Explore the vast range of titles available.

Background/Aims Evaluating heterogeneity of treatment effects (HTE) across subgroups is common in both randomized trials and observational studies. Although several statistical challenges of HTE analyses including low statistical power and multiple comparisons are widely acknowledged, issues specific to clustered data, including cluster randomized trials (CRTs), have received less attention. For testing interactions in linear mixed-effects models (LMM), Barr et al. (2013) suggested that: random slopes for interaction terms should be studied. In this paper, we explore the impact of model misspecification, including generalized LMM (GLMM) with or without random slopes, and provide recommendations for conducting inference for HTE across subgroups in CRTs. Methods We conducted a simulation study to evaluate the performance of common analytic approaches for testing the presence of HTE for continuous, binary, and count outcomes: generalized linear mixed models (GLMM) and generalized estimating equations (GEE) including interaction terms between treatment and subgroup. Several simulation scenarios covered broad range of scenarios in CRTs, for example, small to a large number of clusters, small to moderate cluster-specific random slopes for subgroup. The performance metric was the empirical type I error rate compared to a nominal level. We applied the analytical methods to a real-world CRT using the count outcome utilization of healthcare from the motivating Primary Care Opioid Use Disorder treatment (PROUD) trial. Results We found that standard GLMM analyses that assume a common correlation of participants within clusters can lead to severely elevated type 1 error rates of up to 47.2% compared to the 5% nominal level if the within-cluster correlation varies across subgroups. A maximal GLMM, which allows subgroup-specific within-cluster correlations, achieved the nominal type 1 error rate, as did GEE (though rates were slightly elevated even with as many as 50 clusters). Applying the methods to the real-world CRT, we found a large impact of the model specification on inference. Conclusions We recommend that HTE analyses using the maximal GLMM account for within-subgroup correlation to avoid anti-conservative inference. For Wald t-testing of HTE in small sample clusters, appropriate small sample correction methods should be considered based on the outcome data type.

BackgroundSelective or non-reporting of study outcomes results in outcome reporting bias.ObjectiveWe sought to develop and assess tools for detecting and adjusting for outcome reporting bias.DesignUsing data from a previously published systematic review, we abstracted whether outcomes were reported as collected, whether outcomes were statistically significant, and whether statistically significant outcomes were more likely to be reported. We proposed and tested a model to adjust for unreported outcomes and compared our model to three other methods (Copas, Frosi, trim and fill). Our approach assumes that unreported outcomes had a null intervention effect with variance imputed based on the published outcomes. We further compared our approach to these models using simulation, and by varying levels of missing data and study sizes.ResultsThere were 286 outcomes reported as collected from 47 included trials: 142 (48%) had the data provided and 144 (52%) did not. Reported outcomes were more likely to be statistically significant than those collected but for which data were unreported and for which non-significance was reported (RR, 2.4; 95% CI, 1.9 to 3.0). Our model and the Copas model provided similar decreases in the pooled effect sizes in both the meta-analytic data and simulation studies. The Frosi and trim and fill methods performed poorly.LimitationsSingle intervention of a single disease with only randomized controlled trials; approach may overestimate outcome reporting bias impact.ConclusionThere was evidence of selective outcome reporting. Statistically significant outcomes were more likely to be published than non-significant ones. Our simple approach provided a quick estimate of the impact of unreported outcomes on the estimated effect. This approach could be used as a quick assessment of the potential impact of unreported outcomes.

Telemedicine provides patients access to episodic and longitudinal care. Policy discussions surrounding future support for telemedicine require an understanding of factors associated with successful video visits. To assess patient and clinician factors associated with successful and with failed video visits. This was a quality improvement study of 137 846 scheduled video visits at a single academic health system in southeastern Wisconsin between March 1 and December 31, 2020, supplemented with patient experience survey data. Patient information was gathered using demographic information abstracted from the electronic health record and linked with block-level socioeconomic data from the US Census Bureau. Data on perceived clinician experience with technology was obtained using the survey. The primary outcome of interest was the successful completion of a scheduled video visit or the conversion of the video visit to a telephone-based service. Visit types and administrative data were used to categorize visits. Mixed-effects modeling with pseudo R2 values was performed to compare the relative associations of patient and clinician factors with video visit failures. In total, 75 947 patients and 1155 clinicians participated in 137 846 scheduled video encounters, 17 190 patients (23%) were 65 years or older, and 61 223 (81%) patients were of White race and ethnicity. Of the scheduled video encounters, 123 473 (90%) were successful, and 14 373 (10%) were converted to telephone services. A total of 16 776 patients (22%) completed a patient experience survey. Lower clinician comfort with technology (odds ratio [OR], 0.15; 95% CI, 0.08-0.28), advanced patient age (66-80 years: OR, 0.28; 95% CI, 0.26-0.30), lower patient socioeconomic status (including low high-speed internet availability) (OR, 0.85; 95% CI, 0.77-0.92), and patient racial and ethnic minority group status (Black or African American: OR, 0.75; 95% CI, 0.69-0.81) were associated with conversion to telephone visits. Patient characteristics accounted for systematic components for success; marginal pseudo R2 values decreased from 23% (95% CI, 21.1%-26.1%) to 7.8% (95% CI, 6.3%-9.4%) with exclusion of patient factors. As policy makers consider expanding telehealth coverage and hospital systems focus on investments, consideration of patient support, equity, and friction should guide decisions. In particular, this quality improvement study suggests that underserved patients may become disproportionately vulnerable by cuts in coverage for telephone-based services.

Background Declining incidence of gastric cancer in the USA has presumably resulted in lower rates of major gastrectomy for cancer. The impact on perioperative outcomes remains undefined. The aims of this study were to characterize national trends in frequency of major gastrectomy for cancer, identify factors associated with in-hospital mortality, and examine outcome disparities by race/ethnicity. Methods Nationwide inpatient sample data from 1993 to 2013 were queried for procedural and diagnostic codes (ICD-9) relating to total and partial gastrectomy procedures. Gastric resections for cancer were compared to those for peptic ulcer disease for reference. Patient demographics, comorbidity score, mortality, and hospital characteristics were recorded as covariates. Results A significant decrease in annual rates of partial and total gastrectomy was observed from 1993 to 2013 ( p  < 0.0001). The change in absolute number and percent decline was greater for partial gastrectomy (− 39.3%) than total gastrectomy (− 19%). There was a 34.0% decrease in gastrectomy for cancer in Whites and a 61.2% increase among Hispanic patients over two decades. In-hospital mortality also significantly decreased over the study period (7.7% to 2.7%). Factors associated with lower mortality rates included male sex and treatment at urban teaching hospitals. Analysis of trends revealed that gastrectomy for cancer was performed with increasing frequency at urban teaching hospitals. Conclusions The frequency of major gastric resections in the USA has declined over two decades. Overall, in-hospital mortality rates also have decreased significantly. Declining in-hospital mortality after gastrectomy for cancer is associated with more frequent treatment at urban teaching hospitals.

INTRODUCTION Poor representation of racial/ethnic minority groups limits the validity and generalizability of clinical trials and contributes to inequities in medicine and science. OBJECTIVES To recruit a multicultural sample of mid‐life individuals using multiple recruitment modalities for a randomized controlled trial of diet and cognition comparing an anti‐inflammatory dietary intervention versus usual diet and the effect on cognition. METHODS This study describes the utility of various modalities to recruit a multi‐cultural cohort. Recruitment techniques, the success rate of each, and characteristics of participants are compared to representative Bronx U.S. Census statistics. Participants were identified in target communities using voter registration rolls paired with marketing lists and enriched patient lists extracted from electronic health records of mid‐life (40–65 years) adults in Bronx, New York. Outreach activities, including print and social media, supplemented these lists to promote the study. RESULTS Over 4 years of recruitment, invitation letters, followed by telephone calls, yielded the highest number of randomized recruits, with 80.5% of participants recruited prior to the pandemic and 90.1% during the pandemic. A total of 290 participants enrolled in proportion to the racial/ethnic breakdown of targeted Bronx communities. However, women were overrepresented compared to the overall Bronx population. Each recruitment modality had strengths and weaknesses. The combination resulted in reaching an important sector of the population that could benefit from interventions. Voter registration lists reached a broad spectrum of targeted communities and resulted in enrollment and randomization of the majority of participants. Online registries (e.g., ResearchMatch) and outreach activities yielded efficient enrollment. DISCUSSION Our multi‐pronged strategy led to successful enrollment of a multi‐cultural sample. Although the systematic list approach was the most productive, the importance of reaching out to community was crucial. Refining techniques of online registries, working with trusted community organizations, continuous assessment, and experimentation with other modalities may be helpful. Highlights ADRD affects US minority populations disproportionately. Multiple recruitment methods help engage the underrepresented in clinical trials. Use of voter registration and EHR lists allow recruiters to reach a wide and heterogenous audience. Letters followed by personal phone calls are effective in recruitment. Outreach to the community provides a person‐to‐person connection to the study

Kidney dysfunction is prevalent and impacts prognosis in patients with acute decompensated heart failure (ADHF). However, most previous reports were from a single hospital, limiting their generalizability. Also, contemporary data using new equation for estimated glomerular filtration rate (eGFR) are needed. We analyzed data from the ARIC Community Surveillance for ADHF conducted for residents aged ≥55 years in four US communities between 2005-2011. All ADHF cases (n = 5, 391) were adjudicated and weighted to represent those communities (24,932 weighted cases). The association of kidney function (creatinine-based eGFR by the CKD-EPI equation and blood urea nitrogen [BUN]) during hospitalization with 1-year mortality was assessed using logistic regression. Based on worst and last serum creatinine, there were 82.5% and 70.6% with reduced eGFR (<60 ml/min/1.73m2) and 37.4% and 26.6% with severely reduced eGFR (<30 ml/min/1.73m2), respectively. Lower eGFR (regardless of last or worst eGFR), particularly eGFR <30 ml/min/1.73m2, was significantly associated with higher 1-year mortality independently of potential confounders (odds ratio 1.60 [95% CI 1.26-2.04] for last eGFR 15-29 ml/min/1.73m2 and 2.30 [1.76-3.00] for <15 compared to eGFR ≥60). The association was largely consistent across demographic subgroups. Of interest, when both eGFR and BUN were modeled together, only BUN remained significant. Severely reduced eGFR (<30 ml/min/1.73m2) was observed in ~30% of ADHF cases and was an independent predictor of 1-year mortality in community. For prediction, BUN appeared to be superior to eGFR. These findings suggest the need of close attention to kidney dysfunction among ADHF patients.

Purpose Tobacco smoking and occupational exposures are the leading risk factors for developing urothelial bladder carcinoma (UBC), yet little is known about the contribution of these two factors to risk of UBC recurrence. We evaluated whether smoking status and usual adult occupation are associated with time to UBC recurrence for 406 patients with muscle-invasive bladder cancer submitted to The Cancer Genome Atlas (TCGA) project. Methods Kaplan–Meier and Cox proportional hazard methods were used to assess the association between smoking status, employment in a high-risk occupation for bladder cancer, occupational diesel exhaust exposure, and 2010 Standard Occupational Classification group and time to UBC recurrence. Results Data on time to recurrence were available for 358 patients over a median follow-up time of 15 months. Of these, 133 (37.2%) experienced a recurrence. Current smokers who smoked for more than 40 pack-years had an increased risk of recurrence compared to never smokers (HR 2.1, 95% CI 1.1, 4.1). Additionally, employment in a high-risk occupation was associated with a shorter time to recurrence (log-rank p  = 0.005). We found an increased risk of recurrence for those employed in occupations with probable diesel exhaust exposure (HR 1.8, 95% CI 1.1, 3.0) and for those employed in production occupations (HR 2.0, 95% CI 1.1, 3.6). Conclusions These findings suggest smoking status impacts risk of UBC recurrence, although several previous studies provided equivocal evidence regarding this association. In addition to the known causal relationship between occupational exposure and bladder cancer risk, our study suggests that occupation may also be related to increased risk of recurrence.

While patient interest in telehealth increases, clinicians' perspectives may influence longer-term adoption. We sought to identify facilitators and barriers to continued clinician incorporation of telehealth into practice. A cross-sectional 24-item web-based survey was emailed to 491 providers with ≥50 video visits (VVs) within an academic health system between 1 March 2020 and 31 December 2020. We quantitatively summarised the characteristics and perceptions of respondents by using descriptive and test statistics. We used systematic content analysis to qualitatively code open-ended responses, double coding at least 25%. 247 providers (50.3%) responded to the survey. Seventy-nine per cent were confident in their ability to deliver excellent clinical care through VV. In comparison, 48% were confident in their ability to troubleshoot technical issues. Most clinicians (87%) expressed various concerns about VV. Providers across specialties generally agreed that VV reduced infection risk (71%) and transportation barriers (71%). Three overarching themes in the qualitative data included infrastructure and training, usefulness and expectation setting for patients and providers. As healthcare systems plan for future delivery directions, they must address the tension between patients' and providers' expectations of care within the digital space. Telehealth creates new friction, one where the healthcare system must fit into the patient's life rather than the usual dynamic of the patient fitting into the healthcare system. Telehealth infrastructure and patient and clinician technological acumen continue to evolve. Clinicians in this survey offered valuable insights into the directions healthcare organisations can take to right-size this healthcare delivery modality.

Background Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored. Objective Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey. Participants Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019–9/12/2019; n  = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included. Main Measures We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies. Key Results Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C ( p -values < 0.001) and ranged from 12.7% (6.3–19.2%) and 0.9% (0.0–2.7%) for < monthly to 44.6% (41.4–47.7%) and 20.3% (17.8–22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey. Conclusions Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.

Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored. Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey. Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019-9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included. We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies. Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3-19.2%) and 0.9% (0.0-2.7%) for < monthly to 44.6% (41.4-47.7%) and 20.3% (17.8-22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey. Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD.