Abstract
AIMS: To examine the association of person-specific trajectories of withdrawal symptoms of urge-to-smoke, negative affect, physical symptoms and hunger during the first 7 days after smoking cessation with abstinence at end of treatment (EOT) and at 6 months. DESIGN: Hierarchical linear modeling (HLM) was used to model person-specific trajectory parameters (level, slope, curvature and volatility) for withdrawal symptoms. SETTING: University-based smoking cessation trials. PARTICIPANTS: Treatment-seeking smokers in clinical trials of transdermal nicotine versus nicotine spray (n = 514) and bupropion versus placebo (n = 421). MEASUREMENTS: Self-reported withdrawal symptoms for 7 days after the planned quit date, and 7-day point prevalence and continuous abstinence at EOT and 6 months. FINDINGS: In regressions that included trajectory parameters for one group of withdrawal symptoms, both urge-to-smoke and negative affect were predictive of abstinence while physical symptoms and hunger were generally not predictive. In stepwise regressions that included the complete set of trajectory parameters across withdrawal symptoms (for urge-to-smoke, negative affect, physical symptoms and hunger), with a single exception only the trajectory parameters for urge-to-smoke were predictive. Area under the receiver operator characteristic curve was 0.594 for covariates alone, and 0.670 for covariates plus urge-to-smoke trajectory parameters. CONCLUSIONS: Among a number of different withdrawal symptoms (urge-to-smoke, negative affect, physical symptoms and hunger) urge-to-smoke trajectory parameters (level, slope and volatility) over the first 7 days of smoking cessation show the strongest prediction of both short- and long-term relapse. Other withdrawal symptoms increase the predictive ability by negligible amounts.