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Pooled Safety Analysis From Phase (Ph) 1 and 2 Studies of Carfilzomib (CFZ) In Patients with Relapsed and/or Refractory Multiple Myeloma (MM)

2010· article· en· W2523786227 on OpenAlexaff
Seema Singhal, David S. Siegel, Thomas G. Martin, Ravi Vij, Michael Wang, Andrzej Jakubowiak, Sagar Lonial, Vishal Kukreti, Jeffrey A. Zonder, Alvin Wong, Leanne McCulloch, Michael Kauffman, Ashraf Badros, Rubén Niesvizky, Robert Z. Orlowski, A. Keith Stewart, Sundar Jagannath

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsCarfilzomibTolerabilityProteasome inhibitorNeutropeniaBortezomibMedicineAdverse effectInternal medicinePharmacologyMultiple myelomaToxicity

Abstract

fetched live from OpenAlex

Abstract Abstract 1954 Background: Carfilzomib (CFZ) is a novel, highly selective epoxyketone proteasome inhibitor that produces potent and sustained proteasome inhibition both in vitro and in vivo. CFZ appears to lack many of the off-target activities frequently associated with bortezomib (BTZ). This lack of off-target activity may account for observed differences in tolerability seen with CFZ including lack of significant neuropathy and minimal neutropenia and diarrhea. To date, single agent CFZ has been evaluated in Ph 1 and 2 studies in >600 patients, and the vast majority of patients treated had relapsed and/or refractory (R/R) MM. In these settings, CFZ has demonstrated durable single-agent activity and was well-tolerated in patients with advanced stage disease with co-morbidities including baseline neuropathy or renal insufficiency. Here we present the results of parallel safety analyses of patients from four Ph 1 and 2 studies with CFZ. Materials and Methods: The present safety analyses were based on data accumulated from patients enrolled in the following trials: PX-171-003 A0 (R/R MM), PX-171-003 A1 (R/R MM), PX-171-004 (relapsed MM), and PX-171-005 (R/R MM with varying degrees of renal function). In all studies, the treatment schedule was based on a 28-day cycle, dosing CFZ QDx2 each week for 3 weeks (Days 1, 2, 8, 9, 15, 16) with 12 days of rest. Doses of CFZ ranged from 15–20 mg/m2 in cycle 1 (005 [15 mg/m2], 003 A0 and A1, 004 [20 mg/m2]). In three studies CFZ was escalated to 27 mg/m2 after the first cycle, as tolerated (003- A1, 004-BTZ naïve subset and 005). In PX-171-005, low-dose dexamethasone was added in the majority of patients. Results: CFZ was well-tolerated by patients across the 4 studies analyzed. The most common treatment-emergent adverse events (AEs) included fatigue, anemia, nausea, dyspnea, and thrombocytopenia. Detailed descriptions of the incidence of treatment-related AEs (all Grades (G) in ≥25% of pts; ≥G3 in ≥5% of pts) across studies are presented in the table. Peripheral neuropathy (PN) occurred infrequently across all 4 studies (N= 517), with only 20 patients (3.9%) experiencing PN of any G and only 2 patients (0.4%) with G3 PN. Febrile neutropenia was likewise uncommon, occurring in only 3 patients (0.6%). Serious treatment emergent AEs (SAEs) occurring in ≥1% of patients and considered possibly/probably related to study drug across all 4 studies included: pneumonia (3.5%), congestive cardiac failure (2.5%), acute renal failure (1.7%), pyrexia (1.2%), and dyspnea (1%). Conclusions: Despite a substantial disease burden present in the patient populations described here, CFZ was well-tolerated by patients with MM across all studies examined. The excellent safety/tolerability profile of CFZ has permitted prolonged administration (in some cases over 24 mos of continuous therapy including extension study) with minimal dose modifications or discontinuations due to toxicity. The low levels of neuropathy seen with CFZ make this agent a potentially important treatment option for patients with pre-existing neuropathy from either underlying disease or prior neuropathic anti-myeloma therapy. Disclosures: Singhal: Celgene: Speakers Bureau; Takeda/Millenium: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Onyx: Research Funding. Siegel:Millenium: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Martin:Celgene: Honoraria; Onyx: Consultancy. Vij:Onyx: Honoraria. Wang:Celgene: Research Funding; Onyx: Research Funding; Millenium: Research Funding; Novartis: Research Funding. Jakubowiak:Millennium Pharmaceuticals, Inc.: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Celgene: Consultancy, Honoraria; Centocor Ortho Biotec: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Exelixis: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees. Lonial:Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Onyx: Consultancy, Research Funding. Kukreti:Celgene: Honoraria; Roche: Honoraria; Ortho Biotech: Honoraria. Zonder:Millenium: Consultancy, Honoraria, Research Funding; Cephalon: Research Funding; Celgene: Honoraria. Wong:Onyx Pharmaceuticals: Employment. McCulloch:Onyx Pharmaceuticals: Employment. Kauffman:Onyx Pharmaceuticals: Employment. Niesvizky:Celgene: Consultancy, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millenium: Consultancy, Membership on an entity’s Board of Directors or advisory committees, Research Funding, Speakers Bureau; Onyx: Consultancy, Research Funding. Stewart:Millennium: Consultancy; Celgene: Honoraria. Jagannath:Millenium, OrthoBiotec, Celgene, Merck, Onyx: Honoraria; Imedex, Medicom World Wide, Optum Health Education, PER Group: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau.

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)0.015
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.301
Teacher spread0.282 · 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 designMeta-analysis
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".

Quick stats

Citations11
Published2010
Admission routes1
Has abstractyes

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