0890 Participant Background Characteristics on Pediatric Obstructive Sleep Apnea Clinical Trials

Abstract Introduction Adequate representation of the US population in clinical trials is essential to ensuring generalizability of findings and advancing equitable care. Despite obstructive sleep apnea (OSA) being one of the most common chronic conditions in children, the US population is not adequately represented in medical research. The extent of population background reporting and whether study participants reflect the US population has not been evaluated for pediatric OSA trials. We hypothesize that current OSA clinical trials insufficiently reflect the diversity of the general population, thereby limiting the applicability and equity of their findings. Methods Cross-sectional study of US-based clinical trials registered on ClinicalTrials.gov that enrolled participants aged < 18 years old between October 2007 and October 2025. We included US-based trials with a “completed study” status and with “available study results” only. We calculated the Enrollment-Census Difference (ECD), defined as the percentage point difference between the proportion of trial participants and the 2019 US Census pediatric population for each racial/ethnic group. One-sample Wilcoxon signed-rank test was performed to determine if the median ECD deviated significantly from 0, indicating parity. Results 23 studies met the inclusion criteria; 65.2% (n=15) reported race, and 56.5% (n=13) reported ethnicity (all of the latter reported race simultaneously). 91.3% (n=21) were sponsored by academic centers, and 2 by industry. Among the studies reporting race and ethnicity data, the median proportional enrollment was 64.0% (IQR: 34.2–72.4%) for Whites, 21.1% (IQR: 13.3–54.0%) for Black/African Americans, 6.7% (IQR: 0.0–45.5%) for Hispanics, 1.6% (IQR: 0-4.9%) and 0% (IQR: 0-0%) for American-Indians/Alaskan- Natives. Analysis of ECD revealed white participants were over-represented (median difference +32.06% [IQR: 1.80, 40.04]; p-value< 0.01), while Asian (median -3.33% [IQR: -5.00, -0.09]; p-value< 0.01) and American- Indian groups/Alaskan-Natives (median -1.00% [IQR: -1.00, -1.00]; p-value<.01) were significantly under-represented. Hispanic populations showed a trend of underrepresentation (median -18.08%; p-value=0.31), while Black participants showed a tendency toward over-representation (median +7.70%; p-value=0.05); however, neither difference reached statistical significance. Conclusion Our study identified a significant underrepresentation of US populations of varied backgrounds in pediatric OSA clinical trials. These gaps highlight a need for population-level recruitment frameworks, and evidence-based policy-driven strategies to enhance inclusion in pediatric OSA research. Support (if any)

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Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.0889
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
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article

0890 Participant Background Characteristics on Pediatric Obstructive Sleep Apnea Clinical Trials

Rasa Tiano, Rakesh Bhattacharjee, Jeremy Landeo Gutierrez, Jayden Marquez et al.
SLEEP
Advanced Causal Inference Techniques
article

0890 Participant Background Characteristics on Pediatric Obstructive Sleep Apnea Clinical Trials

Rasa Tiano, Rakesh Bhattacharjee, Jeremy Landeo Gutierrez, Jayden Marquez, Shayna Salerno
article en

Abstract

Abstract Introduction Adequate representation of the US population in clinical trials is essential to ensuring generalizability of findings and advancing equitable care. Despite obstructive sleep apnea (OSA) being one of the most common chronic conditions in children, the US population is not adequately represented in medical research. The extent of population background reporting and whether study participants reflect the US population has not been evaluated for pediatric OSA trials. We hypothesize that current OSA clinical trials insufficiently reflect the diversity of the general population, thereby limiting the applicability and equity of their findings. Methods Cross-sectional study of US-based clinical trials registered on ClinicalTrials.gov that enrolled participants aged < 18 years old between October 2007 and October 2025. We included US-based trials with a “completed study” status and with “available study results” only. We calculated the Enrollment-Census Difference (ECD), defined as the percentage point difference between the proportion of trial participants and the 2019 US Census pediatric population for each racial/ethnic group. One-sample Wilcoxon signed-rank test was performed to determine if the median ECD deviated significantly from 0, indicating parity. Results 23 studies met the inclusion criteria; 65.2% (n=15) reported race, and 56.5% (n=13) reported ethnicity (all of the latter reported race simultaneously). 91.3% (n=21) were sponsored by academic centers, and 2 by industry. Among the studies reporting race and ethnicity data, the median proportional enrollment was 64.0% (IQR: 34.2–72.4%) for Whites, 21.1% (IQR: 13.3–54.0%) for Black/African Americans, 6.7% (IQR: 0.0–45.5%) for Hispanics, 1.6% (IQR: 0-4.9%) and 0% (IQR: 0-0%) for American-Indians/Alaskan- Natives. Analysis of ECD revealed white participants were over-represented (median difference +32.06% [IQR: 1.80, 40.04]; p-value< 0.01), while Asian (median -3.33% [IQR: -5.00, -0.09]; p-value< 0.01) and American- Indian groups/Alaskan-Natives (median -1.00% [IQR: -1.00, -1.00]; p-value<.01) were significantly under-represented. Hispanic populations showed a trend of underrepresentation (median -18.08%; p-value=0.31), while Black participants showed a tendency toward over-representation (median +7.70%; p-value=0.05); however, neither difference reached statistical significance. Conclusion Our study identified a significant underrepresentation of US populations of varied backgrounds in pediatric OSA clinical trials. These gaps highlight a need for population-level recruitment frameworks, and evidence-based policy-driven strategies to enhance inclusion in pediatric OSA research. Support (if any)

SLEEPVol. 49(Supplement_1)
University of California San Diego (US)
Reduced inequalities
Openalex Percentile: Top 4%
Advanced Causal Inference Techniques
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