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Enregistrement W4411425995 · doi:10.1016/j.ard.2025.06.474

POS1123 Myositis Community Proposes a Framework to Guide Clinical Trials and Ensure Patient Safety during Influx of CAR-Based Therapies

2025· article· en· W4411425995 sur OpenAlexaff
Lesley Ann Saketkoo, K. Cheng, Ingrid de Groot, Marjolein Visser, Susan Shenoi, Mazen M. Dimachkie, Gary S. Gilkeson, Victoria P. Werth, J. Day, Jibi Paul, Kunal Chandwar, Takahisa Gono, Julie J. Paik, A. Valenzuela Vegara, Felix Muehlensiepen, Elie Naddaf, Floranne C. Ernste, Jemima Albayda, Pari Basharat, Helene Alexanderson, Barbara Shafranski, K.B. Highland, Laurel Stine, Vincenzo Venerito, Linda Kobert, C. Galloway, Carmine V. Oddis, Rebecca Nicolai, Jaimy E. Koopman, Edoardo Marrani, Ho So, Jennifer Andrews, Constantin von zur Mühlen, Amer Khojah, Rukhsana G. Mirza, Pandiarajan Vignesh, Adam M. Huber, Eduardo Dourado, Margherita Giannini, M. Kuwana, V. Leclair, L. Chung, Adeel Zubair, Joselyn Sanchez, Chih‐Wei Tseng, Manuel Lubinus, Adele Meyer, David Araújo, Siamak Moghadam‐Kia, Bin Yi, B. Bader-Meunier, M. Sumaila, Faysal Gök, Lilia Andrade Ortega, Patrick Gordon, Astia Allenzara, Anna Haemel, Niels Vidiendal Olsen, M. Shaaf, Ricardo Gómez, Jéssica M. de Souza, William J Gregory, Arti Sharma, Mireia López-Corbeto, Iazsmin Bauer Ventura, Nicolás González, Charikleia Papadopoulou, G.W.G. Bird, Marco Fornaro, J. Vencovský, Joanna Makowska, Arturo Benitez, Alicia Fernández, S. O'Connor, Marwin Groener, A. Dihkan, Christopher F. Lowe, Pedro Machado

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueBiomedical Ethics and Regulation
Établissements canadiensMcGill UniversityDalhousie UniversityMcMaster UniversityWestern University
Organismes subventionnairesnon disponible
Mots-clésMedicineMyositisClinical trialIntensive care medicineMedical emergencyMedical physicsPhysical therapyPhysical medicine and rehabilitationPathology

Résumé

récupéré en direct d'OpenAlex

Background: Chimeric Antigen Receptor T-cell (CAR-T) and other cellular targets holds promise for ‘refractory' connective tissue diseases (CTDs) through potential ‘resetting' the cellularity of bone marrow and thus re-directing the behaviour of the immune system. The intention is to bring the disease course to potential complete ‘remission' [1]. Lately, there has been a surge in clinical trials in myositis, and a growing number of CAR therapy trials since a case series of successfully treated patients with CTDs were published [2]. In the myositis rare disease space, a total of 42 interventional drug trials worldwide are currently recruiting of which 19 (45%) are CAR therapies [3]. Objectives: Amidst confusion and pressure expressed by both patients and early investigators, the Myositis International Health & Research Collaborative Alliance (MIHRA) Clinical Trial Sites Network (CTSN) set out to systematically identify concerns which were increasingly expressed in our global network of patient organisations, with the hypothesis that actionable concerns related to CAR trials will emerge from community-voiced perceptions & experiences [4, 5]. Methods: Qualitative investigations in an open-ended, unrestricted response survey design queried two major myositis stakeholders 1. Patients/patient supporters and 2. Investigators. Stakeholders were contacted through the MIHRA investigator membership, MIHRA Patient Contact Registry and outreach efforts by the MIHRA Patient Advisory. In addition, a global forum to present and discuss the interim analysis with investigators and patients occurred on 14 December 2024 [6]. Respondents self-reported their role and demographic details. Due to perceived urgency and to avoid delays in the anticipated need for task force formation, a multi-stage grounded theory analysis was devised to use the results from the 1st stage of the analysis to identify major/urgent, actionable concerns and, if so, to convene as a community in a timely manner to develop strategies that address these. In the stage 1 analysis (reported here), globally repetitive concepts are extracted by manual coding. In the stage 2 analysis, a highly detailed deductive qualitative content analysis supported by large language model applications will take place. Results: 103 patient and 77 pediatric & adult investigator respondents from 32 countries/6 continents participated in the study. Stage 1 analysis yielded 7 preliminary ‘concern' domains of which 3 were shared by both groups with sub-domains (diagram) some with overlapping concepts. Four urgent patient & investigator collaborations were identified during the forum which were to establish: 1. Educational materials and communication protocols that are patient-centered and patient-driven/developed which are a perceived as a critical unmet need voiced in this effort. 2. Preliminary treatment algorithm defining ‘refractory' that accounts for disease activity, severity, rate of progression and extent of irreversible though symptomatic damage. 3. Preliminary models for logistics of site initiation and inter-disciplinary collaboration. 4. Dialogue between regulatory agencies, industry, and the patient and investigator communities to strategize a cautious combined rate of enrollment during this discovery period and attempt to stabilise the trial landscape to protect the investigations of other promising therapeutics with possibly wider relevance than CAR therapies. Further deliverables are anticipated with Stage 2 analyses. Table 1 . Conclusion: CAR therapies offer promising potential in CTDs, providing targeted and long-lasting treatments through the potential of directing the immune system to act with precision. However, both sets of stakeholders express strong concern that the surge in CAR-based therapy trials is ‘overwhelming' with high pressure for patient enrollment and site initiation. But yet, there is insufficient safety information and many unknowns for the projected rate of enrollment in CTDs and IIMs, populations that are very different than the originally studied oncology populations. Furthermore, there is lack of adequate investigator & patient educational materials, which has been voiced as potentially compromising the consent process. Also voiced were the challenges for sites inexperienced in non-oncological CAR therapy applications who are struggling to navigate site initiation and voice being ill-equipped to manage financial and procedural logistics to ensure timely activation, quality implementation, and with proper safety measures in place. Based on these analyses, immediate action is being planned to address urgent needs. REFERENCES: [1] Schett G et al. Nat Rev Rheumatol. 2024 Sep;20(9):531-544. [2] Müller F et al. N Engl J Med. 2024 Feb 22;390(8):687-700. [3] www.clinicaltrials.gov. Last accessed 12 January 2025. [4] Saketkoo LA et al. Clin Exp Rheumatol. 2024 Feb;42(2):207-212. [5] Azevedo SF et al. Ann Rheum Dis. 2024 Oct 21;83(11):e22. [6] Saketkoo et al, https://mihrafoundation.org/mihra-ctsn-car-t-trials-community-forum/; last accessed 12 January 2025. Acknowledgements: NIL . Disclosure of Interests: Lesley Ann Saketkoo The list presented for the 1st author is representative of conflict of interest for all authors: Janssen, Johnson & Johnson, Abbvie, The list presented for the 1st author is representative of conflict of interest for all authors: Argenx, aTyr, Boehringer Ingelheim, EMD Serono, Pfizer, The list presented for the 1st author is representative of conflict of interest for all authors: Argenx, aTyr, EMD Serono, Horizon, Kinevant, Mallinckrodt, Pfizer, Karen Cheng Sobi Pharmaceuticals, Ingrid de Groot: None declared, Marianne de Visser Please see 1st author listing, Please see 1st author listing, Susan Shenoi: None declared, Mazen Dimachkie Several - please see 1st author listing, Several - please see 1st author listing, Gary Gilkeson Several - please see 1st author listing, several - please see 1st author listing, Victoria P. Werth several - please see 1st author listing, several, please see 1st author listing, Jessica Day NKARTA, several - please see 1st author listing, Jisna Paul Please see 1st author listing, Kunal Ashutosh Chandwar: None declared, Takahisa Gono Please see 1st author listing, Please see 1st author listing, Latika Gupta Please see 1st author listing, Please see 1st author listing, Julie Paik Please see 1st author listings, Please see 1st author listings, Please see 1st author listings, Antonia Valenzuela Vegara Please see 1st author listings, Please see 1st author listings, Felix Muehlensiepen AbbVie, Novartis, AbbVie, Novartis, Elie Naddaf Please see listing in 1st author, Please see listing in 1st author, Please see listing in 1st author, Floranne C. Ernste: None declared, Jemima Albayda Please see listing under 1st author, Please see listing under 1st author, Please see listing under 1st author, Pari Basharat: None declared, Helene Alexanderson: None declared, Barbara Shafranski: None declared, Kristin Highland Please see 1st author listing, Please see 1st author listing, Please see 1st author listing, Lisa Christopher Stine Please see 1st author listing, Please see 1st author listing, Please see 1st author listing, Vincenzo Venerito Please see 1st author listing, Please see 1st author listing, Please see 1st author listing, Linda Kobert: None declared, Chip Galloway: None declared, Chester V Oddis Please see 1st author listing, Please see 1st author listing, Please see 1st author listing, Rebecca Nicolai: None declared, Jacob Koopman: None declared, Edoardo Marrani: None declared, Ho So: None declared, James Andrews: None declared, Carlos von Muhlen: None declared, Amer Khojah: None declared, Reza Mirza: None declared, Pandiarajan Vignesh: None declared, Adam Huber: None declared, Eduardo Dourado: None declared, Margherita Giannini: None declared, Masataka Kuwana Please see 1st author listings, Please see 1st author listings, Please see 1st author listings, Valérie Leclair: None declared, Lorinda Chung Kyverna, CRSPR Tx, Kyverna, CRISPR Tx, Adeel S. Zubair: None declared, Joseph Sanchez: None declared, Chih-Wei Tseng: None declared, Manuel Lubinus: None declared, Alain Meyer: None declared, DANIEL BRITO DE ARAUJO: None declared, Siamak Moghadam-Kia: None declared, Belina Yi: None declared, Brigitte Bader-Meunier: None declared, Mintah Sumaila: None declared, Faysal Gok: None declared, Lilia Andrade Ortega: None declared, Patrick Gordon: None declared, Astia Allenzara: None declared, Anna Haemel: None declared, Nancy Olsen: None declared, Muhammad Shaaf: None declared, Ramiro Gomez: None declared, Jean Marcus de Souza: None declared, William Gregory: None declared, Akanksha Sharma: None declared, Mireia López-Corbeto: None declared, Iazsmin Ventura: None declared, Natalia Gonzalez: None declared, Charalampia Papadopoulou: None declared, georgina bird: None declared, Marco Fornaro: None declared, Jiří Vencovský: None declared, Joanna Makowska: None declared, Alejandro Benitez: None declared, Anthony Fernandez: None declared, Shannon O'Connor: None declared, Marwin Groener: None declared, Anneli Dihkan: None declared, Christine Lowe: None declared, Pedro Machado Please see 1st author listing, Please see 1st author listing, Please see 1st author listing. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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)0,270
score de la tête « metaresearch » (Gemma)0,198
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesMétarecherche
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,730
Score d'incertitude au seuil0,900

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,2700,198
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0040,002
Études des sciences et des technologies0,0250,047
Communication savante0,0290,024
Science ouverte0,0100,048
Intégrité de la recherche0,0250,039
Charge utile insuffisante (le modèle a refusé de juger)0,0100,005

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 Opus0,109
Tête enseignante GPT0,459
Écart entre enseignants0,350 · 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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
DomaineMéthodes
GenreMéthodes

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
Publié2025
Routes d'admission1
Résumé présentoui

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Même revueAnnals of the Rheumatic DiseasesMême sujetBiomedical Ethics and RegulationTravaux en français237 207