Introduction: There is increasing evidence that response to pharmacological treatment for nicotine dependence may be moderated by genetic polymorphisms. However, the feasibility, acceptability, and impact of genetically tailoring treatment in real-world clinical settings are unknown.
Methods: We conducted a multiphased, mixed-methods feasibility study with current smokers to develop and evaluate a patient-centered, theoretically grounded personalized medicine treatment protocol. The initial research phase included formative work to develop intervention materials. The second phase included a randomized pilot trial to evaluate the intervention. Trial participants (n = 36) were genotyped for ANKK1 rs1800497 and were randomized to receive genetic feedback (GF) plus standard behavioral counseling (BC) for smoking cessation or BC without GF. All participants received genetically tailored pharmacotherapy (nicotine patch or bupropion).
Results: The intervention was feasible to implement and was acceptable to participants based on satisfaction ratings and objective measures of participation. There was no evidence that the GF resulted in adverse psychological outcomes (e.g., depression, fatalism, reduced perceived control over quitting, differential motivation for quitting) based on quantitative or qualitative outcomes.
Conclusions: Study results suggest that it is feasible to offer treatment within a health care setting that includes genetically tailored pharmacotherapy and doing so had no apparent adverse psychological impacts. Further evaluation of pharmacogenetically tailored smoking cessation interventions appears warranted.
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http://dx.doi.org/10.1093/ntr/nts173 | DOI Listing |
Drug Alcohol Depend Rep
December 2024
Department of Family and Preventive Medicine, College of Medicine, The University of Oklahoma Health Sciences, Oklahoma City, OK, USA.
Background: Smoking prevalence among U.S. adults experiencing homelessness is ≥70 %.
View Article and Find Full Text PDFTob Control
January 2025
Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy.
BackgroundTobacco use is linked to increased cancer risk, and people who smoke represent a large proportion of newly diagnosed patients with cancer. The fact that smoking cessation at the time of diagnosis can improve the patient's life expectancy is still not broadly understood. We conducted a systematic review and meta-analysis to quantify the survival benefits obtainable by quitting smoking on diagnosis.
View Article and Find Full Text PDFEur J Public Health
January 2025
Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
We quantified the fraction of cardiovascular deaths attributable to smoking in Germany over time, accounting for population ageing. We calculated population-attributable fractions to quantify cardiovascular deaths attributable to smoking for 1992 to 2021, and compared actual with age-standardized figures. We found a significant decline in the number of cardiovascular deaths attributable to smoking: from about 71 900 cases in 1992 to around 42 000 cases in 2021, with a steeper decline in men.
View Article and Find Full Text PDFIntern Emerg Med
January 2025
Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA.
Recent data on methods used by adults to stop smoking can inform tobacco control policies. Nationally representative Centers for Disease Control and Prevention survey data from the 2022 National Health Interview Survey (N = 27,651) were used to analyze populations of US adults who self-reported having stopped smoking cigarettes for 6 months or longer in the last year and the methods they used, or who did not stop smoking but tried in the last year (N = 1735). In 2022, an estimated 2.
View Article and Find Full Text PDFPsychol Methods
January 2025
Department of Psychology, University of Pittsburgh.
Intensive longitudinal data analysis, commonly used in psychological studies, often concerns outcomes that have strong floor effects, that is, a large percentage at its lowest value. Ignoring a strong floor effect, using regular analysis with modeling assumptions suitable for a continuous-normal outcome, is likely to give misleading results. This article suggests that two-part modeling may provide a solution.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!