High Blood Pressure in Children Aged 3 to 12 Years Old With Overweight or Obesity.

Objective: (1) To describe the prevalence of high blood pressure (BP) and the association with BMI in young children with overweight/obesity; (2) to evaluate the accuracy of a single high BP to diagnose sustained hypertension over three visits. Methods: We used pre-intervention data from the Improving Pediatric Obesity Practice Using Prompts (iPOP-UP) trial. We included children aged 3-12 years with BMI ≥85th percentile at well-visits in 2019-2021 at 84 primary care practices in 3 US health systems in the Northeast, Midwest, and South. BP percentiles were calculated from the first visit with BP recorded during the study period. Hypertensive-range BP was defined by the 2017 American Academy of Pediatrics guideline. We tested the association between BMI classification and hypertensive BP using multivariable logistic regression. Results: Of 78,280 children with BMI ≥85th percentile, 76,214 (97%) had BP recorded during the study period (mean 7.4 years, 48% female, 53% with overweight, and 13% with severe obesity). The prevalence of elevated or hypertensive BP was 31%, including 27% in children with overweight and 33%, 39%, and 49% with class I, II, and III obesity, respectively. Higher obesity severity was associated with higher odds of hypertensive BP in the multivariable model. Stage 2 hypertensive BP at the initial visit had specificity of 99.1% (95% confidence interval 98.9-99.3) for detecting sustained hypertension over ≥3 visits. Conclusions: High BP is common in 3- to 12-year-olds with overweight/obesity, with higher obesity severity associated with greater hypertension. Children with overweight/obesity and stage 2 BP are likely to have sustained hypertension and should be prioritized for evaluation. Trial Registration: ClinicalTrials.gov Identifier: NCT05627011.

Assessing readiness to use electronic health record data for outcome ascertainment in clinical trials - A case study.

BACKGROUND: Variable data quality poses a challenge to using electronic health record (EHR) data to ascertain acute clinical outcomes in multi-site clinical trials. Differing EHR platforms and data comprehensiveness across clinical trial sites, especially if patients received care outside of the clinical site's network, can also affect validity of results. Overcoming these challenges requires a structured approach. METHODS: We propose a framework and create a checklist to assess the readiness of clinical sites to contribute EHR data to a clinical trial for the purpose of outcome ascertainment, based on our experience with the Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) study, which enrolled 5451 participants in 86 primary care practices across 10 healthcare systems (sites). RESULTS: The site readiness checklist includes assessment of the infrastructure (i.e., size and structure of the site's healthcare system or clinical network), data procurement (i.e., quality of the data), and cost of obtaining study data. The checklist emphasizes the importance of understanding how data are captured and integrated across a site's catchment area and having a protocol in place for data procurement to ensure consistent and uniform extraction across each site. CONCLUSIONS: We suggest rigorous, prospective vetting of the data quality and infrastructure of each clinical site before launching a multi-site trial dependent on EHR data. The proposed checklist serves as a guiding tool to help investigators ensure robust and unbiased data capture for their clinical trials. ORIGINAL TRIAL REGISTRATION NUMBER: NCT02475850.

Integrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality.

BACKGROUNDPatients hospitalized for COVID-19 exhibit diverse clinical outcomes, with outcomes for some individuals diverging over time even though their initial disease severity appears similar to that of other patients. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity.METHODSWe performed deep immunophenotyping and conducted longitudinal multiomics modeling, integrating 10 assays for 1,152 Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) study participants and identifying several immune cascades that were significant drivers of differential clinical outcomes.RESULTSIncreasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, formation of neutrophil extracellular traps, and T cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma Igs and B cells and dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to failure of viral clearance in patients with fatal illness.CONCLUSIONOur longitudinal multiomics profiling study revealed temporal coordination across diverse omics that potentially explain the disease progression, providing insights that can inform the targeted development of therapies for patients hospitalized with COVID-19, especially those who are critically ill.TRIAL REGISTRATIONClinicalTrials.gov NCT04378777.FUNDINGNIH (5R01AI135803-03, 5U19AI118608-04, 5U19AI128910-04, 4U19AI090023-11, 4U19AI118610-06, R01AI145835-01A1S1, 5U19AI062629-17, 5U19AI057229-17, 5U19AI125357-05, 5U19AI128913-03, 3U19AI077439-13, 5U54AI142766-03, 5R01AI104870-07, 3U19AI089992-09, 3U19AI128913-03, and 5T32DA018926-18); NIAID, NIH (3U19AI1289130, U19AI128913-04S1, and R01AI122220); and National Science Foundation (DMS2310836).

A Bayesian platform trial design with hybrid control based on multisource exchangeability modelling.

Enrolling patients to the standard of care (SOC) arm in randomized clinical trials, especially for rare diseases, can be very challenging due to the lack of resources, restricted patient population availability, and ethical considerations. As the therapeutic effect for the SOC is often well documented in historical trials, we propose a Bayesian platform trial design with hybrid control based on the multisource exchangeability modelling (MEM) framework to harness historical control data. The MEM approach provides a computationally efficient method to formally evaluate the exchangeability of study outcomes between different data sources and allows us to make better informed data borrowing decisions based on the exchangeability between historical and concurrent data. We conduct extensive simulation studies to evaluate the proposed hybrid design. We demonstrate the proposed design leads to significant sample size reduction for the internal control arm and borrows more information compared to competing Bayesian approaches when historical and internal data are compatible.

Validation of a Rule-Based ICD-10-CM Algorithm to Detect Fall Injuries in Medicare Data.

BACKGROUND: Diagnosis-code-based algorithms to identify fall injuries in Medicare data are useful for ascertaining outcomes in interventional and observational studies. However, these algorithms have not been validated against a fully external reference standard, in ICD-10-CM, or in Medicare Advantage (MA) data. METHODS: We linked self-reported fall injuries leading to medical attention (FIMA) from the Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) trial (reference standard) to Medicare fee-for-service (FFS) and MA data from 2015-2019. We measured the area under the receiver operating characteristic curve (AUC) based on sensitivity and specificity of a diagnosis-code-based algorithm against the reference standard for presence or absence of ≥1 FIMA within a specified window of dates, varying the window size to obtain points on the curve. We stratified results by source (FFS versus MA), trial arm (intervention versus control), and STRIDE's ten participating healthcare systems. RESULTS: Both reference standard data and Medicare data were available for 4941 (of 5451) participants. The reference standard and algorithm identified 2054 and 2067 FIMA, respectively. The algorithm had 45% sensitivity (95% confidence interval [CI], 43%-47%) and 99% specificity (95% CI, 99%-99%) to identify reference standard FIMA within the same calendar month. The AUC was 0.79 (95% CI, 0.78-0.81) and was similar by FFS or MA data source or trial arm, but showed variation among STRIDE healthcare systems (AUC range by healthcare system, 0.71 to 0.84). CONCLUSIONS: An ICD-10-CM algorithm to identify fall injuries demonstrated acceptable performance against an external reference standard, in both MA and FFS data.

Association Between Rental Assistance Programs and Undiagnosed Diabetes Among U.S.

BACKGROUND: Rental assistance programs have been linked to better housing quality, stability, healthcare access, and reduced likelihood of uncontrolled diabetes. However, its direct association with diabetes screening is uncertain. OBJECTIVE: To determine whether federal rental assistance programs are associated with lower odds of undiagnosed diabetes. DESIGN: We used a quasi-experimental approach, comparing outcomes among adults receiving rental assistance to those who entered assisted housing within 2 years after their health data were collected. We test the a priori hypothesis that rental assistance will be associated with decreased odds of undiagnosed diabetes. PARTICIPANTS: Participants in the National Health and Nutrition Examination Survey 1999-2018 who received rental assistance and who had diabetes. INTERVENTION: Current rental assistance participation, including specific housing programs. MAIN MEASURES: Undiagnosed diabetes based on having hemoglobin A1c ≥ 6.5% but answering no to the survey question of being diagnosed with diabetes. KEY RESULTS: Among 435 eligible adults (median age 54.5 years, female 68.5%, non-Hispanic white 32.5%), 80.7% were receiving rental assistance programs at the time of the interview, and 19.3% went on to receive rental assistance within 2 years. The rates of undiagnosed diabetes were 15.0% and 25.3% among those receiving rental assistance programs vs. those in the future assistance group (p-value = 0.07). In an adjusted logistic regression model, adults receiving rental assistance had lower odds of undiagnosed diabetes (OR 0.52, 95% CI 0.28-0.94) than those in future assistance groups. Sex, race and ethnic group, educational level, and poverty ratio were not significantly associated with having undiagnosed diabetes, but individuals aged 45-64 years had significantly lower odds of undiagnosed diabetes (OR 0.21, 95% CI 0.08-0.53) compared with those aged 18-44. CONCLUSIONS: Rental assistance was linked to lower odds of undiagnosed diabetes, suggesting that affordable housing programs can aid in early recognition and diagnosis, which may improve long-term outcomes.

Association between diet quality and ovarian cancer risk and survival.

BACKGROUND: Research on diet quality and ovarian cancer is limited. We examined the association between diet quality and ovarian cancer risk and survival in a large prospective cohort. METHODS: We utilized data from women in the prospective NIH-AARP Diet and Health Study enrolled from 1995-1996 and were 50-71 years old at baseline with follow-up through 12/31/2017. Participants completed a 124-item Food Frequency Questionnaire at baseline and diet quality was assessed via the Healthy Eating Index-2015 (HEI-2015), the alternate Mediterranean diet score (aMED), and the Dietary Approaches to Stop Hypertension score (DASH). Primary outcomes were first primary epithelial ovarian cancer diagnosis from cancer registry data, and among those diagnosed with ovarian cancer all-cause mortality. We used a semi-Markov multi-state model with Cox proportional hazards regression to account for semi-competing events. RESULTS: Among 150,643 participants with a median follow-up time of 20.5 years, 1,107 individuals were diagnosed with a first primary epithelial ovarian cancer. There was no evidence of an association between diet quality and ovarian cancer risk. Among those diagnosed with epithelial ovarian cancer, 893 deaths occurred with a median survival of 2.5 years. Better pre-diagnosis diet quality, according to the HEI-2015 (Quintile 5 vs Quintile 1 HR = 0.75 [0.60-0.93]) and aMED (Quintile 5 vs Quintile 1: HR = 0.68, [0.53-0.87]) was associated with lower all-cause mortality. There was no evidence of an association between DASH and all-cause mortality. CONCLUSIONS: Better pre-diagnosis diet quality was associated with lower all-cause mortality after ovarian cancer diagnosis, but was not associated with ovarian cancer risk.

Hierarchical Bayesian modeling of heterogeneous outcome variance in cluster randomized trials.

BACKGROUND: Heterogeneous outcome correlations across treatment arms and clusters have been increasingly acknowledged in cluster randomized trials with binary endpoints, where analytical methods have been developed to study such heterogeneity. However, cluster-specific outcome variances and correlations have yet to be studied for cluster randomized trials with continuous outcomes. METHODS: This article proposes models fitted in the Bayesian setting with hierarchical variance structure to quantify heterogeneous variances across clusters and explain it with cluster-level covariates when the outcome is continuous. The models can also be extended to analyzing heterogeneous variances in individually randomized group treatment trials, with arm-specific cluster-level covariates, or in partially nested designs. Simulation studies are carried out to validate the performance of the newly introduced models across different settings. RESULTS: Simulations showed that overall the newly introduced models have good performance, reporting low bias and approximately 95% coverage for the intraclass correlation coefficients and regression parameters in the variance model. When variances are heterogeneous, our proposed models had improved model fit over models with homogeneous variances. When used to analyze data from the Kerala Diabetes Prevention Program study, our models identified heterogeneous variances and intraclass correlation coefficients across clusters and examined cluster-level characteristics associated with such heterogeneity. CONCLUSION: We proposed new hierarchical Bayesian variance models to accommodate cluster-specific variances in cluster randomized trials. The newly developed methods inform the understanding of how an intervention strategy is implemented and disseminated differently across clusters and can help improve future trial design.

Group sequential two-stage preference designs.

The two-stage preference design (TSPD) enables inference for treatment efficacy while allowing for incorporation of patient preference to treatment. It can provide unbiased estimates for selection and preference effects, where a selection effect occurs when patients who prefer one treatment respond differently than those who prefer another, and a preference effect is the difference in response caused by an interaction between the patient's preference and the actual treatment they receive. One potential barrier to adopting TSPD in practice, however, is the relatively large sample size required to estimate selection and preference effects with sufficient power. To address this concern, we propose a group sequential two-stage preference design (GS-TSPD), which combines TSPD with sequential monitoring for early stopping. In the GS-TSPD, pre-planned sequential monitoring allows investigators to conduct repeated hypothesis tests on accumulated data prior to full enrollment to assess study eligibility for early trial termination without inflating type I error rates. Thus, the procedure allows investigators to terminate the study when there is sufficient evidence of treatment, selection, or preference effects during an interim analysis, thereby reducing the design resource in expectation. To formalize such a procedure, we verify the independent increments assumption for testing the selection and preference effects and apply group sequential stopping boundaries from the approximate sequential density functions. Simulations are then conducted to investigate the operating characteristics of our proposed GS-TSPD compared to the traditional TSPD. We demonstrate the applicability of the design using a study of Hepatitis C treatment modality.

The design and baseline characteristics for the HOPE Consortium Trial to reduce pain and opioid use in hemodialysis.

The HOPE Consortium Trial to Reduce Pain and Opioid Use in Hemodialysis (HOPE Trial) is a multicenter randomized trial addressing chronic pain among patients receiving maintenance hemodialysis for end-stage kidney disease. The trial uses a sequential, multiple assignment design with a randomized component for all participants (Phase 1) and a non-randomized component for a subset of participants (Phase 2). During Phase 1, participants are randomized to Pain Coping Skills Training (PCST), an intervention designed to increase self-efficacy for managing pain, or Usual Care. PCST consists of weekly, live, coach-led cognitive behavioral therapy sessions delivered by video- or tele-conferencing for 12 weeks followed by daily interactive voice response sessions delivered by telephone for an additional 12 weeks. At 24 weeks (Phase 2), participants in both the PCST and Usual Care groups taking prescription opioid medications at an average dose of ≥20 morphine milligram equivalents per day are offered buprenorphine, a partial opioid agonist with a more favorable safety profile than full-agonist opioids. All participants are followed for 36 weeks. The primary outcome is pain interference ascertained, for the primary analysis, at 12 weeks. Secondary outcomes include additional patient-reported measures and clinical outcomes including falls, hospitalizations, and death. Exploratory outcomes include acceptability, tolerability, and efficacy of buprenorphine. The enrollment target of 640 participants was met 27 months after trial initiation. The findings of the trial will inform the management of chronic pain, a common and challenging issue for patients treated with maintenance hemodialysis. NCT04571619.

Estimating Surveillance Bias in Child Maltreatment Reporting During Home Visiting Program Involvement.

It is unclear if surveillance bias (increased reports to Child Protective Services [CPS] related to program involvement) has a substantial impact on evaluation of home visiting (HV) prevention programs. We estimated surveillance bias using data from Connecticut's HV program, birth certificates, CPS, and hospitals. Using propensity score matching, we identified 15,870 families similar to 4015 HV families. The difference-in-differences approach was used to estimate surveillance bias as the change in investigated reports from the last 6 months of program involvement to the next 6 months. The median age of the children at program exit was 1.2 years (range: 60 days, 5 years). We estimated that 25.6% of investigated reports in the HV group resulted from surveillance bias. We reviewed CPS reports of 194 home-visited families to determine if a home visitor made the report and found that 10% were directly from home visitors. Program evaluations should account for surveillance bias.

A compressed large language model embedding dataset of ICD 10 CM descriptions.

This paper presents novel datasets providing numerical representations of ICD-10-CM codes by generating description embeddings using a large language model followed by a dimension reduction via autoencoder. The embeddings serve as informative input features for machine learning models by capturing relationships among categories and preserving inherent context information. The model generating the data was validated in two ways. First, the dimension reduction was validated using an autoencoder, and secondly, a supervised model was created to estimate the ICD-10-CM hierarchical categories. Results show that the dimension of the data can be reduced to as few as 10 dimensions while maintaining the ability to reproduce the original embeddings, with the fidelity decreasing as the reduced-dimension representation decreases. Multiple compression levels are provided, allowing users to choose as per their requirements, download and use without any other setup. The readily available datasets of ICD-10-CM codes are anticipated to be highly valuable for researchers in biomedical informatics, enabling more advanced analyses in the field. This approach has the potential to significantly improve the utility of ICD-10-CM codes in the biomedical domain.

Integrated longitudinal multi-omics study identifies immune programs associated with COVID-19 severity and mortality in 1152 hospitalized participants.

Hospitalized COVID-19 patients exhibit diverse clinical outcomes, with some individuals diverging over time even though their initial disease severity appears similar. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity. In this study, we carried out deep immunophenotyping and conducted longitudinal multi-omics modeling integrating ten distinct assays on a total of 1,152 IMPACC participants and identified several immune cascades that were significant drivers of differential clinical outcomes. Increasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, NETosis, and T-cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma immunoglobulins and B cells, as well as dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to the failure of viral clearance in patients with fatal illness. Our longitudinal multi-omics profiling study revealed novel temporal coordination across diverse omics that potentially explain disease progression, providing insights that inform the targeted development of therapies for hospitalized COVID-19 patients, especially those critically ill.

Facilitation and Preferred Models for Delivering Substance Use Disorder Treatment in HIV Clinics: Results From a Multisite Randomized Trial.

BACKGROUND: Integrated addiction treatment in HIV clinics is associated with improved outcomes, yet it is offered inconsistently and with variable models of care. We sought to evaluate the impact of Implementation Facilitation ("Facilitation") on clinician and staff preference for provision of addiction treatment in HIV clinics with on-site resources (all trained or designated on-site specialist) versus outside resources (outside specialist or refer out). METHODS: From July 2017 to July 2020, surveys assessed clinician and staff preferences for addiction treatment models during control (ie, baseline), intervention, evaluation, and maintenance phases in 4 HIV clinics in the Northeast United States. RESULTS: During the control phase, among 76 respondents (response rate, 58%), the proportions who preferred treatment with on-site resources for opioid use disorder (OUD), alcohol use disorder (AUD), and tobacco use disorder (TUD) were 63%, 55%, and 63%, respectively. Compared with control, there were no significant differences in preferred model during the intervention and evaluation phases except for AUD where there was an increased preference for treatment with on-site resources in the intervention versus control phase. Compared with control, during the maintenance phase, a higher proportion of clinicians and staff preferred providing addiction treatment with on-site resources versus outside resources: OUD, 75% (odds ratio [OR; 95% confidence interval {CI}], 1.79 [1.06-3.03]); AUD, 73% (OR [95% CI], 2.23 [1.36-3.65]), and TUD, 76% (OR [95% CI], 1.88 [1.11-3.18]). CONCLUSIONS: The findings from this study lend support for "Facilitation" as a strategy to enhance clinician and staff preference for integrated addiction treatment in HIV clinics with on-site resources.

Alcohol Use and Sustained Virologic Response to Hepatitis C Virus Direct-Acting Antiviral Therapy.

Importance: Some payers and clinicians require alcohol abstinence to receive direct-acting antiviral (DAA) therapy for chronic hepatitis C virus (HCV) infection. Objective: To evaluate whether alcohol use at DAA treatment initiation is associated with decreased likelihood of sustained virologic response (SVR). Design, Setting, and Participants: This retrospective cohort study used electronic health records from the US Department of Veterans Affairs (VA), the largest integrated national health care system that provides unrestricted access to HCV treatment. Participants included all patients born between 1945 and 1965 who were dispensed DAA therapy between January 1, 2014, and June 30, 2018. Data analysis was completed in November 2020 with updated sensitivity analyses performed in 2023. Exposure: Alcohol use categories were generated using responses to the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire and International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses for alcohol use disorder (AUD): abstinent without history of AUD, abstinent with history of AUD, lower-risk consumption, moderate-risk consumption, and high-risk consumption or AUD. Main Outcomes and Measures: The primary outcome was SVR, which was defined as undetectable HCV RNA for 12 weeks or longer after completion of DAA therapy. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% CIs of SVR associated with alcohol category. Results: Among 69 229 patients who initiated DAA therapy (mean [SD] age, 62.6 [4.5] years; 67 150 men [97.0%]; 34 655 non-Hispanic White individuals [50.1%]; 28 094 non-Hispanic Black individuals [40.6%]; 58 477 individuals [84.5%] with HCV genotype 1), 65 355 (94.4%) achieved SVR. A total of 32 290 individuals (46.6%) were abstinent without AUD, 9192 (13.3%) were abstinent with AUD, 13 415 (19.4%) had lower-risk consumption, 3117 (4.5%) had moderate-risk consumption, and 11 215 (16.2%) had high-risk consumption or AUD. After adjustment for potential confounding variables, there was no difference in SVR across alcohol use categories, even for patients with high-risk consumption or AUD (OR, 0.95; 95% CI, 0.85-1.07). There was no evidence of interaction by stage of hepatic fibrosis measured by fibrosis-4 score (P for interaction = .30). Conclusions and Relevance: In this cohort study, alcohol use and AUD were not associated with lower odds of SVR. Restricting access to DAA therapy according to alcohol use creates an unnecessary barrier to patients and challenges HCV elimination goals.

Effect of Exercise on Chemotherapy-Induced Peripheral Neuropathy Among Patients Treated for Ovarian Cancer: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Chemotherapy-induced peripheral neuropathy (CIPN), one of the most common and severe adverse effects of chemotherapy, is associated with worse quality of life among survivors of ovarian cancer. Currently, there is no effective treatment for CIPN. Objective: To evaluate the effect of a 6-month aerobic exercise intervention vs attention-control on CIPN among women treated for ovarian cancer in the Women's Activity and Lifestyle Study in Connecticut (WALC) to provide evidence to inform the guidelines and recommendations for prevention or treatment of CIPN. Design, Setting, and Participants: This prespecified secondary analysis evaluated the Women's Activity and Lifestyle Study in Connecticut (WALC), a multicentered, open-label, population-based, phase 3 randomized clinical trial of an aerobic exercise intervention vs attention control for CIPN in patients who were diagnosed with ovarian cancer. Only WALC participants who received chemotherapy were included in this analysis. Participants were randomized 1:1 to either a 6-month aerobic exercise intervention or to attention control. All analyses were conducted between September 2022 and January 2023. Interventions: The exercise intervention consisted of home-based moderate-intensity aerobic exercise facilitated by weekly telephone counseling from an American College of Sports Medicine/American Cancer Society-certified cancer exercise trainer. Attention control involved weekly health education telephone calls from a WALC staff member. Main Outcomes and Measure: Change in CIPN was the primary outcome in this secondary analysis. This outcome was represented by CIPN severity, which was self-measured by participants at baseline and 6 months using the Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity scale, with a score range of 0 to 44. A mixed-effects model was used to assess the 6-month change in CIPN between the exercise intervention and attention control arms. Results: Of the 134 participants (all females; mean [SD] age, 57.5 [8.3] years) included in the analysis, 69 were in the exercise intervention arm and 65 were in the attention control arm. The mean (SD) time since diagnosis was 1.7 (1.0) years. The mean (SD) baseline CIPN scores were 8.1 (5.6) in the exercise intervention arm and 8.8 (7.9) in the attention control arm (P = .56). At 6 months, the self-reported CIPN score was reduced by 1.3 (95% CI, -2.3 to -0.2) points in the exercise intervention arm compared with an increase of 0.4 (95% CI, -0.8 to 1.5) points in the attention control arm. The between-group difference was -1.6 (95% CI, -3.1 to -0.2) points. The point estimate was larger among the 127 patients with CIPN symptoms at enrollment (-2.0; 95% CI, -3.6 to -0.5 points). Conclusions and Relevance: Findings of this secondary analysis of the WALC trial indicate that a 6-month aerobic exercise intervention vs attention control significantly improved self-reported CIPN among patients who were treated for ovarian cancer. While replication of the findings in other studies is warranted, incorporating referrals to exercise programs into standard oncology care could reduce CIPN symptoms and increase quality of life in patients with ovarian cancer. Trial Registration: ClinicalTrials.gov Identifier: NCT02107066.

Structural Racism, Lifestyle Behaviors, and Obesity-related Cancers among Black and Hispanic/Latino Adults in the United States: A Narrative Review.

One in three adults in the United States has obesity; a chronic disease that is implicated in the etiology of at least 14 cancers. Cancer is the leading cause of death among U.S. Hispanic/Latino adults and the second most common cause of death, after cardiovascular disease, for Black adults. Our country's legacy in overt discrimination (e.g., slavery, segregation) generated inequities across all spheres in which people function as defined by the socioecological model-biological, individual, community, structural-and two of the many areas in which it manifests today are the disproportionate burden of obesity and obesity-related cancers in populations of color. Inequities due to environmental, social, and economic factors may predispose individuals to poor lifestyle behaviors by hindering an individual's opportunity to make healthy lifestyles choices. In this review, we examined the evidence on obesity and the lifestyle guidelines for cancer prevention in relation to cancer risk and outcomes for Black and Hispanic/Latino adults. We also discussed the role of structural and societal inequities on the ability of these two communities to adopt and maintain healthful lifestyle behaviors in accordance with the lifestyle guidelines for cancer prevention and control.

Developing and testing a COVID-19 vaccination acceptance intervention: A pragmatic trial comparing vaccine acceptance intervention vs usual care - Rationale, methods, and implementation.

BACKGROUND: COVID-19 has resulted in significant disability and loss of life. COVID-19 vaccines effectively prevent severe illness, hospitalization, and death. Nevertheless, many people remain hesitant to accept vaccination. Veterans perceive healthcare providers (HCP) and staff as trusted vaccine information sources and thereby are well suited to initiate vaccine discussions. The overall objective of this study is to implement and test a virtual COVID-19 Vaccine Acceptance Intervention (VAI) training that is informed by motivational interviewing (MI) techniques. METHODS: The VAI training is being delivered to VA HCPs and staff within a Hybrid Type 2 pragmatic implementation-effectiveness trial using Implementation Facilitation as the implementation strategy. The implementation team includes external facilitators paired with VA Healthcare System (VAHCS)-level internal facilitators. The trial has three aims: 1) Examine the effectiveness of the VAI versus usual care on unvaccinated veterans' vaccination rates in a one-year cluster randomized controlled trial, with randomization at the level of VAHCS. 2) Determine factors associated with veterans' decisions to accept or decline primary COVID-19 vaccination, and better understand how these factors influence vaccination decisions, through survey and qualitative data; and 3) Use qualitative interviews with HCPs and staff from clinics with high and low vaccination rates to learn what was helpful and not helpful about the VAI and implementation strategies. CONCLUSION: This is the first multisite randomized controlled trial to test an MI-informed vaccine acceptance intervention to improve COVID-19 vaccine acceptance. Information gained can be used to inform healthcare systems' approaches to improve future vaccination and other public health campaigns. CLINICALTRIALS: gov Identifier: NCT05027464.

Design, implementation and preliminary results of a type-2 hybrid cluster-randomized trial of integrating screening and treatment for major depressive disorder into specialty clinics providing opioid agonist therapies in Ukraine.

INTRODUCTION: Ukraine has a high prevalence of co-occurring disorders (COD), defined as having both substance use (SUD) and psychiatric disorders. Major depressive disorder (MDD) is the most prevalent psychiatric disorder among people with SUD. People with COD experience poor health outcomes, and international agencies propose integrated COD care. In Ukraine, treatment for SUD is delivered in specialized substance use clinics, without providing any other medical services for comorbidities, including MDD. Here we present the protocol, along the with the preliminary results of the MEDIUM project, including observations over the first 6 months. METHODS: A cluster-randomized type-2 hybrid trial was conducted to integrate MDD treatment into specialty clinics providing opioid agonist therapies (OAT) in Ukraine. Twelve clinics in four regions underwent randomization to control (N = 1) vs experimental arms (N = 2) in each region. Clinicians at experimental sites received tele-education through modified project ECHO using a facilitated screening, evaluation, and treatment algorithm of depression, with or without financial incentives. Service-, patient- and provider-level data were collected for the analysis every 6 months for 24 months. PRELIMINARY RESULTS: For service delivery outcomes, 4421 patients enrolled on OAT across all sites were assessed for MDD for screening (76.7%), evaluation with diagnosis (43.5%) and treatment (30.7%) for MDD; 13.8% continued treatment at least for 6 months. For patient-level outcomes, 1345 patients and 54 providers participated in serial surveys every six months. CONCLUSION: This study will be the first to explore integrated COD care in Ukraine and generate evidence on effective service integration and delivery strategies for people with COD receiving treatment at substance use clinics with broader implications for Eastern Europe and Central Asia region.