Precision Preventive Medicine of Relapse in Smoking Cessation: Can MRI Inform the Search of Intermediate Phenotypes?

Chronic tobacco smoking remains a major health problem worldwide. Numerous smokers wish to quit but most fail, even if they are helped. The possibility of identifying neuro-biomarkers in smokers at high risk of relapse could be of incredible progress toward personalized prevention therapy. Our aim is to provide a scoping review of this research topic in the field of Magnetic Resonance Imaging (MRI) and to review the studies that investigated if MRI defined markers predicted smoking cessation treatment outcome (abstainers versus relapsers). Based on the available literature, a meta-analysis could not be conducted. We thus provide an overview of the results obtained and take stock of methodological issues that will need to be addressed to pave the way toward precision medicine. Based on the most consistent findings, we discuss the pivotal role of the insula in light of the most recent neurocognitive models of addiction.

Smoking, race, ancestry and prospective abstinence

Background: Factors influencing cessation include biopsychosocial characteristics, treatments and responses to treatment. The first cessation trial designed to assess cessation disparities between African American and White cigarette smokers demonstrated that socioeconomic, treatment, psychosocial and smoking characteristics explained cessation disparities. Ongoing translational efforts in precision cessation treatment grounded in genetically informed biomarkers have identified cessation differences by genotype, metabolism, ancestry and treatment. Methods: In planned analyses, we evaluated six smoking-related measures, demographic and socioeconomic covariates, and prospective abstinence (7-day point prevalence at 12 weeks with bupropion, nicotine replacement and counseling treatments). We assessed concurrent and predictive validity in two covariate models differing by inclusion of Office of Management and Budget (OMB) race/ethnicity or genomic ancestry. Results: We studied Pharmacogenetic Study participants (N=456, mean age 49.5 years, 41.5% female, 7.4% African American, 9.4% Multiracial, 6.5% Other, and 6.7% Hispanic). Cigarettes per day (OR=0.95, P<.001), Fagerström score (OR=0.89, P≤.014), Time-To-First-Cigarette (OR=0.75, P≤.005) and predicted urinary nicotine metabolite ratio (OR=0.57, P≤.039) were associated with abstinence. OMB African American race (ORs from 0.31 and 0.35, p-values≤.007) and African genomic ancestry (ORs from 0.21 and 0.26, p-values≤.004) were associated in all abstinence models. Conclusions: Four smoking-related measures exhibited association with abstinence, including predicted nicotine metabolism based on a novel genomic model. African genomic ancestry was independently associated with reduced abstinence. Treatment research that includes social, psychological, treatment and biological factors is needed to reduce cessation disparities.

Can inpatient pharmacists move the needle on smoking cessation? Evaluating reach and representativeness of a pharmacist-led opt-out smoking cessation intervention protocol for hospital settings

Disclaimer In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose Hospitalization affords an opportunity to reduce smoking, but fewer than half of patients who smoke receive evidence-based cessation treatment during inpatient stays. This study evaluated a pharmacist-led, electronic health record (EHR)-facilitated opt-out smoking cessation intervention designed to address this need. Methods Analyses of EHR records for adult patients who smoked in the past 30 days admitted to an academic medical center in the upper Midwest were conducted using the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. The reach of a pharmacist-led, EHR-facilitated protocol for smoking cessation treatment was assessed by comparing patients’ receipt of nicotine replacement therapy (NRT) and tobacco quitline referral before and after implementation. χ 2 tests, t tests, and multiple logistic regression models were used to compare reach across patient demographic groups to assess treatment disparities and the representativeness of reach. Adoption of the program by hospital services was also assessed. Results Of the 70 hospital services invited to implement the program, 88.6% adopted it and 78.6% had eligible admissions. Treatment reach increased as rates of delivering NRT rose from 43.6% of eligible patients before implementation to 50.4% after implementation (P &lt; 0.0001) and quitline referral rates rose from 0.9% to 11.9% (P &lt; 0.0001). Representativeness of reach by sex and ethnicity improved after implementation, although disparities by race and age persisted after adjustment for demographics, insurance, and primary diagnosis. Pharmacists addressed tobacco use for eligible patients in 62.5% of cases after protocol implementation. Conclusion Smoking cessation treatment reach and representativeness of reach improved after implementation of a proactive, pharmacist-led, EHR-facilitated opt-out smoking cessation treatment protocol in adult inpatient services.

Validity of urges to smoke measures in predicting smoking relapse during treatment in primary care

In the context of smoking cessation treatment in primary care, identifying patients at the highest risk of relapse is relevant. We explored data from a primary care trial to assess the validity of two simple urges to smoke questions in predicting long-term relapse and their diagnostic value. Of 295 patients who received behavioural support and varenicline, 180 were abstinent at week 9. In this subgroup, we measured time spent with urges to smoke (TSU) and strength of urges to smoke (SUT; both scales 1 to 6 = highest). We used separate regression models with TSU or SUT as predictor and relapse from week 9–26 or week 9–52 as an outcome. We also calculated the sensitivity (SP), specificity and positive predictive values (PPV) of TSU and SUT in correctly identifying patients who relapsed at follow-up. The adjusted odds ratios (aOR) for predicting relapse from week 9–26 were 1.74 per point increase (95% CI = 1.05–2.89) for TSU and 1.59 (95% CI = 1.11–2.28) for SUT. The aORs for predicting relapse from week 9–52 were 2.41 (95% CI = 1.33–4.37) and 1.71 (95% CI = 1.14–2.56), respectively. Applying a cut-point of ≥3 on TSU resulted in SP = 97.1 and PPV = 70.0 in week 9–26, and SP = 98.8 and PPV = 90.0 in week 9–52. Applying a cut-point of ≥4 on SUT resulted in SP = 99.0 and PPV = 85.7 in week 9–26, and SP = 98.8 and PPV = 85.7 in week 9–52. Both TSU and SUT were valid predictors of long-term relapse in patients under smoking cessation treatment in primary care. These simple questions may be useful to implement in primary care.Trial registration: Dutch Trial Register (NTR3067).

Internal Validity of Two Promising Methods of Altering Temporal Orientation among Cigarette Smokers

Relapse to smoking continues to be among the most urgent global health concerns. Novel, accessible, and minimally invasive treatments to aid in smoking cessation are likely to improve the reach and efficacy of smoking cessation treatment. Encouraging prospection by decreasing delay discounting (DD) is a new therapeutic target in the treatment of smoking cessation. Two early-stage interventions, delivered remotely and intended to increase prospection, decrease DD and promote cessation are Episodic Future Thinking (EFT) and Future Thinking Priming (FTP). EFT and FTP have demonstrated at least modest reductions in delay discounting, but understanding whether these interventions are internally valid (i.e., are accomplishing the stated intention) is key. This study examined the internal validity of EFT and FTP. Participants (n = 20) seeking to quit smoking were randomly assigned to active or control conditions of EFT and FTP. Linguistic Inquiry Word Count (LIWC2015) was used to examine the language participants used while engaged in the tasks. Results revealed significant differences in the language participants used in the active and control conditions. Women employed more words than men, but no other demographic differences were found in language. The active conditions for both tasks showed a greater emphasis on future orientation. Risk-avoidance was significantly higher in the active vs. control condition for EFT. Remote delivery of both EFT and FTP was valid and feasible as participants adhered to instructions in the remote prompts, and trends in DD were in the expected directions.

Involving Family and Social Support Systems in Tobacco Cessation Treatment for Patients With Cancer

Individuals from the family and social support network of patients with cancer can have a pivotal role in reinforcing patients’ efforts to become and remain tobacco-free. This support is critical along the entire continuum of cancer care. Although NCI-designated Cancer Centers across the United States are increasingly offering tobacco cessation services as a result of the NCI Cancer Center Cessation Initiative (C3I), engaging patients’ family and other support network in tobacco treatment is not yet a routine practice. To facilitate the consideration and involvement of patients’ social support systems (including family, peers, and non–healthcare provider caregivers), we formed the C3I Family and Social Support Systems Working Group. This paper describes the current practices and challenges among C3I cancer centers centers in engaging the support systems of patients with cancer in order to reduce tobacco use and/or secondhand smoke exposure. Building on this knowledge, this Working Group proposes a research agenda to facilitate support persons’ involvement in tobacco treatment as part of oncology care. The research priorities identified include establishing (1) evidence-based strategies for engaging family and social support systems in patients’ cessation efforts, (2) interventions to provide cessation treatment options to support persons, and (3) best practices to routinely identify and engage family and social support systems in patients’ cessation efforts.