The American Southeast has some of the highest rates of cigarette smoking and smoking-attributable cancer mortality in the nation. Medicaid and Medicare (CMS) beneficiaries who smoke are at high risk of smoking- related disease, yet each year fewer than one in five CMS-enrolled smokers (and fewer than one in ten Tennessee Medicaid smokers) with pharmacy benefits receive smoking cessation medication. Furthermore, when smoking cessation medication is provided, it is not biologically tailored for maximum efficacy. The ratio of 3-hydroxycotinine to cotinine, known as the nicotine metabolite ratio (NMR), reflects CYP2A6 activity and the rate of nicotine metabolism. Among ?normal? metabolizers as assessed by NMR, varenicline produces quit rates roughly double those of nicotine patch at 6 months (23% vs. 13%, p<0.05), while among ?slow? metabolizers, quit rates do not differ by drug. The number needed to treat to help one normal metabolizer quit smoking is only 4.9 for varenicline vs. 26 for nicotine patch, establishing the scientific premise to pair normal metabolizers with varenicline and slow metabolizers with nicotine. We propose to test Metabolism-Informed Smoking Treatment (MIST), a precision approach that biologically tailors medication to nicotine metabolism, for CMS beneficiaries in the Mid-South who smoke. We hypothesize that MIST will be superior to usual care (UC), i.e., selection of medication uninformed by NMR, for smoking cessation. We randomized 81 adult daily smokers at Vanderbilt University Medical Center (VUMC) to MIST vs control. MIST increased NMR-medication match rates more than 3-fold: unadjusted odds ratio 3.67 (95% confidence interval 1.33-11.00; p-value=0.02), and was highly acceptable to patients. To assess the efficacy of MIST relative to UC for abstinence and its use by patients and providers in clinical practice, the MIST RCT will enroll 1,000 CMS-enrolled adult daily smokers who are hospitalized and counseled by the inpatient VUMC Tobacco Treatment Service.
Specific AIMS are to compare the effects of MIST vs. UC on: (1) Abstinence at 6 months (1a, 1 study outcome), defined by biochemically-verified 7-day point prevalence abstinence, and 12 months (1b, 2 outcome); (2) Clinical implementation, defined by patient self-reported medication adherence (2a, 2 outcome), PCP prescription of medication for patients smoking after hospital discharge (2b, 2 outcome), and whether the prescription is NMR-matched (2c, 2 outcome); and (3) Health care utilization and mortality (exploratory) as tracked by existing databases including the statewide Tennessee Hospital Discharge Data System and CMS data. All participants will receive counseling and medication for tobacco use. Investigators have broad, complementary expertise in smoking cessation clinical trials, precision medicine, smoking pharmacogenomics, and use of large databases, and leverage extensive health system infrastructure. IMPACT: This is the first large RCT to incorporate nicotine metabolism into clinical care, and could fundamentally shift smoking treatment away from a generic approach and into the era of precision medicine.
People who smoke respond differently to some quit smoking medications based on how their body metabolizes (breaks down) nicotine; some people break down nicotine quickly, while others break it down more slowly. This information may be helpful to choose a quit smoking medication with the highest chances of success, and may encourage smokers and their doctors to keep trying. We are testing whether using information about speed of nicotine metabolism will help more people successfully quit smoking.
