Abstract A082: Is there value in gynecologic cancer clinical trial participation for Black women?
Notice bibliographique
Résumé
Abstract Purpose Black women are underrepresented in gynecologic cancer clinical trials despite disproportionately worse cancer outcomes. While etiology of clinical trial enrollment disparities is multifactorial, at the individual level, underrepresented populations may be dissuaded from study participation without perceived value. The concept of Return of Value (ROV) describes return of individual research information (both actionable and non-actionable) that participants find most valuable. Ranking of ROV components varies among racial/ethnic groups. In a national survey, Black individuals were more likely to value information on ancestry, genetic traits, future use of their information, and remuneration, compared to White individuals who highly valued information on connections with other study participants and response to medications. Both groups valued information on how genetics affect the risk of getting a medical condition. We evaluated to what extent gynecologic cancer clinical trials include information most valued by Black women to ascertain whether clinical trial design may influence accrual of Black patients. Methods We queried the ClinicalTrials.gov registry for NCI sponsored gynecologic cancer clinical trials in the US between Jan.1994 and Nov.2021. We extracted pre-specified ROV items in basic information, medical record information, research questionnaires (e.g. EORTC QLQ-C30), life-style risk factors (e.g. smoking), ancestry, genetic traits, genetic testing, biomarker testing, imaging, future use of participant information, information about other clinical trials, how to connect with others in the study, and remuneration. We assessed inclusion proportions for each ROV item and assessed temporal changes in these proportions with chi-square tests. Results 279 gynecologic cancer clinical trials were included, with 21% of trials with year of first accrual in 1994-2000, 37% in 2001-2007, 28% in 2008-2014, and 15% in 2015-2021. Most commonly, trials targeted ovarian cancer (48%), were phase II (53%), and utilized chemotherapy (60%) or targeted therapy (34%). Nearly all trials included ROV items in basic information (99%), medical record information (99%), and imaging (82%). 41% of trials included ROV items in biomarker testing, 20% genetic testing, and 20% research questionnaires. Over time, there were significant increases in the proportion of trials that included genetic testing (3% to 51%; p < 0.001) and biomarker testing (14 to 78%, p < 0.001). Information on lifestyle risk factors was rare (1%), and no trials included ROV in ancestry, genetic traits, how to connect with other participants, and remuneration. Conclusion Gynecologic cancer clinical trials include few design elements that provide high value to Black women. In any multi-pronged effort to improve diversity in clinical trial enrollment, inclusion of items valued by Black women should be considered in order to increase enrollment of Black women. This work contributes to the evidence base supporting the importance of person-centered, community-informed clinical trial design. Citation Format: Ann Oluloro, Liz Sage, Elizabeth Swisher, Sarah M. Temkin, Kemi Doll. Is there value in gynecologic cancer clinical trial participation for Black women? [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A082.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,033 | 0,126 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».