Program for lung cancer screening and tobacco cessation: Study protocol of a sequential, multiple assignment, randomized trial

A new measure of regulatory focus: Preventing measurement error by promoting best validation practices

OBJECTIVE AND BACKGROUND

The goals of this project were to improve our understanding of chronic regulatory focus constructs and to provide researchers with a measure that adequately assesses the constructs, can distinguish individual differences effectively across the range of the constructs, and is appropriate for use in diverse populations.

METHOD

Employing best practices in construct validation, we developed the International Personality Item Pool Regulatory Focus Scale (IPIP-RFS). Utilizing 14 samples (N = 4867), we established substantive (via expert ratings and regulatory focus literature), structural (via factor analysis, item response theory, and measurement invariance), and external (via convergent, discriminant, and predictive associations) validity.

RESULTS

The IPIP-RFS adequately assesses the constructs of chronic promotion focus and prevention focus, can accurately assess individuals along the continua of the constructs, and is suitable for use among populations that vary in gender, race, and age. Individual differences in promotion focus reflect self-regulation and goal pursuit related to cognitive and behavioral exploration and flexibility (i.e., plasticity), whereas individual differences in prevention focus reflect self-regulation and goal pursuit related to motivational and interpersonal steadiness (i.e., stability).

CONCLUSIONS

Promotion and prevention focus are important elements of personality with broad implications for functioning and outcomes in health and other important domains.

Smoking cessation, harm reduction, and biomarkers protocols in the PhenX Toolkit: Tools for standardized data collection

The use of standard protocols in studies supports consistent data collection, improves data quality, and facilitates cross-study analyses. Funded by the National Institutes of Health, the PhenX (consensus measures for Phenotypes and eXposures) Toolkit is a catalog of recommended measurement protocols that address a wide range of research topics and are suitable for inclusion in a variety of study designs. In 2020, a PhenX Working Group of smoking cessation experts followed a well-established consensus process to identify and recommend measurement protocols suitable for inclusion in smoking cessation and smoking harm reduction studies. The broader scientific community was invited to review and provide feedback on the preliminary recommendation of the Working Group. Fourteen selected protocols for measuring smoking cessation, harm reduction, and biomarkers research associated with smoking cessation were released in the PhenX Toolkit ( https://www.phenxtoolkit.org) in February 2021. These protocols complement existing PhenX Toolkit content related to tobacco regulatory research, substance use and addiction research, and other measures of smoking-related health outcomes. Adopting well-established protocols enables consistent data collection and facilitates comparing and combining data across studies, potentially increasing the scientific impact of individual studies.

Optimizing adaptive stepped-care interventions to change adults' health behaviors: A systematic review

Chronic diseases are ubiquitous and costly in American populations. Interventions targeting health behavior change to manage chronic diseases are needed, but previous efforts have fallen short of producing meaningful change on average. Adaptive stepped-care interventions, that tailor treatment based on the needs of the individual over time, are a promising new area in health behavior change. We therefore conducted a systematic review of tests of adaptive stepped-care interventions targeting health behavior changes for adults with chronic diseases. We identified 9 completed studies and 13 research protocols testing adaptive stepped-care interventions for health behavior change. The most common health behaviors targeted were substance use, weight management, and smoking cessation. All identified studies test intermediary tailoring for treatment non-responders via sequential multiple assignment randomized trials (SMARTs) or singly randomized trials (SRTs); none test baseline tailoring. From completed studies, there were few differences between embedded adaptive interventions and minimal differences between those classified as treatment responders and non-responders. In conclusion, updates to this work will be needed as protocols identified here publish results. Future research could explore baseline tailoring variables, apply methods to additional health behaviors and target populations, test tapering interventions for treatment responders, and consider adults' context when adapting interventions.

Optimizing Longitudinal Tobacco Cessation Treatment in Lung Cancer Screening: A Sequential, Multiple Assignment, Randomized Trial

Importance

Nearly half of the 14.8 million US adults eligible for lung cancer screening (LCS) smoke cigarettes. The optimal smoking cessation program components for the LCS setting are unclear.

Objective

To assess the effect of adding a referral to prescription medication therapy management (MTM) to the tobacco longitudinal care (TLC) program among patients eligible for LCS who smoke and do not respond to early tobacco treatment and to assess the effect of decreasing the intensity of TLC among participants who do respond to early treatment.

Design, Setting, and Participants

This randomized clinical trial included patients who currently smoked cigarettes daily and were eligible for LCS. Recruitment took place at primary care centers and LCS programs at 3 large health systems in the US and began in October 2016, and 18-month follow-up was completed April 2021.

Interventions

(1) TLC comprising intensive telephone coaching and combination nicotine replacement therapy for 1 year with at least monthly contact; (2) TLC with MTM, MTM offered pharmacist-referral for prescription medications; and (3) Quarterly TLC, intensity of TLC was decreased to quarterly contact. Intervention assignments were based on early response to tobacco treatment (abstinence) that was assessed either 4 weeks or 8 weeks after treatment initiation.

Main outcomes and Measures

Self-reported, 6-month prolonged abstinence at 18-month.

Results

Of 636 participants, 228 (35.9%) were female, 564 (89.4%) were White individuals, and the median (IQR) age was 64.3 (59.6-68.8) years. Four weeks or 8 weeks after treatment initiation, 510 participants (80.2%) continued to smoke (ie, early treatment nonresponders) and 126 participants (19.8%) had quit (ie, early treatment responders). The 18 month follow-up survey response rate was 83.2% (529 of 636). Across TLC groups at 18 months follow-up, the overall 6-month prolonged abstinence rate was 24.4% (129 of 529). Among the 416 early treatment nonresponders, 6-month prolonged abstinence for TLC with MTM vs TLC was 17.8% vs 16.4% (adjusted odds ratio [aOR] 1.13; 95% CI, 0.67-1.89). In TLC with MTM, 98 of 254 participants (39%) completed at least 1 MTM visit. Among 113 early treatment responders, 6-month prolonged abstinence for Quarterly TLC vs TLC was 24 of 55 (43.6%) vs 34 of 58 (58.6%) (aOR, 0.54; 95% CI, 0.25-1.17).

Conclusions and Relevance

In this randomized clinical trial, adding referral to MTM with TLC for participants who did not respond to early treatment did not improve smoking abstinence. Stepping down to Quarterly TLC among early treatment responders is not recommended. Integrating longitudinal tobacco cessation care with LCS is feasible and associated with clinically meaningful quit rates.

Trial Registration

ClinicalTrials.gov Identifier: NCT02597491.

Outcome trajectory estimation for optimal dynamic treatment regimes with repeated measures

In recent sequential multiple assignment randomized trials, outcomes were assessed multiple times to evaluate longer-term impacts of the dynamic treatment regimes (DTRs). Q-learning requires a scalar response to identify the optimal DTR. Inverse probability weighting may be used to estimate the optimal outcome trajectory, but it is inefficient, susceptible to model mis-specification, and unable to characterize how treatment effects manifest over time. We propose modified Q-learning with generalized estimating equations to address these limitations and apply it to the M-bridge trial, which evaluates adaptive interventions to prevent problematic drinking among college freshmen. Simulation studies demonstrate our proposed method improves efficiency and robustness.

Increasing Physical Activity in Persons With Spinal Cord Injury With an eHealth-Based Adaptive Exercise Intervention: Protocol for a Sequential Multiple Assignment Randomized Trial

BACKGROUND

Participating in an adequate amount of physical activity to acquire health benefits is challenging for people with spinal cord injury (SCI) due to personal and logistic barriers. Barriers in the built and social environments may include lack of transportation, lack of accessible facilities or programs, and lack of training among fitness personnel. Low self-efficacy, lack of self-regulation skills, and improper outcome expectations are examples of personal barriers. Current approaches to investigating physical activity programs in people with SCI have been limited to traditional "one-size-fits-all" design, which has yielded low adherence rates, high dropout rates, and participants not maintaining physical activity levels at follow-up.

OBJECTIVE

The primary aim of this study is to test the feasibility of a tele-exercise program that applies an adaptive intervention design for 30 adults with SCI, targeting increases in adherence to the exercise program and physical activity participation.

METHODS

The Sequential Multiple Assignment Randomized Trial for Home-based Exercise and Lifestyle Tele-Health (SMART-HEALTH) is a 12-week, home-based, movement-to-music (M2M) program. The goal of a SMART-designed study is to develop an adaptive intervention that modifies support provisions based on response levels. In SMART-HEALTH, 2 groups of participants will undergo 3-week and 6-week asynchronous M2M interventions in the first phase. Participants who did not achieve the desired adherence rate (≥95% of video watch minutes) will be rerandomized into M2M Live (switch) or individualized behavioral coaching (augmented with the asynchronous M2M program). The study will primarily assess rates of recruitment or enrollment, adherence and retention, timing to identify nonresponders, and scientific outcomes (eg, physical activity and exercise self-efficacy). The study will qualitatively evaluate the acceptability of the study using semistructured interviews among participants who complete the 12-week intervention.

RESULTS

Recruitment procedures started in June 2022. All data are expected to be collected by September 2023. Full trial results are expected to be published by March 2024. Secondary analyses of data will be subsequently published. Results will include exercise adherence rates; changes in self-reported physical activity levels and blood pressure; and changes in secondary conditions including pain, sleep, and fatigue. Thematic analysis of semistructured interviews will include results on participant enjoyment and acceptability of SMART-HEALTH and inform modifications for future delivery of the program.

CONCLUSIONS

This study will strengthen our understanding of the potential benefits of the tele-exercise intervention for people with SCI and build upon adaptive intervention design and its delivery strategies that aim to increase adoption and sustainable exercise behavior. This pilot trial will inform future SMART-designed studies and provide new and innovative strategies for investigating intervention effects on physical activity behavior in the SCI population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04726891; https://classic.clinicaltrials.gov/ct2/show/NCT04726891.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47665.

Adaptive interventions for alcohol misuse and violent behaviors among adolescents and emerging adults in the emergency department: A sequential multiple assignment randomized controlled trial protocol

Alcohol use and violent behaviors among youth are associated with morbidity and mortality. An emergency department (ED) visit provides an opportunity to initiate prevention efforts. Despite promising findings from our single session SafERteens brief intervention (BI), impact is limited by modest effect sizes, with data lacking on optimal boosters to enhance effects. This paper describes the protocol for a sequential, multiple assignment, randomized trial (SMART). Adolescents and emerging adults (ages 14-20) in the ED screening positive for alcohol use and violent behaviors (physical aggression) were randomly assigned to: 1) SafERteens BI + Text Messaging (TM), or 2) SafERteens BI + remote Health Coach (HC). Participants completed weekly surveys over 8 weeks after the ED visit to tailor intervention content and measure mechanisms of change. At one-month, intervention response/non-response is determined (e.g., binge drinking or violent behaviors). Responders are re-randomized to continued intervention condition (e.g., maintenance) or minimized condition (e.g., stepped down). Non-responders are re-randomized to continued condition (e.g., maintenance), or intensified condition (e.g., stepped up). Outcomes were measured at 4 and 8 months, including primary outcomes of alcohol consumption and violence, with secondary outcomes of alcohol consequences and violence consequences. Although the original goal was to enroll 700 participants, COVID-19 impacts on research diminished recruitment in this trial (enrolled n = 400). Nonetheless, the proposed SMART is highly innovative by blending real-time assessment methodologies with adaptive intervention delivery among teens with comorbid alcohol misuse and violent behaviors. Findings will inform the content and timing booster interventions to alter risk behavior trajectories. Trial Registration:ClinicalTrials.govNCT03344666. University of Michigan # HUM00109156.

A pilot adaptive trial of text messages, mailed nicotine replacement therapy, and telephone coaching among primary care patients who smoke

INTRODUCTION

Sequential multiple assignment randomized trials (SMART) inform the design of adaptive treatment interventions. We tested the feasibility of a SMART to deliver a stepped-care intervention among primary care patients who smoked daily.

METHODS

In a 12-week pilot SMART (NCT04020718), we tested the feasibility of recruiting and retaining (>80 %) participants to an adaptive intervention starting with cessation text messages (SMS). The study randomly assigned participants (R1) to assessment of quit status, the tailoring variable, after either 4 or 8 weeks of SMS. The study offered continued SMS alone to those reporting abstinence. Those reporting smoking were randomized (R2) to SMS + mailed NRT or SMS + NRT + brief telephone coaching.

RESULTS

During Jan-March and July-Aug 2020, we enrolled 35 patients (>18 years) from a primary care network in Massachusetts. Two (6 %) of 31 participants reported seven-day point prevalence abstinence at their tailoring variable assessment. The 29 participants who continued to smoke at 4 or 8 weeks were randomized (R2) to SMS + NRT (n = 16) or SMS + NRT + coaching (n = 13). Thirty of 35 participants (86 %) completed 12-weeks; 13 % (2/15) of those in 4-week group and 27 % (4/15) of those in 8-week group had CO < 6 ppm at 12-weeks (p = 0.65). Among 29 participants in R2, one was lost to follow-up, 19 % (3/16) of the SMS + NRT group had CO < 6 ppm vs. 17 % (2/12) of SMS + NRT + coaching (p = 1.00). Treatment satisfaction was high (93 %, 28 of 30 who completed 12-weeks).

CONCLUSIONS

A SMART exploring a stepped-care adaptive intervention combining SMS, NRT, and coaching for primary care patients was feasible. Retention and satisfaction were high and quit rates were promising.

Use of Sequential Multiple Assignment Randomized Trials (SMARTs) in oncology: systematic review of published studies

Sequential multiple assignments randomized trials (SMARTs) are a type of experimental design where patients may be randomised multiple times according to pre-specified decision rules. The present work investigates the state-of-the-art of SMART designs in oncology, focusing on the discrepancy between the available methodological approaches in the statistical literature and the procedures applied within cancer clinical trials. A systematic review was conducted, searching PubMed, Embase and CENTRAL for protocols or reports of results of SMART designs and registrations of SMART designs in clinical trial registries applied to solid tumour research. After title/abstract and full-text screening, 33 records were included. Fifteen were reports of trials' results, four were trials' protocols and fourteen were trials' registrations. The study design was defined as SMART by only one out of fifteen trial reports. Conversely, 13 of 18 study protocols and trial registrations defined the study design SMART. Furthermore, most of the records considered each stage separately in the analysis, without considering treatment regimens embedded in the trial. SMART designs in oncology are still limited. Study powering and analysis is mainly based on statistical approaches traditionally used in single-stage parallel trial designs. Formal reporting guidelines for SMART designs are needed.

Design considerations and analytical framework for reliably identifying a beneficial individualized treatment rule

An individualized treatment rule (ITR) formalizes personalized medicine by assigning treatment as a function of patients' clinical information, which contrasts with a static treatment rule that assigns everyone the same treatment. ITR identification has become a common aim in randomized clinical trials but sample size considerations for this aim are lacking. One approach is to select a sample size that will reliably identify an ITR with a performance close to the theoretical optimal rule. However, this approach could still lead to identifying ITRs that perform worse than the optimal static rule, particularly in the absence of substantial effect heterogeneity. This limitation motivates sample size considerations aimed at reliable identification of a beneficial ITR, which outperforms the optimal static rule, and analysis methods that identify the estimated optimal static rule when there is substantial uncertainty about whether an ITR will improve outcomes. To address these limitations, we propose a sample size approach based on the probability of identifying a beneficial ITR and introduce an approach for selecting the LASSO penalty parameter such that in the absence of treatment effect heterogeneity the estimated optimal static rule is identified with high probability. We apply these approaches to the PLUTO trial aimed at developing methods to assist with smoking cessation.

Latent constructs identified in older individuals who smoke cigarettes and are eligible for lung cancer screening: Factor analysis of baseline data from the PLUTO smoking cessation trial

Introduction

Lung cancer screening (LCS) combined with smoking cessation intervention is currently recommended for older individuals with a history of heavy smoking. Tailoring tobacco treatment for this patient population of older, people who smoke (PWS) may improve cessation rates while efficiently using limited smoking cessation resources. Although some older people who smoke will need more intensive treatment to achieve sustained abstinence, others may be successful with less intensive treatment. A framework to identify them a priori would be helpful to distribute smoking cessation resources accordingly.

Methods

Baseline demographic, smoking, and health data are reported from a randomized clinical trial of longitudinal smoking cessation interventions delivered in the setting of LCS. Candidate variables were factor analyzed to identify latent factors, or constructs, to identify subgroups of older participants among the heterogenous population of older people who smoke.

Results

We identified three factor-derived constructs: self-reported health status, heaviness of smoking, and nicotine dependence. Nicotine dependence was moderately correlated with both of the other two factors.

Conclusions

This factor analysis of baseline participant characteristics identified a set of latent constructs – based on a few practical clinical variables -- that can be used to classify the heterogenous population of older people who smoke to identify. We propose this framework to identify subgroups of people who smoke who might successfully quit with less intense treatment at the time of lung cancer screening.

Adaptive interventions to optimise the mobile phone-based smoking cessation support: study protocol for a sequential, multiple assignment, randomised trial (SMART)

BACKGROUND

Mobile health (mHealth) is promising in developing personalised smoking cessation interventions. By using an adaptive trial design, we aim to evaluate the effectiveness of personalised mHealth intervention in increasing smoking cessation.

METHODS

This study is a two-arm, parallel, accessor-blinded Sequential Multiple-Assignment Randomised Trial (SMART) that randomises 1200 daily cigarette smokers from 70 community sites at two timepoints. In the first phase, participants receive brief cessation advice plus referral assistance to smoking cessation services and are randomly allocated to receive personalised instant messaging (PIM) or regular instant messaging (RIM). In the second phase, PIM participants who are non-responders (i.e. still smoking at 1 month) are randomised to receive either optional combined interventions (multi-media messages, nicotine replacement therapy sampling, financial incentive for active referral, phone counselling, and family/peer support group chat) or continued-PIM. Non-responders in the RIM group are randomised to receive PIM or continued-RIM. Participants who self-report quitting smoking for 7 days or longer at 1 month (responders) in both groups continue to receive the intervention assigned in phase 1. The primary outcomes are biochemical abstinence validated by exhaled carbon monoxide (< 4 ppm) and salivary cotinine (< 10 ng/ml) at 3 and 6 months from treatment initiation. Intention-to-treat analysis will be adopted.

DISCUSSION

This is the first study using a SMART design to evaluate the effect of adaptive mHealth intervention on abstinence in community-recruited daily smokers. If found effective, the proposed intervention will inform the development of adaptive smoking cessation treatment and benefits smokers non-responding to low-intensity mHealth support.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03992742 . Registered on 20 June 2019.

Cost-Effectiveness of a Telephone-Based Smoking Cessation Randomized Trial in the Lung Cancer Screening Setting

BACKGROUND

There are limited data on the cost-effectiveness of smoking cessation interventions in lung cancer screening settings. We conducted an economic analysis embedded in a national randomized trial of 2 telephone counseling cessation interventions.

METHODS

We used a societal perspective to compare the short-term cost per 6-month bio-verified quit and long-term cost-effectiveness of the interventions. Trial data were used to micro-cost intervention delivery, and the data were extended to a lifetime horizon using an established Cancer Intervention Surveillance and Modeling Network lung cancer model. We modeled the impact of screening accompanied by 8 weeks vs 3 weeks of telephone counseling (plus nicotine replacement) vs screening alone based on 2021 screening eligibility. Lifetime downstream costs (2021 dollars) and effects (life-years gained, quality-adjusted life-years [QALYs]) saved were discounted at 3%. Sensitivity analyses tested the effects of varying quit rates and costs; all analyses assumed nonrelapse after quitting.

RESULTS

The costs for delivery of the 8-week vs 3-week protocol were $380.23 vs $144.93 per person, and quit rates were 7.14% vs 5.96%, respectively. The least costly strategy was a 3-week counseling approach. An 8-week (vs 3-week) counseling approach increased costs but gained QALYs for an incremental cost-effectiveness ratio of $4029 per QALY. Screening alone cost more and saved fewer QALYs than either counseling strategy. Conclusions were robust in sensitivity analyses.

CONCLUSIONS

Telephone-based cessation interventions with nicotine replacement are considered cost-effective in the lung screening setting. Integrating smoking cessation interventions with lung screening programs has the potential to maximize long-term health benefits at reasonable costs.

Engaging Patients in Smoking Cessation Treatment within the Lung Cancer Screening Setting: Lessons Learned from an NCI SCALE Trial

Offering smoking cessation treatment at lung cancer screening (LCS) will maximize mortality reduction associated with screening, but predictors of treatment engagement are not well understood. We examined participant characteristics of engagement in an NCI SCALE cessation trial. Eligible LCS patients (N = 818) were randomized to the Intensive arm (8 phone counseling sessions +8 weeks of nicotine replacement therapy (NRT)) vs. Minimal arm (3 sessions + 2 weeks of NRT). Engagement was measured by number of sessions completed (none, some, or all) and NRT mailed (none vs. any) in each arm. In the Intensive arm, those with ≥some college (OR = 2.1, 95% CI = 1.1, 4.0) and undergoing an annual scan (OR = 2.1, 95% CI = 1.1, 4.2) engaged in some counseling vs. none. Individuals with higher nicotine dependence were more likely (OR = 2.8, 95% CI = 1.3, 6.2) to request NRT. In the Minimal arm, those with higher education (OR = 2.1, 95% CI = 1.1, 3.9) and undergoing an annual scan (OR = 2.0, 95% CI = 1.04, 3.8) completed some sessions vs. none. Requesting NRT was associated with more pack-years (OR = 1.9, 95% CI = 1.1, 3.5). Regardless of treatment intensity, additional strategies are needed to engage those with lower education, less intensive smoking histories, and undergoing a first scan. These efforts will be important given the broader 2021 LCS guidelines.

Sequential multiple assignment randomized trial studies should report all key components: a systematic review

OBJECTIVE

Sequential Multiple Assignment Randomised Trial (SMART) designs allow multiple randomisations of participants; this allows assessment of stage-specific questions (individual randomisations) and adaptive interventions (i.e. treatment strategies). We assessed the quality of reporting of the information required to design SMART studies.

STUDY DESIGN AND SETTING

We systematically searched four databases (PubMed, Ovid, Web of Science and Scopus) for all trial reports, protocols, reviews, and methodological papers which mentioned SMART designs up to June 15, 2020.

RESULTS

Of the 157 selected records, 12 (7.64%) were trial reports, 24 (15.29%) were study protocols, 91 (58%) were methodological papers, and 30 (19.1%) were review papers. All these trials were powered using stage-specific aims. Only four (33.33%) of these trials reported parameters required for sample size calculations. A small number of the trials (16.67 %) were interested in determining the best embedded adaptive interventions. Most of the trials did not report information about multiple testing adjustment. Furthermore, most of records reported designs that were mainly focused on stage-specific aims.

CONCLUSIONS

Some features of SMART designs are seldomly reported and/or used. Furthermore, studies using this design tend to not adequately report information about all the design parameters, limiting their transparency and interpretability.

A SMARTTT approach to Treating Tobacco use disorder in persons with HIV (SMARTTT): Rationale and design for a hybrid type 1 effectiveness-implementation study

BACKGROUND

Tobacco use disorder is a leading threat to the health of persons with HIV (PWH) on antiretroviral treatment and identifying optimal treatment approaches to promote abstinence is critical. We describe the rationale, aims, and design for a new study, "A SMART Approach to Treating Tobacco Use Disorder in Persons with HIV (SMARTTT)," a sequential multiple assignment randomized trial.

METHODS

In HIV clinics within three health systems in the northeastern United States, PWH with tobacco use disorder are randomized to nicotine replacement therapy (NRT) with or without contingency management (NRT vs. NRT + CM). Participants with response (defined as exhaled carbon monoxide (eCO)-confirmed smoking abstinence at week 12), continue the same treatment for another 12 weeks. Participants with non-response, are re-randomized to either switch medications from NRT to varenicline or intensify treatment to a higher CM reward schedule. Interventions are delivered by clinical pharmacists embedded in HIV clinics. The primary outcome is eCO-confirmed smoking abstinence; secondary outcomes include CD4 cell count, HIV viral load suppression, and the Veterans Aging Cohort Study (VACS) Index 2.0 score (a validated measure of morbidity and mortality based on laboratory data). Consistent with a hybrid type 1 effectiveness-implementation design and grounded in implementation science frameworks, we will conduct an implementation-focused process evaluation in parallel. Study protocol adaptations related to the COVID-19 pandemic have been made.

CONCLUSIONS

SMARTTT is expected to generate novel findings regarding the impact, cost, and implementation of an adaptive clinical pharmacist-delivered intervention involving medications and CM to promote smoking abstinence among PWH. ClinicalTrials.govidentifier:NCT04490057.

Self-reported exercise capacity among current smokers eligible for lung cancer screening: Distribution and association with key comorbidities

ONE CONCERN: as lung cancer screening (LCS) is implemented is that patients will be screened who are too ill to benefit. Poor exercise capacity (EC) predicts adverse outcomes following lung resection.

OBJECTIVE

Describe the distribution of EC among smokers eligible for LCS and examine associations with comorbidities.

METHODS

Cross-sectional analysis of baseline data from a randomized controlled trial of tobacco treatment in the context of LCS. Participants responded regarding limitations in moderate activities, ability to climb stairs, and frequency of dyspnea on a scale from never/almost never to all or most of the time. Responses were assigned a numeric score and summed to categorize exercise limitation. Associations between poor EC and key comorbidities were examined using adjusted logistic regression.

RESULTS

660 participants completed a survey with the following characteristics: 64.4% male, 89.5% white, mean age 64.5. Overall EC categories were: good 39.0%, intermediate 41.6%, and poor 19.4%.  Prevalence of poor EC was higher among patients with COPD (OR 4.62 95%CI 3.05-7.02), heart failure (OR 3.07 95%CI 1.62-5.82) and cardiovascular disease (OR 2.24, 95%CI 1.45-3.47), and was highest among patients with multimorbidity. Among patients with COPD and heart failure, 57% had poor and 0% had good EC. In adjusted logistic regression, only COPD and Charlson comorbidity index remained significantly associated with poor EC.

CONCLUSIONS

Many patients eligible for LCS reported poor EC, with increased odds of poor EC among patients with comorbidities. More research is needed to determine how to best integrate EC and comorbidity into eligibility and shared decision-making conversations.

Predictors of Enrollment of Older Smokers in Six Smoking Cessation Trials in the Lung Cancer Screening Setting: The Smoking Cessation at Lung Examination (SCALE) Collaboration

SIGNIFICANCE

Increased rates of smoking cessation will be essential to maximize the population benefit of low-dose CT screening for lung cancer. The NCI's Smoking Cessation at Lung Examination (SCALE) Collaboration includes eight randomized trials, each assessing evidence-based interventions among smokers undergoing lung cancer screening (LCS). We examined predictors of trial enrollment to improve future outreach efforts for cessation interventions offered to older smokers in this and other clinical settings.

METHODS

We included the six SCALE trials that randomized individual participants. We assessed demographics, intervention modalities, LCS site and trial administration characteristics, and reasons for declining.

RESULTS

Of 6,285 trial- and LCS-eligible individuals, 3,897 (62%) declined and 2,388 (38%) enrolled. In multivariable logistic regression analyses, Blacks had higher enrollment rates (OR 1.5, 95% CI 1.2,1.8) compared to Whites. Compared to 'NRT Only' trials, those approached for 'NRT+prescription medication' trials had higher odds of enrollment (OR 6.1, 95% CI 4.7,7.9). Regarding enrollment methods, trials using 'Phone+In Person' methods had higher odds of enrollment (OR 1.6, 95% CI 1.2,1.9) compared to trials using 'Phone Only' methods. Some of the reasons for declining enrollment included 'too busy' (36.6%), 'not ready to quit' (8.2%), 'not interested in research' (7.7%), and 'not interested in the intervention offered' (6.2%).

CONCLUSION

Enrolling smokers in cessation interventions in the LCS setting is a major priority that requires multiple enrollment and intervention modalities. Barriers to enrollment provide insights that can be addressed and applied to future cessation interventions to improve implementation in LCS and other clinical settings with older smokers.

IMPLICATIONS

We explored enrollment rates and reasons for declining across six smoking cessation trials in the lung cancer screening setting. Offering multiple accrual methods and pharmacotherapy options predicted increased enrollment across trials. Enrollment rates were also greater among Blacks compared to Whites. The findings offer practical information for the implementation of cessation trials and interventions in the lung cancer screening context and other clinical settings, regarding intervention modalities that may be most appealing to older, long-term smokers.

Lung Cancer Screening in a Surgical Lung Cancer Population: Analysis of a Rural, Quaternary, Academic Experience

BACKGROUND

Rural populations face many health disadvantages including higher rates of tobacco use and lung cancer than more populated areas. Given this, we specifically sought to understand the current screening landscape in a cohort of patients with resected lung cancer to help direct improvements in the screening process.

MATERIALS AND METHODS

We retrospectively reviewed our prospective database at a rural, quaternary, academic institution from January 2015 to June 2018. All patients who underwent resection for primary lung cancer were studied to assess the frequency of preoperative low-dose chest computed tomography per accepted guidelines. The intent was to evaluate participant demographics, clinical stage, frequency, and distribution of Lung-RADS reporting.

RESULTS

About 446 patients underwent primary resection, of which 252 were deemed screening-eligible. About 57 (22.6%) underwent low-dose chest computed tomography screening and 195 (77.4%) did not. No significant demographic differences were identified between groups. However, 82.5% (47/57) of the screened patients presented with clinical stage IA disease, compared with 67.1% (131/195) of the nonscreened patients (P = 0.03). Among those screened, 36.8% (21/57) did not have a Lung-RADS score documented despite 52.3% (11/21) of those coming from accredited programs.

CONCLUSIONS

Our screening completion rate was only 22.6% of eligible patients and 36.8% of those patients did not have a documented Lung-RADS score. These findings, in combination with the increased rate of diagnosis of stage IA disease, provide compelling reasons to further investigate factors designed to improve access and screening practices at rural institutions.

Joint modeling and multiple comparisons with the best of data from a SMART with survival outcomes

A dynamic treatment regimen (DTR) is a sequence of decision rules that can alter treatments or doses based on outcomes from prior treatment. In the case of two lines of treatment, a DTR specifies first-line treatment, and second-line treatment for responders and treatment for non-responders to the first-line treatment. A sequential, multiple assignment, randomized trial (SMART) is one such type of trial that has been designed to assess DTRs. The primary goal of our project is to identify the treatments, covariates, and their interactions result in the best overall survival rate. Many previously proposed methods to analyze data with survival outcomes from a SMART use inverse probability weighting and provide non-parametric estimation of survival rates, but no other information. Other methods have been proposed to identify and estimate the optimal DTR, but inference issues were seldom addressed. We apply a joint modeling approach to provide unbiased survival estimates as a mechanism to quantify baseline and time-varying covariate effects, treatment effects, and their interactions within regimens. The issue of multiple comparisons at specific time points is addressed using multiple comparisons with the best method.

Potential Impact of Cessation Interventions at the Point of Lung Cancer Screening on Lung Cancer and Overall Mortality in the United States

INTRODUCTION

Annual lung cancer screening with low-dose computed tomography is recommended for adults aged 55 to 80 years with a greater than or equal to 30 pack-year smoking history who currently smoke or quit within the past 15 years. The 50% who are current smokers should be offered cessation interventions, but information about the impact of adding cessation to screening is limited.

METHODS

We used an established lung cancer simulation model to compare the effects on mortality of a hypothetical one-time cessation intervention and annual screening versus annual screening only among screen-eligible individuals born in 1950 or 1960. Model inputs were derived from national data and included smoking history, probability of quitting with and without intervention, lung cancer risk and treatment effectiveness, and competing tobacco-related mortality. We tested the sensitivity of results under different assumptions about screening use and cessation efficacy.

RESULTS

Smoking cessation reduces lung cancer mortality and delays overall deaths versus screening only across all assumptions. For example, if screening was used by 30% of screen-eligible individuals born in 1950, adding an intervention with a 10% quit probability reduces lung cancer deaths by 14% and increases life years gained by 81% compared with screening alone. The magnitude of cessation benefits varied under screening uptake rates, cessation effectiveness, and birth cohort.

CONCLUSIONS

Smoking cessation interventions have the potential to greatly enhance the impact of lung cancer screening programs. Evaluation of specific interventions, including costs and feasibility of implementation and dissemination, is needed to determine the best possible strategies and realize the full promise of lung cancer screening.

Correlates of adherence in a home-based, self-managed exercise program tailored to wheelchair users with spinal cord injury

STUDY DESIGN

Cross-sectional design.

OBJECTIVES

To examine personal factors, secondary health conditions, and environmental factors as potential correlates of adherence to a 12-week home-based exercise trial in people with spinal cord injury.

SETTING

Home METHODS: Participants (n = 28) were prescribed a set of exercise videos that they were asked to complete three times each week for 12 weeks (36 total sessions). The videos were accessible through a custom-designed mobile application and included movements targeting strength, cardiorespiratory fitness, and balance that were accompanied with music. Watched video minutes were automatically recorded on the web-based platform. At baseline, participants completed self-report questionnaires that measured personal (e.g., age, self-efficacy) and environmental (e.g., barriers) factors and secondary health conditions (e.g., depression). Data were analyzed using quantile (median) regression analysis.

RESULTS

Race (African American; β = -65.62, p = 0.004), community barriers (β = -9.12, p = 0.026), anxiety (β = -3.84, p = <0.001), depression (β = -1.42, p = 0.038), physical function (β = -1.35, p = 0.048), and self-efficacy (β = -0.61, p = 0.007) were associated with a lower number of exercise video minutes. Pain intensity (β = 2.03, p = 0.032), pain interference (β = 1.84, p = 0.012), and age (β = 1.13, p = 0.013) were associated with a higher number of exercise video minutes. Total variance explained by the model was 77% (pseudo R² = 0.77).

CONCLUSIONS

Factors associated with lower and higher adherence to home-based exercise should guide future research efforts in creating more precision-based approaches for self-managed home exercise.

Sample size considerations for comparing dynamic treatment regimens in a sequential multiple-assignment randomized trial with a continuous longitudinal outcome

Clinicians and researchers alike are increasingly interested in how best to personalize interventions. A dynamic treatment regimen is a sequence of prespecified decision rules which can be used to guide the delivery of a sequence of treatments or interventions that is tailored to the changing needs of the individual. The sequential multiple-assignment randomized trial is a research tool which allows for the construction of effective dynamic treatment regimens. We derive easy-to-use formulae for computing the total sample size for three common two-stage sequential multiple-assignment randomized trial designs in which the primary aim is to compare mean end-of-study outcomes for two embedded dynamic treatment regimens which recommend different first-stage treatments. The formulae are derived in the context of a regression model which leverages information from a longitudinal outcome collected over the entire study. We show that the sample size formula for a sequential multiple-assignment randomized trial can be written as the product of the sample size formula for a standard two-arm randomized trial, a deflation factor that accounts for the increased statistical efficiency resulting from a longitudinal analysis, and an inflation factor that accounts for the design of a sequential multiple-assignment randomized trial. The sequential multiple-assignment randomized trial design inflation factor is typically a function of the anticipated probability of response to first-stage treatment. We review modeling and estimation for dynamic treatment regimen effect analyses using a longitudinal outcome from a sequential multiple-assignment randomized trial, as well as the estimation of standard errors. We also present estimators for the covariance matrix for a variety of common working correlation structures. Methods are motivated using the ENGAGE study, a sequential multiple-assignment randomized trial aimed at developing a dynamic treatment regimen for increasing motivation to attend treatments among alcohol- and cocaine-dependent patients.

"Every day I think about your messages": assessing text messaging engagement among Latino smokers in a mobile cessation program

INTRODUCTION

Mobile health interventions are a promising mode to address tobacco-related disparities among Latinos, the largest minority group and the highest users of text messaging technology. The purpose of this pilot study was to assess engagement in a smoking cessation intervention delivered via text message (Kick Buts) among Latino smokers.

METHODS

We relied on a community-based recruitment strategy to enroll 20 Latino smokers in Kick Buts. Outcome measures included biochemically verified abstinence at 12 weeks, participant text messaging interactivity with the program, and satisfaction.

RESULTS

Participants' mean age was 40.7 years old (SD=14.6). Most of the participants were male (70%), did not have health insurance (75%), and reported low nicotine-dependence (60%). The majority of participants (75%) sent at least one text message to the program. On average, participants who interacted with the program sent 31.8 (SD=39.7) text messages. Eight themes were identified in participants' messages (eg, well-being, self-efficacy, strategies to quit, extra-treatment social support, etc). At 12 weeks, 30% of the participants were biochemically verified as abstinent.

CONCLUSION

A smoking cessation text message intervention generated high engagement among Latinos and resulted in noteworthy cessation rates. Future studies should assess the relationship of text messaging interactions with psychological effects (eg, intra-treatment social support, therapeutic alliance, and perceived autonomy support).