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Enregistrement W2559685064 · doi:10.1182/blood.v126.23.3034.3034

Analysis of Final Data from the Multinational, Non-Interventional, Observational Emmos Study (NCT01241396) in Patients (Pts) with Multiple Myeloma (MM) in Real-World Clinical Practice

2015· article· en· W2559685064 sur OpenAlexaff
Mohamad Mohty, Evangelos Terpos, María‐Victoria Mateos, Antonio Palumbo, Sandra Lejniece, Meral Beksaç, Mohamed Amine Bekadja, Wojciech Legieć, Meletios Α. Dimopoulos, Svetlana Stankovic, María Soledad Durán, Valerio De Stefano, Alessandro Corso, Yulia Kochkareva, Edward Laane, Christian Berthou, Hans-Juergen Salwender, Zvenyslava Masliak, Valdas Pečeliūnas, Wolfgang Willenbacher, João Da Silva, Vernon Louw, Damir Nemet, Zita Borbényi, Uri Abadi, Robert Schou Pedersen, Peter Černelč, Anna Potamianou, Catherine Couturier, Robert A. Olie, Caroline Feys, Florence Thoret-Bauchet, Mario Boccadoro

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineInternal medicineClinical trialFamily medicineSurgery

Résumé

récupéré en direct d'OpenAlex

Abstract Background A lack of objective data exists on differences in treatment practices and outcomes for MM between countries. The EMMOS study aimed to document and describe current treatment regimens and disease progression patterns of MM pts at different stages of the disease in real-world medical practice. Methods Adult pts initiating any new MM therapy, irrespective of treatment line at study entry or therapy type received, were eligible for inclusion in the EMMOS registry. A multi-staged pt/site recruitment model was applied to minimize selection bias; enrollment was stratified by country, region, and practice type. Pts' medical/disease features, treatment history, and remission status were recorded at baseline. Prospective data on treatment, efficacy, and safety were collected electronically every 3 mos until 2 yrs after the last pt enrolled. Responses were investigator-assessed (no predefined criteria). Here we report data from the final analysis of EMMOS. Pts were grouped according to receipt of high-dose chemotherapy/stem cell transplantation in any treatment line (SCT pts, non-SCT pts). Within a given line, pts may have received induction, SCT, consolidation, and/or maintenance therapy; if multiple drug combinations were used within a line, the line grouping was based on the combination received in cycle 1. Results 2358 pts were enrolled between Oct 2010-Oct 2012 in 22 countries in Europe and Africa; the last pt completed follow-up in Oct 2014. Of these, 775 pts had undergone SCT in any treatment line. Baseline characteristics in the prospective phase by starting line are shown in the Table. As expected, there was a higher proportion of younger pts (≤65 yrs) in the SCT vs non-SCT group across all treatment lines, and in both groups a higher proportion of pts in 4th + vs earlier lines with ISS stage III disease. While cytogenetics were evaluated in a small number of pts overall (670/2358 [28%]), these assessments were performed significantly more frequently in SCT vs non-SCT pts (p<0.0001). In 380 prospective 1st line (L1) SCT pts, 299 (79%) underwent SCT-based treatment in L1; induction was with a bortezomib (btz)-based combination in 83% (47% btz without immunomodulatory drug [IMiD]; 36% btz + IMiD), IMiD in 11%, and other (ie. no btz/IMiD) in 6%. In 81 SCT pts who received non-SCT-based treatment in L1 (21%), 36% received btz without IMiD, 40% other, and 17% IMiD-based combinations. In 345 pts receiving L2, most frequent therapies were btz without IMiD (45% of pts), IMiD without btz (30%), other (13%), and btz + IMiD (12%); non-btz/IMiD combinations were increasingly prevalent in pts receiving L3 or L4 (24% and 40%, respectively). In the non-SCT population, 58% of pts received a btz-based combination in L1, most frequently btz without IMiDs (54%). In pts receiving L2, btz or IMID were equally represented (39%); in L3, non-SCT pts were most likely to receive other therapies (39%) versus 27% btz without IMiD and 32% IMiD without btz. Based on preliminary data, mean EQ5D score at baseline was 0.316 (range -0.594, 0.731) in the overall pt population, which increased slightly to 0.410 (-0.429, 0.731) at 12 mos and was largely comparable between countries. Resource utilization (hospitalization, ICU, ER visit, outpatient visit, full-time care) appeared highest in Germany (67.6 records per pt) and lowest in Croatia (7.5 per pt), with those in Germany spending a mean of 12.1 days in hospital per stay. Efficacy/safety data will be presented at the meeting. Conclusion This large, real-world, observational study provides for the first time a comprehensive picture of the baseline characteristics and therapy of MM pts treated in Europe, the Middle-East, and Africa. These data provide a framework towards the design of future protocols aiming to improve outcomes in MM. Table. Baseline characteristics by starting line Non-SCT pts SCT pts L1 (n=897) L2 (n=319) L3 (n=184) L4+ (n=166) Total* (N=1566) L1 (n=378) L2 (n=161) L3 (n=107) L4+ (n=120) Total* (N=775) Age ≤65 yrs, % 36 34 35 39 36 87 76 72 71 80 ISS Stage II/III, % 36/44 34/47 43/38 22/52 35/44 33/35 44/27 34/26 23/48 34/34 Salmon-Durie Stage 2/3, % 28/64 25/66 24/71 29/62 27/65 22/68 25/67 20/65 11/81 20/69 Bone lesion history, % 64 72 75 70 68 66 74 77 80 71 Cytogenetics assessed, % 24 19 19 14 21 51 35 43 33 44 Del 17p 8 8 9 13 8 10 7 4 13 9 t(4,14) 6 7 9 4 6 7 14 13 8 9 ISS, International staging system; L, line *17 non-SCT and 9 SCT pts were enrolled but did not receive a line of therapy within 75 days of baseline Disclosures Mohty: Celgene: Honoraria; Janssen: Honoraria. Terpos:Amgen: Honoraria, Research Funding; Janssen: Honoraria; Celgene: Honoraria; Novartis: Honoraria. Mateos:Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees. Palumbo:Array BioPharma: Consultancy; Onyx Pharmaceuticals: Consultancy; Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Genmab A/S: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy; Sanofi Aventis: Consultancy. Lejniece:Amgen: Honoraria; Sandoz: Honoraria. Beksac:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen-Cilag: Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Dimopoulos:Novartis: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Onyx: Honoraria; Celgene: Honoraria; Genesis Pharma: Research Funding. De Stefano:Shire: Speakers Bureau; Roche: Research Funding; Bruno Farmaceutici: Research Funding; Janssen Cilag: Research Funding; Amgen: Speakers Bureau; GlaxoSmithKline: Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Celgene: Speakers Bureau. Salwender:Celgene: Honoraria; Janssen Cilag: Honoraria; Bristol Meyer Sqibb: Honoraria; Amgen: Honoraria; Novartis: Honoraria. Pečeliūnas:Johnson & Johnson: Honoraria, Research Funding. Willenbacher:CTI: Consultancy, Other: Travel, Accommodations, Expenses; Gilead: Consultancy, Other: Travel, Accommodations, Expenses, Speakers Bureau; Amgen: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Janssen: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Roche: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding; Celgene: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding; Novartis: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses, Research Funding. Da Silva:Janssen Pharmaceuticals: Research Funding. Louw:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Nemet:Sanofi: Honoraria; Pliva: Honoraria; Pfizer: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Potamianou:Janssen: Employment. Couturier:Janssen-Cilag: Employment. Olie:Johnson & Johnson: Equity Ownership; Janssen-Cilag: Employment. Feys:Janssen Pharmaceutica N.V.: Employment, Equity Ownership. Thoret-Bauchet:Janssen-Cilag: 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 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)0,008
score de la tête « metaresearch » (Gemma)0,018
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 enseignants0,008
Score d'incertitude au seuil0,044

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,018
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,003
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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 Opus0,268
Tête enseignante GPT0,449
Écart entre enseignants0,181 · 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

Citations1
Publié2015
Routes d'admission1
Résumé présentoui

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