Protocol to evaluate sequential electronic health record-based strategies to increase genetic testing for breast and ovarian cancer risk across diverse patient populations in gynecology practices.

BACKGROUND: Germline genetic testing is recommended by the National Comprehensive Cancer Network (NCCN) for individuals including, but not limited to, those with a personal history of ovarian cancer, young-onset (< 50 years) breast cancer, and a family history of ovarian cancer or male breast cancer. Genetic testing is underused overall, and rates are consistently lower among Black and Hispanic populations. Behavioral economics-informed implementation strategies, or nudges, directed towards patients and clinicians may increase the use of this evidence-based clinical practice. METHODS: Patients meeting eligibility for germline genetic testing for breast and ovarian cancer will be identified using electronic phenotyping algorithms. A pragmatic cohort study will test three sequential strategies to promote genetic testing, two directed at patients and one directed at clinicians, deployed in the electronic health record (EHR) for patients in OB-GYN clinics across a diverse academic medical center. We will use rapid cycle approaches informed by relevant clinician and patient experiences, health equity, and behavioral economics to optimize and de-risk our strategies and methods before trial initiation. Step 1 will send patients messages through the health system patient portal. For non-responders, step 2 will reach out to patients via text message. For non-responders, Step 3 will contact patients' clinicians using a novel "pend and send" tool in the EHR. The primary implementation outcome is engagement with germline genetic testing for breast and ovarian cancer predisposition, defined as a scheduled genetic counseling appointment. Patient data collected through the EHR (e.g., race/ethnicity, geocoded address) will be examined as moderators of the impact of the strategies. DISCUSSION: This study will be one of the first to sequentially examine the effects of patient- and clinician-directed strategies informed by behavioral economics on engagement with breast and ovarian cancer genetic testing. The pragmatic and sequential design will facilitate a large and diverse patient sample, allow for the assessment of incremental gains from different implementation strategies, and permit the assessment of moderators of strategy effectiveness. The findings may help determine the impact of low-cost, highly transportable implementation strategies that can be integrated into healthcare systems to improve the use of genomic medicine. TRIAL REGISTRATION: ClinicalTrials.gov. NCT05721326. Registered February 10, 2023. https://www. CLINICALTRIALS: gov/study/NCT05721326.

Cancer-related disease factors and smoking cessation treatment: Analysis of an ongoing clinical trial.

OBJECTIVE: Smoking cessation treatment should be an important aspect of cancer care. In this study, we evaluated whether cancer-related disease factors adversely influence smoking cessation treatment. METHODS: Smokers with cancer (within 5 years of diagnosis, any tumor site) were recruited for an ongoing trial of varenicline for smoking cessation. Disease factors, assessed at baseline, included tumor site, cancer treatment, time since diagnosis, and health-related quality of life. Medication adherence was defined by 132 of 165 pills taken and counseling adherence was defined by 4 of 4 behavioral counseling sessions attended. Abstinence was bioverified at Week 12. Using logistic regression analysis, we assessed the relationship between disease factors and 12-week medication adherence, counseling adherence, and abstinence. RESULTS: Of 144 participants, 56% were medication adherent, 74% were counseling adherent, and 39% were abstinent. Health-related quality of life predicted medication adherence (OR: 1.08, 95% CI, 1.01-1.16, P = .019, d = 0.20) but not counseling adherence or 12-week abstinence. Tumor site, cancer treatment, and time since diagnosis did not predict any smoking cessation treatment outcomes. CONCLUSIONS: Cancer-related disease factors did not predict cancer survivors' engagement or success in smoking cessation treatment. Findings support National Comprehensive Cancer Network Clinical Practice guidelines that recommend smoking cessation treatment for all smokers with cancer, regardless of time since diagnosis.

Does cannabis use moderate smoking cessation outcomes in treatment-seeking tobacco smokers? Analysis from a large multi-center trial.

BACKGROUND AND OBJECTIVE: Tobacco and cannabis are frequently used in combination and cannabis co-use may lead to poor tobacco cessation outcomes. Therefore, it is important to explore if cannabis co-use is associated with a reduced likelihood of achieving successful tobacco abstinence among treatment-seeking tobacco smokers. The present study examined whether current cannabis use moderated tobacco cessation outcomes after 12 weeks of pharmacological treatment (varenicline vs. nicotine patch vs. placebo) with adjunctive behavioral counseling. METHODS: Treatment-seeking tobacco smokers (N = 1,246) were enrolled in an intent-to-treat study, of which 220 were current cannabis users. Individuals were randomly assigned to 12 weeks of placebo (placebo pill plus placebo patch), nicotine patch (active patch plus placebo pill), or varenicline (active pill plus placebo patch), plus behavioral counseling. The primary endpoint was biochemically verified 7-day point prevalence abstinence at the end of treatment. RESULTS: Controlling for rate of nicotine metabolism, treatment arm, age, sex, alcohol, and level of nicotine dependence, cannabis users were as successful at achieving biochemically verified 7-day point prevalence abstinence compared to tobacco-only smokers. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Findings suggest that cannabis use does not hinder the ability to quit tobacco smoking. Future tobacco cessation studies should employ prospective, longitudinal designs investigating cannabis co-use over time and at different severity levels. (Am J Addict 2016;25:291-296).

Decreased Nicotinic Receptor Availability in Smokers with Slow Rates of Nicotine Metabolism.

UNLABELLED: The nicotine metabolite ratio (NMR), a stable measure of hepatic nicotine metabolism via the CYP2A6 pathway and total nicotine clearance, is a predictive biomarker of response to nicotine replacement therapy, with increased quit rates in slower metabolizers. Nicotine binds directly to nicotinic acetylcholine receptors (nAChRs) to exert its psychoactive effects. This study examined the relationship between NMR and nAChR (α4ß2* subtype) availability using PET imaging of the radiotracer 2-(18)F-fluoro-3-(2(S)-azetidinylmethoxy)pyridine (2-(18)F-FA-85380, or 2-(18)F-FA). METHODS: Twenty-four smokers-12 slow metabolizers (NMR < 0.26) and 12 normal metabolizers (NMR ≥ 0.26)-underwent 2-(18)F-FA-PET brain imaging after overnight nicotine abstinence (18 h before scanning), using a validated bolus-plus-infusion protocol. Availability of nAChRs was compared between NMR groups in a priori volumes of interest, with total distribution volume (VT/fP) being the measure of nAChR availability. Cravings to smoke were assessed before and after the scans. RESULTS: Thalamic nAChR α4ß2* availability was significantly reduced in slow nicotine metabolizers (P = 0.04). Slow metabolizers exhibited greater reductions in cravings after scanning than normal metabolizers; however, craving was unrelated to nAChR availability. CONCLUSION: The rate of nicotine metabolism is associated with thalamic nAChR availability. Additional studies could examine whether altered nAChR availability underlies the differences in treatment response between slow and normal metabolizers of nicotine.

Comparing cancer patients who enroll in a smoking cessation program at a comprehensive cancer center with those who decline enrollment.

BACKGROUND: Despite the availability of smoking interventions for cancer patients, many eligible patients decline enrollment into such programs. We examined reasons patients provide for declining smoking treatment and compared treatment decliners to enrollees. METHODS: Eligible cancer patients (N = 231) were offered smoking cessation treatment. During recruitment, demographic, medical (eg, cancer stage), and smoking-related behavioral (eg, readiness to quit) data were collected, and decliners stated a reason for refusal. Patients who enrolled in the cessation program (N = 109) were compared with those who declined (N = 122) in terms of recruitment data, and reasons for declining were compiled. RESULTS: Decliners were significantly more likely to: (1) have head and neck cancer (vs lung cancer); (2) exhibit fewer physical symptoms (eg, shortness of breath); (3) report a lower readiness to quit smoking; (4) indicate no intention to quit smoking; and (5) smoke fewer cigarettes. A preference to quit without professional assistance was the most common reason for declining treatment. CONCLUSIONS: Our findings highlight important differences between patients who enroll in a smoking cessation program and those who decline and underscore the need for motivational interventions to facilitate enrollment into smoking interventions for cancer patients.

Implementation of a comprehensive cancer control program at the worksite: year one summary report.

The worksite is an ideal forum for cancer risk assessment. We describe here the baseline characteristics of a large cohort. Participants completed surveys that assessed a variety of risk factors and behavioral mediators. Personalized feedback letters identified cancer risks. A total of 4395 surveys were received. Cancer prevalence was 6.5% (range, 4.3% to 11.2%). The most common risk factors were lack of exercise (41%; 32% to 68%), obesity (28%; 24% to 39%), and smoking (14%; 13% to 32%). Cardiovascular risk was also common (25%; 15% to 48%). Screening was fair to good for all cancers except colon cancer. The perceived risk for cancer was less than that for cardiovascular disease (P < 0.0001). Most smokers were in the pre-contemplation phase, whereas action/maintenance phases predominated for breast and colon cancer screening. Modifiable cancer risk factors can be identified in the majority of workers. Inaccurate risk perception is an important target for future interventions.

Processes of change related to smoking behavior among cancer patients.

PURPOSE: The purpose of this study was to examine the degree to which transtheoretical model processes of change (methods and strategies for cessation) were associated with smoking status and quitting behavior (ie, intentions and attempts to quit) among patients with head and neck or lung cancer. The relationship between medical variables and processes of change was also explored. DESCRIPTION OF STUDY: Twenty-nine smokers and 45 abstainers who were recruited from treatment clinics within a comprehensive cancer center completed a brief survey. Multivariate analysis of variance and Pearson correlation procedures were used to evaluate hypothesized relationships. RESULTS: As hypothesized, quitters used behavioral processes such as counter-conditioning and reinforcement management significantly more than smokers and used self-reevaluation, an experiential process, significantly less than smokers. Contrary to the hypothesis, however, quit attempts and intentions were associated with both experiential (ie, consciousness raising and self-reevaluation) and behavioral (ie, reinforcement management and self-liberation) processes of change. Use of the processes of change was not influenced by medical variables, including cancer type, illness phase, disease stage, type of current medical treatment, and duration of illness. CLINICAL IMPLICATIONS: These findings suggest that behavioral counseling to promote smoking cessation for patients with cancer should involve assisting the patient to do the following: develop an awareness of the health risks related to continued smoking; devise and use alternative behaviors; implement the use of reinforcement strategies for cessation successes; and develop a sense of confidence and commitment about quitting as well as healthy lifestyle values. These strategies are discussed within the context of models and guidelines for smoking cessation in clinical practice.