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Rates of cigarette smoking in people with HIV (PWH) are two to three times higher than in people without HIV. Nicotine is metabolized by CYP2A6 and the nicotine metabolite ratio (NMR; 3-hydroxycotinine/cotinine) is a measure of nicotine clearance. Higher NMR has been observed in PWH and is associated with lower quit rates. Efavirenz, a mainstay antiretroviral therapy (ART) globally, partially upregulates its own metabolism through CYP2A6. We hypothesized that efavirenz also upregulates nicotine metabolism by CYP2A6, resulting in a higher NMR, and switching to non-efavirenz ART would decrease the NMR, potentially leading to improved quit rates. We compared the NMR during and after efavirenz use among PWH in a longitudinal, multisite cohort. Eligibility criteria included: (i) active cigarette smoking, (ii) ART switched from efavirenz-based to non-efavirenz-based regimen, (iii) plasma available at pre- and post-ART switch, and (iv) viral suppression during study period. Plasma cotinine and 3-hydroxycotinine were measured by liquid chromatography-tandem mass spectrometry. T-tests compared the NMR on and off efavirenz. Samples were collected between 2010 and 2019 in 72 PWH. The mean NMR difference after switching to a non-efavirenz-based regimen was -0.24 (SD: 0.37, P

BACKGROUND: Smoking contributes to significant morbidity and mortality in people with HIV. People with HIV have relatively high nicotine metabolism rates, as measured by the nicotine metabolite ratio (NMR, 3-hydroxycotinine/cotinine). A higher NMR is associated with difficulty quitting smoking. We hypothesized that HIV infection might upregulate nicotine metabolism. SETTING: A retrospective study of male current smokers in the Multicenter AIDS Cohort Study who HIV seroconverted between 1985 and 1993. METHODS: Eligibility included having plasma stored before and after confirmed HIV seroconversion and current tobacco use. Samples were selected from the closest available visits before (median 3.3 months) and after (median 9.4 months) seroconversion. Antiretroviral therapy use was exclusionary. Cotinine and 3-hydroxycotinine were measured using liquid chromatography-tandem mass spectrometry. We compared NMR from plasma pre-HIV and post-HIV infection using signed-rank tests. We targeted a sample size of 71 pairs to achieve 80% power to detect a 0.1 unit increase in NMR with P = 0.05. RESULTS: We analyzed paired samples from 78 participants; the median age was 34.5 years [interquartile range (IQR 29-40 years)]. The median NMR pre-HIV and post-HIV was 0.45 (IQR 0.32-0.54) and 0.46 (IQR 0.34-0.56), respectively. The median change in NMR postseroconversion was +0.01 (IQR -0.05, +0.09), P = 0.25. Stratification of median change in NMR by timing between samples or time since HIV seroconversion did not alter this finding. CONCLUSIONS: Acquiring HIV had no measurable effect on NMR. We postulate that upregulation of the NMR may be due to direct pharmacologic effects of HIV medications or metabolic changes in response to HIV infection.

The use of antiretroviral therapy for people with HIV (PWH) has improved life expectancy. However, PWH now lose more life-years to tobacco use than to HIV infection. Unfortunately, PWH smoke at higher rates and have more difficulty maintaining abstinence than the general population, compounding their risk for chronic disease. In this Commentary, we describe a United States National Cancer Institute-led initiative to address the relative lack of research focused on developing, testing, and implementing smoking cessation interventions for PWH. This initiative supports seven clinical trials designed to systematically test and/or develop and test adaptations of evidence-based smoking cessation interventions for PWH (eg, combination of behavioral and pharmacological). We summarize each project, including setting/recruitment sites, inclusion/exclusion criteria, interventions being tested, and outcomes. This initiative provides critical opportunities for collaboration and data harmonization across projects. The knowledge gained will inform strategies to assist PWH to promote and maintain abstinence, and ensure that these efforts are adaptable and scalable, thereby addressing one of the major threats to the health of PWH. Reducing smoking behavior may be particularly important during the COVID-19 pandemic given that smokers who become infected with SARS-CoV-2 may be at risk for more severe disease.ImplicationsThis Commentary describes a National Cancer Institute-led initiative to advance the science and practice of treating tobacco use among PWH, which is now responsible for more life years lost than HIV. We describe the scope of the problem, the objectives of the initiative, and a summary of the seven funded studies. Harmonization of data across projects will provide information related to treatment mediators and moderators that was not previously possible. Stakeholders interested in tobacco cessation, including researchers, clinicians and public health officials, should be aware of this initiative and the evidence-base it will generate to advance tobacco treatment among this high-risk population.

BackgroundAdherence to nicotine patches relates to cessation. This is the first study to examine the validity of self-reported nicotine patch adherence relative to saliva cotinine.MethodsWe used data from 198 clinical trial participants who received 11 weeks of nicotine patches, self-reported patch use, had saliva cotinine 1-week after the start of treatment assessed, and were not smoking when saliva was collected (CO < 6). Self-reported patch adherence was defined as: 3-day (before saliva collection), 7-day (before saliva collection), 3-week use (7 days before, and 14 days after, saliva collection), and 11-week use (7 days before, and 10 weeks after, saliva collection). Analyses, including receiver operating characteristic curves, considered differences in nicotine metabolism. Sensitivity, specificity and positive (PPV) and negative predictive value (NPV) assessed optimal cotinine cut-point for adherence.ResultsSelf-reported 7-day (r = 0.13) and 3-week (r = 0.13) patch use marginally correlated with week 1 cotinine (p's = 0.08) but not 3-day or 11-week. Significant area under the curve (AUC) values of 0.67 (95 %CI: 0.55-0.79) and 0.72 (95 %CI: 0.57-0.88) were found using 7-day self-report for the overall sample and for slow metabolizers (p's

Smokers attempting to quit often attribute smoking relapse to negative affect, craving, and other nicotine withdrawal symptoms. In addition, there is evidence that smoking relapse can increase these symptoms, particularly negative affect. To address this issue, we analyzed data from an 11-week smoking cessation clinical trial in which smokers (n = 1,246) were randomized to receive either nicotine replacement therapy (NRT), varenicline, or placebo, combined with behavioral counseling. Using cross-lagged analyses, we examined the temporal bidirectional relationships between self-reported measures of affect, craving, and composite withdrawal symptoms and biochemically verified smoking abstinence. The relative strength of these temporal relationships was examined by comparing the explained variances of the models. The results showed that higher negative affect, craving, and composite withdrawal symptoms increased the likelihood of subsequent smoking relapse, and that smoking relapse led to subsequent increases in these same symptoms. A comparison of the explained variances found symptom predicting subsequent relapse models to be stronger than those where relapse predicted subsequent symptoms. Although the explained variance findings generally support a negative reinforcement conceptualization of nicotine dependence, the bidirectional relationship between symptoms and smoking relapse suggests that struggling with quitting smoking leads to significant negative affect, craving, and other withdrawal symptoms that do not quickly resolve. These findings highlight the importance of addressing specific symptoms within the context of smoking cessation. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Background and aimsThe activity of CYP2A6, the major nicotine-inactivating enzyme, is measurable in smokers using the nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine). Due to its role in nicotine clearance, the NMR is associated with smoking behaviours and response to pharmacotherapies. The NMR is highly heritable (~80%), and on average lower in African Americans (AA) versus whites. We previously identified several reduce and loss-of-function CYP2A6 variants common in individuals of African descent. Our current aim was to identify novel genetic influences on the NMR in AA smokers using genome-wide approaches.DesignGenome-wide association study (GWAS).SettingMultiple sites within Canada and the United States.ParticipantsAA smokers from two clinical trials: Pharmacogenetics of Nicotine Addiction Treatment (PNAT)-2 (NCT01314001; n = 504) and Kick-it-at-Swope (KIS)-3 (NCT00666978; n = 450).MeasurementsGenome-wide SNP genotyping, the NMR (phenotype) and population substructure and NMR covariates.FindingsMeta-analysis revealed three independent chromosome 19 signals (rs12459249, rs111645190 and rs185430475) associated with the NMR. The top overall hit, rs12459249 (P = 1.47e-39; beta = 0.59 per C (versus T) allele, SE = 0.045), located ~9.5 kb 3' of CYP2A6, remained genome-wide significant after controlling for the common (~10% in AA) non-functional CYP2A6*17 allele. In contrast, rs111645190 and rs185430475 were not genome-wide significant when controlling for CYP2A6*17. In total, 96 signals associated with the NMR were identified; many were not found in prior NMR GWASs in individuals of European descent. The top hits were also associated with the NMR in a third cohort of AA (KIS2; n = 480). None of the hits were in UGT or OCT2 genes.ConclusionsThree independent chromosome 19 signals account for ~20% of the variability in the nicotine metabolite ratio in African American smokers. The hits identified may contribute to inter-ethnic variability in nicotine metabolism, smoking behaviours and tobacco-related disease risk.

IntroductionWhile adherence to medication in smoking cessation clinical trials is strongly associated with clinical outcome, very few studies have evaluated the validity of pill count as a measure of adherence relative to a biological assay, and evaluated a broad range of correlates of adherence.MethodsIn a smoking cessation clinical trial of varenicline, we compared pill counts collected over 4 different time periods to varenicline salivary levels taken after 2weeks of treatment, as well as evaluated predictors of adherence to varenicline.ResultsUsing a binary measure of adherence based on salivary varenicline levels, adherence was higher among older, white, and more educated participants. Relative to 3, 7, and 14-day pill count, 12-week pill count was the only significant measure able to discriminate adherence as defined by salivary varenicline levels (assessed by area under the receiver operating characteristic curve; AUC=0.59, p=0.004). Seventy-two percent of participants who indicated adherence on 12-week pill count were classified as adherent based on varenicline saliva levels (sensitivity=0.80; specificity=0.40). There was modest variability in the relationship between 12-week pill count and varenicline levels across race and rate of nicotine metabolism. Lastly, General Estimating Equation models demonstrated that longitudinal changes in withdrawal, craving, negative and positive affect, and side effect count and severity were not related to adherence based on salivary varenicline levels.ConclusionsThese results indicate that 12-week pill count was the best, albeit a relatively weak, measure of varenicline adherence; additional factors associated with treatment adherence need to be identified.

ObjectivesLittle is known about the degree of nicotine replacement across first-generation e-cigarette brands, how e-cigarettes are used, and if there is variation across brands in relevant smoking phenotypes. The objective of this project was to collect data that are critical to better understanding, use, and exposure when using e-cigarettes, which may then inform clinical trials and tobacco regulatory policy.MethodsTwenty-eight cigarette smokers were randomized to use one of 5 popular brands of e-cigarettes for a 10-day study. Day 1 (own cigarette brand) data established baseline levels for cotinine, carbon monoxide (CO), topography, cigarette liking, withdrawal, and craving. Participants returned on Days 5 and 10 to reassess these measures while exclusively using e-cigarettes.ResultsCompared to cigarette smoking, e-cigarettes provided significantly lower nicotine levels (25%-50%), reduced CO exposure, and lower ratings of liking (p < .05). Topography significantly differed between cigarette and e-cigarette sessions (p < .05). All brands significantly reduced withdrawal and craving (p < .05). There were no significant brand differences in outcome measures associated with exposure or use.ConclusionsE-cigarettes are not liked as much as cigarettes, provide significantly lower nicotine replacement, reduce CO exposure, and mitigate withdrawal and craving. The patterns of use significantly differ compared to cigarette smoking.

Rate of nicotine metabolism has been identified as an important factor influencing nicotine intake and can be estimated using the nicotine metabolite ratio (NMR), a validated biomarker of CYP2A6 enzyme activity. Individuals who metabolize nicotine faster (higher NMR) may alter their smoking behavior to titrate their nicotine intake in order to maintain similar levels of nicotine in the body compared to slower nicotine metabolizers. There are known racial differences in the rate of nicotine metabolism with African Americans on average having a slower rate of nicotine metabolism compared to Whites. The goal of this study was to determine if there are racial differences in the relationship between rate of nicotine metabolism and measures of nicotine intake assessed using multiple biomarkers of nicotine and tobacco smoke exposure. Using secondary analyses of the screening data collected in a recently completed clinical trial, treatment-seeking African American and White daily smokers (10 or more cigarettes per day) were grouped into NMR quartiles so that the races could be compared at the same NMR, even though the distribution of NMR within race differed. The results indicated that rate of nicotine metabolism was a more important factor influencing nicotine intake in White smokers. Specifically, Whites were more likely to titrate their nicotine intake based on the rate at which they metabolize nicotine. However, this relationship was not found in African Americans. Overall there was a greater step-down, linear type relationship between NMR groups and cotinine or cotinine/cigarette in African Americans, which is consistent with the idea that differences in blood cotinine levels between the African American NMR groups were primarily due to differences in CYP2A6 enzyme activity without titration of nicotine intake among faster nicotine metabolizers.

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.

UnlabelledThe nicotine metabolite ratio (NMR), a stable measure of hepatic nicotine metabolism via the CYP2A6 pathway and total nicotine clearance, is a predictive biomarker of response to nicotine replacement therapy, with increased quit rates in slower metabolizers. Nicotine binds directly to nicotinic acetylcholine receptors (nAChRs) to exert its psychoactive effects. This study examined the relationship between NMR and nAChR (α4β2* subtype) availability using PET imaging of the radiotracer 2-(18)F-fluoro-3-(2(S)-azetidinylmethoxy)pyridine (2-(18)F-FA-85380, or 2-(18)F-FA).MethodsTwenty-four smokers-12 slow metabolizers (NMR < 0.26) and 12 normal metabolizers (NMR ≥ 0.26)-underwent 2-(18)F-FA-PET brain imaging after overnight nicotine abstinence (18 h before scanning), using a validated bolus-plus-infusion protocol. Availability of nAChRs was compared between NMR groups in a priori volumes of interest, with total distribution volume (VT/fP) being the measure of nAChR availability. Cravings to smoke were assessed before and after the scans.ResultsThalamic nAChR α4β2* availability was significantly reduced in slow nicotine metabolizers (P = 0.04). Slow metabolizers exhibited greater reductions in cravings after scanning than normal metabolizers; however, craving was unrelated to nAChR availability.ConclusionThe rate of nicotine metabolism is associated with thalamic nAChR availability. Additional studies could examine whether altered nAChR availability underlies the differences in treatment response between slow and normal metabolizers of nicotine.

BackgroundSubstantial variability exists in therapeutic response and adverse effects with pharmacotherapies for tobacco dependence. Biomarkers to optimise treatment choice for individual smokers might improve treatment outcomes. We tested whether a genetically informed biomarker of nicotine clearance, the nicotine metabolite ratio (NMR; 3'-hydroxycotinine:cotinine), predicts response to nicotine patch or varenicline for smoking cessation.MethodsWe undertook NMR-stratified multicentre, randomised, placebo-controlled clinical trial from Nov 16, 2010, to Sept 12, 2014, at four sites. Smokers seeking treatment were randomly assigned by baseline NMR status and study site, in blocks of 12 patients (1:1:1 ratio), to 11 weeks of placebo (placebo pill plus placebo patch), nicotine patch (active patch plus placebo pill), or varenicline (active pill plus placebo patch), plus behavioural counselling. Participants and investigators were masked to group allocation and NMR status. An intention-to-treat analysis was done. Participants were followed up for 12 months after the target quit date. The primary endpoint was biochemically verified 7 day point prevalence abstinence at the end of treatment to estimate the pharmacological effect of treatment by NMR. The trial is registered at ClinicalTrials.gov, number NCT01314001.Findings1246 participants (662 slow metabolisers of nicotine, 584 normal metabolisers of nicotine) were enrolled and randomly assigned to the three interventions (408 placebo, 418 nicotine patch, 420 varenicline). At end of treatment, varenicline was more efficacious than nicotine patch in normal metabolisers (OR 2·17, 95% CI 1·38-3·42; p=0·001), but not in slow metabolisers (OR 1·13, 0·74-1·71; p=0·56). In the longitudinal model including all timepoints, the NMR-by-treatment interaction was significant (ratio of odds ratios [ORR] 1·96, 95% CI 1·11-3·46; p=0·02). An NMR-by-treatment interaction showed that slow (vs normal) metabolisers reported greater overall side-effect severity with varenicline versus placebo (β=-1·06, 95% CI -2·08 to -0·03; p=0·044).InterpretationTreating normal metabolisers with varenicline and slow metabolisers with nicotine patch could optimise quit rates while minimising side-effects.FundingNational Institutes of Health, Canadian Institutes of Health Research, Abramson Cancer Center, Centre for Addiction and Mental Health Foundation, and Pennsylvania Department of Health.

The National Cancer Institute's (NCI) Implementation Science in Cancer Control Centers (ISC3) Network represents a large-scale initiative to create an infrastructure to support and enable the efficient, effective, and equitable translation of approaches and evidence-based treatments to reduce cancer risk and improve outcomes. This Cancer Moonshot funded ISC3 Network consists of seven P50 Centers that support and advance the rapid development, testing, and refinement of innovative approaches to implement a range of evidence-based cancer control interventions. The Centers were designed to have research-practice partnerships at their core, and to create the opportunity for a series of pilot studies that could explore new and sometimes risky ideas and embed in their infrastructure a two-way engagement and collaboration essential to stimulating lasting change. ISC3 also seeks to enhance capacity of researchers, practitioners and communities to apply implementation science approaches, methods, and measures. The Organizing Framework that guides the work of ISC3 highlights a collective set of three core areas of collaboration within and among Centers, including: (1) assess and incorporate dynamic, multilevel context; (2) develop and conduct rapid and responsive pilot and methods studies; and (3) build capacity for knowledge development and exchange. Core operating principles that under-gird the framework include open collaboration, consideration of the dynamic context and engagement of multiple implementation partners to advance pragmatic methods, advancement of health equity, and facilitation of leadership and capacity building across Implementation Science and cancer control. [ABSTRACT FROM AUTHOR]