AB0796 CANVASC CONSENSUS RECOMMENDATIONS FOR THE USE OF AVACOPAN IN ANTINEUTROPHIL CYTOPLASM ANTIBODY-ASSOCIATED VASCULITIS: 2022 ADDENDUM
Notice bibliographique
Résumé
Background In 2020, the Canadian Vasculitis Research Network (CanVasc) published their updated recommendations for the management of antineutrophil cytoplasm antibody (ANCA)-associated vasculitides (AAV). Since then, clinical data on the complement C5a receptor inhibitor avacopan (formerly, CCX168) has continued to expand. Objectives The current addendum provides further recommendations regarding the use of avacopan in AAV based on a review of newly available evidence. Methods An updated systematic literature review on avacopan using Medline, Embase, and the Cochrane Library was performed for publications up to September 2022. New recommendations were developed and categorized according to the EULAR grading levels, as done for previous CanVasc recommendations. A modified Delphi procedure and videoconferences were used to reach ≥80% consensus on the inclusion, wording and grading of each recommendation. Results Three new recommendations were developed. They focus on avacopan therapy indication and duration, as well as timely glucocorticoid tapering. Conclusion These 2022 addended recommendations provide rheumatologists, nephrologists, and other specialists caring for patients with AAV with guidance for the use of avacopan, based on current evidence and consensus from Canadian experts. References [1]Jayne DRW, Merkel PA, Schall TJ, Bekker P; ADVOCATE Study Group. Avacopan for the Treatment of ANCA-Associated Vasculitis. N Engl J Med. 2021;384(7):599-609. [2]Jayne DRW, Bruchfeld AN, Harper L, et al. Randomized Trial of C5a Receptor Inhibitor Avacopan in ANCA-Associated Vasculitis. J Am Soc Nephrol. 2017;28(9):2756-2767. [3]Merkel PA, Niles J, Jimenez R, et al. Adjunctive Treatment With Avacopan, an Oral C5a Receptor Inhibitor, in Patients With Antineutrophil Cytoplasmic Antibody-Associated Vasculitis. ACR Open Rheumatol. 2020;2(11):662-671. [4]van Leeuwen JR, Bredewold OW, van Dam LS, et al. Compassionate Use of Avacopan in Difficult-to-Treat Antineutrophil Cytoplasmic Antibody-Associated Vasculitis. Kidney Int Rep. 2021;7(3):624-628. [5]Gabilan C, Pfirmann P, Ribes D, et al. Avacopan as First-Line Treatment in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: A Steroid-Sparing Option. Kidney Int Rep. 2022;7(5):1115-1118. [6]Mendel A, Ennis D, Go E, et al. CanVasc Consensus Recommendations for the Management of Antineutrophil Cytoplasm Antibody-associated Vasculitis: 2020 Update. J Rheumatol. 2021;48(4):555-566. Acknowledgements CanVasc wishes to acknowledge the work of Matt Adamson, Sarah Ali, Susanne Benseler MD, Jean-Philippe Bergeron MD, Stephanie Garner MD, Majed Khraishi MD, and Frédéric Morin MD for their additional input on the final draft of the recommendations. Disclosure of Interests David Turgeon: None declared, Volodko Bakowsky Speakers bureau: Abbvie, Consultant of: Advisory board attendance from Abbvie, Apotex, Eli Lily, Novartis, Pfizer, Jamp, and Sandoz UCB, Corisande Baldwin: None declared, David Cabral: None declared, Marie Clements-Baker Speakers bureau: Honoraria from Abbvie, Novartis, Boehringer Ingleheim and Otsuka, Alison Clifford Speakers bureau: Hoffman La-Roche Limited, Consultant of: Participation in clinical trials with Abbvie and UCB, Jan Willem Cohen Tervaert Speakers bureau: Pfizer, Sanofi, AbbVie, Hoffmann-La Roche, Medexus, and GSK, Paid instructor for: Chair IDMC InflaRx (2017-2022), Consultant of: Merck, Novartis, and Mallinckrodt Pharmaceuticals, Natasha Dehghan: None declared, Daniel Ennis: None declared, LEILANI FAMORCA: None declared, Aurore Fifi-Mah Speakers bureau: ChemoCentryx, Grant/research support from: Roche, Louis-Philippe Girard: None declared, Frédéric Lefebvre: None declared, Patrick Liang Grant/research support from: Roche, Amgen, Janssen, Abbvie, BMS, and Novartis, Jean-Paul Makhzoum Speakers bureau: Teva, Otsuka Pfizer, GKS, and Jansenn, David Massicotte-Azarniouch: None declared, Arielle Mendel: None declared, Nataliya Milman Consultant of: Otsuka, Heather Reich Consultant of: Calliditas, Novartis, Pfizer, Eledon, Omeros, Travere and Chinnook, David Robinson: None declared, Carolyn Ross: None declared, Dax G. Rumsey Consultant of: AbbVie, Mylan, and Novartis, Grant/research support from: Pfizer, Medha Soowamber: None declared, Tanveer Towheed: None declared, Judith Trudeau Consultant of: Hoffman-Laroche, Medexus, and ChemoCentryx, Marinka Twilt: None declared, Elaine Yacyshyn: None declared, Gozde Yardimci: None declared, [Nader Khalidi} Consultant of: Roche, Bristol Meyers Squibb, Lillian Barra Consultant of: Roche, Bristol-Myers Squibb, Boehringer-Ingelheim, Otsuka and Pfizer, Grant/research support from: Pfizer, Christian Pagnoux Speakers bureau: ChemoCentryx, Astra-Zeneca, and InflaRx GmbH, Grant/research support from: Roche, GSK, Otsuka, Pfizer.
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 | 0,043 | 0,107 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,009 |
| Bibliométrie | 0,015 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,006 | 0,005 |
| Intégrité de la recherche | 0,011 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,018 |
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 ».