Dataset Information

Race and ethnicity do not impact eligibility for remdesivir: A single-center experience.

ABSTRACT: As the Coronavirus-2019 (COVID-19) pandemic continues, multiple therapies are rapidly being evaluated for efficacy in clinical trials. Clinical trials should be racially and ethnically representative of the population that will eventually benefit from these medications. There are multiple potential barriers to racial and ethnic minority enrollment in clinical trials, one of which could be that inclusion and exclusion criteria select for certain racial or ethnic groups disproportionately. In this observational cohort study at a single health care system, we examined if there were differences in eligibility for treatment with remdesivir based on clinical trial criteria for racial and ethnic minorities compared to non-Hispanic Whites. 201 electronic medical record charts were reviewed manually. Self-identified Whites were older than other racial or ethnic groups. At the time of presentation, Black, Latinx, and White participants met inclusion criteria for remdesivir at similar rates (72%, 80%, and 73% respectively), and exclusion criteria at similar rates (43%, 38% and 49% for Black, Latinx and White participants respectively). In this study, there was no difference in eligibility for remdesivir based on race or ethnicity alone.

SUBMITTER: Pischel L

PROVIDER: S-EPMC8101938 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Race and ethnicity do not impact eligibility for remdesivir: A single-center experience.

Pischel Lauren L Walelo Makeda M Benson Jemma J Osborn Rebecca R Schrier Rachel R Tuan Jessica J Barakat Lydia L Ogbuagu Onyema O

PloS one 20210506 5

As the Coronavirus-2019 (COVID-19) pandemic continues, multiple therapies are rapidly being evaluated for efficacy in clinical trials. Clinical trials should be racially and ethnically representative of the population that will eventually benefit from these medications. There are multiple potential barriers to racial and ethnic minority enrollment in clinical trials, one of which could be that inclusion and exclusion criteria select for certain racial or ethnic groups disproportionately. In this ...[more]

PMID: 33956849

Similar Datasets

Project description:ImportanceThe development of therapeutics for patients who are positive for specific human leukocyte antigen (HLA) subtypes evokes the question of whether certain racial and ethnic groups are more or less likely to be eligible for novel products.ObjectiveTo determine whether racial and ethnic inequities were present with regard to trial eligibility in trials investigating a therapeutic restricted to patients with specific HLA subtypes.Design, setting, and participantsThis cross-sectional study included all clinical trials registered in ClinicalTrials.gov through March 18, 2022, that investigated an interventional study of a therapeutic strategy and restricted participants to those with at least 1 HLA subtype. Data were analyzed from May 8 to July 1, 2022.Main outcomes and measuresThe type of therapeutics used in trials, the condition under study, the HLA subtypes used, and the likelihood of being enrolled in such a trial according to race and ethnicity.ResultsOf 2135 trials identified, 263 met inclusion criteria. Overall, the estimated likelihood of being eligible for an HLA-based trial was 50.3%. Individuals of African American descent had the lowest likelihood of eligibility (33.0%), while being an individual of European descent conferred the highest (53.0%; 1.6 times more likely than African American individuals). Most trials studied anticancer therapeutics (258 [98.1%; 95% CI, 96.4%-99.7%]), and most were a therapeutic vaccine (179 [68.1%; 95% CI, 62.4%-73.7%]). The HLA-A*02:01 allele and the HLA-A2 serotype were the most frequent HLA subtypes for trial eligibility. The frequency of the HLA-A*02:01 allele in the population varied, with 11.9% (95% CI, 11.8%-12.0%) in African or African American individuals and 27.1% (95% CI, 27.1%-27.1%) in individuals of European descent.Conclusions and relevanceThe findings of this cross-sectional study suggest that enrollment restrictions for clinical trials investigating novel HLA therapeutics may be associated with racial and ethnic inequities with regard to trial eligibility. Overcoming these restrictions poses biological challenges, but solutions must be implemented to provide equal access to innovative strategies regardless of race or ethnicity.

Project description:ImportanceUsing race and ethnicity in clinical prediction models can reduce or inadvertently increase racial and ethnic disparities in medical decisions.ObjectiveTo compare eligibility for lung cancer screening in a contemporary representative US population by refitting the life-years gained from screening-computed tomography (LYFS-CT) model to exclude race and ethnicity vs a counterfactual eligibility approach that recalculates life expectancy for racial and ethnic minority individuals using the same covariates but substitutes White race and uses the higher predicted life expectancy, ensuring that historically underserved groups are not penalized.Design, setting, and participantsThe 2 submodels composing LYFS-CT NoRace were refit and externally validated without race and ethnicity: the lung cancer death submodel in participants of a large clinical trial (recruited 1993-2001; followed up until December 31, 2009) who ever smoked (n = 39 180) and the all-cause mortality submodel in the National Health Interview Survey (NHIS) 1997-2001 participants aged 40 to 80 years who ever smoked (n = 74 842, followed up until December 31, 2006). Screening eligibility was examined in NHIS 2015-2018 participants aged 50 to 80 years who ever smoked. Data were analyzed from June 2021 to September 2022.ExposureIncluding and removing race and ethnicity (African American, Asian American, Hispanic American, White) in each LYFS-CT submodel.Main outcomes and measuresBy race and ethnicity: calibration of the LYFS-CT NoRace model and the counterfactual approach (ratio of expected to observed [E/O] outcomes), US individuals eligible for screening, predicted days of life gained from screening by LYFS-CT.ResultsThe NHIS 2015-2018 included 25 601 individuals aged 50 to 80 years who ever smoked (2769 African American, 649 Asian American, 1855 Hispanic American, and 20 328 White individuals). Removing race and ethnicity from the submodels underestimated lung cancer death risk (expected/observed [E/O], 0.72; 95% CI, 0.52-1.00) and all-cause mortality (E/O, 0.90; 95% CI, 0.86-0.94) in African American individuals. It also overestimated mortality in Hispanic American (E/O, 1.08, 95% CI, 1.00-1.16) and Asian American individuals (E/O, 1.14, 95% CI, 1.01-1.30). Consequently, the LYFS-CT NoRace model increased Hispanic American and Asian American eligibility by 108% and 73%, respectively, while reducing African American eligibility by 39%. Using LYFS-CT with the counterfactual all-cause mortality model better maintained calibration across groups and increased African American eligibility by 13% without reducing eligibility for Hispanic American and Asian American individuals.Conclusions and relevanceIn this study, removing race and ethnicity miscalibrated LYFS-CT submodels and substantially reduced African American eligibility for lung cancer screening. Under counterfactual eligibility, no one became ineligible, and African American eligibility increased, demonstrating the potential for maintaining model accuracy while reducing disparities.

Project description:ImportanceBlack and Hispanic US residents are disproportionately affected by stroke incidence, and patients with dual eligibility for Medicare and Medicaid may be predisposed to more severe strokes. Little is known about differences in stroke severity for individuals with dual eligibility, Black individuals, and Hispanic individuals, but understanding hospital admission stroke severity is the first important step for focusing strategies to reduce disparities in stroke care and outcomes.ObjectiveTo examine whether dual eligibility and race and ethnicity are associated with stroke severity in Medicare beneficiaries admitted to acute hospitals with ischemic stroke.Design, setting, and participantsThis retrospective cross-sectional study was conducted using Medicare claims data for patients with ischemic stroke admitted to acute hospitals in the United States from October 1, 2016, to November 30, 2017. Data were analyzed from July 2021 and January 2022.ExposuresDual enrollment for Medicare and Medicaid; race and ethnicity categorized as White, Black, Hispanic, and other.Main outcomes and measuresClaim-based National Institutes of Health Stroke Scale (NIHSS) categorized into minor (0-7), moderate (8-13), moderate to severe (14-21), and severe (22-42) stroke.ResultsOur sample included 45 459 Medicare fee-for-service patients aged 66 and older (mean [SD] age, 80.2 [8.4]; 25 303 [55.7%] female; 7738 [17.0%] dual eligible; 4107 [9.0%] Black; 1719 [3.8%] Hispanic; 37 715 [83.0%] White). In the fully adjusted models, compared with White patients, Black patients (odds ratio [OR], 1.21; 95% CI, 1.06-1.39) and Hispanic patients (OR, 1.54; 95% CI, 1.29-1.85) were more likely to have a severe stroke. Using White patients without dual eligibility as a reference group, White patients with dual eligibility were more likely to have a severe stroke (OR, 1.75; 95% CI, 1.56-1.95). Similarly, Black patients with dual eligibility (OR, 2.15; 95% CI, 1.78-2.60) and Hispanic patients with dual eligibility (OR, 2.50; 95% CI, 1.98-3.16) were more likely to have a severe stroke.Conclusions and relevanceIn this cross-sectional study, Medicare fee-for-service patients with ischemic stroke admitted to acute hospitals who were Black or Hispanic had a higher likelihood of worse stroke severity. Additionally, dual eligibility status had a compounding association with stroke severity regardless of race and ethnicity. An urgent effort is needed to decrease disparities in access to preventive and poststroke care for dual eligible and minority patients.

Project description:BackgroundCriteria for low-dose CT scan lung cancer screening vary across guidelines. Knowledge of the eligible pool across demographic groups can enable policy and programmatic decision-making, particularly for disproportionately affected populations.Research questionWhat are the eligibility rates for low-dose CT scan screening according to sex and race or ethnicity and how do these rates relate to corresponding lung cancer incidence rates?Study design and methodsThis was a cross-sectional study using data from the 2015 National Health Interview Survey adult and cancer control supplement files. In addition to eligibility rates, the ratio of the eligibility rate to the lung cancer incidence rate in a given population group (eligibility to incidence [E-I] ratio) also was determined. Guidelines assessed were: Centers for Medicare and Medicaid Services, National Comprehensive Cancer Network, and US Preventive Services Task Force current or with expansion of age and smoking or quit thresholds. We also assessed a risk model (PLCOM2012 risk model).ResultsTotal numbers eligible based on current guidelines ranged from 8.3 to 13.3 million, representing 8.3% to 13.4% of the US population 50 to 80 years of age, and up to 17.5 million with expanded criteria. Overall eligibility rates on average were about 10 percentage points higher for men than women. For both men and women, and both overall and among ever smokers, non-Hispanic Whites had the highest eligibility rates across all guidelines, followed generally by non-Hispanic Blacks, and then Asians and Hispanics. Among both men and women, non-Hispanic Whites had the highest E-I ratios across all guidelines; non-Hispanic Black men had higher lung cancer incidence, but 30% to 50% lower E-I ratios, than non-Hispanic White men.InterpretationScreening eligibility rates vary widely across guidelines, with disparities evident in E-I ratios, including among non-Hispanic Black men, despite higher lung cancer burden. Consideration of smoking duration in risk assessment criteria may address current disparities.

Project description:ObjectiveTo assess the impact of the Medicare Shared Savings Program (MSSP) ACOs on mental health and substance use services utilization and racial/ethnic disparities in care for these conditions.Data sourcesFive percent random sample of Medicare claims from 2009 to 2016.Study designWe compared Medicare beneficiaries in MSSP ACOs to non-MSSP beneficiaries, stratifying analyses by Medicare eligibility (disability vs age 65+). We estimated difference-in-difference models of MSSP ACOs on mental health and substance use visits (outpatient and inpatient), medication fills, and adequate care for depression adjusting for age, sex, race/ethnicity, region, and chronic medical and behavioral health conditions. To examine the differential impact of MSSP on our outcomes by race/ethnicity, we used a difference-in-difference-in-differences (DDD) design.Data collection/extraction methodsNot applicable.Principal findingsMSSP ACOs were associated with small reductions in outpatient mental health (Coeff: -0.012, P < .001) and substance use (Coeff: -0.001, P < .01) visits in the disability population, and in adequate care for depression for both the disability- and age-eligible populations (Coeff: -0.028, P < .001; Coeff: -0.012, P < .001, respectively). MSSP ACO's were also associated with increases in psychotropic medications (Coeff: 0.007 and Coeff: 0.0213, for disability- and age-eligible populations, respectively, both P < .001) and reductions in inpatient mental health stays (Coeff:-0.004, P < .001, and Coeff:-0.0002, P < .01 for disability- and age-eligible populations, respectively) and substance use-related stays for disability-eligible populations (Coeff:-0.0005, P<.05). The MSSP effect on disparities varied depending on type of service.ConclusionsWe found small reductions in outpatient and inpatient stays and in rates of adequate care for depression associated with MSSP ACOs. As MSSP ACOs are placed at more financial risk for population-based treatment, it will be important to include more robust behavioral health quality measures in their contracts and to monitor disparities in care.

Dataset Information

Race and ethnicity do not impact eligibility for remdesivir: A single-center experience.

Publications

Race and ethnicity do not impact eligibility for remdesivir: A single-center experience.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets