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Enregistrement W2949446669 · doi:10.1182/blood-2019-126867

Outcomes of Patients with t(11;14) Multiple Myeloma: An International Myeloma Working Group Multicenter Study

2019· article· en· W2949446669 sur OpenAlexaff
Shaji Kumar, Jin Lu, Yang Terry Liu, Max Bittrich, Juan Du, Hartmut Goldschmidt, Charalampia Kyriakou, Donna Reece, Kihyun Kım, María‐Victoria Mateos, Verónica González‐Calle, Wen-Ming Chen, Heinz Ludwig, Giampaolo Merlini, Silvia Mangiacavalli, Meletios Α. Dimopoulos, Eftathios Kastritis, Chang‐Ki Min, Graça Esteves, Andrew J. Yee, Noopur Raje, Emily Rosta, Anja Haltner, Chris Cameron, Brian G.M. Durie

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMultiple myelomaMedicineInternal medicineRegimenChromosome abnormalityCohortLenalidomideBortezomibStage (stratigraphy)Median follow-upOncologyGastroenterologySurgeryKaryotypeChemotherapyChromosomeBiology

Résumé

récupéré en direct d'OpenAlex

Background: Multiple myeloma (MM) is a heterogeneous disease with varying survival outcomes depending on the presence of certain genetic abnormalities. Common abnormalities include trisomies, translocations involving the chromosome 14, and amplifications or deletions of chromosomes 1, 13, and 17. t(11;14), occurring in 15% of patients with myeloma, had been considered a standard risk abnormality, but recent data suggest inferior outcome. This is important as new therapeutic options such as the BCL-2 inhibitor venetoclax has been shown to be particularly effective in t(11;14) patients. Methods: This was a multicenter study to identify the outcomes of patients with t(11;14), using a retrospectively assembled cohort. Patients with MM diagnosed between 2005 and 2015 with t(11;14) identified on FISH performed within six months of diagnosis, and with treatment details available and if alive, a minimum of 12 months of follow up, were enrolled. Results: The current analysis includes 1216 patients; median age of 62.56 years; 58.7% male. The median follow-up from diagnosis for the entire cohort was 51.9 months; 69.1% of the patients were alive at the last follow up. ISS stage distribution included: Stage I (35.7%), Stage II (34.0%) and Stage III (15.1%), data was missing for the rest. The distribution of concurrent FISH abnormalities included: trisomies (3.5%), del 13q (13.3%), 1q amp (8.8%), and del 17p or monosomy 17 (5.8%). Initial regimen included: 27.2% had an immunomodulatory (IMiD), 45.9% had a proteasome inhibitor (PI), 17.7% had both, and 9.0% had no novel agent. The drug classes by line of therapy are shown in Table 1. An early stem cell transplant (defined as within 12 months of start of first line treatment) was used in 49.4% of patients. The median time to next treatment (TTNT) after starting initial treatment was 26.6 (95% CI: 23.9 to 29.2) months. The median overall survival (OS) from diagnosis for the entire cohort was 95.1 (95% CI: 85.9 to 105.9) months; 4-year estimates for those diagnosed from January 2005 to December 2009, and from January 2010 to December 2014 were 77.5% and 78.6%, respectively. The median OS for those with any one high risk FISH lesion (del 17p/ 1q amp) was 67.5 (55.2, 97.1) versus 101.7 (89.7, 107.3) months. Patients with early SCT (within 12 months of diagnosis) had better OS: 108.3 (103.8, 133.0) vs. 69.8 (61.5, 80.3) months. Conclusion: Patients with t(11;14) without high risk FISH abnormalities have an excellent survival. Patients receiving a PI + IMiD combination and those receiving autologous SCT as part of initial therapy had best survival. Though numbers are limited, patients in the later lines receiving newer drugs such as venetoclax and daratumumab had high response rates and durable responses. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Bittrich:Celgene: Other: Travel Funding, Research Funding; Else Kröner Fresenius Foundation: Research Funding; Otsuka Pharmaceuticals Europe: Other: N/A; SANOFI Aventis: Membership on an entity's Board of Directors or advisory committees, N/A, Research Funding; University Hospital Wuerzburg: Employment; Bristol Myers Squibb: Research Funding; Pfizer: Other: Travel Funding; AMGEN: Other: Travel Funding; JAZZ Pharmaceuticals: Other: Travel Funding; Wilhelm Sander Foundation: Research Funding; German Research Foundation (DFG): Other: N/A; University of Würzburg: Other: N/A. Goldschmidt:Mundipharma: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; John-Hopkins University: Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; John-Hopkins University: Research Funding; Amgen: Consultancy, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Honoraria, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Reece:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Otsuka: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; BMS: 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; Takeda: Consultancy, Honoraria, Research Funding; Merck: Research Funding. Mateos:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees. Ludwig:Celgene: Speakers Bureau; Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; PharmaMar: Consultancy; Janssen: Speakers Bureau; BMS: Speakers Bureau. Mangiacavalli:celgene: Consultancy; Amgen: Consultancy; Janssen cilag: Consultancy. Dimopoulos:Sanofi Oncology: Research Funding. Kastritis:Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Honoraria; Prothena: Honoraria; Genesis: Honoraria. Yee:Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Karyopharm: Consultancy; Adaptive: Consultancy. Raje:Amgen Inc.: Consultancy; Bristol-Myers Squibb: Consultancy; Celgene Corporation: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Merck: Consultancy. Rosta:Cornerstone Research Group: Employment. Haltner:Cornerstone Research Group: Employment. Cameron:Cornerstone Research Group: Employment, Equity Ownership. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy.

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)0,002
score de la tête « metaresearch » (Gemma)0,002
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 seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
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 Opus0,019
Tête enseignante GPT0,284
Écart entre enseignants0,265 · 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

Citations7
Publié2019
Routes d'admission1
Résumé présentoui

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