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Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances.

ABSTRACT: Genotype scores that predict relevant clinical outcomes may detect other disease features and help direct prevention efforts. We report data that validate a previously established v1.0 smoking cessation quit success genotype score and describe striking differences in the score in individuals who display differing developmental trajectories of use of common addictive substances. In a cessation study, v1.0 genotype scores predicted ability to quit with P=0.00056 and area under receiver-operating characteristic curve 0.66. About 43% vs 13% quit in the upper vs lower genotype score terciles. Latent class growth analyses of a developmentally assessed sample identified three latent classes based on substance use. Higher v1.0 scores were associated with (a) higher probabilities of participant membership in a latent class that displayed low use of common addictive substances during adolescence (P=0.0004) and (b) lower probabilities of membership in a class that reported escalating use (P=0.001). These results indicate that: (a) we have identified genetic predictors of smoking cessation success, (b) genetic influences on quit success overlap with those that influence the rate at which addictive substance use is taken up during adolescence and (c) individuals at genetic risk for both escalating use of addictive substances and poor abilities to quit may provide especially urgent focus for prevention efforts.

SUBMITTER: Uhl GR

PROVIDER: S-EPMC3922203 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances.

Uhl G R GR Walther D D Musci R R Fisher C C Anthony J C JC Storr C L CL Behm F M FM Eaton W W WW Ialongo N N Rose J E JE

Molecular psychiatry 20121106 1

Genotype scores that predict relevant clinical outcomes may detect other disease features and help direct prevention efforts. We report data that validate a previously established v1.0 smoking cessation quit success genotype score and describe striking differences in the score in individuals who display differing developmental trajectories of use of common addictive substances. In a cessation study, v1.0 genotype scores predicted ability to quit with P=0.00056 and area under receiver-operating c ...[more]

PMID: 23128154

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Project description:IntroductionMost 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 methodsThis 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.ResultsIn 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).ConclusionPredictors 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.ImplicationsMotivation-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.

Project description:AIMS:To quantify associations between the success of smoking quit attempts and factors that have varied throughout 2007-2018 at a population level. DESIGN:time series analysis using Autoregressive Integrated Moving Average with Exogeneous Input (ARIMAX) modelling. SETTING AND PARTICIPANTS:Data were aggregated from 54?847 past-year smokers taking part in the Smoking Toolkit Study which involves monthly repeated cross-sectional household surveys of individuals aged 16+ in England. MEASUREMENTS:The input series were: (1) attempts at smoking reduction using (a) e-cigarettes and (b) nicotine replacement therapy (NRT); (2) use during a quit attempt of (a) e-cigarettes, (b) NRT over-the-counter, (c) medication on prescription and (d) face-to-face behavioural support; (3) use of roll-your-own tobacco; (4) prevalence of (a) smoking and (b) non-daily smoking; (5) tobacco control mass media expenditure; (6) expenditure on smoking; (7) smoker characteristics in the form of (a) high motivation to quit, (b) average age, (c) socio-economic status and (d) cigarette consumption; (8) implementation of tobacco control policies; and (9) quit attempt rate. FINDINGS:The licensing of NRT for harm reduction was associated with a 0.641% [95% confidence interval (CI) = 0.073-1.209, P = 0.027] increase in the mean point prevalence of the success rate of quit attempts. For every 1% increase in the mean point prevalence of e-cigarette use and use of prescription medication during a quit attempt, the mean point prevalence of successful quit attempts increased by 0.106% (95% CI = 0.011-0.201, P = 0.029) and 0.143% (95% CI = 0.009-0.279, P = 0.038), respectively. For every 1% increase in the mean expenditure on tobacco control mass media, the mean point prevalence of successful quit attempts increased by 0.046% (95% CI = 0.001-0.092, P = 0.046). Other associations were not statistically significant. CONCLUSION:In England between 2007 and 2018, licensing of nicotine replacement therapy for use in harm reduction, greater use of e-cigarettes and prescription medications during a quit attempt and higher expenditure on tobacco control mass media were all associated with higher success rates of quit attempts.

Project description:IntroductionAlthough many studies have examined the association between e-cigarette use and smoking cessation, fewer have considered the impact of e-cigarette flavors on cessation outcomes. This study extends previous studies by examining the effects of e-cigarette use and e-cigarette flavors on quit attempts and quit success of smoking.Aims and methodsWe used data from the 2018-2019 Tobacco Use Supplement-Current Population Survey (TUS-CPS) survey. Multivariate logistic regression analyses were used to investigate the associations between flavored e-cigarette use with quit attempts and quit success of smoking among individuals who smoked 12 months ago. Two current e-cigarette use definitions were used in these logistic regression analyses; currently use every day or some days versus 20+ days in the past 30 days.ResultsCompared to those not using e-cigarettes, current every day or someday e-cigarette use with all nontobacco flavors had an adjusted odds ratio (AOR) of 2.9 (95% CI: 2.4 to 3.5) for quit attempts and 1.7 (95% CI: 1.3 to 2.2) for quit success. 20+ days e-cigarette use with flavors had stronger associations with quit attempts (AOR = 4.2, 95% CI: 3.1 to 5.5) and quit success (AOR = 4.0, 95% CI: 2.9 to 5.4). E-cigarette users with nontobacco flavors were more likely to succeed in quitting compared to those exclusively using non-flavored or tobacco-flavored e-cigarettes. Menthol or mint flavor users had slightly higher odds of quit attempts and success than users of other nontobacco flavors.ConclusionsE-cigarette use is positively associated with both making smoking quit attempts and quit success. Those using flavored e-cigarettes, particularly menthol or mint, are more likely to quit successfully.ImplicationsE-cigarette use is positively associated with both making a quit attempt and quit success, and those using flavored e-cigarettes are more likely to successfully quit smoking, with no statistically significant differences between the use of menthol or mint-flavored e-cigarettes versus the use of other nontobacco flavored products. This suggests that the potential for e-cigarettes to help people who currently smoke quit could be maintained with the availability of menthol or mint-flavored e-cigarettes, even if other nontobacco flavored products, which are associated with e-cigarette use among youth, were removed from the market.

Project description:BackgroundSetting a target quit date (TQD) is often an important component in smoking cessation treatment, but ambiguity remains concerning the optimal timing (ie, quitting spontaneously versus delaying to prepare).ObjectiveWe examined four questions about the timing of TQDs and smoking outcomes in secondary analyses of The iQUITT Study, a randomized trial of Internet and telephone treatment for cessation: (1) What are the characteristics of TQDs set using an online interactive quit date tool?, (2) What are the characteristics of individuals who use a quit date tool and do they differ from those who do not?, (3) Are there differences in smoker characteristics, treatment utilization, and cessation outcomes based TQD timing?, and (4) Is maintenance of an initial TQD predictive of abstinence or do changes to TQDs lead to cessation?MethodsA total of 825 adult current cigarette smokers were randomized to enhanced Internet or enhanced Internet plus telephone counseling. Latency to TQD in days was calculated as the date difference between the initial TQD and enhanced Internet registration; prospective TQD setters were stratified into four latency groups (0, 1-14, 15-28, 29+ days). Baseline variables, website utilization, and 3-month cessation outcomes were examined between prospective TQD groups. Desire and confidence to quit, number of TQDs, and website logins were tested as predictors of 30-day point prevalence abstinence (ppa) at 3 months (responder-only analyses). Classification and regression tree (CART) analysis explored interactions among baseline variables, website utilization, and latency to TQD as predictors of 30-day ppa.ResultsThere were few baseline differences between individuals who used the quit date tool and those who did not. Prospective TQDs were set as follows: registration day was 17.1% (73/427), 1-14 days was 37.7% (161/427), 15-28 days was 18.5% (79/427), and 29+ days was 26.7% (114/427). Participants with a TQD within 2 weeks had higher baseline self-efficacy scores but did not differ on smoking variables. Individuals whose TQD was the same day as registration had the highest logins, page views, number of TQDs set using the tool, and messages sent to other members. Logistic regression revealed a significant interaction between number of TQDs and website logins for 30-day ppa (P=.005). Among those with high logins, 41.8% (33/79) with 1 TQD were abstinent versus 25.9% (35/135) with 2+TQDs. Logins and self-efficacy predicted 30-day ppa in the CART model.ConclusionsTQD timing did not predict cessation outcomes in standard or exploratory analyses. Self-efficacy and an apparent commitment to an initial TQD were the components most highly related to abstinence but only via interactions with website utilization. Findings highlight the importance of feeling efficacious about handling specific smoking situations and engaging with treatment. Additional research focused on increasing engagement in Web-based cessation studies is needed.Trial registrationClinicalTrials.gov: NCT00282009; http://clinicaltrials.gov/show/NCT00282009 (Archived by WebCite at http://www.webcitation.org/6Kt7NrXDl).

Dataset Information

Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances.

Publications

Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances.

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