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Background To recognize fully the benefit of lung cancer screening (LCS), annual adherence must approach the high levels seen in the National Lung Screening Trial. Emerging data suggest that annual adherence is poor and that a centralized approach to screening improves adherence. Research Questions Do differences in adherence exist between a centralized and decentralized approach to LCS within a hybrid program and what are predictors of adherence? Study Design A retrospective evaluation of a single-center hybrid LCS program was conducted to compare outcomes including patient eligibility and adherence between the centralized and decentralized approaches. Methods Patient demographics and outcomes were compared between those screened with a centralized and decentralized approach and between adherent and nonadherent patients using two-sample t tests, χ 2 tests, or analyses of variance, as appropriate. Annual adherence analysis was conducted using data from patients who remained eligible for screening with a baseline Lung CT Screening Reporting and Data System (Lung-RADS) score of 1 or 2. Logistic regression was used to estimate the association between adherence and the primary exposure, adjusting for potential confounders. Results A cohort of 1,117 patients underwent baseline low-dose CT imaging. Two hundred eleven patients (19%) were ineligible by United States Preventative Services Task Force criteria and most (90%) were screened with the decentralized approach. After exclusions, 765 patients with Lung-RADS score of 1 or 2 remained eligible for annual screening. Overall adherence was 56%; however, adherence in the centralized program was 70%, compared with 41% with the decentralized approach (P Interpretation Those screened using a centralized approach were more likely to meet eligibility criteria for LCS and more likely to return for annual screening than those screened using a decentralized approach.

Veterans suffer disproportionate health impacts from the opioid epidemic, including overdose, suicide, and death. Prediction models based on electronic medical record data can be powerful tools for identifying patients at greatest risk of such outcomes. The Veterans Health Administration implemented the Stratification Tool for Opioid Risk Mitigation (STORM) in 2018. In this study we propose changes to the original STORM model and propose alternative models that improve risk prediction performance. The best of these proposed models uses a multivariate generalized linear mixed modeling (mGLMM) approach to produce separate predictions for overdose and suicide-related events (SRE) rather than a single prediction for combined outcomes. Further improvements include incorporation of additional data sources and new predictor variables in a longitudinal setting. Compared to a modified version of the STORM model with the same outcome, predictor and interaction terms, our proposed model has a significantly better prediction performance in terms of AUC (84% vs. 77%) and sensitivity (71% vs. 66%). The mGLMM performed particularly well in identifying patients at risk for SREs, where 72% of actual events were accurately predicted among patients with the 100,000 highest risk scores compared with 49.7% for the modified STORM model. The mGLMM’s strong performance in identifying true cases (sensitivity) among this highest risk group was the most important improvement given the model’s primary purpose for accurately identifying patients at most risk for adverse outcomes such that they are prioritized to receive risk mitigation interventions. Some predictors in the proposed model have markedly different associations with overdose and suicide risks, which will allow clinicians to better target interventions to the most relevant risks. Supplementary Information The online version contains supplementary material available at 10.1007/s10742-021-00263-7.

BACKGROUND: Over decades, there have been several alterations to cigarettes, including the addition of filters and flavoring. However, lung cancer remains the leading cause of cancer-related death in the United States. RESEARCH QUESTION: The aim of this study was to examine the association of type of cigarette on nicotine dependence in the setting of lung cancer screening. STUDY DESIGN AND METHODS: This study is a secondary analysis of the American College of Radiology Imaging Network arm of the National Lung Screening Trial. Tobacco dependence was evaluated by using the Fagerstrӧm Test for Nicotine Dependence, the Heaviness of Smoking Index, and time to first cigarette. Clinical outcomes, including nicotine dependence and tobacco abstinence, were assessed with descriptive statistics and χ(2) tests, stratified according to cigarette tar level, flavor, and filter. Logistic regression was used to study the influence of variables on smoking abstinence. RESULTS: More than one-third of individuals presenting for lung cancer screening are highly addicted to nicotine and smoke within 5 min of waking up. Smokers of unfiltered cigarettes were more nicotine dependent compared with filtered cigarette smokers (OR, 1.32; P < .01). Although smokers of light/ultralight cigarettes had lower dependence (OR, 0.76, P < .0001), there was no difference in smoking abstinence compared with regular cigarette smokers. There was no difference in outcomes when comparing smokers of menthol vs unflavored cigarettes. INTERPRETATION: In a screening population, the type of cigarette smoked is associated with different levels of dependence. Eliciting type of cigarette and time to first cigarette has the potential to allow for tailored tobacco treatment interventions within this context.

Background Adherence to annual low-dose CT was 95% in the National Lung Screening Trial and must be replicated to achieve mortality benefit from screening. Research Question How do we determine adherence rates within the Veterans Affairs Lung Cancer Screening Demonstration Project and identify factors predictive of adherence? Study Design and Methods A secondary data analysis of the Lung Cancer Screening Demonstration Project that was conducted at eight Veterans Affairs medical centers was performed to determine adherence to follow up imaging and to determine factors predictive of adherence. Results A total of 2,103 patients were screened. The adherence to screening from baseline scan (T0) to first follow-up scan (T1) was 82.2% and 65.2% from T1 to second follow-up scan (T2). Logistic regression modeling showed that presence of a nodule and the site of lung cancer screening were predictive of adherence. After three rounds of screening, 1,343 patients (64%) who underwent baseline screening underwent both subsequent annual low-dose CT scans; 225 patients (11%) had only one subsequent low-dose CT; 0.4% did not have a T1 scan but did have a T2 scan; 70 patients (3%) died, and 36 patients (1.7%) were diagnosed with lung cancer. There was significant variation in screening adherence across the eight sites, which ranged from 63% to 94% at T1 and 52% to 82% at T2 (P Interpretation Despite a centralized program design with dedicated navigator and registry to assist with adherence to annual lung cancer screening, variations between sites suggest that active follow-up strategies are needed to optimize adherence. For the mortality benefit from lung cancer screening to be recognized, adherence to annual screening must achieve higher rates.

Objective Veterans suffer disproportionately from the combined adverse health impacts of chronic pain and hazardous opioid use. This evaluation involved a substance use treatment program that included medication for opioid use disorder (SATP-MOUD) in a large metro-area Veterans Health Administration (VHA). This form of treatment has become increasingly important during the opioid crisis and is among several important Department of Veteran's Affairs (VA) initiatives to improve treatment for opioid use disorder (OUD), for which chronic pain is often a comorbid condition. Methods We compared clinical measures related to substance use and mental health between groups who were considered either engaged or not engaged in completing treatment. The study used propensity score matching methods and Cox proportional hazards models to compare the mortality risk for treated and untreated veterans who had chronic pain with concurrent opioid use. Results We identified 1559 SATP-MOUD patients with 1 year of pre- and post-treatment follow-time. From those with chronic pain and concurrent opioid use, we matched 478 SATP-MOUD patients to 647 untreated patients. Engaged patients (at least 4 visits in the first 8 weeks of treatment) had significant improvements in Brief Addiction Monitor (BAM) scores and in PHQ-9 depression screening scores compared to those who started treatment but did not meet the engagement threshold. In Cox proportional hazards analysis, participation in SATP-MOUD was associated with a 38% lower mortality risk among veterans with chronic pain and opioid use when compared to the untreated group: (HR: 0.62, 95% CI: 0.47, 0.82). Conclusions SATP-MOUD, as delivered in actual practice, was associated with significant improvements in depression and addiction severity scores, and was associated with reduced mortality risk for veterans with chronic pain and OUD.

This study uses data from the National Lung Screening Trial to investigate the association of cigarette tar level, flavor, and filter status with lung cancer diagnosis, mortality, and all-cause mortality.