Interactive effects of depression symptoms, nicotine dependence, and weight change on late smoking relapse

Abstract

Signal detection methods were used to develop an algorithm useful in distinguishing those at risk for late relapse from those likely to maintain abstinence. Four subgroups with 24-month survival (nonrelapse) rates ranging from 79% to 33% were identified. Among participants whose depression symptoms decreased from baseline to the end of treatment, lower levels of nicotine dependence were associated with less relapse at the 24-month follow-up (odds ratio = 2.77; 95% confidence interval: 1.36-5.62). Among participants whose depression symptoms increased from baseline to the end of treatment, greater weight gain was associated with less relapse at follow-up (odds ratio = 2.90; 95% confidence interval: 1.41-5.96). This study suggested that it may become possible to use both baseline and treatment information to "titrate" interventions.