Patterns of Smoking Cessation Strategies and Perception of E-cigarette Harm Among Bladder Cancer Survivors.

BACKGROUND: Cigarette smoking is the leading preventable cause of bladder cancer (BC). Some proponents of e-cigarettes describe their use as a risk mitigation strategy despite potential carcinogen exposure and uncertain long-term risks. OBJECTIVE: We assessed smoking cessation strategies, including e-cigarette use, and harm perception among patients with BC. METHODS: We performed a cross-sectional study on a convenience sample of patients with BC at a single institution from August 2021 - October 2022. The survey instrument was sourced from the Cancer Patient Tobacco Use Questionnaire (C-TUQ) from the American Association for Cancer Research with standardized questions on tobacco use, cessation questions, and e-cigarette harm perceptions. RESULTS: Of the 104 surveyed BC patients (mean age: 72 years; 27% female; 55% with muscle-invasive disease), 20% were current smokers (median pack years: 40) and 51% were former smokers (median pack years: 20). A minority (9%) had quit smoking at the time of diagnosis. Pharmacotherapy for smoking cessation included nicotine patches (25%), gum (21%), lozenges (8%), e-cigarettes (8%), and Varenicline/Bupropion (4%). Notably, 43% of patients who continued to smoke expressed willingness to switch to e-cigarettes as a cessation aid. E-cigarette users (11%) more commonly perceived e-cigarettes as non-harmful compared to former (4%) and non-smokers (4%) (P = .048), though all groups regarded e-cigarettes as equally addictive as traditional cigarettes. CONCLUSIONS: Despite the prevalence of BC survivors who continue to smoke, a significant proportion perceive e-cigarettes as a viable and less harmful cessation aid. The infrequent use of FDA-approved pharmacotherapies underscores potential implementation gaps. These findings highlight the need for further research and targeted interventions in addressing smoking cessation among BC survivors.

Economic Considerations for Implementing Tobacco Cessation Programs in Cancer Care Settings.

Increasingly, research demonstrates economic benefits of tobacco cessation in cancer care, as seen in a new study by Kypriotakis and colleagues of the MD Anderson cessation program, demonstrating median health care cost savings of $1,095 per patient over 3 months. While the cost-effectiveness of tobacco cessation programs from a hospital perspective is important, implementation decisions in a predominantly fee-for-service system, such as in the United States, too often insufficiently value this outcome. Economic barriers, stakeholder disincentives, and payment models all impact program implementation. Combining economic evaluation with implementation research, including assessment of return-on-investment, may enhance sustainability and inform decision-making in cancer care settings. See related article by Kypriotakis et al., p. 217.

Bladder Cancer Survivors Who Do Not Smoke Have Better Longitudinal Health-Related Quality of Life Measures: An Assessment of the Comparative Effectiveness and Survivorship Health in Bladder Cancer (CEASE-BC) Study.

PURPOSE: Cigarette smoking is the most common risk factor for the development of bladder cancer (BC), yet there is a paucity of data characterizing the relationship between smoking status and longitudinal health-related quality of life (HRQoL) outcomes in patients with BC. We examined the association between smoking status and HRQoL among patients with BC. MATERIALS AND METHODS: Data were sourced from a prospective, longitudinal study open between 2014 and 2017, which examined HRQoL in patients aged ≥ 18 years old diagnosed with BC across North Carolina. The QLQ-C30 (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core instrument) was administered at 3, 12, and 24 months after BC diagnosis. Our primary exposure of interest was current smoking status. Linear regression using generalized estimating equations was used to analyze the relationship between smoking status and various domains of the QLQ-C30. RESULTS: A total of 154 patients enrolled in the study. Eighteen percent were classified as smoking at 3 months from diagnosis, and packs per day ranged from < 0.5 to 2. When controlling for time from diagnosis, demographic covariates, cancer stage, and treatment type, mean differences for physical function (7.4), emotional function (5.6), and fatigue measures (-8.2) were significantly better for patients with BC who did not smoke. CONCLUSIONS: Patients with BC who do not smoke have significantly better HRQoL scores in the domains of physical function, emotional function, and fatigue. These results underscore the need to treat smoking as an essential component of BC care.

Data envelopment analysis to evaluate the efficiency of tobacco treatment programs in the NCI Moonshot Cancer Center Cessation Initiative.

BACKGROUND: The Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency-i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources. METHODS: DEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes. RESULTS: In the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8). CONCLUSION: Most C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.

The Impact of the COVID-19 Pandemic on Tobacco Treatment Program Implementation at National Cancer Institute-Designated Cancer Centers.

INTRODUCTION: The COVID-19 pandemic disrupted cancer screening and treatment delivery, but COVID-19's impact on tobacco cessation treatment for cancer patients who smoke has not been widely explored. AIMS AND METHODS: We conducted a sequential cross-sectional analysis of data collected from 34 National Cancer Institute (NCI)-designated cancer centers participating in NCI's Cancer Center Cessation Initiative (C3I), across three reporting periods: one prior to COVID-19 (January-June 2019) and two during the pandemic (January-June 2020, January-June 2021). Using McNemar's Test of Homogeneity, we assessed changes in services offered and implementation activities over time. RESULTS: The proportion of centers offering remote treatment services increased each year for Quitline referrals (56%, 68%, and 91%; p = .000), telephone counseling (59%, 79%, and 94%; p = .002), and referrals to Smokefree TXT (27%, 47%, and 56%; p = .006). Centers offering video-based counseling increased from 2020 to 2021 (18% to 59%; p = .006), Fewer than 10% of centers reported laying off tobacco treatment staff. Compared to early 2020, in 2021 C3I centers reported improvements in their ability to maintain staff and clinician morale, refer to external treatment services, train providers to deliver tobacco treatment, and modify clinical workflows. CONCLUSIONS: The COVID-19 pandemic necessitated a rapid transition to new telehealth program delivery of tobacco treatment for patients with cancer. C3I cancer centers adjusted rapidly to challenges presented by the pandemic, with improvements reported in staff morale and ability to train providers, refer patients to tobacco treatment, and modify clinical workflows. These factors enabled C3I centers to sustain evidence-based tobacco treatment implementation during and beyond the COVID-19 pandemic. IMPLICATIONS: This work describes how NCI-designated cancer centers participating in the Cancer Center Cessation Initiative (C3I) adapted to challenges to sustain evidence-based tobacco use treatment programs during the COVID-19 pandemic. This work offers a model for resilience and rapid transition to remote tobacco treatment services delivery and proposes a policy and research agenda for telehealth services as an approach to sustaining evidence-based tobacco treatment programs.

Integrating Tobacco Treatment Into Oncology Care: Reach and Effectiveness of Evidence-Based Tobacco Treatment Across National Cancer Institute-Designated Cancer Centers.

PURPOSE: Quitting smoking improves patients' clinical outcomes, yet smoking is not commonly addressed as part of cancer care. The Cancer Center Cessation Initiative (C3I) supports National Cancer Institute-designated cancer centers to integrate tobacco treatment programs (TTPs) into routine cancer care. C3I centers vary in size, implementation strategies used, and treatment approaches. We examined associations of these contextual factors with treatment reach and smoking cessation effectiveness. METHODS: This cross-sectional study used survey data from 28 C3I centers that reported tobacco treatment data during the first 6 months of 2021. Primary outcomes of interest were treatment reach (reach)-the proportion of patients identified as currently smoking who received at least one evidence-based tobacco treatment component (eg, counseling and pharmacotherapy)-and smoking cessation effectiveness (effectiveness)-the proportion of patients reporting 7-day point prevalence abstinence at 6-month follow-up. Center-level differences in reach and effectiveness were examined by center characteristics, implementation strategies, and tobacco treatment components. RESULTS: Of the total 692,662 unique patients seen, 44,437 reported current smoking. Across centers, a median of 96% of patients were screened for tobacco use, median smoking prevalence was 7.4%, median reach was 15.4%, and median effectiveness was 18.4%. Center-level characteristics associated with higher reach included higher smoking prevalence, use of center-wide TTP, and lower patient-to-tobacco treatment specialist ratio. Higher effectiveness was observed at centers that served a larger overall population and population of patients who smoke, reported a higher smoking prevalence, and/or offered electronic health record referrals via a closed-loop system. CONCLUSION: Whole-center TTP implementation among inpatients and outpatients, and increasing staff-to-patient ratios may improve TTP reach. Designating personnel with tobacco treatment expertise and resources to increase tobacco treatment dose or intensity may improve smoking cessation effectiveness.

Systematic review of smoking relapse rates among cancer survivors who quit at the time of cancer diagnosis.

BACKGROUND: Tobacco cessation, at the time of cancer diagnosis, has been associated with better oncologic outcomes. Cancer diagnosis has been shown to serves as a "teachable moment," inspiring tobacco cessation. However, the sustainability of abstinence from smoking is understudied. Similarly, there is a paucity of data regarding the utility of behavioral/pharmacologic intervention to support continued smoking cessation. METHODS: A systematic literature review was conducted in August 2021 with no date limits. Relevant studies that reported tobacco smoking relapse rates for patients who quit at the time of cancer diagnosis were included. Our literature search identified 1620 articles and 29 met inclusion criteria. The primary endpoint of the study was smoking relapse rate. Secondary outcome was a descriptive assessment of behavioral and pharmacologic interventions to promote continued cessation. Exploratory outcomes included a regression analysis to examine associations between study factors and relapse rates. RESULTS: There were 3021 smokers who quit at the time of cancer diagnosis. Weighted overall relapse rate for the study population was 44 % (range 5-57 %). Interventions to support smoking cessation were employed in 17 of the 29 included studies and protocols were heterogenous, including behavioral, pharmacologic, or mixed intervention strategies. Exploratory analysis demonstrated no association between relapse rates and publication year, gender, or study type. Relapse rates were indirectly associated with age (p = .003), suggesting that younger patients were more likely to relapse. CONCLUSION: The sustainability of smoking cessation after a cancer diagnosis is understudied, and existing literature is difficult to interpret due to heterogeneity. Relapse rates remain significant and, although many studies have included the employment of an intervention to promote continued cessation, few studies have measured the effect of a protocolized intervention to support abstinence.

Evaluating a Tobacco Treatment Program's Transition to Telehealth Using a Social Determinants of Health Lens.

INTRODUCTION: While strong associations exist between social determinants of health (SDOH), socioeconomic status, and smoking, these factors are not routinely assessed in tobacco treatment programs (TTP). This study addresses this gap by evaluating a composite metric of SDOH and a measure of access to care to determine program reach before and after the implementation of telehealth tobacco treatment delivery. AIMS AND METHODS: We examined inpatient data from a large TTP during two comparable time periods from April 1, 2019 to September 30, 2019 (pre-telehealth) and from April 1, 2020 to September 30, 2020 (telehealth). The populations were compared using point-of-care data, including 5-digit zip codes mapped to the CDC's Social Vulnerability Index (SVI) and driving distance (in 60-min increments) to the study hospital. Chi-square tests for homogeneity were performed for SVI and driving distance comparisons. RESULTS: While distance distributions were significantly different between the pre-telehealth and telehealth populations (χ 2 = 13.5 (df = 3, N = 3234), p = .004, no significant differences existed in the proportion of SVI categories between the two populations (χ 2 = 5.8 (df = 3, N = 3234), p = .12). In the telehealth population, patients with the highest SVI vulnerability had the greatest proportions living >1 h from the hospital. CONCLUSIONS: This study offers a novel evaluation of tobacco treatment in relation to an SDOH metric (SVI) and care access (distance to the hospital) for inpatient populations. Patient reach, including to those with high vulnerabilities, remained consistent in a transition to telehealth. These methods can inform future reach and engagement of patients who use tobacco products, including patients with high vulnerability or who reside at greater distances from treatment programs. IMPLICATIONS: This study provides the first analysis of inpatient tobacco use treatment (TUT) transition to telehealth delivery of care during the COVID-19 pandemic using the CDC's SVI metric and patient distance to the hospital. The transition resulted in consistent reach to patients at the highest vulnerability. These findings can inform efforts to evaluate SDOH measures and improve reach, engagement, and research on telehealth delivery of inpatient TUT.

An Analysis of Inpatient Tobacco Use Treatment Transition to Telehealth.

INTRODUCTION: During the COVID-19 pandemic, many tobacco users increased their tobacco use, and calls to quitlines decreased. Among inpatients, the pandemic also necessitated a rapid transition of intensive tobacco use counseling to telehealth counseling. No data exist comparing the outcomes of telehealth inpatient counseling with in-person (pre-telehealth) counseling. AIMS AND METHODS: We examined inpatient data from a large tobacco treatment program (TTP) during two comparable time periods 04/01/2019-09/30/2019 (pre-telehealth) and 04/01/2020-09/30/2020 (telehealth). The pre-telehealth and telehealth populations were compared using Pearson's chi-square test for homogeneity on each populations' patient, visit, and medication acceptance characteristics. Reach to "current tobacco users" was analyzed using TTP flowsheet and electronic health record (EHR) data in relation to aggregate EHR data in the data warehouse. RESULTS: Mean monthly tobacco treatment inpatient counseling and outreach visits increased 38.9% in the telehealth period (M = 376, SD = 36.7) compared with the pre-telehealth period (M = 271, SD = 50.0) (t(10) = 3.8, p = .004). Reach significantly increased from 32.8% to 65.9% among all "current tobacco users" admitted, including 31.8% to 66.6% in races at higher risk for COVID-19 severe disease. Pearson's chi-square tests for homogeneity showed significant differences in the pre-telehealth and telehealth population distributions for age, visit type, ethnicity, and medication acceptance. CONCLUSIONS: This study offers the first understanding of characteristics of patients, visits, and medication acceptances in pre-telehealth and telehealth tobacco use treatment for inpatient populations. Larger reach and counseling were identified in the telehealth population. This study's findings on inpatient tobacco use treatment can inform future reach and engagement of large numbers of patients who use tobacco products. IMPLICATIONS: This study provides the first analysis of inpatient tobacco use treatment transition to telehealth delivery of care during the COVID-19 pandemic. The transition resulted in increases in reach and cessation counseling. These findings can inform efforts to improve reach, engagement, and research on telehealth delivery of inpatient tobacco use treatment.

The STUN (STop UNhealthy) Alcohol Use Now trial: study protocol for an adaptive randomized trial on dissemination and implementation of screening and management of unhealthy alcohol use in primary care.

BACKGROUND: Unhealthy alcohol use is a leading cause of preventable deaths in the USA and is associated with many societal and health problems. Less than a third of people who visit primary care providers in the USA are asked about or ever discuss alcohol use with a health professional. METHODS/DESIGN: This study is an adaptive, randomized, controlled trial to evaluate the effect of primary care practice facilitation and telehealth services on evidence-based screening, counseling, and pharmacotherapy for unhealthy alcohol use in small-to-medium-sized primary care practices. Study participants will include primary care practices in North Carolina with 10 or fewer providers. All enrolled practices will receive a practice facilitation intervention that includes quality improvement (QI) coaching, electronic health record (EHR) support, training, and expert consultation. After 6 months, practices in the lower 50th percentile (based on performance) will be randomized to continued practice facilitation or provision of telehealth services plus ongoing facilitation for the next 6 months. Practices in the upper 50th percentile after the initial 6 months of intervention will continue to receive practice facilitation alone. The main outcome measures include the number (and %) of patients in the target population who are screened for unhealthy alcohol use, screen positive, and receive brief counseling. Additional measures include the number (and %) of patients who receive pharmacotherapy for AUD or are referred for AUD services. Sample size calculations determined that 35 practices are needed to detect a 10% increase in the main outcome (percent screened for unhealthy alcohol use) over 6 months. DISCUSSION: A successful intervention would significantly reduce morbidity among adults from unhealthy alcohol use by increasing counseling and other treatment opportunities. The study will produce important evidence about the effect of practice facilitation on uptake of evidence-based screening, counseling, and pharmacotherapy for unhealthy alcohol use when delivered on a large scale to small and medium-sized practices. It will also generate scientific knowledge about whether embedded telehealth services can improve the use of evidence-based screening and interventions for practices with slower uptake. The results of this rigorously conducted evaluation are expected to have a positive impact by accelerating the dissemination and implementation of evidence related to unhealthy alcohol use into primary care practices. TRIAL REGISTRATION: ClinicalTrials.gov NCT04317989 . Registered on March 23, 2020.

Natural language processing of lifestyle modification documentation.

Lifestyle modification, including diet, exercise, and tobacco cessation, is the first-line treatment of many disorders including hypertension, obesity, and diabetes. Lifestyle modification data are not easily retrieved or used in research due to their textual nature. This study addresses this knowledge gap using natural language processing to automatically identify lifestyle modification documentation from electronic health records. Electronic health record notes from hypertension patients were analyzed using an open-source natural language processing tool to retrieve assessment and advice regarding lifestyle modification. These data were classified as lifestyle modification assessment or advice and mapped to a coded standard ontology. Combined lifestyle modification (advice and assessment) recall was 99.27 percent, precision 94.44 percent, and correct classification 88.15 percent. Through extraction and transformation of narrative lifestyle modification data to coded data, this critical information can be used in research, metric development, and quality improvement efforts regarding care delivery for multiple medical conditions that benefit from lifestyle modification.

Patient free text reporting of symptomatic adverse events in cancer clinical research using the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE).

OBJECTIVE: The study sought to describe patient-entered supplemental information on symptomatic adverse events (AEs) in cancer clinical research reported via a National Cancer Institute software system and examine the feasibility of mapping these entries to established terminologies. MATERIALS AND METHODS: Patients in 3 multicenter trials electronically completed surveys during cancer treatment. Each survey included a prespecified subset of items from the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Upon completion of the survey items, patients could add supplemental symptomatic AE information in a free text box. As patients typed into the box, structured dropdown terms could be selected from the PRO-CTCAE item library or Medical Dictionary for Regulatory Activities (MedDRA), or patients could type unstructured free text for submission. RESULTS: Data were pooled from 1760 participants (48% women; 78% White) who completed 8892 surveys, of which 2387 (26.8%) included supplemental symptomatic AE information. Overall, 1024 (58%) patients entered supplemental information at least once, with an average of 2.3 per patient per study. This encompassed 1474 of 8892 (16.6%) dropdowns and 913 of 8892 (10.3%) unstructured free text entries. One-third of the unstructured free text entries (32%) could be mapped post hoc to a PRO-CTCAE term and 68% to a MedDRA term. DISCUSSION: Participants frequently added supplemental information beyond study-specific survey items. Almost half selected a structured dropdown term, although many opted to submit unstructured free text entries. Most free text entries could be mapped post hoc to PRO-CTCAE or MedDRA terms, suggesting opportunities to enhance the system to perform real-time mapping for AE reporting. CONCLUSIONS: Patient reporting of symptomatic AEs using a text box functionality with mapping to existing terminologies is both feasible and informative.