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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 on 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

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineInternal medicineClinical trialFamily medicineSurgery

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.268
GPT teacher head0.449
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2015
Admission routes1
Has abstractyes

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