Results : We confirmed the importance of the 4 main factors influencing SC : ( 1 ) environmental factors , ( 2 ) genomic factors , ( 3 ) gene-environment interactions , and ( 4 ) evidence -based interventions .
The model demonstrates the complex network of factors influencing SC .
Background : Smoking behaviour is a major public health problem worldwide .
Several sources have confirmed the implication of genomic factors in smoking behaviour .
These factors interact both with environmental factors and interventions to develop a certain behaviour .
Objectives : Describing the environmental and genomic factors as well as the interventions influencing smoking cessation  ( SC ) and developing a working model incorporating the different factors influencing SC were our main objectives .
Identification of pharmacogenetic markers in smoking cessation therapy
Pharmacogenetic clinical trials seek to identify genetic modifiers of treatment effects . When a trial has collected data on many potential genetic markers , a first step in analysis is to screen for evidence of pharmacogenetic effects by testing for treatment‐by‐marker interactions in a statistical model for the outcome of interest . This approach is potentially problematic because ( i ) individual significance tests can be overly sensitive , particularly when sample sizes are large ; and ( ii ) st and ard significance tests fail to distinguish between markers that are likely , on biological grounds , to have an effect , and those that are not . One way to address these concerns is to perform Bayesian hypothesis tests [ Berger ( 1985 ) Statistical decision theory and Bayesian analysis . New York : Springer ; Kass and Raftery ( 1995 ) J Am Stat Assoc 90:773–795 ] , which are typically more conservative than st and ard uncorrected frequentist tests , less conservative than multiplicity‐corrected tests , and make explicit use of relevant biological information through specification of the prior distribution . In this article we use a Bayesian testing approach to screen a panel of genetic markers recorded in a r and omized clinical trial of bupropion versus placebo for smoking cessation . From a panel of 59 single‐nucleotide polymorphisms ( SNPs ) located on 11 c and i date genes , we identify four SNPs ( one each on CHRNA5 and CHRNA2 and two on CHAT ) that appear to have pharmacogenetic relevance . Of these , the SNP on CHRNA5 is most robust to specification of the prior . An unadjusted frequentist test identifies seven SNPs , including these four , none of which remains significant upon correction for multiplicity . In a panel of 43 r and omly selected control SNPs , none is significant by either the Bayesian or the corrected frequentist test . © 2007 Wiley‐Liss ,
Results : We confirmed the importance of the 4 main factors influencing SC : ( 1 ) environmental factors , ( 2 ) genomic factors , ( 3 ) gene-environment interactions , and ( 4 ) evidence -based interventions .
The model demonstrates the complex network of factors influencing SC .
Background : Smoking behaviour is a major public health problem worldwide .
Several sources have confirmed the implication of genomic factors in smoking behaviour .
These factors interact both with environmental factors and interventions to develop a certain behaviour .
Objectives : Describing the environmental and genomic factors as well as the interventions influencing smoking cessation  ( SC ) and developing a working model incorporating the different factors influencing SC were our main objectives .