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Enregistrement W4405040983 · doi:10.1182/blood-2024-201712

Real-World Characteristics and Treatment Patterns of Transplant-Eligible Patients with Newly Diagnosed Multiple Myeloma Treated with Daratumumab, Bortezomib, Lenalidomide, and Dexamethasone (DVRd) As Front-Line Treatment: Results from a Multicenter Chart Review Study

2024· article· en· W4405040983 sur OpenAlexaff
Carlyn Tan, Lucio Gordan, Rachel Dileo, Prerna Mewawalla, Sarah Larson, Faith E. Davies, David Oveisi, Niodita Gupta-Werner, Rohan Medhekar, Annelore Cortoos, Marjohn Armoon, Alvi Rahman, Claire Vanden Eynde, Marie‐Hélène Lafeuille, John Reitan, Gary Milkovitch, Joseph Bubalo, Adam Forman, Douglas W. Sborov, Shuchita Kaila, Saad Z. Usmani

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensGroup for Research in Decision Analysis
Organismes subventionnairesnon disponible
Mots-clésDaratumumabLenalidomideBortezomibMedicineDexamethasoneMultiple myelomaInternal medicineOncology

Résumé

récupéré en direct d'OpenAlex

Introduction: The treatment paradigm for transplant-eligible (TE) patients (pts) with newly diagnosed multiple myeloma (NDMM) is shifting from frontline (FL) triplet (e.g., bortezomib [V], lenalidomide [R], and dexamethasone [d]) towards FL quadruplet regimens based on the pivotal PERSEUS and GRIFFIN trials, which showed that addition of daratumumab (D) to VRd during induction/consolidation followed by DR maintenance improved response as well as progression-free survival compared to VRd followed by R maintenance. In the real world, pt characteristics and treatment patterns, including maintenance therapy selection, may differ from clinical trial protocols. Therefore, this study aimed to describe the demographic and clinical characteristics as well as treatment patterns (overall and stratified by maintenance regimen) among TE NDMM pts treated with DVRd as FL therapy in the real-world. Methods: A retrospective, multi-center, chart review study was conducted at 9 clinical sites in the US. All eligible adults (except at one site, where eligible pts were randomly selected) with TE NDMM initiating FL DVRd therapy between January 1, 2019, and June 30, 2022, were included (index date = date of initiation). Pts were excluded if they previously received any treatment for MM for ≥30 days, previously participated in a clinical trial related to MM, were treated for any other invasive malignancy within 12 months prior to FL DVRd initiation or had amyloidosis at the index date. Demographic and clinical characteristics were evaluated up to 12 months pre-index and pts were followed until death or the last record of clinical activity. This abstract presents results from an interim analysis. Results: A total of 180 pts initiating FL DVRd were included (median [interquartile range] age: 63 [12.5] years, age ≥65 years: 46.1%; male: 58.3%; White: 67.8%; Black: 11.7%), with a median follow-up of 26.4 months. Of 158 pts with a reported Eastern Cooperative Oncology Group (ECOG) score, 43.0% had a score of 0. Moreover, 86 pts had a reported R-ISS stage (I: 32.6%, II: 41.9%, III: 25.6%). Out of 151 pts with available data, 39 (25.8%) had high-risk cytogenetic abnormalities (HRC), including del[17p], t[14;16], or t[4;14]. Baseline demographics and disease characteristics are in line with the pts treated with DVRd in the PERSEUS (median age: 61.0 years; male: 59.4%; White: 93.0%; ECOG 0: 62.3%, HRC: 21.4%) and GRIFFIN (median age: 59.0 years; male: 55.8%; White: 82.0%; Black: 13% ECOG 0: 38.6%, HRC: 16%) trials. During follow-up, the median duration of the DVRd induction phase was 6.1 months and 128 (71.1%) pts received an autologous stem cell transplantation (SCT). Of the 51 pts without SCT, 37 (72.5%) deferred transplant, among which 21 (56.8%) of the deferrals went directly to maintenance therapy, with 14 (66.7%) using >1 agent in maintenance. In the overall population, 17 (9.4%) pts received consolidation therapy and 155 (86.1%) pts received maintenance therapy, including 64 (41.2%) with R monotherapy, 60 (38.7%) with DR, 12 with VR, 7 with DV, 6 with DVR, 4 with V monotherapy, and 2 with D monotherapy. The cohort treated with DVRd induction followed by DR maintenance (DVRd-DR) was slightly older (median: 65 years), had more males (63.3%), and a lower proportion of Black pts (6.7%) than the cohort with DVRd induction followed by R maintenance (DVRd-R; median age: 62 years, males: 56.3%, and Black: 14.1%). More pts in the DVRd-R cohort received a SCT (79.7% vs. 68.3%) than those in the DVRd-DR cohort. Compared to the DVRd-DR cohort, more pts with DVRd-R had ECOG score of ≥1 (63.9% vs. 45.0%). In contrast, the DVRd-DR cohort had more pts with HRC (17.0%) compared to DVRd-R (13.0%). For the DVRd-R and DVRd-DR group, the median duration of the induction phase was 6.4 and 6.1 months, respectively, and median duration of active maintenance was 16.5 and 14.3 months, respectively. Conclusion: Compared to pts in the PERSEUS trial, the TE NDMM pts treated with FL DVRd identified in this real-world chart review study were observed to be older, and with a more diverse racial profile comparable to the US-only GRIFFIN trial population. In the real-world, use of consolidation therapy was less common and DVRd-DR maintenance was used more often in pts aged ≥65 years and in those with higher cytogenetic risk. Also, fewer pts with DVRd-DR than DVRd-R received a SCT. Data on outcomes will be presented at the conference, with additional pts expected.

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)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
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 Opus0,023
Tête enseignante GPT0,288
Écart entre enseignants0,264 · 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'étudeObservationnel
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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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