Racial and Ethnic Diversity in Vitiligo Clinical Trials: A Retrospective Cross-Sectional Study Assessing Demographic Reporting of Participants.

BACKGROUND: While the prevalence of vitiligo is similar across racial and ethnic groups, the effects of vitiligo vary by demographic group, culture, and skin color, with darker-skinned individuals facing greater stigma due to increased visibility of the disease.1,2 The recruitment of diverse participants that are representative of the United States (US) population is crucial to ensuring the generalizability of findings and understanding the impacts of vitiligo across diverse patient groups.   Objectives: This study aimed to determine demographic reporting trends in US vitiligo clinical trials and to determine whether participants are representative of the US population. METHODS: A search for US vitiligo clinical trials was conducted on clinicaltrials.gov. Trials conducted between 2006 to September 5, 2023, were included if they intended to treat vitiligo, were conducted in the US, and were completed or terminated.  Results: Of the 15 trials meeting inclusion criteria, only 60% (n=9) reported participant race/ethnicity. These 9 studies included 1,510 participants, of which only 25.43% (n=384) were non-White and 20.40% were Hispanic. There was disproportionately low representation of racial minorities, particularly Black, Native American, and Native Hawaiian groups.   Limitations: Limitations of our study include small sample size, variations in demographic reporting between trials, and undercounting of minority groups by the US Census.  Conclusions: Racial and ethnic minority groups remain underrepresented in US vitiligo clinical trials. Given that the impact of vitiligo can vary by the affected individual’s demographic group and skin color, investigators must be intentional about including a more diverse and representative population in vitiligo clinical trials.  J Drugs Dermatol. 2024;23(7):e164-e166. doi:10.36849/JDD.8117e.

Mapping Strategies for Reaching Socioeconomically Disadvantaged Populations in Clinical Trials.

Importance: Socioeconomically disadvantaged patients, such as persons with low income and those with low educational attainment, are less likely to participate in clinical trials than those with higher earnings and higher educational attainment, despite the former being more likely to have chronic medical conditions. Ways to improve the representation of socioeconomically disadvantaged patients in clinical trials deserve attention. Objective: To examine whether current recruitment and enrollment strategies used by US clinical research sites appropriately include patients from socioeconomically disadvantaged backgrounds. Design, Setting, and Participants: This survey study was conducted between April and July 2023. An online survey was distributed among US clinical research sites to explore their use of these strategies and the types of patient sociodemographic and socioeconomic data they collect. The survey was distributed by 13 pharmaceutical companies and 1 clinical research organization. Eight targeted strategies known to increase the recruitment and retention of socioeconomically disadvantaged participants as well as 6 general strategies to recruit and retain clinical trial participants were identified. Data analysis was performed between August and September 2023. Main Outcomes and Measures: Proportions of for-profit vs nonprofit or governmental sites that use recruitment and retention strategies, proportions that have partnerships with community organizations that target socioeconomically disadvantaged groups, and the distribution of sociodemographic and socioeconomic data collected by sites about their patients. A χ2 test of independence was performed to assess the association between research site ownership type and levels of adoption of strategies. Results: A total of 492 responses were collected from 381 clinical research sites in the US (219 for-profit sites [57.5%] and 162 nonprofit or governmental sites [42.5%]). Overall, compared with nonprofit or governmental sites, for-profit sites reported higher use of strategies shown to increase the recruitment and retention of socioeconomically disadvantaged populations, including always or often providing after-hours visits (84 of 173 for-profit sites [48.6%]; 22 of 123 nonprofit or governmental sites [17.9%]) and offering financial compensation (135 of 162 for-profit sites [83.3%]; 60 of 123 nonprofit or governmental sites [48.8%]). Additionally, there was an association between research site ownership type and levels of adoption of these strategies; for example, for-profit sites were more likely to provide after-hours visits (χ2 = 30.33; P < .001) and offer financial compensation (χ2 = 49.35; P < .001). Only 7.2% of for-profit sites (12 of 167) and 13.0% of nonprofit or governmental sites (16 of 123) collected information on the patient's annual income. Conclusions and Relevance: In this survey study, we found an association between a clinical research site's ownership type (for-profit vs nonprofit or governmental) and how often it used strategies to engage socioeconomically diverse populations in clinical research. Regardless of ownership type, most clinical research sites did not collect socioeconomic information from patients. Adoption of strategies to engage socioeconomically diverse populations, particularly by nonprofit or governmental sites, may help minimize barriers to participation for socioeconomically disadvantaged patients.

Diversity, Equity, and Inclusion in Urolithiasis Clinical Trials: Representative Enrollment by Race, Ethnicity, and Sex.

INTRODUCTION: We sought to assess whether participant enrollment is appropriately representative of the overall urolithiasis population in published urolithiasis clinical trials. METHODS: PubMed was queried for urolithiasis US clinical trials published from 2000 to 2022. Trials were evaluated for reporting patient race/ethnicity and sex data. These were then compared to the stone prevalence reported by the National Health and Nutrition Examination Survey from 2015 to 2018. We calculated a representation quotient (RQ) to describe enrollment of patients and then stratified by geographic location, study type, and funding source. RESULTS: Of the 180 urolithiasis trials performed in the US, we identified 40 trials (22%) reporting race or ethnicity and 104 trials (58%) reporting sex. Male and female participants are well represented (RQ 0.97 and 1.02, respectively). Overall, the RQ of Black, Asian American and Pacific Islander, White, Hispanic, and mixed/other participants is 1.84, 1.06, 1.04, 0.46, and 0.34, respectively. Trials completed in the Western Section and multi-institutional trials have the most proportional enrollment, while trials in the South Central and Southeastern Sections have underrepresentation of mixed/other and Hispanic patients. Enrollment was similar among all trial subtypes. Government- and industry-funded trials had more diverse enrollment than academic-funded trials. CONCLUSIONS: Only 1 in 4 published US urolithiasis trials report race or ethnicity enrollment. Mixed race and Hispanic participants are consistently underrepresented, while Black participants are overrepresented. Government- and industry-sponsored multi-institutional trials have the most proportional representation. Investigators should prioritize inclusive recruitment and improve reporting practices to accurately reflect the diversity of the urolithiasis population.

Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review.

Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the safety and efficacy of new treatments, interventions, and medical procedures. The Bayesian framework offers a unique advantage over the classical framework, especially when incorporating prior information into a new trial with quality external data, such as historical data or another source of co-data. In recent years, there has been a significant increase in regulatory submissions using Bayesian statistics due to its flexibility and ability to provide valuable insights for decision-making, addressing the modern complexity of clinical trials where frequentist trials are inadequate. For regulatory submissions, companies often need to consider the frequentist operating characteristics of the Bayesian analysis strategy, regardless of the design complexity. In particular, the focus is on the frequentist type I error rate and power for all realistic alternatives. This tutorial review aims to provide a comprehensive overview of the use of Bayesian statistics in sample size determination, control of type I error rate, multiplicity adjustments, external data borrowing, etc., in the regulatory environment of clinical trials. Fundamental concepts of Bayesian sample size determination and illustrative examples are provided to serve as a valuable resource for researchers, clinicians, and statisticians seeking to develop more complex and innovative designs.

Comparing prospectively assigned trial and real-world lung cancer patients.

Aim: To evaluate the comparability of a probable clinical trial (CT) cohort derived from electronic medical records (EMR) data with a real-world cohort treated with the same therapy and identified using the same inclusion and exclusion criteria to emulate an external control. Methods: We utilized de-identified patient-level structured data sourced from EMRs. We then compared patterns of overall survival (OS) between probable CT patients with those drawn from non-contemporaneous real-world data (RWD) using a two-sided log-rank test, hazard ratios (HRs) using a Cox proportional-hazards model and Kaplan-Meier (KM) survival curves. Each regression estimate was calculated with a corresponding 95% confidence interval. We additionally conducted multiple matching methods to assess their relative performance. Results: Median (standard deviation) OS was 10.2 (0.7) months for the RWD arm and 11.3 (1.3) for the probable CT arm with a Log rank p-value equal to 0.4771. OS in both cohorts is longer than the reported CT median OS of 9.2 (0.6). The HRs generated under all five assessed matching methods (including without adjustment) were not statistically significant at the 95% confidence level. Conclusion: Our results suggest, with caveats noted, that survival patterns between real-world and CT cohorts in this NSCLC setting are not statistically significantly different.

A unified Bayesian framework for bias adjustment in multiple comparisons from clinical trials.

In clinical trials, multiple comparisons arising from various treatments/doses, subgroups, or endpoints are common. Typically, trial teams focus on the comparison showing the largest observed treatment effect, often involving a specific treatment pair and endpoint within a subgroup. These findings frequently lead to follow-up pivotal studies, many of which do not confirm the initial positive results. Selection bias occurs when the most promising treatment, subgroup, or endpoint is chosen for further development, potentially skewing subsequent investigations. Such bias can be defined as the deviation in the observed treatment effects from the underlying truth. In this article, we propose a general and unified Bayesian framework to address selection bias in clinical trials with multiple comparisons. Our approach does not require a priori specification of a parametric distribution for the prior, offering a more flexible and generalized solution. The proposed method facilitates a more accurate interpretation of clinical trial results by adjusting for such selection bias. Through simulation studies, we compared several methods and demonstrated their superior performance over the normal shrinkage estimator. We recommended the use of Bayesian Model Averaging estimator averaging over Gaussian Mixture Models as the prior distribution based on its performance and flexibility. We applied the method to a multicenter, randomized, double-blind, placebo-controlled study investigating the cardiovascular effects of dulaglutide.

Why location matters: associations between county-level characteristics and availability of National Cancer Oncology Research Program and National Cancer Institute sites.

BACKGROUND: The majority of patients with cancer seek care at community oncology sites; however, most clinical trials are available at National Cancer Institute (NCI)-designated sites. Although the NCI National Cancer Oncology Research Program (NCORP) was designed to address this problem, little is known about the county-level characteristics of NCORP site locations. METHODS: This cross-sectional analysis determined the association between availability of NCORP or NCI sites and county-level characteristic theme percentile scores from the Center for Disease Control and Prevention's Social Vulnerability Index themes. Health Resources and Services Administration's Area Health Resource Files were used to determine contiguous counties. We estimated risk ratios and 95% confidence intervals (CIs) using modified Poisson regression models to evaluate the association between county-level characteristics and site availability within singular and singular and contiguous counties. RESULTS: Of 3141 included counties, 14% had an NCORP, 2% had an NCI, and 1% had both sites. Among singular counties, for a standard deviation increase in the racial and ethnic theme score, there was a 22% higher likelihood of NCORP site availability (95% CI = 1.10 to 1.36); for a standard deviation increase in the socioeconomic status theme score, there was a 24% lower likelihood of NCORP site availability (95% CI = 0.67 to 0.87). Associations were of smaller magnitude when including contiguous counties. NCI sites were located in more vulnerable counties. CONCLUSIONS: NCORP sites were more often in racially diverse counties and less often in socioeconomically vulnerable counties. Research is needed to understand how clinical trial representation will increase if NCORP sites strategically increase their locations in more vulnerable counties.

Publication rates of registered strabismus trials from ClinicalTrials.gov.

Presently, little is known regarding the characteristics and publication rates of registered strabismus trials from ClinicalTrials.gov. We queried registered strabismus trials that were completed prior to January 1, 2021, from ClinicalTrials.gov. Publication of trials in peer-reviewed journals was confirmed using PubMed.gov, ClinicalTrials.gov, and Google Scholar. Of the 117 trials found, only 69 (59%) were published with a publication delay of nearly 2.5 years. Interventional trials were associated with publication status compared with observational trials. The low publication rates and significant publication delay indicate potential bias in information dissemination of completed strabismus trials.

Enrollment on upfront high-risk neuroblastoma trials by race, ethnicity, and poverty status: A report from the Children's Oncology Group.

It is not clear whether trial access disparities exist in the Children's Oncology Group (COG). Here, we leverage a cohort of children with high-risk neuroblastoma (HR-NBL) enrolled on the COG ANBL00B1 neuroblastoma biology study to examine subsequent enrollment to upfront COG therapeutic trials by race, ethnicity, and proxied poverty status. Among 1917 children with HR-NBL enrolled on ANBL00B1, 696 (36.3%) subsequently enrolled on an upfront therapeutic trial with no difference by race, ethnicity, or proxied poverty status. In neuroblastoma, trial access disparities are not comparable to adult oncology, and efforts to advance equity should prioritize other mechanisms of survival disparities.

Comparison of revision rates and epidemiological data of a single total knee arthroplasty system of different designs (cruciate retaining, posterior stabilized, mobile bearing, and fixed bearing): a meta-analysis and systematic review of clinical trials and national arthroplasty registries.

BACKGROUND: This study aimed to meta-analyze epidemiological data, revision rates, and incidences of different designs of a single Total Knee Arthroplasty System and compare these factors across different countries. METHODS: A systematic review was conducted on clinical studies and arthroplasty registries of ATTUNE TKA from 1999 to 2020. The main endpoints analyzed were revision rates and epidemiological data. RESULTS: The average age of patients was 67.8 years, with a gender distribution of 60% female and 40% male. The pooled average BMI was 29.4 kg/m2. Eight clinical studies showed a pooled revision rate per 100 observed CY of 0.5 (n = 1343 cases). Cumulative revision rates after 1, 3, and 5 years varied among registries, with the Swiss registry having the highest revision data (after 5 years: 6.3%) and the American registry having the lowest revision data (after 5 years: 1.7%). A comparison of the revision rates of mobile bearing and fixed bearing (41,200 cases) as well as cruciate retaining and posterior stabilized (n = 123,361 cases) showed no significant advantage in the first 5 years after implantation. CONCLUSION: In conclusion, pooled data from 41,200 cases of TKA with a single Total Knee Arthroplasty System in two arthroplasty registries revealed that there was no significant difference in revision rates between the mobile bearing and fixed bearing design within the first 5 years after implantation. In addition, a comparison of the revision rates in n = 123,361 cases showed no significant advantage for cruciate retaining or posterior stabilized in the first 5 years after implantation.

Methods for non-proportional hazards in clinical trials: A systematic review.

For the analysis of time-to-event data, frequently used methods such as the log-rank test or the Cox proportional hazards model are based on the proportional hazards assumption, which is often debatable. Although a wide range of parametric and non-parametric methods for non-proportional hazards has been proposed, there is no consensus on the best approaches. To close this gap, we conducted a systematic literature search to identify statistical methods and software appropriate under non-proportional hazard. Our literature search identified 907 abstracts, out of which we included 211 articles, mostly methodological ones. Review articles and applications were less frequently identified. The articles discuss effect measures, effect estimation and regression approaches, hypothesis tests, and sample size calculation approaches, which are often tailored to specific non-proportional hazard situations. Using a unified notation, we provide an overview of methods available. Furthermore, we derive some guidance from the identified articles.

Distributional imputation for the analysis of censored recurrent events.

Longitudinal clinical trials for which recurrent events endpoints are of interest are commonly subject to missing event data. Primary analyses in such trials are often performed assuming events are missing at random, and sensitivity analyses are necessary to assess robustness of primary analysis conclusions to missing data assumptions. Control-based imputation is an attractive approach in superiority trials for imposing conservative assumptions on how data may be missing not at random. A popular approach to implementing control-based assumptions for recurrent events is multiple imputation (MI), but Rubin's variance estimator is often biased for the true sampling variability of the point estimator in the control-based setting. We propose distributional imputation (DI) with corresponding wild bootstrap variance estimation procedure for control-based sensitivity analyses of recurrent events. We apply control-based DI to a type I diabetes trial. In the application and simulation studies, DI produced more reasonable standard error estimates than MI with Rubin's combining rules in control-based sensitivity analyses of recurrent events.

National Estimates of the Participation of Patients With Cancer in Clinical Research Studies Based on Commission on Cancer Accreditation Data.

PURPOSE: National estimates of cancer clinical trial participation are nearly two decades old and have focused solely on enrollment to treatment trials, which does not reflect the willingness of patients to contribute to other elements of clinical research. We determined inclusive, contemporary estimates of clinical trial participation for adults with cancer using a national sample of data from the Commission on Cancer (CoC). METHODS: The data were obtained from accreditation information submitted by the 1,200 CoC programs, which represent more than 70% of all cancer cases diagnosed in the United States each year. Deidentified, institution-level aggregate counts of annual enrollment to treatment, biorepository, diagnostic, economic, genetic, prevention, quality-of-life (QOL), and registry studies were examined. Overall, study-type estimates for the period 2013-2017 were estimated. Multiple imputation by chained equations was used to account for missing data, with summary estimates calculated separately by type of program (eg, National Cancer Institute [NCI]-designated cancer centers) and pooled. RESULTS: The overall estimated patient participation rate to cancer treatment trials was 7.1%. Patients with cancer participated in a wide variety of other studies, including biorepository (12.9%), registry (7.3%), genetic (3.6%), QOL (2.8%), diagnostic (2.5%), and economic (2.4%) studies. Treatment trial enrollment was 21.6% at NCI-designated comprehensive cancer centers, 5.4% at academic (non-NCI-designated) comprehensive cancer programs, 5.7% at integrated network cancer programs, and 4.1% at community programs. One in five patients (21.9%) participated in one or more cancer clinical research studies. CONCLUSION: In a first-time use of national accreditation information from the CoC, enrollment to cancer treatment trials was 7.1%, higher than historical estimates of <5%. Patients participated in a diverse set of other study types. Contributions of adult patients with cancer to clinical research is more common than previously understood.

"We are not invited": Australian focus group results on how to improve ethnic diversity in trials.

OBJECTIVES: Lack of ethnic diversity in trials may contribute to health disparities and to inequity in health outcomes. The primary objective was to investigate the experiences and perspectives of ethnically diverse populations about how to improve ethnic diversity in trials. STUDY DESIGN AND SETTING: Qualitative data were collected via 16 focus groups with participants from 21 ethnically diverse communities in Australia. Data collection took place between August and September 2022 in community-based settings in six capital cities: Sydney, Melbourne, Perth, Adelaide, Brisbane, and Darwin, and one rural town: Bordertown (South Australia). RESULTS: One hundred and fifty-eight purposively sampled adults (aged 18-85, 49% women) participated in groups speaking Tamil, Greek, Punjabi, Italian, Mandarin, Cantonese, Karin, Vietnamese, Nepalese, and Arabic; or English-language groups (comprising Fijian, Filipino, African, and two multicultural groups). Only 10 participants had previously taken part in medical research including three in trials. There was support for medical research, including trials; however, most participants had never been invited to participate. To increase ethnic diversity in trial populations, participants recommended recruitment via partnering with communities, translating trial materials and making them culturally accessible using audiovisual ways, promoting retention by minimizing participant burden, establishing trust and rapport between participants and researchers, and sharing individual results. Participants were reluctant to join studies on taboo topics in their communities (eg, sexual health) or in which physical specimens (eg, blood) were needed. Participants said these barriers could be mitigated by communicating about the topic in more culturally cognizant and safe ways, explaining how data would be securely stored, and reinforcing the benefit of medical research to humanity. CONCLUSION: Participants recognized the principal benefits of trials and other medical research, were prepared to take part, and offered suggestions on recruitment, consent, data collection mechanisms, and retention to enable this to occur. Researchers should consider these community insights when designing and conducting trials; and government, regulators, funders, and publishers should allow for greater innovation and flexibility in their processes to enable ethnic diversity in trials to improve.

Isotonic design for single-arm biomarker stratified trials.

In single-arm trials with a predefined subgroup based on baseline biomarkers, it is often assumed that a biomarker defined subgroup, the biomarker positive subgroup, has the same or higher response to treatment compared to its complement, the biomarker negative subgroup. The goal is to determine if the treatment is effective in each of the subgroups or in the biomarker positive subgroup only or not effective at all. We propose the isotonic stratified design for this problem. The design has a joint set of decision rules for biomarker positive and negative subjects and utilizes joint estimation of response probabilities using assumed monotonicity of response between the biomarker negative and positive subgroups. The new design reduces the sample size requirement when compared to running two Simon's designs in each biomarker positive and negative. For example, the new design requires 23%-35% fewer patients than running two Simon's designs for scenarios we considered. Alternatively, the new design allows evaluating the response probability in both biomarker negative and biomarker positive subgroups using only 40% more patients needed for running Simon's design in the biomarker positive subgroup only.

Toward Equitable Precision Oncology: Monitoring Racial and Ethnic Inclusion in Genomics and Clinical Trials.

PURPOSE: Ethnic diversity in cancer research is crucial as race/ethnicity influences cancer incidence, survival, drug response, molecular pathways, and epigenetic phenomena. In 2018, we began a project to examine racial/ethnic diversity in cancer research, with a commitment to review these disparities every 4 years. This report is our second assessment, detailing the present state of racial/ethnic diversity in cancer genomics and clinical trials. METHODS: To study racial/ethnic inclusion in cancer genomics, we extracted ethnic records from all data sets available at cBioPortal (n = 125,128 patients) and cancer-related genome-wide association studies (n = 28,011,282 patients) between 2018 and 2022. Concerning clinical trials, we selected studies related to breast cancer (n = 125,518 patients, 181 studies), lung cancer (n = 34,329 patients, 119 studies), and colorectal cancer (n = 40,808 patients, 105 studies). RESULTS: In cancer genomics (N = 28,136,410), 3% of individuals lack racial/ethnic registries; tumor samples were collected predominantly from White patients (89.14%), followed by Asian (7%), African American (0.55%), and Hispanic (0.21%) patients and other populations (0.1%). In clinical trials (N = 200,655), data on race/ethnicity are missing for 60.14% of the participants; for individuals whose race/ethnicity was recorded, most were characterized as White (28.33%), followed by Asian (7.64%), African (1.79), other ethnicities (1.37), and Hispanic (0.73). Racial/ethnic representation significantly deviates from global ethnic proportions (P ≤ .001) across all data sets, with White patients outnumbering other ethnic groups by a factor of approximately 4-6. CONCLUSION: Our second update on racial/ethnic representation in cancer research highlights the persistent overrepresentation of White populations in cancer genomics and a notable absence of racial/ethnic information across clinical trials. To ensure more equitable and effective precision oncology, future efforts should address the reasons behind the insufficient representation of ethnically diverse populations in cancer research.

Reporting of interventional clinical trial results in an academic center: a survey of completed studies.

BACKGROUND: The dissemination of clinical trial results is an important scientific and ethical endeavour. This survey of completed interventional studies in a French academic center describes their reporting status. METHODS: We explored all interventional studies sponsored by Rennes University Hospital identified on the French Open Science Monitor which tracks trials registered on EUCTR or clinicaltrials.gov, and provides an automatic assessment of the reporting of results. For each study, we ascertained the actual reporting of results using systematic searches on the hospital internal database, bibliographic databases (Google Scholar, PubMed), and by contacting all principal investigators (PIs). We describe several features (including total budget and numbers of trial participants) of the studies that did not report any results. RESULTS: The French Open Science Monitor identified 93 interventional studies, among which 10 (11%) reported results. In contrast, our survey identified 36 studies (39%) reporting primary analysis results and an additional 18 (19%) reporting results for secondary analyses (without results for their primary analysis). The overall budget for studies that did not report any results was estimated to be €5,051,253 for a total of 6,735 trial participants. The most frequent reasons for the absence of results reported by PIs were lack of time for 18 (42%), and logistic difficulties (e.g. delay in obtaining results or another blocking factor) for 12 (28%). An association was found between non-publication and negative results (adjusted Odds Ratio = 4.70, 95% Confidence Interval [1.67;14.11]). CONCLUSIONS: Even allowing for the fact that automatic searches underestimate the number of studies with published results, the level of reporting was disappointingly low. This amounts to a waste of trial participants' implication and money. Corrective actions are needed. TRIAL REGISTRATION: https://osf.io/q5hcs.

Refining the impact of genetic evidence on clinical success.

The cost of drug discovery and development is driven primarily by failure1, with only about 10% of clinical programmes eventually receiving approval2-4. We previously estimated that human genetic evidence doubles the success rate from clinical development to approval5. In this study we leverage the growth in genetic evidence over the past decade to better understand the characteristics that distinguish clinical success and failure. We estimate the probability of success for drug mechanisms with genetic support is 2.6 times greater than those without. This relative success varies among therapy areas and development phases, and improves with increasing confidence in the causal gene, but is largely unaffected by genetic effect size, minor allele frequency or year of discovery. These results indicate we are far from reaching peak genetic insights to aid the discovery of targets for more effective drugs.

Analysis and Optimization of Equitable US Cancer Clinical Trial Center Access by Travel Time.

Importance: Racially minoritized and socioeconomically disadvantaged populations are currently underrepresented in clinical trials. Data-driven, quantitative analyses and strategies are required to help address this inequity. Objective: To systematically analyze the geographical distribution of self-identified racial and socioeconomic demographics within commuting distance to cancer clinical trial centers and other hospitals in the US. Design, Setting, and Participants: This longitudinal quantitative study used data from the US Census 2020 Decennial and American community survey (which collects data from all US residents), OpenStreetMap, National Cancer Institute-designated Cancer Centers list, Nature Index of Cancer Research Health Institutions, National Trial registry, and National Homeland Infrastructure Foundation-Level Data. Statistical analyses were performed on data collected between 2006 and 2020. Main Outcomes and Measures: Population distributions of socioeconomic deprivation indices and self-identified race within 30-, 60-, and 120-minute 1-way driving commute times from US cancer trial sites. Map overlay of high deprivation index and high diversity areas with existing hospitals, existing major cancer trial centers, and commuting distance to the closest cancer trial center. Results: The 78 major US cancer trial centers that are involved in 94% of all US cancer trials and included in this study were found to be located in areas with socioeconomically more affluent populations with higher proportions of self-identified White individuals (+10.1% unpaired mean difference; 95% CI, +6.8% to +13.7%) compared with the national average. The top 10th percentile of all US hospitals has catchment populations with a range of absolute sum difference from 2.4% to 35% from one-third each of Asian/multiracial/other (Asian alone, American Indian or Alaska Native alone, Native Hawaiian or Other Pacific Islander alone, some other race alone, population of 2 or more races), Black or African American, and White populations. Currently available data are sufficient to identify diverse census tracks within preset commuting times (30, 60, or 120 minutes) from all hospitals in the US (N = 7623). Maps are presented for each US city above 500 000 inhabitants, which display all prospective hospitals and major cancer trial sites within commutable distance to racially diverse and socioeconomically disadvantaged populations. Conclusion and Relevance: This study identified biases in the sociodemographics of populations living within commuting distance to US-based cancer trial sites and enables the determination of more equitably commutable prospective satellite hospital sites that could be mobilized for enhanced racial and socioeconomic representation in clinical trials. The maps generated in this work may inform the design of future clinical trials or investigations in enrollment and retention strategies for clinical trials; however, other recruitment barriers still need to be addressed to ensure racial and socioeconomic demographics within the geographical vicinity of a clinical site can translate to equitable trial participant representation.

Racial and ethnic associations with comprehensive cancer center access and clinical trial enrollment for acute leukemia.

BACKGROUND: Clinical trial participation at Comprehensive Cancer Centers (CCC) is inequitable for minoritized racial and ethnic groups with acute leukemia. CCCs care for a high proportion of adults with acute leukemia. It is unclear if participation inequities are due to CCC access, post-access enrollment, or both. METHODS: We conducted a retrospective cohort study of adults with acute leukemia (2010-2019) residing within Massachusetts, the designated catchment area of the Dana-Farber/Harvard Cancer Center (DF/HCC). Individuals were categorized as non-Hispanic Asian (NHA), Black (NHB), White (NHW), Hispanic White (HW), or Other. Decomposition analyses assessed covariate contributions to disparities in (1) access to DF/HCC care and (2) post-access enrollment. RESULTS: Of 3698 individuals with acute leukemia, 85.9% were NHW, 4.5% HW, 4.3% NHB, 3.7% NHA, and 1.3% Other. Access was lower for HW (age- and sex-adjusted OR = 0.64, 95% CI = 0.45 to 0.90) and reduced post-access enrollment for HW (aOR = 0.54, 95% CI =0.34 to 0.86) and NHB (aOR = 0.60, 95% CI = 0.39 to 0.92) compared to NHW. Payor and socioeconomic status (SES) accounted for 25.2% and 21.2% of the +1.1% absolute difference in HW access. Marital status and SES accounted for 8.0% and 7.0% of the -8.8% absolute disparity in HW enrollment; 76.4% of the disparity was unexplained. SES and marital status accounted for 8.2% and 7.1% of the -9.1% absolute disparity in NHB enrollment; 73.0% of the disparity was unexplained. CONCLUSIONS: A substantial proportion of racial and ethnic inequities in acute leukemia trial enrollment at CCCs are from post-access enrollment, the majority of which was not explained by sociodemographic factors.