Treatment of Multiple Myeloma Patients Progressing on Lenalidomide-Based Regimens
Notice bibliographique
Résumé
Lenalidomide in combination with dex (Len + dex) was introduced as treatment for relapsed/refractory myeloma in Canada over a decade ago; more recently, Len has been routinely available as part of first-line therapy, both in transplant-eligible patients-- as post-ASCT maintenance--and in transplant-ineligible patients as the Len + dex combination, and is typically given until disease progression. The management of patients progressing on Len regimens is evolving as newer anti-myeloma drugs become available. Many questions remain regarding the sequencing of treatments to obtain the longest periods of disease control between repeated relapses. We utilized the national Myeloma Canada Research Network (MCRN) Database to analyze therapy administered immediately after progression on a Len-based regimen in real-world practice. The MCRN Database contains disease-specific information on over 6000 patients reported from 13 academic centres in Canada. Between 2007 and 2019, 1482 patients (pts) progressed on Len-containing regimens in lines 1-3. 57% were male, 23% had light chain myeloma, 38% had high-risk FISH and 43% had undergone prior ASCT. Median values (range) for other pt characteristics included: age 64 range (31-92) yrs, creatinine 93 µmol/L (32-2700), B2M 329 nmol/L (range 1-7193), Hb 104 g/L (3-169), WBC 5.7 (0.12-107.6), platelets 211 (10-832), LDH 191 U/L (55-1908). The next regimen was based on bortezomib (BTZ) in 370, as part of a triplet in 278 (CyBorD, VMP); carfilzomib (CFZ) in 100, triplet in 62(KCD, KRD, KPD); ixazomib (IXA) in 75, triplet in 63 (IxaCD, IxaRD, IxaPomD); daratumumab (Dara) in 80, triplet in 75 (DaraCD, DaraRD, DaraPomD, DaraVD, DaraKD); pomalidomide (POM) in 195, triplet in 79 (PomCD/P, PomVD, PomKD); and continuation of Len in 212, triplet in 124 (RCD, RVD, RVCD). 346 (23%) did not receive any further therapy, including 79 (15%) after 1st line Len, 199 (26%) after 2nd line Len and 68 (33%) after 3rd line Len; other regimens were used in 6%, 18% and 11% of each group, respectively. The overall response rates (ORR)/median duration of treatment in months (mos) for each of the regimens included: BTZ 67%-5.8 mos; CFZ 70%-5.6 mos; IXA 60%-6.7 mos; Dara 86%-6.9 mos; POM 36%-4.0 mos; Len 39%-5.7 mos; and other 48%-3.3 mos. PFS by regimen is shown in Figure 1. 514 pts had progressed after Len as 1st line therapy, 766 after Len as 2nd line therapy and 202 after Len as 3rd line therapy. Median follow-up was 15 mos (1-130) after 1st progression and 55 mos (1-278) from diagnosis. The median PFS (95% CI) and OS (95% CI) after progression following Len as 1st line therapy were 14.5 mos (12.1-17.3) and 31.2 mos (25.3-39.0), as 2nd line therapy 8.6 mos (7.3-9.8) and 14.1 mos (11.6-16.5); and as 3rd line therapy 8.0 mos (6.7-9.9) and 11.0 mos (6.9-14.1), respectively. Figure 2 shows PFS by prior Len subgroup. More detailed analyses to assess outcomes for specific regimens after Len progression in different lines of therapy are in progress. In summary, this analysis provides an overview of treatment patterns following progression on Len in Canada, as well as the ORR, PFS and OS of different regimens. Results appeared better for proteasome inhibitor and Dara regimens after progression on Len, although some pts derived benefit from further Len regimens as well as POM-based ones; further exploration of specific treatment subgroups is ongoing. These data provide benchmarks for real-world outcomes that can be utilized as newer therapies, such as those based on immunotherapy, become available. Disclosures Reece: Amgen: Consultancy, Honoraria, Research Funding; Merck: Research Funding; BMS: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Otsuka: Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. McCurdy:Janssen: Honoraria; Celgene: Honoraria. Song:Janssen: Honoraria; Celgene: Honoraria, Research Funding; Amgen: Honoraria; Takeda: Honoraria. Sebag:Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Leblanc:Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Louzada:Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Bayer: Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. White:Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Stakiw:Janssen: Honoraria, Research Funding, Speakers Bureau; Roche: Research Funding; BMS: Honoraria; Novartis: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Lundbeck: Honoraria; Sanofi: Honoraria. Kotb:Karyopharm: Equity Ownership; Amgen: Honoraria; Merck: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Takeda: Honoraria. Venner:J&J: Research Funding; Takeda: Honoraria; Sanofi: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Amgen: Honoraria, Research Funding. OffLabel Disclosure: This abstract describes several combinations not specifically approved by the FDA but utilized in the real-world setting. However, all of the individual drugs in these combinations have been approved as single agents or in other combinations.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».