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Aim. Plasma values of nicotine and its metabolites are highly variable, and this variability has a strong genetic influence. In our study, we analysed the impact of common polymorphisms associated with smoking on the plasma values of nicotine, nicotine metabolites and their ratios and investigated the potential effect of these polymorphisms and nicotine metabolite ratios on the successful treatment of tobacco dependence. Methods. Five variants (rs16969968, rs6474412, rs578776, rs4105144 and rs3733829) were genotyped in a group of highly dependent adult smokers (n=103). All smokers underwent intensive treatment for tobacco dependence; 33 smokers were still abstinent at the 12-month follow-up. Results. The rs4105144 (CYP2A6, P

ObjectivesMost people gain weight on stopping smoking but the extent of weight gain varies greatly. Interventions aimed at all quitters to prevent weight gain on cessation have proven unpopular but targeting people who have gained excess weight immediately after quitting may improve uptake and cost-effectiveness. We examined whether early large postcessation weight gain predicts overall large weight gain.DesignRetrospective cohort study.SettingPrimary care setting—smoking cessation centre in Prague, Czech Republic.ParticipantsOut of 3537 patients treated between 2005 and 2013, 1050 were continuous abstainers (verified by carbon monoxide measurement) at 1-year follow-up and formed the cohort of the current report. 48.7% were women (n=511) with the mean age of 46 (±14.4) years.MethodsIn this retrospective cohort study, all patients underwent usual tobacco dependence treatment using evidence-based methods. Weight was measured prior to smoking cessation and at each visit after quitting.ResultsThe mean weight gain in the first month (n=763) was 0.79% (±2.03%), in the second month (n=646) was 1.49% (±2.58%), for the third month (n=566) 2.33% (±3.44%) and 4.1% (±5.31%) after 1-year follow-up (n=1050). The regression coefficient per 1% rise in the first 3 months was +0.13% (95% CI −0.04% to 0.30%). A receiver operating curve analysis showed that patients gaining more than 0.98% of their baseline weight during first 3 months had a sensitivity of 66% and specificity of 44% for gaining 7% or more weight by 12 months. In addition, lower body mass index and an increase in appetite at 3 months after quitting were associated with greater weight gain, while using nicotine replacement therapy was associated with less weight gain at 1-year follow-up.ConclusionsPeople who stop smoking and gain a larger amount of weight early after quitting are not more likely to gain excessively at 1 year.

To identify possible predictors of post-cessation weight gain in smoking abstainers.A sample of 607 successful abstainers seen at the Centre for Tobacco-Dependent in Prague, Czech Republic, between 2005 and 2010, was included in this analysis. This sample was followed up for 1year and included 47.9% women (N=291) with the mean age of 48years (18-85).Post-cessation weight gain occurred in 88.6% of the 607 abstainers. The mean weight gain after one year post-quit was 5.1kg (95% confidence interval 4.7-5.5kg). Baseline characteristics associated with increased weight gain included a higher baseline smoking rate (p0.001), more severe cigarette dependence (p=0.003), less physical activity (p=0.008), and a report of increased appetite on the baseline assessment of withdrawal symptoms (p0.001).Smokers who are more dependent and have minimal physical activity are at increased risk for post-cessation weight gain. For these smokers, incorporating interventions targeting the weight issue into tobacco dependence treatment is recommended. Further research should be done to identify reasons for this important quitting complication.

Purpose Tobacco/nicotine dependence has a significant heritable component. Genome-wide association studies have associated the single nucleotide polymorphisms (SNPs) rs578776, rs16969968, rs6474412, rs3733829 and rs4105144 with nicotine dependence in Western European populations. We examined whether these SNPs influence nicotine dependence and successful treatment of tobacco dependence in the Czech middle-European population. Materials and methods Variants were analysed by PCR-RFLP or by TaqMan assay in 807 adult heavy tobacco-dependent smokers – patients of the Centre for Treatment of Tobacco Dependence (Prague) as well as 1,362 self-reported non-smokers. Results and discussion Except for rs3733829, association with tobacco dependence was confirmed for all other genetic variants. In agreement with previous studies, the strongest determinant of tobacco dependence was rs16969968 with OR (95%CI) 1.32 (1.08–1.62) for A allele carriers vs. GG comparison (P = 0.003). In contrast, none of the analysed variants reached significance with respect to a 1-year course of successful tobacco dependence treatment (all P over 0.18) in a subset of 525 patients. Conclusion We confirmed the association between variants within genes that code nicotinic-acetylcholine receptors (-A3, -A5 and -B3), CYP2A6/B6 and tobacco dependence development in the Czech population. The success of the tobacco dependence treatment was not influenced by the analysed SNPs.

The mechanisms behind the changes of body weight after smoking cessation are only partially understood. To this end, we explored the possible effects of smoking cessation on incretin hormones, leptin and selected anthropometric, biochemical and other hormonal parameters. Twenty-two non-obese male adult smokers attending an ambulatory smoking cessation program in Prague, Czech Republic, were examined at the baseline. Thirteen patients (mean age 37.92±2.66 years, mean body mass index 25.56±0.69 kg/m2) successfully quit smoking and were examined three months after smoking cessation; relapsed smokers were not followed up. The patients underwent 2-h liquid meal test with Fresubin and repeated blood sampling for measurements of blood glucose, gastric inhibitory polypeptide (GIP), glucagon-like peptide 1 (GLP-1), amylin, insulin, leptin, peptide-YY (PYY) and pancreatic polypeptide (PP). Three months after smoking cessation, body weight increased (4.35±3.32 kg, p

Introduction Higher prevalence of smoking among depressed patients, as well as the risk of depression in smokers, is well documented. The proportion of patients with a history of depression among those seeking intensive treatment of tobacco dependence is also high. In contrast, evidence of treatment success in this subgroup of patients is controversial. The aim of this study was to compare smoking abstinence rates after tobacco treatment in smokers with and without a history of depression. Methods We reviewed retrospective data from 1,730 smokers seeking treatment in Prague, Czech Republic. History of depression was defined as past diagnosis of depression or current treatment of depression. After a 1-year, self-reported smoking status was validated by expired-air carbon monoxide. We used logistic regression to analyze associations between abstinence rates, history of depression, and other factors (eg, age, sex, tobacco dependence). Results Of 1,730 smokers treated, 289 (16.7%) had a history of depression. The smoking abstinence rate at 1 year was 32.5% for smokers with a history of depression and 38.7% for those with no history (P = .048). Among women, abstinence did not differ between groups (35.0% vs 35.7%; P = .86). However, among men, those with a history of depression had lower rates of abstinence (27.4% vs 41.3%; P = .009). After adjustment for baseline covariates, history of depression was not significantly associated with smoking abstinence in men or women. Conclusion Intensive outpatient tobacco treatment programs can achieve abstinence rates among smokers with a history of depression similar to rates among the general population.

Smoking cessation is an essential part of cardiovascular disease (CVD) prevention. At the Center for Tobacco-Dependent (CTD), clients are screened to identify and reduce cardiovascular (CV) risk factors. In our study we have focused on the role of the CTD in reducing global CV risk.1,334 CTD patients aged 25-64 years (52.2% men, mean age 44±12 years, Fagerström Test for Cigarette Dependence 6±2) were included in a retrospective cross-sectional survey. Medical history, blood samples and physical examination were analysed. Blood pressure, weight and exhaled CO were measured at each visit (12-months-follow-up). Patients' CV risk was scored. CO-verified abstinence according to CV risk and prevalence of detected CV risk factors were examined.Among patients who had attended at least their first visit and a visit after one year, 37.9% (506/1,334) had stopped smoking. Among patients with a SCORE of5%, the success rate was 44.3% (254/574) and 41.2% for patients at high CV risk (105/255, p=0.41). There was a trend towards a lower success rate among patients with CVD, but this difference was not significant. The smoking cessation rate among low and high CV risk patients at the baseline visit was identical (46.2%, resp. 47.3%, p=0.81). 3.1% (42/1,334) of patients were referred to a specialist for hypertension. 62.5% (223/357), without a prior history, were found to have dyslipidemia.High CV risk patients have the same chance to stop smoking as low risk patients.

Cross-study comparisons of effect sizes suggest that varenicline is more effective than nicotine replacement therapy (NRT) in aiding smoking cessation, but evidence from direct comparisons is limited. This study compared biochemically verified 52-week sustained abstinence rates in smokers attending the same clinical service according to whether they used varenicline or NRT in their quit attempt.This was a prospective cohort study of 855 smokers attending a large smoking cessation clinic who used their choice of NRT product or varenicline in their quit attempt. All received the same behavioural support programme and chose their medication option (n = 519 varenicline; n = 336 NRT). The primary outcome measure was self-report of 52 weeks' abstinence following the target quit date confirmed by expired air carbon monoxide concentration. Baseline measures included socio-demographic variables, mental health diagnoses, measures of smoking, cigarette dependence and past use of NRT or varenicline.The 52-week abstinence rates were 42.8% versus 31.0% in those using varenicline versus NRT, respectively (P 0.001). After adjusting for all baseline variables, the odds of remaining abstinent for 52 weeks were 2.03 (95% CI 1.46-2.82), P 0.001 times higher in those using varenicline than those using NRT.Smokers in the same behavioural support programme who use varenicline appear to have a greater probability of achieving long-term abstinence than those using their choice of nicotine replacement therapy options, even after adjusting for potentially confounding smoker characteristics.

BACKGROUND: Smoking is more prevalent among people with depression. Depression may make cessation more difficult and cessation may affect depression symptoms.PURPOSE: The aims of this study were to assess the associations between (1) baseline depression and 1-year smoking abstinence and (2) abstinence and change in depression.METHODS: Observational study using data collected routinely in a smoking cessation clinic in the Czech Republic from 2008 to 2014. Aim 1: N = 3775 patients; 14.3% reported mild and 15.4% moderate/severe baseline depression levels measured using Beck's Depression Inventory (BDI-II). Logistic regressions assessed if depression level predicted 1-year biochemically verified abstinence while adjusting for patient and treatment characteristics. Aim 2: N = 835 patients abstinent at 1 year; change in depression was analysed using Chi-square statistics, t test and mixed method analyses of variance.RESULTS: Rate of abstinence was lower for patients with mild (32.5%, OR = 0.68; 95% CI: 0.54 to 0.87, p = 0.002) and moderate/severe depression (25.8%; OR = 0.57, 95% CI: 0.45 to 0.74, p < 0.001) compared with patients without depression (40.5%). Across abstinent patients, the majority with baseline depression reported lower depression levels at follow-up. Overall mean (SD) BDI-II scores improved from 9.2 (8.6) to 5.3 (6.1); t(834) = 14.6, p < 0.001. There were significant main effects of time (F(1832) = 880.8, p < 0.001, partial η(2) = 0.51) and baseline depression level (F(2832) = 666.4, p < 0.001, partial η(2) = 0.62) on follow-up depression and a significant depression * time interaction (F(2832) = 296.5, p < 0.001, partial η(2) = 0.42).CONCLUSIONS: In this effective smoking cessation clinic, depression at the start of treatment predicted reduced smoking abstinence 1 year later. Patients abstinent from smoking experienced considerable improvement in depression.