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Descriptive Analysis of Bortezomib Use in Multiple Myeloma in Four Adult University Teaching Hospitals in Quebec, Canada

2015· article· en· W2594828897 on OpenAlexaffabout
Nathalie Marcotte, M F Michel, Louise Deschênes, Nathalie Letarte, Daniel Froment, Émilie Lemieux‐Blanchard, France Varin, Ghislain Bérard, Paul Farand, Élaine Pelletier, Pierre Gaudreault, Chantal Guévremont, Raghu Rajan, Michaël Sébag

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsHôpital Notre-DameCentre Hospitalier Universitaire Sainte-JustineCentre Hospitalier Universitaire de SherbrookeMcGill UniversityCentre Hospitalier de l’Université de MontréalUniversité Laval
Fundersnot available
KeywordsBortezomibMedicineMultiple myelomaProteasome inhibitorInternal medicineAdverse effectMantle cell lymphomaAutologous stem-cell transplantationOncologyPopulationRegimenSurgeryLymphoma

Abstract

fetched live from OpenAlex

Abstract Background: Bortezomib, a reversible inhibitor of the 26S proteasome widely used in the treatment of multiple myeloma, is now being used in various other indications. Pharmacy directors gave the Therapeutic Drug Management Program (TDMP - www.pgtm.qc.ca) the mandate to evaluate bortezomib use in four University Hospitals in Quebec, Canada. Objectives: Describe bortezomib use for all indications in our hospitals and review its utilisation in the treatment of multiple myeloma. Methods: A review of pharmacy databases was performed to identify patients who received bortezomib between June1st 2012 and May 31st 2013. The pharmaceutical and medical records of every patient who received bortezomib were reviewed to assess the treatment, pathology and adverse events. Results: Two hundred and thirty two bortezomib regimens were administered to 227 different patients during the study period. Median age was 68. The most frequent indication (55%) was first-line treatment of multiple myeloma (n=128) followed by treatment of relapsed/refractory disease (31%) (n=73). Various other indications, including amyloidosis (n=17), lymphoplasmacytic lymphoma (n=12) and mantle cell lymphoma (n=2), represented 13% of the population. At the time of data analysis, 35% of patients were still treated with bortezomib, 25% had finished their planned treatment and 34% had discontinued treatment because of adverse events or disease progression. Fifteen patients (6%) died during the study period. Among the 45 patients eligible for autologous stem cell transplant (ASCT), the main regimen used was the association of bortezomib and dexamethasone (VelDex) (n=27), primarily using subcutaneous bortezomib (n=24) at 1.3 mg/m2 (n=30). Median treatment duration was four cycles. Twenty-eight patients have undergone ASCT and only two progressed. The association of bortezomib, melphalan and prednisone (VMP) (54.2%) followed by VelDex (29%) and the association of cyclophosphamide, bortezomib and dexamethasone (CyborD) (16.8%) were the regimens used in the population (n=83) not eligible to ASCT. Response rate using international uniform response criteria for multiple myeloma was 47.9% excluding patients still receiving treatment at the time of data collection. Seventy three patients received bortezomib for relapsed/refractory myeloma. Of these patients, thirty two (43.8%) discontinued therapy, nineteen due to disease progression, eight for the occurrence of side effects and five for other reasons. The initial dose was variable, from 1.0 to 1.6 mg/m2, and close to half of this patient population received CYBorD (49.4%), followed by VelDex (30.2%) and VMP protocols (15%). The number of cycles for patients who completed treatment (4 to 9) as well as the median exposure time (57 to 223 days) was also highly variable. Respectively 8.5% and 10.9% of the population treated with bortezomib for multiple myeloma were hospitalized (n=17) or had to discontinue treatment (n=22) because of adverse events (mostly hematologic toxicity, peripheral neuropathy or gastro-intestinal toxicity). Conclusions: Bortezomib is widely used in the treatment of multiple myeloma. Treatment algorithms should be developed and implemented to optimize the use of bortezomib, particularly in the relapsed/refractory setting. Standard regimens should also be implemented in each center. The utilisation of pre-printed orders for the prescription of chemotherapy regimens promotes uniform prescription. A review of the literature should be performed and recommendations should be made for the use of bortezomib in off-label indications like amyloidosis and lymphoplasmacytic lymphoma. Disclosures Off Label Use: bortezomib use in amyloidosis and lymphoplasmacitic lymphoma. Lemieux-Blanchard:celgene: Membership on an entity's Board of Directors or advisory committees; Amgen and Janssen: Other: preceptorship. Bérard:Janssen: Honoraria. Sebag:Janssen: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Novartis: Honoraria.

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)0.002
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 score0.061
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.251
Teacher spread0.219 · 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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Citations0
Published2015
Admission routes2
Has abstractyes

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