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Enregistrement W3030936584 · doi:10.1111/hae.14015

World Federation of Hemophilia Gene Therapy Registry

2020· article· en· W3030936584 sur OpenAlexaff
Barbara A. Konkle, Donna Coffin, Glenn F. Pierce, C. Clark, Lindsey A. George, Alfonso Iorio, Johnny Mahlangu, Mayss Naccache, Brian O’Mahony, Flora Peyvandi, S. W. PIPE, Adrian Quartel, Eileen K. Sawyer, Mark W. Skinner, Bartholomew J. Tortella, Crystal Watson, Ian Winburn

Notice bibliographique

RevueHaemophilia · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueHemophilia Treatment and Research
Établissements canadiensMcMaster UniversityCanadian Hemophilia Society
Organismes subventionnairesNational Heart, Lung, and Blood Institute
Mots-clésMedicineHaemophiliaClinical trialGenetic enhancementHaemophilia AIntensive care medicinePediatricsInternal medicineGene

Résumé

récupéré en direct d'OpenAlex

We are at an exciting juncture in the treatment of haemophilia. The first gene therapy product for patients with haemophilia could receive regulatory approval as soon as August 2020, with several other products close on the horizon. Gene therapy carries the potential for a ‘functional cure of haemophilia’, with bleeding essentially eliminated in the majority of treated patients for the duration of multi-year follow-up reports to date.1-3 This is a dream that has been in the making since the cloning of the F8 and F9 genes in the early 1980s.4-9 Although the potential for these transformative gene therapies is huge, emerging technologies by definition have some unknowns in their safety and efficacy profiles.10 Such novel therapies are usually evaluated and approved based on a small number of treated individuals. Most phase I-II gene therapy clinical trials in haemophilia enroll less than 30 patients and current phase III trial protocols plan for enrolment of 40-134 patients.11 For a long lasting, potentially life long, therapy, mandated follow-up by the FDA is only 5 years, a relatively short time.12 This imposes a heavy reliance on the postmarketing surveillance to gather critical post-therapy evidence of safety and durable efficacy.10 Some data will come from open-label extensions of ongoing phase III and future phase IV clinical trials; however, much of the burden will be on registry studies to amass long-term data on a large cohort of patients. While clinical trial data provide reassurance of short-term safety and efficacy of specific gene therapy products, we are entering this new treatment era with limited experience of the longer-term impact of gene therapy. Ultimately, the accumulation of patient exposure captured in longitudinal registries is the most robust means of revealing unexpected or rare events associated with this new technology class. Detecting low incident or delayed safety events, particularly in small treatment cohorts of a rare disease, necessitates that each patient who receives gene therapy be followed over the long term, preferably their lifetime. Our current knowledge leaves many unanswered questions about the safety and long-term efficacy of gene therapy.10, 13-16 These gaps in evidence dictate that we must all contribute to strengthening the evidence base. This data collection/surveillance effort should be a shared responsibility. Healthcare providers and patients will need to work together to collect standardized data on patients who receive gene therapy, ensuring that their experiences are captured in a registry, over their entire lifetime. Such longer-term data will assist regulators and manufacturers who are also closely monitoring signals of potential safety events and may provide assistance to payers regarding the efficacy and potential safety milestones needed to inform their reimbursement strategies. Surveillance in rare diseases such as haemophilia necessitates a global reach, as patients who receive gene therapy will be dispersed throughout many countries and continents.17 A global strategy is required to ensure a large enough patient pool to allow robust evaluation and detection of low-incident events that may otherwise go undetected. If events are captured in disparate registries or databases, it would be more complex, laborious, technically challenging and ultimately slower to combine the data. Such delays should be avoided at all cost. As the overall field of gene therapy continues to make progress, a growing set of long-term safety and efficacy data will ultimately define the future of gene therapy in haemophilia. Integrating the collection of data into the clinical practice of physicians and the daily lives of patients requires a harmonious and uniform data collection methodology that will be accepted and used by all stakeholders. Only through cohesive efforts by all treating physicians, patients, regulatory agencies and manufacturers worldwide, will we be successful in ensuring gene therapy is safe and efficacious for our patients today, and in the future. Through a collaboration with the International Society of Thrombosis and Hemostasis (ISTH), the European Haemophilia Consortium (EHC), the US National Hemophilia Foundation (NHF), the American Thrombosis and Hemostasis Network (ATHN), industry gene therapy development partners and Regulatory liaisons, the WFH has formulated a world Gene Therapy Registry (WFH GTR), that aims to collect a standardized set of core data, developed with input from a multi-stakeholder steering committee. The aim of the WFH GTR project is to provide a robust, scientifically valid data collection avenue, available to all healthcare providers treating patients who receive gene therapy. The WFH GTR will collaborate with individual haemophilia treatment centres and existing gene therapy registries to leverage established data repositories. A patient mobile application will allow integrating patient-reported outcomes directly into the WFH GTR. The data stemming from the WFH GTR will provide for robust ongoing surveillance of safety and efficacy.8 We are now expanding our outreach for the WFH GTR to the provider and patient communities with implementation of the registry to begin later in 2020.

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)0,000
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 enseignants0,092
Score d'incertitude au seuil0,714

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
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)0,0010,000

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 Opus0,076
Tête enseignante GPT0,321
Écart entre enseignants0,245 · 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

Citations51
Publié2020
Routes d'admission1
Résumé présentoui

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