Search

BackgroundSmoking rates among people living with behavioral health conditions (BHC) range from 30 to 65% and are 2-4 times higher than rates found in the general population. Starting tobacco treatment during a hospital stay is effective for smoking cessation, but little is known regarding treatment response among inpatients with BHC.ObjectiveThis study pooled data across multiple clinical trials to determine the relative success in quitting among participants with BHC compared to other study participants.ParticipantsAdults who smoke (≥ 18 years old) from five hospital-based smoking cessation randomized clinical trials.DesignA retrospective analysis using data from the electronic health record to identify participants with primary diagnoses related to BHC. Recruitment and data analysis were conducted from 2011 to 2016. We used propensity score matching to pair patients with BHC to those with similar characteristics and logistic regression to determine differences between groups.MeasuresThe main outcome was self-reported 30-day abstinence 6 months post-discharge.ResultsOf 6612 participants, 798 patients had a BHC-related primary diagnosis. The matched sample included 642 pairs. Nearly 1 in 3 reported using tobacco medications after hospitalization, with no significant difference between patients with and without BHC (29.3% vs. 31.5%; OR (95% CI) = 0.90 (0.71, 1.14), p = 0.40). Nearly 1 in 5 patients with BHC reported abstinence at 6 months; however, their odds of abstinence were 30% lower than among people without BHC (OR (95% CI) = 0.70 (0.53,0.92), p = 0.01).ConclusionWhen offered tobacco treatment, hospitalized patients with BHC were as likely as people without BHC to accept and engage in treatment. However, patients with BHC were less likely to report abstinence compared to those without BHC. Hospitals are a feasible and promising venue for tobacco treatment among inpatients with BHC. More studies are needed to identify treatment approaches that help people with BHC achieve long-term abstinence.

AimsTo estimate the prevalence and predictors of failed biochemical verification of self-reported abstinence among participants enrolled in trials of hospital-initiated smoking cessation interventions.DesignComparison of characteristics between participants who verified and those who failed to verify self-reported abstinence.SettingsMulti-site randomized clinical trials conducted between 2010 and 2014 in hospitals throughout the United States.ParticipantsRecently hospitalized smokers who reported tobacco abstinence 6 months post-randomization and provided a saliva sample for verification purposes (n = 822).MeasurementsOutcomes were salivary cotinine-verified smoking abstinence at 10 and 15 ng/ml cut-points. Predictors and correlates included participant demographics and tobacco use; hospital diagnoses and treatment; and study characteristics collected via surveys and electronic medical records.FindingsUsable samples were returned by 69.8% of the 1178 eligible trial participants who reported 7-day point prevalence abstinence. The proportion of participants verified as quit was 57.8% [95% confidence interval (CI) = 54.4, 61.2; 10 ng/ml cut-off] or 60.6% (95% CI = 57.2, 63.9; 15 ng/ml). Factors associated independently with verification at 10 ng/ml were education beyond high school education [odds ratio (OR) = 1.51; 95% CI = 1.07, 2.11], continuous abstinence since hospitalization (OR = 2.82; 95% CI = 2.02, 3.94), mailed versus in-person sample (OR = 3.20; 95% CI = 1.96, 5.21) and race. African American participants were less likely to verify abstinence than white participants (OR = 0.64; 95% CI = 0.44, 0.93). Findings were similar for verification at 15 ng/ml. Verification rates did not differ by treatment group.ConclusionsIn the United States, high rates (40%) of recently hospitalized smokers enrolled in smoking cessation trials fail biochemical verification of their self-reported abstinence.

Clinical trials powered to detect subgroup effects provide the most reliable data on heterogeneity of treatment effect among different subpopulations. However, pre-specified subgroup analysis is not always practical and post hoc analysis results should be examined cautiously. Bayesian hierarchical modelling provides grounds for defining a controlled post hoc analysis plan that is developed after seeing outcome data for the population but before unblinding the outcome by subgroup. Using simulation based on the results from a tobacco cessation clinical trial conducted among the general population, we defined an analysis plan to assess treatment effect among American Indians and Alaska Natives (AI/AN) enrolled in the study. Patients were randomized into two arms using Bayesian adaptive design. For the opt-in arm, clinicians offered a cessation treatment plan after verifying that a patient was ready to quit. For the opt-out arm, clinicians provided all participants with free cessation medications and referred them to a Quitline. The study was powered to test a hypothesis of significantly higher quit rates for the opt-out arm at one-month post randomization. Overall, one-month abstinence rates were 15.9% and 21.5% (opt-in and opt-out arm, respectively). For AI/AN, one-month abstinence rates were 10.2% and 22.0% (opt-in and opt-out arm, respectively). The posterior probability that the abstinence rate in the treatment arm is higher is 0.96, indicating that AI/AN demonstrate response to treatment at almost the same probability as the whole population. [ABSTRACT FROM AUTHOR]

Bayesian adaptive designs with response adaptive randomization (RAR) have the potential to benefit more participants in a clinical trial. While there are many papers that describe RAR designs and results, there is a scarcity of works reporting the details of RAR implementation from a statistical point exclusively. In this paper, we introduce the statistical methodology and implementation of the trial Changing the Default (CTD). CTD is a single-center prospective RAR comparative effectiveness trial to compare opt-in to opt-out tobacco treatment approaches for hospitalized patients. The design assumed an uninformative prior, conservative initial allocation ratio, and a higher threshold for stopping for success to protect results from statistical bias. A particular emerging concern of RAR designs is the possibility that time trends will occur during the implementation of a trial. If there is a time trend and the analytic plan does not prespecify an appropriate model, this could lead to a biased trial. Adjustment for time trend was not pre-specified in CTD, but post hoc time-adjusted analysis showed no presence of influential drift. This trial was an example of a successful two-armed confirmatory trial with a Bayesian adaptive design using response adaptive randomization. [ABSTRACT FROM AUTHOR]

Author(s): Taneisha S. Scheuermann [sup.1] , Kristopher J. Preacher [sup.2] , Beatriz H. Carlini [sup.3] , Terry Bush [sup.4] , Brooke Magnusson [sup.4] , Niaman Nazir [sup.1] , Kimber P. [...], Quitlines provide evidence-based tobacco treatment and multiple calls yield higher quit rates. This study aimed to identify subgroups of smokers with greater quitline engagement following referral during hospitalization. Data were from a randomized clinical trial assessing the effectiveness of fax referral (referral faxed to proactive quitline) versus warm handoff (patient connected to quitline at bedside) (n = 1054). Classification and regression trees analyses evaluated individual and treatment/health system-related variables and their interactions. Among all participants, warm handoff, higher ratings of the tobacco treatment care transition, and being older predicted completing more quitline calls. Among patients enrolled in the quitline, higher transition of care ratings, being older, and use of cessation medication post-discharge predicted completing more calls. Three of the four factors influencing engagement were characteristics of treatment within the hospital (quality of tobacco treatment care transition and referral method) and therapy (use of cessation medications), suggesting potential targets to increase quitline engagement post-discharge.

Background: Individuals undergoing cancer treatment have better outcomes when they discontinue tobacco use. Few cancer centers systematically provide evidence-based cessation services. As part of a national quality improvement initiative [Cancer Center Cessation Initiative (C3i)], we collaborated with our cancer registry to develop and implement two tobacco treatment metrics for tracking the provision of behavioral support and pharmacotherapy. Methods: Post-development, the tobacco treatment metrics were integrated into the registry for all future patients. We used means and frequencies to summarize tobacco treatment for cases treated between 2017 and 2019, coinciding with the timeframe of C3i participation. Results: Of 17,735 cancer cases reviewed, both measures were captured on 17,654 (99.5%) of patients, with 3,091 (17.4%) identified as users of tobacco. Across the 3 years, 557 (18%) of individuals who used tobacco received either tobacco cessation pharmacotherapy or behavioral support; with 478 (15.5%) receiving behavioral counseling, 352 (11.4%) receiving pharmacotherapy, and 273 (8.8%) receiving both--considered gold standard care. Tobacco treatment varied substantially across cancer types. The odds of receiving gold standard care were 2.37 times greater in 2019 compared with 2017. (OR, 2.37; 95% confidence interval, 1.63-3.46; P < 0.0001). Conclusions: The new metrics demonstrated high completion rates and their potential to track quality improvement efforts over time. They identified suboptimal treatment reach, but a potential increase in treatment over time and greater treatment among tobacco-related versus nontobacco-related cancers. [ABSTRACT FROM AUTHOR]

Examines formative, process, and intermediate outcome results of a school-based project linked to the National 5 A Day for Better Health campaign to increase fruit and vegetable consumption. Three elementary schools conducted the local campaign. Activity logs, redeemed coupons, and focus groups indicated that the project was implemented as planned and increased students' tasting of fruits and vegetables. (SM)

BackgroundIn rural America, cigarette smoking is prevalent and health care providers lack the time and resources to help smokers quit. Telephone quitlines are important avenues for cessation services in rural areas, but they are poorly integrated with local health care resources. ObjectiveThe intent of the study was to assess the comparative effectiveness and cost effectiveness of two models for delivering expert tobacco treatment at a distance: telemedicine counseling that was integrated into smokers’ primary care clinics (Integrated Telemedicine—ITM) versus telephone counseling, similar to telephone quitline counseling, delivered to smokers in their homes (Phone). MethodsSmokers (n=566) were recruited offline from 20 primary care and safety net clinics across Kansas. They were randomly assigned to receive 4 sessions of ITM or 4 sessions of Phone counseling. Patients in ITM received real-time video counseling, similar to Skype, delivered by computer/webcams in clinic exam rooms. Three full-time equivalent trained counselors delivered the counseling. The counseling duration and content was the same in both groups and was available in Spanish or English. Both groups also received identical materials and assistance in selecting and obtaining cessation medications. The primary outcome was verified 7-day point prevalence smoking abstinence at month 12, using an intent-to-treat analysis. ResultsThere were no significant baseline differences between groups, and the trial achieved 88% follow-up at 12 months. Verified abstinence at 12 months did not significantly differ between ITM or Phone (9.8%, 27/280 vs 12%, 34/286; P=.406). Phone participants completed somewhat more counseling sessions than ITM (mean 2.6, SD 1.5 vs mean 2.4, SD 1.5; P=.0837); however, participants in ITM were significantly more likely to use cessation medications than participants in Phone (55.9%, 128/280 vs 46.1%, 107/286; P=.03). Compared to Phone participants, ITM participants were significantly more likely to recommend the program to a family member or friend (P=.0075). From the combined provider plus participant (societal) perspective, Phone was significantly less costly than ITM. Participants in ITM had to incur time and mileage costs to travel to clinics for ITM sessions. From the provider perspective, counseling costs were similar between ITM (US $45.46, SD 31.50) and Phone (US $49.58, SD 33.35); however, total provider costs varied widely depending on how the clinic space for delivering ITM was valued. ConclusionsFindings did not support the superiority of ITM over telephone counseling for helping rural patients quit smoking. ITM increased utilization of cessation pharmacotherapy and produced higher participant satisfaction, but Phone counseling was significantly less expensive. Future interventions could combine elements of both approaches to optimize pharmacotherapy utilization, counseling adherence, and satisfaction. Such an approach could commence with a telemedicine-delivered clinic office visit for pharmacotherapy guidance, and continue with telephone or real-time video counseling delivered via mobile phones to flexibly deliver behavioral support to patients where they most need it—in their homes and communities. Trial RegistrationClinicaltrials.gov NCT00843505; http://clinicaltrials.gov/ct2/show/NCT00843505 (Archived by WebCite at http://www.webcitation.org/6YKSinVZ9).