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Enregistrement W4220749248 · doi:10.1158/1538-7445.sabcs21-ot1-01-01

Abstract OT1-01-01: A randomized, pragmatic trial investigating the timing of radiotherapy and endocrine in patients with early stage breast cancer (REaCT-RETT trial)

2022· article· en· W4220749248 sur OpenAlexaffabout
Sharon F Mc Gee, Mark Clemons, Michelle Liu, Mashari Alzahrani, Terry L. Ng, Arif Awan, Sandeep Sehdev, John Hilton, Jean Caudrelier, Marie-France Savard, Lesley Fallowfield, Vikaash Kumar, Orit Freedman, Dean Fergusson, Gregory R. Pond, Brian Hutton, Jean Marc Bourque

Notice bibliographique

RevueCancer Research · 2022
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueBreast Cancer Treatment Studies
Établissements canadiensMcMaster UniversityLakeridge HealthMarkham Stouffville HospitalOttawa Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineRandomized controlled trialRadiation therapyClinical endpointBreast cancerQuality of life (healthcare)CancerOncologyClinical trialInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract The optimal timing of commencing adjuvant endocrine therapy (ET) relative to adjuvant radiotherapy (RT) (i.e. concurrent with or sequential to radiotherapy) remains unknown. A systematic review performed by our team was unable to answer this question due to a lack of high quality, randomized data on concurrent versus sequential ET and RT. Surveys of physicians confirmed this uncertainty and highlighted theoretical concerns for increased side effects with concurrent treatment. Respondents showed keen interest in obtaining real world, randomized data to guide clinical practice. REaCT-RETT is a pragmatic, randomized, non-inferiority trial comparing concurrent and sequential ET and RT in early breast cancer (EBC). The primary endpoint will assess the change in ET side effects at baseline and 3 months post radiation, using the Functional Assessment of Cancer Therapy-Endocrine Subscale (FACT-ES), with primary analysis based on an analysis of covariance (ANCOVA). With a sample size of 176 patients (88 per arm), an ANCOVA would have 80% power (α=0.05) to detect effect sizes as small as 0.25 regardless of the correlation with covariates. It is hypothesized that concurrent therapy will be non-inferior to sequential therapy in terms of ET side effects. Secondary endpoints will examine RT toxicity, ET compliance, quality of life, and cost-effectiveness. Patients with HR positive EBC planned to receive both adjuvant ET and RT were eligible. Patients who previously received ET for invasive breast cancer, or RT in the same breast, were excluded. The trial is conducted by The Ottawa Hospital’s (TOH) innovative Rethinking Clinical Trials (REaCT) program (https://react.ohri.ca/) which strives to improve access to patient-centered, pragmatic clinical trials by removing barriers for patients and researchers. Integral features of the program include broad eligibility criteria, a verbal consent model, and pragmatic data collection and assessment procedures. REaCT is the largest pragmatic cancer clinical trials program in Canada, with over 3,200 patients randomized in 18 clinical trials at 15 sites across Canada. REaCT-RETT accrued patients from September 2019 to January 2021. Data collection is ongoing, with final patient follow up expected April 2022. The timing of accrual provided a unique opportunity to adapt in response to restrictions due to the COVID-19 pandemic, which began to impact trial sites in March 2020. The target sample size was met with 262 patients randomized (1:1) across 3 sites in Ontario, 98% from TOH. A mean of 19 patients/month were accrued prior to the pandemic, compared to a mean of 13 patients/month after March 2020. Twenty-two patients were removed due to withdrawal of consent, ineligibility, or physician choice, and the pandemic was not a significant contributing factor. Since March 2020 there have been 772 patient follow ups, of which 47% (364/772) have been virtual. Only 10% (102/1028) of trial mandated appointments have been missed to date. Compliance with baseline and 3-month FACT-ES questionnaires for the primary endpoint in evaluable patients was 90% (215/240) and 83% (198/240), respectively. The pandemic posed several challenges to the REaCT-RETT study including a decline in patient accrual, poor accrual at peripheral sites due to delayed opening, and a rapid switch to virtual patient care. However, the nimble REaCT methodology enabled virtual patient consent and data collection during the pandemic, allowing the trial to continue successfully, with final data expected for presentation summer 2022. Finally, despite the challenges of COVID-19 we have seen that patients and physicians remain interested in research, and we are applying valuable lessons learned to forthcoming REaCT trials to strengthen their performance during and beyond the ongoing pandemic. Citation Format: Sharon F Mc Gee, Mark Clemons, Michelle Liu, Mashari Jemaan Alzahrani, Terry Ng, Arif Awan, Sandeep Sehdev, John Hilton, Jean Michel Caudrelier, Marie France Savard, Lesley Fallowfield, Vikaash Kumar, Orit Freedman, Dean Fergusson, Gregory Pond, Brian Hutton, Jean Marc Bourque. A randomized, pragmatic trial investigating the timing of radiotherapy and endocrine in patients with early stage breast cancer (REaCT-RETT trial) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr OT1-01-01.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,036

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,010
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,004
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0110,001

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 Opus0,033
Tête enseignante GPT0,348
Écart entre enseignants0,315 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai randomisé
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

Citations2
Publié2022
Routes d'admission2
Résumé présentoui

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