parts per million (p.p.m.), 95% confidence interval (CI) = −12.04 to 3.24, two studies] and CC (MD = −9.57 p.p.m., 95% CI = −17.30 to −1.83, three studies). eCO was lower in dual users versus CC only (MD = −1.91 p.p.m., 95% CI = −3.38 to −0.45, two studies). Magnitude rather than direction of effect drove substantial statistical heterogeneity. Effect direction plots were used for other biomarkers. Comparing EC with CC, 12 of 13 biomarkers were significantly lower in EC users, with no difference for the 13th. Comparing EC with dual users, 12 of the 25 biomarkers were lower for EC, and five were lower for dual use. For the remaining eight measures, single studies did not detect statistically significant differences, or the multiple studies contributing to the outcome had inconsistent results. Only one study provided data comparing dual use with CC; of the 13 biomarkers measured, 12 were significantly lower in the dual use group, with no statistically significant difference detected for the 13th. Only one study provided data on abstainers. Conclusions Switching from smoking to vaping or dual use appears to reduce levels of biomarkers of potential harm significantly.

Background It is unknown whether post-discharge navigation enhances the impact of hospital-initiated addiction care. This study tested the incremental benefit of telephonic linkage to a post-discharge navigator for patients who received an addiction consultation during hospitalization. Methods A two-arm, randomized controlled trial of 395 hospitalized adults with substance use disorder who received an addiction consultation. The intervention group received post-discharge phone calls from a navigator to review the recommended treatment plan and address barriers to engagement on days 3, 7, 14, and 21. The primary outcome was days of alcohol or drug use in the past 30 assessed by Timeline Follow-back at 1 month. Results Follow-up assessment completion rates were 46% at 1 month, and 41%, at 2 months. At baseline, intervention and control groups did not differ in substance use patterns; 45% reported primary alcohol use, 43% drugs, and 12% both. Heroin was the most common drug. At baseline, mean days of past 30-day alcohol or drug use were 13.6 in the intervention and 14.9 in the control group. The median number of navigation calls completed was 3 out of 4. At 1 month, both groups reported less use (decrease of 4.8 in intervention vs. 4.2 days in control group, p = 0.49). There were no differences between groups at 2 months. Compared to controls, participants who received all four calls had a greater decrease in use with a mean 8.6 days decrease from baseline (difference of 4.4 days, p = 0.0009). Conclusion Post-discharge telephonic patient navigation did not further improve substance use outcomes following addiction consultation.

Background Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e‐liquid. Some people who smoke use ECs to stop or reduce smoking, but some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This is an update conducted as part of a living systematic review. Objectives To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long‐term smoking abstinence. Search methods We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 May 2021, and reference‐checked and contacted study authors. We screened abstracts from the Society for Research on Nicotine and Tobacco (SRNT) 2021 Annual Meeting. Selection criteria We included randomized controlled trials (RCTs) and randomized cross‐over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both. Data collection and analysis We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow‐up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants or both. We used a fixed‐effect Mantel‐Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta‐analyses. Main results We included 61 completed studies, representing 16,759 participants, of which 34 were RCTs. Five of the 61 included studies were new to this review update. Of the included studies, we rated seven (all contributing to our main comparisons) at low risk of bias overall, 42 at high risk overall (including all non‐randomized studies), and the remainder at unclear risk. There was moderate‐certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.53, 95% confidence interval (CI) 1.21 to 1.93; I2 = 0%; 4 studies, 1924 participants). In absolute terms, this might translate to an additional three quitters per 100 (95% CI 1 to 6). There was low‐certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.44, 95% CI 0.94 to 2.19: I2 = 0; 3 studies, 1183 participants). There was moderate‐certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non‐nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate‐certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 0.95, 95% CI 0.52 to 1.72; I2 = 0; 6 studies, 1033 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.61, 95% CI 1.44 to 4.74; I2 = 0%; 6 studies, 2886 participants). In absolute terms this represents an additional six quitters per 100 (95% CI 2 to 15). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that non‐serious AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants), and again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.51, 95% CI 0.70 to 3.24; I2 = 0%; 7 studies, 1303 participants). Data from non‐randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit. Authors' conclusions There is moderate‐certainty evidence that ECs with nicotine increase quit rates compared to NRT and compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non‐nicotine ECs. Overall incidence of SAEs was low across all study arms. We did not detect evidence of harm from nicotine EC, but longest follow‐up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up‐to‐date information to decision‐makers, this review is now a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

PURPOSE: More than half of individuals with serious mental illness (SMI) smoke, contributing to premature cancer mortality. A cancer diagnosis provides an opportunity to assist with smoking cessation; however, supportive oncology trials frequently exclude patients with SMI. To fill this gap, we examined differences in engagement and tobacco cessation in a pragmatic clinical trial. METHODS: We recruited 303 participants from two National Cancer Institute–designated Comprehensive Cancer Centers, of which 10% had prior diagnoses of SMI (major depressive disorder, bipolar disorder, and schizophrenia spectrum disorders). We compared self-reported smoking behaviors, patient attitudes and beliefs about cessation, and rates of trial completion, engagement, and smoking abstinence among recently diagnosed patients with cancer with and without SMI. Six months after trial completion, we completed qualitative interviews on barriers and facilitators to tobacco cessation in a random sample of participants with SMI. RESULTS: Trial participants with SMI had similar motivation to quit smoking as those without SMI. Additionally, participants with SMI had a similar ability to engage in a tobacco treatment trial (6.5 counseling sessions completed v 7.3 sessions) and benefit from tobacco treatment as those without SMI (32.3% v 27.8% 6-month quit rates). CONCLUSION: Patients with cancer and SMI were able to engage in and benefit from a tobacco cessation trial integrated into cancer care. A cancer diagnosis provides an opportunity to assist patients with SMI with smoking cessation referrals and treatment. Pragmatic supportive oncology trials that include a diverse population of adults with SMI are needed to inform care delivery and improve cancer outcomes for patients with SMI and cancer.

The US Preventive Services Task Force recommends lung cancer screening (LCS) to promote early lung cancer detection, and tobacco cessation services are strongly recommended in adjunct. Screen ASSIST (NCT03611881) is a randomized factorial trial to ascertain the best tobacco treatment intervention for smokers undergoing LCS; trial outreach is conducted during 3 recruitment points (RPs): when LCS is ordered (RP1), at screening (RP2), and following results (RP3). Among 177 enrollees enrolled from April 2019 to March 2020, 31.6% enrolled at RP1, 13.0% at RP2, and 55.4% at RP3. The average number of enrollees (per 1000 recruitment days) was 2.26 in RP1, 3.37 in RP2, and 1.04 in RP3. LCS provides an opportunity to offer tobacco treatment at multiple clinical timepoints. Repeated and proactive outreach throughout the LCS experience was beneficial to enrolling patients in tobacco cessation services.

The topic of e-cigarettes is controversial. Opponents focus on e-cigarettes’ risks for young people, while supporters emphasize the potential for e-cigarettes to assist smokers in quitting smoking. Most US health organizations, media coverage, and policymakers have focused primarily on risks to youths. Because of their messaging, much of the public—including most smokers—now consider e-cigarette use as dangerous as or more dangerous than smoking. By contrast, the National Academies of Science, Engineering, and Medicine concluded that e-cigarette use is likely far less hazardous than smoking. Policies intended to reduce adolescent vaping may also reduce adult smokers’ use of e-cigarettes in quit attempts. Because evidence indicates that e-cigarette use can increase the odds of quitting smoking, many scientists, including this essay’s authors, encourage the health community, media, and policymakers to more carefully weigh vaping’s potential to reduce adult smoking-attributable mortality. We review the health risks of e-cigarette use, the likelihood that vaping increases smoking cessation, concerns about youth vaping, and the need to balance valid concerns about risks to youths with the potential benefits of increasing adult smoking cessation.

Tobacco is the leading preventable cause of death globally, causing approximately 7 million deaths each year. No ethical standard exists to guide researchers considering their obligation and ability to provide treatment for study participants who use tobacco. We propose that tobacco cessation treatment should be offered as ancillary care to interested study participants who use tobacco. We share a case study in which we describe our approach to implementing a brief behavioural tobacco cessation intervention as part of an observational study of tobacco use patterns in South Africa.

Background Cigarette smoking is a risk factor for severe COVID-19 disease. Understanding smokers’ responses to the pandemic will help assess its public health impact and inform future public health and provider messages to smokers. Objective To assess risk perceptions and change in tobacco use among current and former smokers during the COVID-19 pandemic. Design Cross-sectional survey conducted in May–July 2020 (55% response rate) Participants 694 current and former daily smokers (mean age 53, 40% male, 78% white) who had been hospitalized pre-COVID-19 and enrolled into a smoking cessation clinical trial at hospitals in Massachusetts, Pennsylvania, and Tennessee. Main Measures Perceived risk of COVID-19 due to tobacco use; changes in tobacco consumption and interest in quitting tobacco use; self-reported quitting and relapse since January 2020. Key Results 68% (95% CI, 65–72%) of respondents believed that smoking increases the risk of contracting COVID-19 or having a more severe case. In adjusted analyses, perceived risk was higher in Massachusetts where COVID-19 had already surged than in Pennsylvania and Tennessee which were pre-surge during survey administration (AOR 1.56, 95% CI, 1.07–2.28). Higher perceived COVID-19 risk was associated with increased interest in quitting smoking (AOR 1.72, 95% CI 1.01–2.92). During the pandemic, 32% (95% CI, 27–37%) of smokers increased, 37% (95% CI, 33–42%) decreased, and 31% (95% CI, 26–35%) did not change their cigarette consumption. Increased smoking was associated with higher perceived stress (AOR 1.49, 95% CI 1.16–1.91). Overall, 11% (95% CI, 8–14%) of respondents who smoked in January 2020 (pre-COVID-19) had quit smoking at survey (mean, 6 months later) while 28% (95% CI, 22–34%) of former smokers relapsed. Higher perceived COVID-19 risk was associated with higher odds of quitting and lower odds of relapse. Conclusions Most smokers believed that smoking increased COVID-19 risk. Smokers’ responses to the pandemic varied, with increased smoking related to stress and increased quitting associated with perceived COVID-19 vulnerability. Supplementary Information The online version contains supplementary material available at 10.1007/s11606-021-06913-3.

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

Introduction Cytisinicline (known as cytisine), a nicotinic acetylcholine receptor partial agonist, is a smoking cessation aid currently marketed in Central and Eastern Europe using a 1.5-mg/tablet 25-day downward titration schedule. No prior studies have evaluated other doses or administration schedules. This study evaluated the effects of a higher dosage and simplified dosing schedule on drug efficacy and tolerability. Methods ORCA-1 was a double-blind, randomized, placebo-controlled clinical trial that provided cytisinicline or placebo tablets plus behavioral support for 25 days. Adult smokers (>10 cigarettes daily) committed to quitting smoking were randomized to compare 2 cytisinicline doses (1.5 mg and 3 mg) versus placebo, and 2 administration schedules [downward titration versus 3 times daily (TID)]. Primary outcome was a reduction in expected cigarettes smoked at end of treatment; secondary outcomes were biochemically confirmed 7-day abstinence at Week 4 and continuous abstinence from Weeks 5 to 8. Results Among 254 participants, those in cytisinicline arms (regardless of dose or schedule) had greater reductions in cigarettes smoked versus placebo, with differences observed in 3 cytisinicline arms statistically significant versus placebo. All cytisinicline arms had statistically significantly higher abstinence rates at Week 4 versus placebo. Both cytisinicline arms using TID schedules had statistically significantly higher continuous abstinence rates from Weeks 5 to 8 compared with placebo. Participants in the cytisinicline 3-mg TID arm had the highest abstinence rate. There were no safety concerns with either 1.5-mg or 3-mg cytisinicline. Conclusion Based on simpler dose scheduling, excellent tolerability, and best-continued abstinence rate, cytisinicline 3-mg TID was selected for future Phase 3 studies. Implications Although the 1.5-mg 25-day titration schedule has been marketed in Central and Eastern Europe for decades, this study explored using a higher dosage and a simplified dosing schedule for impact on cytisinicline efficacy and tolerability. Based on these results, a Phase 3 program was initiated using cytisinicline 3-mg tablets on a TID schedule for potential market approval in the United States.

Introduction Estimates of initiation, cessation, and relapse rates of tobacco cigarette smoking and e-cigarette use can facilitate projections of longer-term impact of their use. We aimed to derive transition rates and apply them to validate a microsimulation model of tobacco that newly incorporated e-cigarettes. Methods We fit a Markov multi-state model (MMSM) for participants in Waves 1–4.5 of the Population Assessment of Tobacco and Health (PATH) longitudinal study. The MMSM had nine cigarette smoking and e-cigarette use states (current/former/never use of each), 27 transitions, two sex categories, and four age categories (youth: 12-17y; adults: 18-24y/25-44y/≥45y). We estimated transition hazard rates, including initiation, cessation, and relapse. We then validated the Simulation of Tobacco and Nicotine Outcomes and Policy (STOP) microsimulation model, by: (a) using transition hazard rates derived from PATH Waves 1–4.5 as inputs, and (b) comparing STOP-projected prevalence of smoking and e-cigarette use at 12 and 24 months to empirical data from PATH Waves 3 and 4. We compared the goodness-of-fit of validations with “static relapse” and “time-variant relapse,” wherein relapse rates did not or did depend on abstinence duration. Results Per the MMSM, youth smoking and e-cigarette use was generally more volatile (lower probability of maintaining the same e-cigarette use status over time) than that of adults. Root-mean-squared error (RMSE) for STOP-projected versus empirical prevalence of smoking and e-cigarette use was Discussion A microsimulation model incorporating smoking and e-cigarette use transition rates from a MMSM accurately projected downstream prevalence of product use. The microsimulation model structure and parameters provide a foundation for estimating the behavioral and clinical impact of tobacco and e-cigarette policies.

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

Smoking cessation interventions for hospitalized patients must continue after discharge to improve long-term tobacco abstinence. How health systems can best deliver postdischarge tobacco treatment is uncertain.To determine if health system-based tobacco cessation treatment after hospital discharge produces more long-term tobacco abstinence than referral to a community-based quitline.This randomized clinical trial was conducted September 2018 to November 2020 in 3 hospitals in Massachusetts, Pennsylvania, and Tennessee. Cigarette smokers admitted to a study hospital who received brief in-hospital tobacco treatment and wanted to quit smoking were recruited for participation and randomized for postdischarge treatment to health system-based Transitional Tobacco Care Management (TTCM) or electronic referral to a community-based quitline (QL). Both multicomponent interventions offered smoking cessation counseling and nicotine replacement therapy (NRT) for up to 3 months. Data were analyzed from February 1, 2021, to April 25, 2022.TTCM provided 8 weeks of NRT at discharge and 7 automated calls with a hospital-based counselor call-back option. The QL intervention sent referrals from the hospital electronic health record to the state quitline, which offered 5 counseling calls and an NRT sample.The main outcome was biochemically verified past 7-day tobacco abstinence at 6 months. Self-reported point-prevalence and continuous tobacco abstinence and tobacco treatment utilization were assessed 1, 3, and 6 months after discharge.A total of 1409 participants (mean [SD] age, 51.7 [12.6] years; 784 [55.6%] women; mean [SD] 16.4 [10.6] cigarettes/day) were recruited, including 706 randomized to TTCM and 703 randomized to QL. Participants were comparable at baseline, including 216 Black participants (15.3%), 82 Hispanic participants (5.8%), and 1089 White participants (77.3%). At 1 and 3 months after discharge, more TTCM participants than QL participants used cessation counseling (1 month: 245 participants [34.7%] vs 154 participants [21.9%]; 3 months: 248 participants [35.1%] vs 123 participants [17.5%]; P .001) and pharmacotherapy (1 month: 455 participants [64.4%] vs 324 participants [46.1%]; 3 months: 367 participants [52.0%] vs 264 participants [37.6%]; P .001). More TTCM than QL participants reported continuous abstinence for 3 months (RR, 1.30; 95% CI, 1.06-1.58) and point-prevalence abstinence at 1 month (RR, 1.22; 95% CI, 1.08-1.35) and 3 months (RR, 1.23; 95% CI, 1.09-1.37) but not at 6 months (RR, 1.14; 95% CI, 0.99-1.29). The primary outcome, biochemically verified point-prevalence abstinence at 6 months, was not statistically significantly different between groups (19.9% vs 16.9%; RR, 1.18; 95% CI, 0.92-1.50).In this randomized clinical trial, biochemically verified tobacco abstinence rates were not significantly different between groups at the 6-month follow-up. However, the health system-based model was superior to the community-based quitline model throughout the 3 months of active treatment. A longer duration of postdischarge treatment may sustain the superiority of the health system-based model.ClinicalTrials.gov Identifier: NCT03603496.