Tobacco smoking is an important risk factor for cancer incidence, an effect modifier for cancer treatment, and a negative prognostic factor for disease outcomes. Inadequate implementation of evidence-based smoking cessation treatment in cancer centers, a consequence of numerous patient-, provider-, and system-level barriers, contributes to tobacco-related morbidity and mortality. This study provides data for a paradigm shift from a frequently used specialist referral model to a point-of-care treatment model for tobacco use assessment and cessation treatment for outpatients at a large cancer center. The point-of-care model is enabled by a low-burden strategy, the Electronic Health Record-Enabled Evidence-Based Smoking Cessation Treatment program, which was implemented in the cancer center clinics on June 2, 2018. Five-month pre- and post-implementation data from the electronic health record (EHR) were analyzed. The percentage of cancer patients assessed for tobacco use significantly increased from 48% to 90% (z = 126.57, p < .001), the percentage of smokers referred for cessation counseling increased from 0.72% to 1.91% (z = 3.81, p < .001), and the percentage of smokers with cessation medication significantly increased from 3% to 17% (z = 17.20, p < .001). EHR functionalities may significantly address barriers to point-of-care treatment delivery, improving its consistent implementation and thereby increasing access to and quality of smoking cessation care for cancer center patients.

Little is known about patients' electronic cigarette use, interest in and use of smoking cessation treatments, and providers' attitude towards such treatment. We assessed patients (N = 231) and providers (45 psychiatrists, 97 case workers) in four Community Mental Health Centers. Interestingly, 50% of smokers reported interest in using electronic cigarettes to quit smoking, and 22% reported current use. While 82% of smokers reported wanting to quit or reduce smoking, 91% of psychiatrists and 84% of case workers reported that patients were not interested in quitting as the lead barrier, limiting the provision of cessation interventions. Providers' assumption of low patient interest in treatment may account for the low rate of smoking cessation treatment. In contrast, patients report interest and active use of electronic cigarettes to quit smoking. This study highlights the need for interventions targeting different phases of smoking cessation in these patients suffering disproportionately from tobacco dependence.

It is unclear if genetic variants affect smoking cessation treatment response. This study tested whether variants in the cholinergic receptor nicotinic alpha 5 subunit (CHRNA5) predict response to smoking cessation medication by directly comparing the two most effective smoking cessation pharmacotherapies. In this genotype-stratified randomized, double-blind, placebo-controlled clinical trial (May 2015-August 2019 in St Louis, Missouri), smokers were randomized by genotype in blocks of six (1:1:1 ratio) to three conditions: 12 weeks of placebo (n = 273), combination nicotine patch and lozenge (combination nicotine replacement therapy, cNRT, n = 275), or varenicline (n = 274). All participants received counseling and were followed for 12 months. The primary end point was biochemically verified 7-day point prevalence abstinence at the end of treatment (EOT, week 12). Trial registration and eligibility criteria are on clinicaltrials.gov (https:// clini caltr ials.gov/) (NCT02351167). We conducted the genetic analyses separately for 516 European ancestry (EA) smokers and 306 non-EA smokers (including 270 African American smokers). In African American smokers, there was a genotype-by-treatment interaction for EOT abstinence (χ 2 = 10.7, degrees of freedom = 2. P = 0.0049): specifically, cNRT was more effective in smokers with rs16969968 GG genotype than was placebo, while varenicline was more effective in smokers of GA/AA genotypes. In EA ancestry smokers, there was no significant genotype-by-treatment interaction. In the whole sample, although both were effective at EOT, only varenicline, and not cNRT, was significantly effective relative to placebo at 6-month follow-up. Importantly, this study suggests that genetic information can further enhance smoking cessation treatment effectiveness.

Rural populations face significant smoking-related health disparities, such as a higher prevalence of lung cancer and cancer mortality, higher prevalence of smoking, and lower likelihood of receiving cessation treatment than urban counterparts. A significant proportion of health disparities in rural populations could be eliminated with low-barrier, easy-access treatment delivery methods for smoking cessation. In this study, we assessed treatment engagement among patients in rural and urban settings. Then, we examined the effect of an electronic health record-based smoking cessation module on patient receipt of evidence-based cessation care. As part of a quality improvement project, we retrospectively observed 479,798 unique patients accounting for 1,426,089 outpatient clinical encounters from June 2018–March 2019 across 766 clinics in the greater St. Louis, southern Illinois, and mid-Missouri regions. Smoking prevalence was higher in rural versus urban clinics (20.7% vs. 13.9%, 6.7% [6.3, 7.1], odds ratio = 1.6 [1.6, 1.6], p < 0.0001), and yet rural smokers were nearly three times less likely than their urban counterparts to receive any smoking cessation treatment after adjusting for patients clustering within clinics (9.6% vs. 25.8%, −16.2% [−16.9, −15.5], odds ratio = 0.304 [0.28, 0.33], p < 0.0001). Although not yet scaled up in the rural setting, we examined the effects of a low-burden, point-of-care smoking module currently implemented in cancer clinics. After adjusting for patient clustering within clinics, patients were more likely to receive smoking treatment in clinics that implemented the module versus clinics that did not implement the module (31.2% vs. 17.5%, 13.7% [10.8, 16.6], odds ratio = 2.1 [1.8, 2.6], p < 0.0001). The point-of-care treatment approach offers a promising solution for rural settings, both in and outside the context of cancer care.

Blue-collar workers, particularly those in the construction trades, are more likely to smoke and have less success in quitting when compared with white-collar workers. Little is known about health communication strategies that might influence this priority population. This article describes our formative work to develop targeted messages to increase participation in an existing smoking cessation program among construction workers. Using an iterative and sequential mixed-methods approach, we explored the culture, health attitudes and smoking behaviors of unionized construction workers. We used focus group and survey data to inform message development, and applied audience segmentation methods to identify potential subgroups. Among 144 current smokers, 65% reported wanting to quit smoking in the next 6 months and only 15% had heard of a union-sponsored smoking cessation program, despite widespread advertising. We tested 12 message concepts and 26 images with the target audience to evaluate perceived relevance and effectiveness. Participants responded most favorably to messages and images that emphasized family and work, although responses varied by audience segments based on age and parental status. This study is an important step towards integrating the culture of a high-risk group into targeted messages to increase participation in smoking cessation activities.