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Enregistrement W4405044256 · doi:10.1182/blood-2024-194610

Efficacy and Safety of Pozelimab Plus Cemdisiran Vs Ravulizumab in Patients with Paroxysmal Nocturnal Hemoglobinuria Who Are Naïve to Complement Inhibition

2024· article· en· W4405044256 sur OpenAlexaff
Christopher J. Patriquin, Jun‐Ho Jang, Lisa Aurand, Deepak Taneja, Andrew P. Magyar, Bradley Dain, Karoline A. Meagher, Lorah Perlee, Amal Souttou, Morag Griffin

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueComplement system in diseases
Établissements canadiensToronto General HospitalUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésParoxysmal nocturnal hemoglobinuriaMedicineInternal medicineEculizumabClinical endpointGastroenterologyInterim analysisNeutropeniaClinical trialSurgeryAntibodyImmunologyChemotherapyComplement system

Résumé

récupéré en direct d'OpenAlex

Background: Paroxysmal nocturnal hemoglobinuria (PNH) is an ultra-rare, acquired, life-threatening disorder, characterized by hemolysis and an increased risk of thrombosis often co-existing with bone marrow insufficiency. Standard of care includes C5 inhibitors, given as chronic intravenous (IV) infusions. The combination of pozelimab and cemdisiran (combo), administered subcutaneously (SC) after one IV loading dose, is a novel approach currently being investigated for its ability to achieve complete, durable inhibition of terminal complement. Pozelimab is an investigational monoclonal antibody that binds to and inhibits activation of C5 while cemdisiran is a silencing RNA that reduces circulating C5. Here, we present results from an exploratory arm of a 26-week (wk), phase 3, open-label, active-controlled trial (NCT05133531) along with interim results of a follow-on open label extension (OLE) study (NCT05744921). Aims/Methods: Treatment-naïve patients (pts) with PNH were randomized 1:1 (combo vs ravulizumab [ravu]) in the main trial. Combo pts received SC treatment every 4 wks (Q4W). From wk 2, ravu was administered IV every 8 wks per label. Both arms included an initial IV loading dose on day 1. The primary efficacy endpoint was the change in intravascular hemolysis assessed by lactate dehydrogenase (LDH). All pts who enrolled in the 108-wk OLE received combo SC Q4W. Ravu pts entering the OLE transitioned to combo therapy over a period of 8 wks following completion of the main trial. The last ravu dose was given 8 wks prior to OLE start. Results: Forty-eight pts were randomized (n=25 combo, n=23 ravu). Mean baseline LDH was 6.5x ULN in combo pts and 6.1x ULN in ravu pts. At wk 26, mean LDH was 0.8x ULN in combo pts and 1.2x ULN in ravu pts. From wks 8 - 26, LDH ≤1.5x ULN was maintained at every visit in 88% of combo pts vs 74% of ravu pts. The % of pts with LDH ≤1.5x ULN across each post-baseline visits ranged from 96-100% with combo vs 65-87% with ravu. Similarly, the % of pts with LDH ≤1x ULN ranged from 67-96% with combo vs 35-74% on ravu. Five of 23 pts treated with ravu and 1/25 on combo failed to achieve meaningful LDH control. Transfusion avoidance was defined as not requiring a red blood cell transfusion based on post-baseline hemoglobin values. A similar number of pts in each arm met criteria for transfusion avoidance (14 combo, 15 ravu). One pt in each arm had breakthrough hemolysis in the main study. Nineteen pts switched from ravu to combo in the OLE (data cut-off Feb 15, 2024), of whom 68% had an LDH ≤1.5x ULN at baseline. After switching to combo, >90% had an LDH ≤1.5x ULN at each visit. Four of 5 pts (80%) not achieving meaningful LDH control on ravu in the main trial achieved control with combo. In the main trial, 84% of combo pts vs 87% of ravu pts had treatment-emergent adverse events (TEAEs); the most common was headache (7 pts [28%] combo vs 4 pts [17%] ravu). Two pts (8%) on combo had serious adverse events (SAEs): 1 with post-traumatic cellulitis that resolved with treatment, and 1 with fever, seizure, and hemolytic crisis within 1 wk of the first combo dose, and prior to achieving LDH control, that resolved on treatment; on day 130 of the study this pt had a fatal SAE of sepsis and disseminated intravascular coagulation. No SAEs were reported in patients who received ravu. In the OLE, 13 (68.4%) pts had TEAEs with the most common being injection site reactions (3 pts,15.8%). Three (15.8%) pts had SAEs (1 pt with pyrexia; 1 pt with a urinary tract infection and a fall; and 1 pt with acute hemolysis secondary to infection and Klebsiella pneumonia; all recovered with treatment). No pt discontinued combo due to an adverse event. There were notype 3 hypersensitivity TEAEs due to large drug-target-drug (DTD) immune complexes nor fatal TEAEs. Conclusion: The combination of pozelimab and cemdisiran led to robust control of LDH, with more pts achieving meaningful LDH control vs ravu. The safety profile is generally consistent with other approved C5 inhibitors. The potential transition regimen using cemdisiran to reduce C5 prior to administering a different C5 antibody appears effective at mitigating DTD reactions. Results support development of the combination of pozelimab and cemdisiran in PNH and other complement-mediated diseases.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,003
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,008
Tête enseignante GPT0,227
Écart entre enseignants0,218 · 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

Citations3
Publié2024
Routes d'admission1
Résumé présentoui

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