We examined whether a pretreatment phenotypic marker of nicotine metabolism rate (NMR) predicts successful smoking cessation with bupropion. Smokers (N = 414) were tested for pretreatment NMR, based on the ratio of 3′-hydroxycotinine/ cotinine derived during smoking, before entering a placebocontrolled randomized trial of bupropion plus counseling. At the end of the 10-week treatment phase, slow metabolizers (1st NMR quartile) had equivalent quit rates with placebo or bupropion (32%). Fast metabolizers (4th NMR quartile) had low quit rates with placebo (10%), and these were enhanced significantly by bupropion (34%). Smokers in the 2nd quartile (placebo: 25%, bupropion: 30%) and the 3rd quartile (placebo: 20%, bupropion: 30%) did not benefit significantly from bupropion. At the 6-month follow-up, the relationship between the NMR and quitting remained similar, but was no longer statistically significant. A pretreatment assessment of NMR may identify smokers who are most and least likely to benefit from treatment with bupropion for smoking cessation.Personalized medicine, in which therapies are delivered to individual patients on the basis of pretreatment biological markers, is emerging as a new model of healthcare delivery. 1,2 In the area of tobacco dependence treatment, genetic variants in nicotinemetabolizing enzymes are plausible candidates for prediction of therapeutic response. 3,4 Nicotine is metabolized to cotinine (COT), predominantly by the liver enzyme cytochrome P450 (CYP) 2A6; 5,6 COT is further metabolized to trans-3ʹ-hydroxycotinine (3HC) by the same enzyme. 5 Consistent with the premise that faster inactivation and elimination of nicotine lead to higher rates of smoking so as to maintain nicotine levels in the system, reproducible associations of CYP2A6 genotype with smoking behavior have been reported. 3,[7][8][9] The ratio of the levels of 3HC/COT arising from cigarette smoking, as measured in plasma, saliva, or urine, is associated with the CYP2A6 genotype. 3,10,11 This phenotype measure is highly reproducible and independent of time elapsed since the last cigarette. 12-14 Further, the ratio is strongly correlated with plasma nicotine levels and nicotine clearance. 10,14-16 Consistent with these genetic and pharmacokinetic data, we have reported that the nicotine metabolite ratio predicts successful quitting of smoking with the use of transdermal nicotine. 16 In this earlier investigation, the odds of achieving smoking cessation with transdermal nicotine therapy were reduced by 30% with each increasing quartile of the nicotine metabolite ratio. Faster metabolizers of nicotine were less successful in quitting than slower metabolizers and also had lower plasma levels of nicotine during treatment and stronger cravings to smoke.In order to extend this line of research on the role of NMR in achieving success in smoking cessation, we examined the predictive clinical validity of the 3HC/COT ratio within a double-blind placebo-controlled pharmacogenetic clinical trial of bupropion efficacy. [17][18][19] ...

Advances in genomics research may improve health outcomes by tailoring treatment according to patients’ genetic profiles. The treatment of nicotine dependence, in particular, may soon encompass pharmacogenetic treatment models. Realizing the benefits of such treatment strategies may depend on physicians’ preparedness to incorporate genetic testing into clinical practice. This article describes barriers to clinical integration of pharmacogenetic treatments that will need to be addressed to realize the benefits of individualized smoking-cessation treatment.

Purpose: American cancer centers supported by the National Cancer Institute (NCI) must ensure that their research addresses the cancer relevant needs and risks of members of their catchment area. In 2016, the NCI supported catchment area assessments. This is the first study to describe a cancer center catchment area cancer risk evaluation, focusing on tobacco use and lung cancer screening. Methods: A cross-sectional survey was conducted in 2017 with 1,005 residents within a Philadelphia cancer center catchment area to identify the rate and correlates of smoking and rate of lung cancer screening. Results: The rate of current smoking in the catchment was 13%. Current smokers were more likely to have depression/ anxiety, less likely to be eating healthy, more likely to use e-cigarettes, and endorsed lower perceived health and higher cancer fatalism, vs. former (27%) or never smokers; 74% of smokers want to quit smoking, but two-thirds think nicotine dependence medications are unsafe and ineffective, which may be addressed with personalized treatment. E-cigarette use was 11% and lung screening rates were < 30%. Conclusions: These results indicate that addressing tobacco use in the cancer center's catchment may require targeting comorbid psychiatric conditions and additional cancer risk behaviors such as poor diet, modifying cancer beliefs that may undermine cessation, and utilizing novel methods to promote utilization of evidence-based treatment for smoking. E-cigarette use should be targeted, as well as identifying methods to promote lung screening. This study shows how a cancer center can identify catchment area needs to plan research that reduces the burden of cancer among their residents.