Background: The role of cigarette smoking as a prognostic factor for kidney cancer (KC) is unclear. In this population‐based study, we analyze cancer‐specific survival (CSS) outcomes among KC patients by smoking status at diagnosis in the diverse state of Florida.Methods: All primary KC cases from the Florida Cancer Registry diagnosed during 2005–2018 were analyzed. Cox proportional regression was conducted to assess the determinants of KC survival, including age, sex, race/ethnicity, socioeconomic status, histology type, cancer stage, and treatment received with a particular focus on smoking status (smokers at diagnosis referred to as current smokers, former smokers, and never smokers).Results: Among all 36,150 KC patients, 18.3% were smokers at diagnosis (n = 6629), 32.9% were former smokers (n = 11,870), and 48.8% were never smokers (n = 17,651). Age‐standardized five‐year survival for current, former, and never smokers was 65.3 (95% CI: 64.1–66.5), 70.6 (95% CI: 69.7–71.5), and 75.3 (95% CI: 74.6–76.0) respectively. In multivariable analysis, current and former smokers had an estimated 30% and 14% higher risk of KC death compared to never smokers, respectively, after adjusting for potential confounders (HR: 1.30, 95% CI: 1.23–1.40; HR: 1.14, 95% CI: 1.10–1.20).Conclusion: Smoking independently contributes to poorer survival, across all KC stages. Clinicians should encourage and facilitate participation in cigarette smoking cessation programs targeted at current smokers. Prospective studies are warranted to assess the role of different types of tobacco use and cessation programs on KC survival.

Despite medicinal cannabis gaining popularity for managing symptoms in cancer patients, a knowledge gap exists in patient-provider communication crucial for monitoring outcomes, optimizing dosing, and educating healthcare providers to integrate cannabis into treatment plans. Our goal is to understand communication dynamics, identify gaps, and pave the way for effective cannabis communication for individuals living with cancer (PLWC). We searched PubMed, CINAHL, and EBSCO for articles published between 2013 and July 2023, capturing the key concepts of cannabis use in cancer patients and their communication with healthcare providers in oncology settings. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guided the review. Studies were appraised by applying the Johns Hopkins Evidence-Based Practice Model for Nursing and Healthcare Professionals. Of the 2384 articles reviewed, 14 met the inclusion criteria. Three were qualitative studies, and 11 were cross-sectional surveys. All studies were level III evidence. Studies captured patients’ and providers’ perspectives; five were conducted among cancer patients, and nine were among healthcare providers in oncology settings. Findings revealed variations in healthcare provider recommendations, patient-initiated discussions, and barriers to discussing medical cannabis (MC). The synthesis of this evidence highlights the complexities surrounding MC in oncology settings, including knowledge gaps among healthcare providers, patient-initiated discussions, and challenges in accessing and prescribing medicinal cannabis. This review contributes valuable insights into the current landscape of MC use in cancer care, emphasizing the need for improved communication, education, and support for both patients and healthcare providers.

• Participants reported both the health benefits and risks of cannabis use. • Potential of cannabis as an alternative therapy or part of holistic medicine. • Thematic analysis guided by the theory of Health Belief Model. • Knowledge on cannabis and its effects primarily derived from personal experiences and anecdotes. • Respondents expressed desire for evidence-based cannabis literacy and need for further research on cannabis science.

Cannabis use among cancer patients for managing treatment-related symptoms is increasing, yet little is known about patterns in patient-provider communication. This study examines demographic differences in cannabis use communication at a National Cancer Institute-designated cancer center. The analysis included cancer patients aged ≥ 18 years who self-reported current cannabis use (past 30 days) and had visited Sylvester Comprehensive Cancer Center within the past 5 years (N = 226). Data were collected via an anonymous electronic survey on REDCap. Responses on patients’ disclosure of cannabis use to cancer doctor/care team and their comfort in discussing cannabis were analyzed. Chi-squared/Fisher’s exact tests and t-tests were applied. Logistic regression estimated the associations between age and stage of cancer treatment with patients’ comfort in discussing cannabis use with cancer doctor (oncologist). The sample was 51.8% male and 39.4% Hispanic (mean age, 45.9 years (SD = 15.1)); 41.1% were aged 20–39 years, 43.8% were undergoing treatment, and 35.4% were in follow-up/had finished treatment. Over half (50.4%) did not disclose cannabis use to their cancer doctor/care team. Non-disclosers were more often younger (20–39 years) than disclosers (52.6% vs. 29.5%, p < 0.01). Most patients (72.5%) felt comfortable discussing cannabis use with their oncologist; however, younger patients (20–39 years) were more often uncomfortable (40.8%). Logistic regression showed newly diagnosed patients had lower odds (aOR, 0.41; 95% CI, 0.12–0.98) of comfort discussing cannabis compared to those in follow-up/finished treatment. Younger patients (20–39 years) also had lower odds (aOR, 0.11; 95% CI, 0.03–0.40) of feeling comfortable discussing cannabis compared to older patients (≥ 60 years). Age and treatment stage significantly impact the cannabis use disclosure and comfort in discussing it with cancer doctor/care team. These findings underscore the importance of considering age-related factors and treatment status when addressing cannabis use discussions within oncology setting.

Purpose: The COVID-19 pandemic has had a profound impact on mental health worldwide, with depression and sleep problems among the most common issues experienced by many individuals. Depression can lead to sleep problems, which can increase the risk of developing depressive symptoms. However, it is unclear which United States (US) sub-population was most affected by depression and sleep problems during the pandemic. Methods: We conducted a secondary analysis using self-reported data from the 2021 National Health Interview Survey (NHIS), focusing on adults aged 18 years and above (n=29,763). We utilized self-reported responses to questions about prescription medication and frequency of depressive feelings to determine participants’ depression status. Appropriate weights were applied to account for the sampling design of the surveys. Our analysis involved descriptive statistics and chi-squared tests to compare sociodemographic, clinical, behavioral, and sleep-related characteristics between US adults with and without depression. Additionally, logistic regression was used to examine the associations between sleep duration, sleep quality and depression. Results: The overall prevalence of depression in our sample was 44.4%. It were higher in certain demographic groups, including younger adults (18– 39 years, 47.7%), non-Hispanic whites (47.9%), females (50.1%), those at the lower income bracket (52.2%), those with no college or degree (48.7%) uninsured individuals (45.2%), and those reporting poor general health (71.9%). Individuals with depression had a 12% increased odds of experiencing short sleep (aOR: 1.12, 95% CI:1.04– 1.20, p< 0.001), 34% increased odds of experiencing long sleep (aOR: 1.34, 95% CI: 1.20– 1.50, p < 0.001) and more than 2.5 fold increased odds of reporting poor sleep quality (aOR:2.57, 95% CI: 2.40– 2.78; p< 0.0001). In the multivariate analysis, all variables (sex, race/ethnicity, education, health insurance coverage, marital status, general health status and use of sleep medications, smoking and alcohol use status) were significantly predictors of poor sleep quality, with the exceptions of age and family income. Conclusion: The findings emphasize the need to address sleep health in treating depression, especially during times of public health crises.

Objective: This study aims to describe patterns, sources, and reasons for cannabis use among cancer patients during active treatment (+CDTX) compared to no‐use during active treatment (−CDTX). Methods: Data are from 385 surveys collected via REDCap during phase I of an ongoing study among adult cancer patients seen at an NCI‐designated comprehensive cancer center within the last 5 years of treatment. A harmonized survey was created with 11 other NCI centers to assess cannabis use patterns, sources, and reasons for use. Sociodemographics and cancer details were also collected via self‐report. Descriptive statistics were calculated and stratified by +/−CDTX. Chi‐squared tests were conducted to compare proportions between groups. Results: Among the sample [49.5 years (SD 15.9); 53.0% male; and 41.6% Hispanic/Latino], 41.0% + CDTX and 59.0% −CDTX. A majority (71.8%) of +CDTX initiated use before diagnosis versus 44.1% in −CDTX ( p < 0.0001); patients diagnosed with stage 4 cancer had a statistically significant higher prevalence of +CDTX (60.0%; p = 0.003); 53.3% in radiation reported +CDTX compared to 42.8% in chemotherapy, and 36.4% in immunotherapy. Dispensaries and local dealers were the top sources of cannabis in both groups. Among +CDTX, 44.3% consumed cannabis at least once a day DTX, dominant cannabinoids used were CBD (35.2%), Delta‐8‐THC (18.3%), and CBD + THC ratio (14.1%); 12.7% were unsure what they consumed. Joints were the most common inhalation method (61.5%), and store‐bought candy was the most common edible (39.2%). Depression/mood, pain, and enjoyment were the top three reasons for +CDTX compared to enjoyment, depression/mood, and nausea/upset stomach in −CDTX ( p = 0.02). Conclusions: Patterns, sources, and reasons for cannabis use varied between +CDTX and ‐CDTX. Future studies should examine the impacts of cannabis and specific cannabinoids on cancer treatment, drug interactions, survival outcomes, and quality of life.