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Cyclophosphamide, Bortezomib and Dexamethasone (CyBorD) Compared to Bortezomib, Thalidomide and Dexamethasone (VTD) As Induction Therapy for the Treatment of Transplant Eligible Multiple Myeloma

2016· article· en· W2639253133 on OpenAlexaffabout
Víctor H. Jiménez‐Zepeda, Nizar J. Bahlis, Peter Duggan, Rafael Alonso, Juan José Lahuerta, Antonio Valeri, Paola Neri, Jason Tay, Joaquín Martínez‐López

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsInstitute of Cancer ResearchUniversity of Calgary
Fundersnot available
KeywordsBortezomibMedicineThalidomideDexamethasoneMultiple myelomaRegimenCyclophosphamideInternal medicineAutologous stem-cell transplantationLenalidomideGastroenterologyOncologySurgeryChemotherapy

Abstract

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Abstract Introduction: Cyclophosphamide, bortezomib and Dexamethasone (CyBorD) has become the standard frontline approach for the treatment of multiple myeloma (MM) in many centers across Canada. A recent study led by the IFM group showed that the triplet combination of bortezomib, thalidomide and dexamethasone is superior as an induction regimen compared to CyBorD for patients undergoing ASCT. Based on the above-mentioned, we aimed to compare the effect of CyBorD and VTD for the treatment of transplant eligible MM patients in 2 different centers from Canada and Spain. Patients and Methods: The primary objective was to assess ORR and ³VGPR rates after induction and at day-100 post-ASCT, as well as MRD assessed by flow cytometry. Two-sided Fisher exact test was used to test for differences between categorical variables. A p value of <0.05 was considered significant and survival curves were constructed according to the Kaplan-Meier method and compared using the log rank test. Results: 101 patients have received CyBorD and 23 have received VTD. Clinical characteristics are shown in Table 1. At the time of analysis, 90 and 19 patients in the CyBorD and VTD are alive of which 25 and 9, respectively, have progressed. ORR and VGPR rates after a median of 4 cycles of induction were 94% and 56.4% for patients treated with CyBorD, and 91% and 78.2% for VTD, respectively (p=0.3 and 0.05). At day-100 post-ASCT, a ³VGPR rate of 84% and 94% was observed for the CyBorD and VTD groups, respectively (p=0.2). MRD negativity and CR rates were higher in the group receiving VTD (36.8% vs 27%, and 61% vs 38%, p=0.3 and 0.01). Furthermore, median OS and PFS did not differ among both groups (p=0.8 and 0.9, respectively) (Fig1a and Fig1b). In Conclusion: CyBorD and VTD appeared to be effective treatment options for transplant-eligible myeloma patients with similar response rates. Our study is in agreement with that reported by the IFM group, showing a higher rate of³VGPR after induction and day-100 post-ASCT in the VTD group. MRD negativity and CR rate appears also higher in the VTD group suggesting a higher degree of response by using animmunomodulatory drug and a proteasome inhibitor together. Overall Survival according to treatment regimen Overall Survival according to treatment regimen Figure 1 Progression-Free survival according to treatment regimen Figure 1. Progression-Free survival according to treatment regimen Disclosures Jimenez-Zepeda: Takeda: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Celgene, Janssen, Amgen, Onyx: Honoraria. Bahlis:Janssen: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria; Onyx: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau; BMS: Honoraria. Neri:Celgene and Jannsen: Consultancy, 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.312
Teacher spread0.274 · 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 designNon-randomized trial
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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Citations5
Published2016
Admission routes2
Has abstractyes

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