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Enregistrement W4389231477 · doi:10.1182/blood-2023-187233

Comparison of Time to Next Treatment or Death between Front-Line Daratumumab, Lenalidomide, and Dexamethasone (DRd) and Bortezomib, Lenalidomide, and Dexamethasone (VRd) in Transplant Ineligible Patients with Multiple Myeloma

2023· article· en· W4389231477 sur OpenAlexaff
Doris K. Hansen, Santosh Gautam, Marie‐Hélène Lafeuille, Carmine Rossi, Bronwyn Moore, Anabelle Tardif‐Samson, Philippe Thompson‐Leduc, Alex Z. Fu, Annelore Cortoos, Shuchita Kaila, Rafaël Fonseca

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensGroup for Research in Decision Analysis
Organismes subventionnairesnon disponible
Mots-clésLenalidomideDaratumumabMedicinePopulationInternal medicineDexamethasoneMultiple myelomaCohortBortezomibSurgeryOncology

Résumé

récupéré en direct d'OpenAlex

Introduction: Daratumumab, lenalidomide, and dexamethasone (DRd) and bortezomib, lenalidomide, and dexamethasone (VRd) are the only two regimens that are considered as preferred per the National Comprehensive Care Network for transplant ineligible (TIE) patients with newly diagnosed multiple myeloma (NDMM). While there are no head-to-head studies comparing clinical outcomes of DRd and VRd in this population, an indirect comparison (PEGASUS study [Durie et al., 2020]) has shown that DRd was associated with significantly lower risk of disease progression or death compared with VRd and Rd. This study aims at supplementing this information by comparing real-world time-to-next-treatment (TTNT) or death between NDMM TIE patients treated with front-line (FL) DRd or VRd. Methods: A retrospective cohort study was conducted for patients with NDMM who initiated FL DRd or VRd in Acentrus (1/1/2018 - 5/31/2023), an electronic medical record (EMR) database from academic and non-teaching hospitals in the United States. Patients were included if they had ≥2 records with an ICD-10-CM diagnosis code for MM, ≥6 months of data availability prior to first record with MM diagnosis (without use of antineoplastic agent), initiated FL treatment (initiation of DRd or VRd; index date) within 12 months of first record of MM diagnosis, and ≥90 days of data availability post-index. Patients with pre-index diagnosis of amyloidosis or other cancers and those who participated in a clinical trial before or during FL treatment were excluded. To limit the analysis to the TIE population, patients who had a record of a stem-cell transplant (SCT) before or during FL treatment and those who were <65 years old (used as proxy to SCT eligibility) were excluded. Patient characteristics were evaluated up to 12-months pre-index (baseline period). Patients were followed from the index date until earliest of date of initiation of a next line of treatment, death, or end of data availability. Medications received within 60 days from the date of the first MM antineoplastic agent were considered as FL therapy regimen. Next line of treatment was identified as initiation of a new antineoplastic agent (excluding corticosteroids) outside of FL therapy or re-treatment of FL after >90-day gap. Inverse probability of treatment weighting (IPTW) was used to balance baseline characteristics between study cohorts, with variables with standardized differences <10% considered balanced. Weighted Kaplan-Meier (KM) curves and a doubly-robust Cox proportional hazards model adjusting for baseline variables remaining imbalanced after IPTW were used compare TTNT or death between study cohorts. Results: Overall, 149 and 494 patients were identified in the DRd and VRd cohorts, respectively. After weighting (N DRd weighted = 302, N VRd weighted = 341), most baseline characteristics in both cohorts were similar, including mean age (DRd: 75.3, VRd: 74.5), female sex (DRd: 48.9%, VRd: 45.8%), white race (DRd: 55.8%, VRd: 58.7%), black race (DRd: 8.8%, VRd: 11.3%), Medicare insurance coverage (DRd: 62.7%, VRd: 65.9%), and mean Quan-Charlson comorbidity index (DRd: 3.8, VRd: 3.6; Table 1). Some imbalances remained for mean age, race, ethnicity, and index year, thus they were additionally adjusted for in doubly-robust Cox model. The median duration of follow-up was 20.2 months and 21.5 months among DRd and VRd patients, respectively. A total of 98 (32.4%) DRd patients and 175 (51.2%) VRd patients received a subsequent line of therapy or died, with the median TTNT or death being 37.8 and 18.7 months in the DRd and VRd cohorts, respectively (hazard ratio: 0.58, 95% CI: 0.35, 0.81; p<0.001; Figure 1). KM estimates for patients remaining on FL therapy were significantly higher for DRd than VRd at 6 months (93.0% vs. 80.1%), 12 months (80.0% vs. 61.0%), 18 months (64.9% vs. 51.3%), and 24 months (60.2% vs. 42.9%). Conclusion: In this retrospective cohort study using EMR data, TIE NDMM patients who initiated DRd had a significantly longer time to next treatment or death than patients who initiated VRd. Results from this real-world study fills an unmet data gap by providing information on the comparative effectiveness evidence for DRd versus VRd among TIE NDMM patients. These findings support the use of DRd as an effective treatment option in the TIE NDMM patient population.

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 enseignants0,003
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,060
Tête enseignante GPT0,331
Écart entre enseignants0,271 · 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

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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