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Natural History of Relapsed Myeloma, Refractory to Immunomodulatory Drugs and Proteasome Inhibitors: A Multicenter IMWG Study

2016· article· en· W2612511582 on OpenAlexaff
Shaji Kumar, Meletios Α. Dimopoulos, Efstathios Kastritis, Evangelos Terpos, Hareth Nahi, Hartmut Goldschmidt, Jens Hillengaß, Xavier Leleu, Meral Beksaç, Melissa Alsina, Albert Oriol, Michèle Cavo, Enrique M. Ocio, María‐Victoria Mateos, Elizabeth O’Donnell, Ravi Vij, Henk M. Lokhorst, Niels W.C.J. van de Donk, Chang‐Ki Min, Tomer M. Mark, Ingemar Turesson, Markus Hansson, Heinz Ludwig, Sundar Jagannath, Michel Delforge, Charalampia Kyriakou, Parameswaran Hari, Ulf‐Henrik Mellqvist, Saad Z. Usmani, Dominik Dytfeld, Ashraf Badros, Philippe Moreau, Kihyun Kım, Paula Rodríguez‐Otero, Jae Hoon Lee, Chaim Shustik, Daniel D. Waller, Wee Joo Chng, Shuji Ozaki, Je‐Jung Lee, Javier de la Rubia, Hyeon Seok Eom, Laura Rosiñol, Juan José Lahuerta, Anna Sureda, Jin Seok Kim, Brian G.M. Durie

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMultiple myelomaPomalidomideLenalidomideMedicineBortezomibRefractory (planetary science)IxazomibProteasome inhibitorInternal medicineNatural historyOncologyCarfilzomibThalidomideBiology

Abstract

fetched live from OpenAlex

Abstract Background: Treatment of multiple myeloma has evolved considerably in the past few years with availability of several news drugs as well as increasing use of multidrug combinations. These changes have no doubt led to the improved survival seen among patients with MM. We have previously shown that outcomes of patients intolerant or refractory to one of the IMiDs and bortezomib had a poor outcome. Since that time, other drugs of the same class as well as new classes of drugs have been introduced for the treatment of MM. We designed this retrospective study to estimate the outcomes in patients with relapsed myeloma, who have become refractory to the current generation IMiDs and proteasome inhibitors. Patients and Methods: Patients with relapsed multiple myeloma who have received at least 3 prior lines of therapy, is refractory to both an IMiD (lenalidomide or pomalidomide) AND a proteasome inhibitor (bortezomib or carfilzomib), and has been exposed to an alkylating agent were identified from multiple centers. The time patients met the above criteria was defined as T0, and details of all treatment regimens before and after T0 were collected using electronic CRFs. The study was approved by the IRB at the respective centers. Results: 543 patients were enrolled in this study; median age was 62 years (31-87) and 61% were males. Patients were enrolled from centers in North America (n=181), Europe (n=318), and Asia Pacific (n=44). Patients were diagnosed between 2006 and 2014, the median duration between diagnosis of myeloma and study entry (T0) was 3.1 years (0.3 to 9). The median (95% CI) estimated follow up from diagnosis and from T0 were 61 (57, 66) months and 13 (11, 15) months respectively. The median number of lines of therapy prior to T0 was 4 (3-13), 48% had a prior transplant. The median OS from T0 for the entire cohort was 13 (11, 15) months. For these 462 patients, the median number of recorded regimens was 2 (1-9). The overall response and the depth of response to each line of treatment following T0 are as shown in the table. The median (95% CI) PFS and OS from T0 was 5 (4, 6), and 15.2 (13, 17), respectively. The overall survival for the 81 patients with no treatment post T0 was only 2.1 months. In a multivariate analysis, duration from diagnosis to T0, ISS stage III and number of lines of therapy were all associated with inferior PFS, as well as OS, and in addition, serum creatinine>2 mg/dL at T0 also predicted inferior OS. Conclusions: The study provides the expected outcome following development of myeloma that is refractory to a PI and an IMiD. The outcomes of these patients appear to be better than we had seen historically in patients refractory/ intolerant to bortezomib and IMiDs, highlighting the increased treatment options available for these patients. However, there is decreasing response rate to sequential regimens highlighting the development of drug resistance. The data provides a bench mark for comparison of new therapies that are being evaluated in this disease. Table Table. Disclosures Dimopoulos: Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genesis: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Kastritis:Takeda: Consultancy, Honoraria; Genesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Terpos:BMS: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Celgene: Honoraria; Takeda: Consultancy, Honoraria; Genesis: Consultancy, Honoraria, Other: Travel expenses; Amgen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Novartis: Honoraria. Hillengass:Sanofi: Research Funding; Novartis: Research Funding; Amgen: Consultancy, Honoraria; BMS: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria. Leleu:TEVA: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; LeoPharma: Honoraria; Amgen: Honoraria; Bristol-Myers Squibb: Honoraria; Pierre Fabre: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Takeda: Honoraria. Oriol:Janssen: Honoraria, Other: Expert board committee; Amgen: Honoraria, Other: Expert board committee. Cavo:Celgene: Consultancy, Honoraria; Millennium: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Mateos:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: 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; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Vij:Shire: Consultancy; Takeda: Consultancy, Research Funding; Jazz: Consultancy; Karyopharma: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy, Research Funding. Lokhorst:Genmab: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. van de Donk:Amgen: Research Funding; Janssen: Research Funding; BMS: Research Funding; Celgene: Research Funding. Mark:Onyx: Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Ludwig:Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau; BMS: Speakers Bureau; Janssen: Speakers Bureau. Jagannath:Novartis: Consultancy; Janssen: Consultancy; Bristol-Myers Squibb: Consultancy; Celgene: Consultancy; Merck: Consultancy. Usmani:Array: Research Funding; Britsol-Myers Squibb: Consultancy, Research Funding; Skyline: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BioPharma: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Speakers Bureau. Dytfeld:Janssen Poland: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees. Moreau:Novartis: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Takeda: Honoraria; Janssen: Honoraria, Speakers Bureau. Lee:Amgen: Membership on an entity's Board of Directors or advisory committees. Shustik:Janssen: 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; Millenium: 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; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. de la Rubia:Celgene: Consultancy; Bristol Myers: Consultancy; Amgen,: Consultancy; Janssen: Consultancy. Durie:Takeda: Consultancy; Amgen: Consultancy; Janssen: Consultancy.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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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Citations31
Published2016
Admission routes1
Has abstractyes

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