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Enregistrement W2037889538 · doi:10.1158/1940-6207.prev-09-cn13-05

Abstract CN13-05: A new resource to accelerate research into the cause and prevention of breast cancer: The Love/Avon Army of Women

2010· article· en· W2037889538 sur OpenAlexaboutno aff
Susan M. Love

Notice bibliographique

RevueCancer Prevention Research · 2010
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueNutrition, Genetics, and Disease
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineBreast cancer awarenessBreast cancerGeneral partnershipCancer preventionFamily medicineTranslational researchResource (disambiguation)Alternative medicineGerontologyMedical educationCancerPathologyPolitical scienceInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background: It is well established that there is a need for more research into the cause and prevention of breast cancer. While many studies are done in cell lines and laboratory animals, translation of their findings to women often falters due to the perceived difficulty in recruiting healthy women for clinical research. The Dr. Susan Love Research Foundation (DSLRF) has had demonstrated success in recruiting healthy community women for studies. When partnering with a Texas Tech University scientist who had planned to do his research in an animal model because it seemed impossible to obtain blood and core needle biopsies from the women fitting his strict criteria, the DSLRF was able to collect all of the required specimens by accessing their registry of potential volunteers. DSLRF's success with subject recruitment along with The Avon Foundation for Women's commitment to breast cancer research and strong following led to a joint venture called the Love/Avon Army of Women (AOW); an on-line recruitment resource designed to create a partnership between women and the research community in an effort to accelerate breast cancer research. Methods: The AOW was launched in October 2008 with the goal of recruiting ONE MILLION women who are willing to consider participating in breast cancer research, and of encouraging researchers to submit studies for recruitment. Researchers - Researchers interested in having the AOW recruit for their studies submit a study proposal that will be reviewed by the AOW Scientific Advisory Committee, comprised of nominees from AACR and NBCC, to determine if the AOW is the appropriate resource. In addition to recruitment, if the researcher is unable obtain his or her own specimens; there are regional Army Centers where the appropriate data and samples can be collected according to the specifications of the protocol. If a study is accepted, a mass e-mail describing the study procedures and inclusion/exclusion criteria is sent to the entire AOW database. Army of Women members - Women sign up on-line at www.armyofwomen.org to become an Army of Women member. In becoming a member, women aren't committing to participating in a particular study, they are merely agreeing to receive AOW e-mails letting them know about breast cancer research studies. If upon receiving a study e-mail, the individual is interested and qualifies for a study, she undergoes a secondary on-line screening and then her contact information is passed on to the principal investigator to begin the enrollment process. To ensure a partnership between the women and the researchers, all scientists are required to participate in a web-cast to explain how their research will move us forward in finding the cause and prevention of breast cancer. In addition, the public will have access to web-casts on the AOW website, discussing issues of research and study participation. Results: Over 300,000 women have become Army of Women (AOW) members since its launch in October 2008. Membership includes both women who have and have not been diagnosed with breast cancer, as well as those with and without a family history of breast cancer, ranging from ages 18 to 100, and who represent all 50 US states and 47 countries. To date, the Army of Women has recruited for 14 studies, both regional and national, that vary from biomarker and circadian rhythm research to psycho-social and quality of life studies. With over 12,000 Army of Women members having participated in the research process, this method of recruitment has been found to be effective and efficient. Many studies were closed to enrollment within the first 24 hours after having accrued all of their subjects. A biomarker study being conducted at the University of Massachusetts required breast milk from women who were scheduled for a breast biopsy. The diversity of the AOW members proved effective when the registration for this study in the first day was more than the PI had seen in 6 months with standard recruitment efforts. A chemo-brain study from Stanford had an n of 180; the AOW e-blast yielded 1,314 potential subjects within 2 weeks. An on-line quality of life study from the University of Ottawa needed 1,000 survivors; close to 6,000 AOW members participated within 48 hours. The AOW was also approached to recruit for studies having difficulty recruiting minority populations. A Northwestern University study, researching discussions that physicians have with younger women diagnosed with breast cancer related to possible fertility impairment due to treatment, was unable to fill the African American arm of their study; within two weeks all of the women the PI needed had registered. Some studies were very quickly over-enrolled by 5–10%. The overwhelming response to their study has led many researchers to seek additional funding to increase their statistical significance and accommodate all of the eligible subjects. Conclusions: The Love/Avon Army of Women is a novel resource for breast cancer scientists to accelerate accrual, to expand the diversity of their subject population, to increase their number of subjects and statistical significance, and to obtain exactly the type of specimens they need when they need it. This new partnership between women and scientists can revolutionize research and accelerate efforts to eradicate breast cancer. Citation Information: Cancer Prev Res 2010;3(1 Suppl):CN13-05.

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)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,386
Score d'incertitude au seuil0,509

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,058
Tête enseignante GPT0,417
Écart entre enseignants0,359 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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