Model Based Approach to Evaluate Isatuximab Monthly Dosing Regimen in Relapsed/Refractory Multiple Myeloma Patients
Notice bibliographique
Résumé
Background: Isatuximab (Isa) is a CD38 monoclonal antibody with multiple modes of action for killing tumor cells through direct tumor targeting and immune cell engagement (Moreno, Clin Cancer Res, 2019). The addition of Isa to pomalidomide (P) and dexamethasone (d) was associated with a significant and clinically meaningful benefit in progression-free survival (PFS) in heavily pre-treated patients with relapsed/refractory multiple myeloma (RRMM) (ICARIA-MM, NCT02514668) (Attal, Lancet, 2019). Isa, in combination with Pd, is approved in the United States, the European Union, Canada, Australia, Switzerland, and Japan for the treatment of adult patients with RRMM who have received at least two prior therapies including lenalidomide and a proteasome inhibitor. Aim: The objectives were to characterize the relationship between serum M-protein kinetics and PFS in RRMM using data from the Phase 3 ICARIA-MM study and to simulate expected longitudinal serum M-protein and PFS when switching to a hypothetical monthly dosing regimen after 6 months. Methods: A joint model of serum M-protein dynamics and PFS was developed using data from 256 evaluable ICARIA-MM patients. Patients received Isa intravenously at 10 mg/kg once weekly (QW) for 4 weeks, then every other week (Q2W) for 28-day cycles in combination with standard Pd (Isa-Pd) or Pd alone in the control arm. A tumor growth inhibition model was used to describe the serum M-protein kinetics under treatment effects of Isa-Pd or Pd alone, in which Isa exposure was predicted using individual PK parameters obtained from the population PK analysis (Fau, Population Approach Group in Europe, 2019) and Pd exposure was predicted from K-PD model using dosing history. Trial simulations were then performed using individual PK/PD parameters of ICARIA-MM patients to evaluate whether efficacy is maintained after switching to a monthly dosing regimen. Results: The joint model identified the instantaneous changes (slope) in serum M-protein as the best on-treatment predictor for PFS and also identified baseline patient characteristics impacting serum M-protein kinetics (serum albumin and serum β2 microglobulin on the baseline serum M-protein levels and the non-IgG type on the serum M-protein growth rate, the serum M-protein slope), and PFS (presence of plasmacytomas). Non-IgG MM patients have similar behavior on serum M-protein kinetics for the first 60 weeks even with higher exposure and similar progression free survival compared to IgG MM patients supporting the non-dose adjustment based on IgG status. Clinical trial simulation of the ICARIA-MM Isa-Pd regimen demonstrated that switching all patients on treatment at 6 months to a monthly Isa regimen would shorten the median time to progression (TTP) (i.e. increase in serum M-protein greater than 25% and an absolute increase greater than 5 g/L compared to nadir) by 4.1 weeks and would shorten median PFS by 2.3 weeks (from 14.03 to 13.45 months). Based on TTP criteria, patients with no risk of earlier progression (57.7%) due to 6 months switch tend to have lower baseline tumor burden (lower serum M-protein and lower percent of bone marrow plasma cell) and better prognostic factors (higher glomerular filtration rate, higher albumin, lower β2 microglobulin). At 6 months, 85% of these patients had predicted stable "at least" VGPR status. Conclusions: Trial simulations supported the choice of the approved isatuximab 10 mg/kg QW/Q2W regimen and showed that switching to a monthly Isa regimen after 6 months may reduce clinical benefit in overall population. However, a subpopulation of patients with good prognosis and obtaining stable at least VGPR status by 6 months may switch to a monthly regimen after 6 months without compromising disease progression risk; this hypothesis will be tested in a prospective clinical trial. Model-based drug development has been successfully applied to support treatment decisions in RRMM patients. Disclosures Thai: Sanofi: Current Employment. Gaudel-Dedieu:Sanofi: Current Employment. Cerou:Sanofi: Current Employment. Sebastien:Sanofi: Current Employment. van de Velde:Sanofi: Current Employment, Current equity holder in publicly-traded company. Semiond:Sanofi: Current Employment. Veyrat-Follet:Sanofi: Current Employment.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
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 ».