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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.

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BACKGROUND: People with HIV (PWH) smoke tobacco at much higher rates than the general population. Previous research has shown that PWH have faster nicotine metabolism than HIV-uninfected individuals, which may underlie this disparity, but the cause is unknown. We investigated whether higher nicotine metabolite ratio (NMR; 3-hydroxycotinine:cotinine), a validated biomarker of nicotine metabolism through CYP2A6, was associated with antiretroviral use among HIV-infected smokers. METHODS: We conducted a retrospective cohort study of HIV-positive smokers in the University of Pennsylvania Center for AIDS Research cohort. We compared the NMR before viral suppression (>10,000 copies/mL) and after viral suppression on antiretroviral therapy (<200 copies/mL). We used mixed-effects linear regression to analyze the change in NMR after viral suppression and assessed for effect modification by efavirenz use. RESULTS: Eighty-nine individuals were included in the study. We observed effect modification by efavirenz use (interaction term for efavirenz use, P < 0.001). Among those on nonefavirenz regimens, the mean NMR increased by 0.14 (95% confidence interval: 0.05 to 0.23, P = 0.002). Among those on efavirenz-containing regimens, the mean NMR increased by 0.53 (95% confidence interval: 0.39-0.66, P < 0.001). CONCLUSIONS: We observed a clinically and statistically significant increase in NMR after viral suppression among smokers with HIV, which more than doubled among those on efavirenz-based regimens. Higher NMR among HIV-positive smokers on antiretroviral therapy may help explain the higher rates of tobacco use and lower quit rates among PWH in care. These findings suggest that regimen choice and other modifiable factors may be targets for future attempts to increase success rates for tobacco cessation among PWH.

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INTRODUCTION: Individuals with serious mental illness (SMI) smoke at rates two to three times greater than the general population but are less likely to receive treatment. Increasing our understanding of correlates of smoking cessation behaviors in this group can guide intervention development. AIMS AND METHODS: Baseline data from an ongoing trial involving smokers with SMI (N = 482) were used to describe smoking cessation behaviors (ie, quit attempts, quit motivation, and smoking cessation treatment) and correlates of these behaviors (ie, demographics, attitudinal and systems-related variables). RESULTS: Forty-three percent of the sample did not report making a quit attempt in the last year, but 44% reported making one to six quit attempts; 43% and 20%, respectively, reported wanting to quit within the next 6 months or the next 30 days. Sixty-one percent used a smoking cessation medication during their quit attempt, while 13% utilized counseling. More quit attempts were associated with lower nicotine dependence and carbon monoxide and greater beliefs about the harms of smoking. Greater quit motivation was associated with lower carbon monoxide, minority race, benefits of cessation counseling, and importance of counseling within the clinic. A greater likelihood of using smoking cessation medications was associated with being female, smoking more cigarettes, and receiving smoking cessation advice. A greater likelihood of using smoking cessation counseling was associated with being male, greater academic achievement, and receiving smoking cessation advice. CONCLUSIONS: Many smokers with SMI are engaged in efforts to quit smoking. Measures of smoking cessation behavior are associated with tobacco use indicators, beliefs about smoking, race and gender, and receiving cessation advice. IMPLICATIONS: Consideration of factors related to cessation behaviors among smokers with SMI continues to be warranted, due to their high smoking rates compared to the general population. Increasing our understanding of these predictive characteristics can help promote higher engagement in evidence-based smoking cessation treatments among this subpopulation.

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INTRODUCTION: Network theories of psychopathology highlight that, rather than being indicators of a latent disorder, symptoms of disorders can causally interact with one another in a network. This study examined tobacco withdrawal from a network perspective. METHODS: Participants (n = 525, 50.67% female) completed the Minnesota Tobacco Withdrawal Scale four times (2 weeks prior to a target quit day, on the target quit day, and 4 and 8 weeks after the target quit day) over the course of 8 weeks of treatment with nicotine patch and behavioral counseling within a randomized clinical trial testing long-term nicotine patch therapy in treatment-seeking smokers. The conditional dependence among seven withdrawal symptoms was estimated at each of the four measurement occasions. Influential symptoms of withdrawal were identified using centrality indices. Changes in network structure were examined using the Network Comparison Test. RESULTS: Findings indicated many associations among the individual symptoms of withdrawal. The strongest associations that emerged were between sleep problems and restlessness, and associations among affective symptoms. Restlessness and affective symptoms emerged as the most central symptoms in the withdrawal networks. Minimal differences in the structure of the withdrawal networks emerged across time. CONCLUSIONS: The cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal rather than simply reflecting passive indicators of a latent disorder. Findings encourage greater consideration of individual withdrawal symptoms and their potential interactions and may be used to generate hypotheses that may be tested in future intensive longitudinal studies. IMPLICATIONS: This study provides a novel, network perspective on tobacco withdrawal. Drawing on network theories of psychopathology, we suggest that the cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal over time, rather than simply reflecting passive indicators of a latent disorder. Results indicating many associations among individual symptoms of withdrawal are consistent with a network perspective. Other results of interest include minimal changes in the network structure of withdrawal across four measurement occasions prior to and during treatment with nicotine patch and behavioral counseling.

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BACKGROUND: The nicotine metabolite ratio (NMR) is a biomarker that represents individual variation in the speed that nicotine is metabolized. The rate of nicotine metabolism alters smoking behavior (eg, amount) and has been validated for personalizing tobacco dependence medication selection to increase treatment efficacy and reduce treatment side effects in the general population of smokers. Although smoking rates are extremely high among those with HIV, the NMR has not been evaluated in this underserved population. METHODS: We used baseline data from a smoking cessation clinical trial for smokers with HIV (N = 131) to examine associations between NMR and demographic, smoking, disease-related, and psychological characteristics. Pearson r and analysis of variance were used to identify univariate correlates of NMR, which were then entered into a multiple linear regression model. RESULTS: In univariate analyses, a higher NMR (faster nicotine metabolism) was associated with being white, and more cigarettes per day, nicotine dependence, exhaled carbon monoxide, and symptoms of depression and anxiety, and using efavirenz. In a multiple regression model, a higher NMR was associated with more cigarettes per day, higher anxiety symptoms, and efavirenz use. CONCLUSIONS: As in other populations, faster nicotine metabolism was associated with the use of more cigarettes and higher anxiety symptoms. Notably, efavirenz use was associated with faster metabolism, which might make it harder to quit smoking for people with HIV treated with that medication. These findings could help guide further study and the clinical use of the NMR to personalize nicotine dependence treatment in this underserved population.

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INTRODUCTION: People with mental illness are more likely to smoke and less likely to receive tobacco treatment than the general population. The Addressing Tobacco Through Organizational Change (ATTOC) approach supports organizational change to increase tobacco treatment in this population. We describe preliminary study feasibility and baseline behaviors and attitudes among clients and staff regarding tobacco treatment, and assesse correlates of treatment of smoking. METHODS: Preliminary accrual, engagement, and baseline data are reported from a cluster-randomized trial comparing ATTOC to usual care. Feasibility, thus far, was the rate of site and participant accrual and engagement (eg, participants remaining in the trial). Correlates of assessing smoking, advising cessation, and providing treatment were assessed. RESULTS: Site and participant accrual is 80% (8/10) and 86% (456/533), and engagement is 100% and 82%. "Staff asking about smoking" was reported by 63% of clients and 38% of staff; "staff advising cessation" was reported by 57% of clients and 46% of staff; staff report "assisting clients with any medication" at most 22% of the time, whereas at most 18% of clients report receiving a cessation medication; 59% of clients want tobacco treatment, but 36% of staff think that it is part of their job. "Staff assisting with medications" is related to more training, believing treating smoking is part of their job, and believing patients are concerned about smoking (ps < .05). CONCLUSIONS: This trial of training in tobacco treatment within mental health care is feasible thus far; self-reported rates of tobacco treatment are low and associated with clinician attitudes and barriers. IMPLICATIONS: Evaluation of ways to help address tobacco use treatment in community mental health care is feasible and needed, including the use of technical assistance and training guided by an organizational change approach.

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OBJECTIVES: Little 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. METHODS: Twenty-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. RESULTS: Compared 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. CONCLUSIONS: E-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.

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OBJECTIVES: There is a critical need for the development of novel treatments for nicotine dependence. Because the majority of smokers who make a quit attempt fail within 7 days, medication screening procedures that focus on this early cessation period may provide an indicator of treatment efficacy. To establish the clinical validity of this paradigm, it is critical to demonstrate the association of early abstinence with longer-term abstinence. We tested the number of days of abstinence during the first week after the target quit date (TQD) as a predictor of point prevalence abstinence in 3 independent pharmacotherapy trials for nicotine dependence. METHODS: This was a secondary data analysis of 3 randomized clinical trials: a placebo-controlled trial of transdermal nicotine (N = 545); an open-label nicotine replacement therapy (patch vs spray) trial (N = 566); and a bupropion placebo-controlled trial (N = 538). In separate logistic regression models, the maximum number of consecutive days of abstinence during the first week after the TQD was used to predict biochemically verified 7-day point prevalence abstinence at the end of treatment (EOT) and 6 months post-TQD. RESULTS: Across the 3 trials, the number of days of abstinence significantly predicted abstinence at EOT and 6 months (odds ratios > 1.4; Ps < 0.0001). Likewise, not having any lapse during the first week predicted abstinence at EOT and 6 months (odds ratios > 4.7; Ps < 0.0001). CONCLUSIONS: The first week of abstinence was highly predictive of EOT and long-term abstinence. Medication screening procedures that focus on this early abstinence period (ie, 6 or 7 days of consecutive abstinence) represent a valid tool for assessing the presence of a signal for medication efficacy.

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