Citations

Objectives: To identify patient characteristics, health concerns, and barriers to care based on overweight or obesity. Methods: A 50-question anonymous survey was administered to patients. Data were compared by body mass index (BMI). Results: Among 3976 distributed surveys, 899 were returned and 682 were analyzed. Most respondents were women (60%), White (94%), and married/partnered (65%) and had some college education (80%). Younger and unmarried persons had higher BMI ( P < .001). Concern for quality of life ( P < .001) and importance of lifestyle changes ( P = .006) increased with BMI, but confidence in making changes decreased as BMI increased ( P < .001). Perceived good health decreased with increasing BMI ( P < .001), whereas depression and other comorbid conditions increased. Self-esteem decreased and stigma increased with higher BMI (both P < .001). Weight discussions with clinicians ( P < .001) and belief that clinicians should be involved in weight management ( P = .002) increased with BMI, yet self-perception of being judged by clinicians also increased ( P < .001). As BMI increased, delays in seeking health care increased ( P < .001). Conclusions: This survey study highlights perceived health concerns and barriers to care among persons with overweight and obesity. With higher BMI, self-esteem decreased, and stigma, self-perception of poor health, perception of being judged by clinicians, and delay in seeking medical care increased.

Abstract Background The legal climate for cannabis use has dramatically changed with an increasing number of states passing legislation legalizing access for medical and recreational use. Among cancer patients, cannabis is often used to ameliorate adverse effects of cancer treatment. Data are limited on the extent and type of use among cancer patients during treatment and the perceived benefits and harms. This multicenter survey was conducted to assess the use of cannabis among cancer patients residing in states with varied legal access to cannabis. Methods A total of 12 NCI-Designated Cancer Centers, across states with varied cannabis-access legal status, conducted surveys with a core questionnaire to assess cannabis use among recently diagnosed cancer patients. Data were collected between September 2021 and August 2023 and pooled across 12 cancer centers. Frequencies and 95% confidence intervals for core survey measures were calculated, and weighted estimates are presented for the 10 sites that drew probability samples. Results Overall reported cannabis use since cancer diagnosis among survey respondents was 32.9% (weighted), which varied slightly by state legalization status. The most common perceived benefits of use were for pain, sleep, stress and anxiety, and treatment side effects. Reported perceived risks were less common and included inability to drive, difficulty concentrating, lung damage, addiction, and impact on employment. A majority reported feeling comfortable speaking to health-care providers though, overall, only 21.5% reported having done so. Among those who used cannabis since diagnosis, the most common modes were eating in food, smoking, and pills or tinctures, and the most common reasons were for sleep disturbance, followed by pain and stress and anxiety with 60%-68% reporting improved symptoms with use. Conclusion This geographically diverse survey demonstrates that patients use cannabis regardless of its legal status. Addressing knowledge gaps concerning benefits and harms of cannabis use during cancer treatment is critical to enhance patient-provider communication.

Guideline-recommended screening programs exist for only a few cancer types. Although all these programs are understood to lead to reductions in cancer-related mortality, standard-of-care screening tests vary in accuracy, adherence and effectiveness. Recent advances in high-throughput technologies and machine learning have facilitated the development of blood-based multi-cancer cancer early detection (MCED) tests. MCED tests are positioned to be complementary to standard-of-care screening and they may broaden screening availability, especially for individuals who are not adherent with current screening programs and for individuals who may harbor cancers with no available screening options. In this article, we outline some key features that should be considered for study design and MCED test development, provide an example of the developmental pathway undertaken for an emerging multi-biomarker class MCED test and propose a clinical algorithm for an imaging-based diagnostic resolution strategy following MCED testing.

11135 Background: Cancer screening programs can improve outcomes and may reduce treatment cost and utilization by shifting cancers to earlier, more curable stages at diagnosis (Dx). Few studies have evaluated the impact of screening on outcomes prior to diagnosis. Such information is needed to better understand the potential impact of newer blood-based multicancer early detection technologies. Methods: We conducted a retrospective cohort study using SEER cancer registry data linked with Medicare claims. Patients with a breast cancer (BC) or colorectal cancer (CRC) Dx between 2010-2019 were included if they were 65-74 years old at Dx, continuously enrolled in Medicare Parts A&B, had a Charlson Comorbidity Index of ≤2, and no cancer for ≥12 months prior to Dx. Those enrolled in an HMO or with high genetic risk for BC (in BC cohort) were excluded. Patients were assigned to screening groups prior to Dx; screening was defined as ≥1 screening procedure in the 6 months prior to Dx using CPT/HCPCS codes. Screening included FIT/FOBT, sigmoidoscopy, colonoscopy, CT colonography, mt-sDNA (CRC), and mammography (BC). Screened and not screened groups were compared for statistical significance using chi-squared for categorical variables, Wilcoxon rank-sum test for continuous variables. Results: Screening procedures were more prevalent in the BC cohort (68%) than the CRC cohort (44%) (table). Both screened subgroups (vs non-screened subgroups) had significantly lower proportions of patients diagnosed at stage 4 (2% vs 10% BC, 16% vs 27% CRC) and shorter times from first screening or imaging procedure to confirmed diagnosis (BC: 33 vs 227 days, CRC: 14 vs 29 days). Screened patients in both cancer cohorts had a similar number of average procedures prior to treatment initiation as non-screened (BC: 4.8 vs 4.2, CRC: 3.3 vs 3.3 respectively, including screening procedures). Conclusions: Individuals diagnosed with BC and CRC through screening exhibit earlier stage diagnoses and shorter intervals to diagnosis. Novel screening technologies such as MCED tests can potentially improve peri-diagnostic outcomes in cancers lacking existing or widely adopted screening methods. [Table: see text]

Objective: To determine if the implementation of smoke-free workplace laws reduced the incidence of the acute coronary events including myocardial infarction (MI) and sudden cardiac death (SCD). Background: Nonsmokers chronically exposed to second-hand smoke (SHS) are at increased risk of death from heart disease. However, a nonlinear dose relationship exists between SHS exposure and coronary heart disease (CHD) such that the relative risk of CHD is 1.31 for nonsmokers and 1.78 for smokers. Reductions in admissions for MI in locales where smoke-free workplace laws have been implemented have been observed, but none have assessed SCD. On January 1, 2002, a smoke-free restaurant law (Ordinance #1) was implemented in Olmsted County, Minnesota, and on October 1, 2007, all workplaces became smoke-free (Ordinance #2). Methods: Under the auspices of the Rochester Epidemiology Project, we measured the incidence of MI and SCD during the 18-month calendar period before and after implementation of each smoke-free ordinance. All MI were validated using biomarkers, cardiac pain, and Minnesota coding of the ECG. SCD was defined as out-of-hospital deaths assigned to CHD (ICD-9 codes 410 through 414). Results: For the overall study period of the 18 months before the implementation of the smoke-free restaurant ordinance and 18 months after the implementation of the smoke-free workplace ordinance, we observed a 45% decline in the incidence for MI (p <0.01) and a 50% decline in the incidence for SCD (p <0.01). See Table. During this same period, the prevalence of hypertension, diabetes, hypercholesterolemia, and obesity either remained constant or increased while the prevalence of smoking among adults declined by 23% (22% to 17%). Conclusion: In the Olmsted County population, substantial declines in the incidence of MI and SCD were observed after smoke-free laws were implemented. Smoke-free workplace laws may not only be associated with a decrease in MI but SCD as well.

Objective To evaluate the clinical outcomes of a remote mental health program for managing anxiety and depression, primarily using asynchronous digital communication. Methods This retrospective cohort study examined U.S. adults seeking remote care for anxiety and depression from January 2021 to May 2022. The program involves clinician-led assessment, patient education, medication management, and ongoing monitoring, primarily via text. Anxiety and depression were measured using Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) scores. Outcomes examined were changes in scores, 50% score improvement rate, and remission rate (score <5) at 1, 3, and 6 months. Results During the period evaluated, 11,844 program participants met the inclusion criteria. Most were female (n = 8328, 70.3%); their age ranged from 18–82 years (median 31 years). At baseline, median PHQ-9 and GAD-7 scores were 13 (IQR 9–17); 67% and 69% met score criteria for depression and anxiety, respectively. Most participants (80%) were prescribed a selective serotonin reuptake inhibitor (SSRI). By one month, average PHQ-9 and GAD-7 scores decreased significantly by 9.2 and 9.1 points (both p < .01). At 1-month follow-up, the 50% score improvement rate was 66% for PHQ-9 and 69% GAD-7 ( p < .01). Scores continued to decrease with follow-up. At 3 months, over half achieved remission (percent [95% CI]: 52% [51–54] for anxiety, 53% [52–55] for depression). Similar improvement was observed at 6 months and in sensitivity analyses accounting for loss to follow-up. Conclusions Use of a remote mental health program with digital tools was associated with significant clinical improvement in anxiety and depression. Challenges remain in maintaining patient engagement and ensuring appropriate care quality monitoring in digital mental health programs. Additional research comparing remote digital care to traditional in-person models is warranted. Studies should examine long-term outcomes, optimal care protocols, and the challenges to integrating these programs into existing healthcare systems and ensuring equitable access.

Background Digital and mobile (mHealth) solutions are online or application-based services intended to support individuals with health needs. Despite evidence supporting the use of mHealth for patients with chronic pain, and the increasing desire of these types of solutions by both patients and providers, adoption of mHealth solutions remains limited. Implementation mapping can serve as a practical method to facilitate implementation and adoption of mHealth solutions within healthcare settings. Methods Implementation mapping was used to develop implementation strategies based on contextual determinants organized within the Consolidated Framework for Implementation Research (CFIR) for mHealth eLearning solutions across an integrated, multi-site healthcare system. We describe our experience identifying stakeholders, delineating implementation facilitators and barriers, defining implementation outcomes using RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, outlining initial implementation strategies, and iterating on implementation strategies. Results A total of 30 implementation strategies were identified and implemented. Over the first year, primary and specialty care providers across all the clinical sites ( n = 70) placed 2559 orders for the mHealth solution. Most patients reported receiving the mHealth eLearning module (74%), and most patients felt that the tool improved their knowledge regarding their condition (82%) and their ability to provide self-care related to the condition (73%). Conclusion Practical applications of implementation science methods can help enable change within healthcare settings. Implementation mapping is an exercise that can engage stakeholders to facilitate the incorporation of new methods of care delivery, including mHealth solutions.

Abstract Introduction We sought to determine what type of treatment reengagement after smoking relapse would increase long-term cessation. Aims and Methods Participants were military personnel, retirees, and family members (TRICARE beneficiaries) recruited across the United States from August 2015 through June 2020. At baseline, consented participants (n = 614) received a validated, four-session, telephonic tobacco-cessation intervention with free nicotine replacement therapy. At the 3-month follow-up, 264 participants who failed to quit or relapsed were offered the opportunity to reengage in cessation. Of these, 134 were randomized into three reengagement conditions: (1) repeat initial intervention (“recycle”), (2) Smoking reduction with eventual cessation goal (“rate reduction”), or (3) Choose #1 or #2 (“choice”). Prolonged abstinence and 7-day point prevalence abstinence were measured at 12 months. Results Despite being in a clinical trial advertised as having the opportunity for reengagement, only 51% (134 of the 264) of participants who still smoked at 3-month follow-up were willing to reengage. Overall, participants randomized to recycle had higher prolonged cessation rates at 12 months than rate reduction conditions (OR = 16.43, 95% CI: 2.52 to 107.09, Bonferroni adjusted p = .011). When participants who randomly received recycle or rate reduction were pooled, respectively, with participants who chose recycle or rate reduction in the Choice group, recycle had higher prolonged cessation rates at 12 months than rate reduction (OR = 6.50, 95% CI: 1.49 to 28.42, p = .013). Conclusions Our findings suggest service members and their family members who fail to quit smoking but are willing to reengage in a cessation program are more likely to benefit from repeating the same treatment. Implications Finding methods that are both successful and acceptable to reengage people who smoke who want to quit can have a significant impact on improving the health of the public by reducing the portion of the population who smoke. This study suggests that repeating established cessation programs will result in more people ready to quit successfully achieving their goal.