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Enregistrement W4407643571 · doi:10.1002/mdc3.70009

Representational Disparities in the Enrollment of Parkinson's Disease Clinical Trials

2025· letter· en· W4407643571 sur OpenAlexafffundabout
Chia‐Chen Tsai, Brendan Tao, Vallen Lin, Jaden Lo, Suhangi Brahmbhatt, Carmen Kalo, Connie Marras, Faisal Khosa

Notice bibliographique

RevueMovement Disorders Clinical Practice · 2025
Typeletter
Langueen
DomaineMedicine
ThématiqueParkinson's Disease Mechanisms and Treatments
Établissements canadiensVancouver General HospitalUniversity of TorontoMcMaster UniversityUniversity of British Columbia
Organismes subventionnairesWeston Brain Institute
Mots-clésParkinson's diseaseDiseaseMedicineClinical trialPsychologyPhysical medicine and rehabilitationGerontologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Parkinson's disease (PD) has diverse clinical presentations across demographics.1 Inclusive clinical trial enrollment ensures representative findings, leading to applicable population-based health decisions. We evaluated the sex, racial, and ethnic representation of PD clinical trial participants relative to the global demographic distribution of PD. “Parkinson's disease” was searched on ClinicalTrials.gov (02/2000–03/2023) for randomized interventional PD trials (Fig. S1). Reviewers screened trial eligibility and extracted data in duplicate. Each trial's geographic, temporal and age-specific female prevalence was attained from the Global Burden of Disease (GBD) database. Participation-to-prevalence ratios (PPRs) of 0.8–1.2 indicated that the proportion of female trial participants reflects that of the wider population.2 Kruskal-Wallis tests with post-hoc comparisons (pairwise Mann–Whitney U test and Bonferroni continuity correction) were conducted. Of 328 trials (Table 1), 38.8% were female. The aggregated female PPR was 0.83 (95% CI:0.79–0.86). Among participants in US-conducted trials, 2.1% were Black or African American, 0.10% American Indian or Alaskan Native (AIAN), 0.22% Native Hawaiian or Other Pacific Islander (NHOPI), and 6.8% Hispanic. While GBD does not report racial or ethnic prevalences, these proportions lag behind the 2021 US demographic representation: 13.6% Black, 1.3% AIAN, 0.3% NHOPI, and 18.9% Hispanic.3 7380 (40.8) Across PD trials, female enrollment reflected the PD disease burden of the wider population, enhancing trial generalizability and external validity. Adequate female representation may aid in understanding how PD differentially affects sexes and determining the sex-specific efficacy of investigational drugs. For instance, sex-specific differences (eg, genetics, hormones, lifestyle) have been suggested to affect PD susceptibility and severity, with estrogen postulated to be neuroprotective.1 Conversely, several racial and ethnic groups were underrepresented (Black, AIAN, NHOPI, Hispanic). While PD prevalence is reportedly higher in White populations, Black individuals with PD experience greater motor impairment and mortality rates than White individuals (income- and education-adjusted).4 To address this, we recommend mandating race and ethnicity reporting in clinical trials and setting enrollment quotas that reflect the study country's demographic distribution. This underrepresentation mirrors broader healthcare access inequities, as underrepresented groups face systemic barriers (eg, socioeconomic challenges, limited access to specialized care, mistrust of healthcare), limiting trial participation. Efforts to address systemic inequities are needed to ensure equitable representation. Our study was limited by uncertainties in GBD prevalence estimates. As GBD does not report racial and ethnic prevalences, we were unable to assess PPRs and region-specific variations. Other limitations include binary sex classifications, exclusion of other demographic data (eg, gender), and the predominance of male-led trials. Future trials could collect gender data and expand racial and ethnic categories. Trials could recruit in diverse regions, partner with local organizations to build trust, reduce participation barriers (eg, remote participation, travel support), diversify leadership, and provide cultural competency training to address recruitment biases. Assessing female representation in PD trials relative to the wider PD population remains challenging due to the underdiagnosis of PD in females.5 Additionally, racial and ethnic minority groups are underrepresented. Diverse enrollment and equitable healthcare access are needed to further PD knowledge and treatment and inform policy decisions applicable to the broader population. (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the first draft, B. Review and Critique C.T.: 1A, 1B, 1C, 2C, 3A. B.T.: 1A, 1B, 1C, 2A, 2B, 3B. V.L.: 1C, 3B. J.L.: 1C, 3B. S.B.: 1C, 3B. C.K.: 1C, 3B. C.M.: 1B, 3B. F.K.: 1A, 3B. None. Funding Sources and Conflict of Interest: No specific funding was received for this work. The authors declare that there are no conflicts of interest relevant to this work. Financial Disclosures for Previous 12 Months: CM received research funding from the Parkinson's Foundation, Michael J. Fox Foundation, International Parkinson and Movement Disorders Society, the Weston Brain Institute and the Mayvon Foundation. FK is the recipient of the Vancouver Medical, Mental and Allied Staff Association Scientific Achievement Award (2024) and the Michael Smith Health Research BC Health Professional-Investigator award (2023–2028). All other authors have no financial disclosures for the preceding 12 months. Ethical Compliance Statement: Ethics approval and informed patient consent were not necessary for this work as all data are publicly available and no patient data were used. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines. The data that support the findings of this study are available from the corresponding author upon reasonable request. Figure S1. Flow diagram of study methods and selection of Parkinson's disease clinical trials for inclusion. aExclusion criteria included studies that were non-randomized, non-interventional, and/or of the wrong condition. bExclusion criteria included studies that had no results or publications available (n = 309), no report of demographic information (n = 108), and/or enrolled fewer than 10 participants (n = 33). NCT, National Clinical Trial. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,015
score de la tête « metaresearch » (Gemma)0,039
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,059
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0150,039
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,143
Tête enseignante GPT0,483
Écart entre enseignants0,340 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2025
Routes d'admission3
Résumé présentoui

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