Predicting Individuals' Probability of Response to Smoking Cessation Pharmacotherapy

Approximately 16% of adults in the United States are current tobacco smokers and the health effects are extremely costly. Though several Food and Drug Administration (FDA)-approved smoking cessation pharmacotherapies exist [e.g., varenicline, bupropion, nicotine replacement therapy (NRT)], utilization rates remain low and a substantial portion of smokers do not respond to existing treatments. Fewer than half of smokers who make a quit attempt use an evidence-based medication. The most effective single medication to-date, varenicline, results in abstinence at treatment completion for approximately 35-50% of smokers, but only 14% of smokers who make a quit attempt use a prescription medication like varenicline. The gold standard method (randomized controlled trial; RCT) for evaluating efficacy of smoking cessation medications provides information about the effect of the medication at the population-level. However, traditional RCTs are not able to provide an individual smoker with an estimate of their probable treatment response. Our goal is to develop and test an algorithm, based on demographic and clinical data assessed prior to treatment, to estimate individual smokers’ likely response to FDA-approved pharmacotherapies for smoking cessation, including varenicline, bupropion, and nicotine replacement therapy (NRT). This will aid in treatment recommendations for smokers and potentially increase medication-aided smoking cessation attempts.