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Contribution of Chemotherapy Mobilization to Disease Control in Multiple Myeloma Treated with Autologous Transplantation

2014· article· en· W2595753835 on OpenAlexaboutno aff
Luciano J. Costa, Geoffrey L. Uy, Parameswaran Hari, Mei‐Jie Zhang, Jiaxing Huang, Amrita Krishnan, Tomer M. Mark, Anita D’Souza

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMultiple myelomaLenalidomideInternal medicineMelphalanThalidomideTransplantationMucositisRegimenPlerixaforCyclophosphamideChemotherapySurgeryOncologyClinical endpointChemotherapy regimenGastroenterologyRandomized controlled trial

Abstract

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Abstract Background: Autologous hematopoietic progenitor cells (auto-HC) can be mobilized either by hematopoietic growth factors (GF) alone or cytotoxic chemotherapy + GF (CC+GF). The latter is associated with higher CD34+ yields, but is associated with increased costs and risks of infection and hospitalization. In patients with multiple myeloma (MM) undergoing Auto-HCT, it is uncertain whether mobilization with CC+GF affects post transplant outcomes. Methods: We conducted a retrospective analysis of patients with MM undergoing their first AHPCT following high dose melphalan (≥140 mg/m2) between 2007 and 2012 in US and Canada and registered with the Center for International Blood and Marrow Transplant Research (CIBMTR). Patients who had a planned subsequent allogeneic transplant, received VAD or similar induction therapy, had disease progression prior to transplant, or were mobilized with plerixafor were excluded from the analysis. The primary endpoint was progression-free survival (PFS) and the main secondary end-points were transplant-related mortality (TRM), relapse and overall survival (OS). Results: There were 519 patients in GF and 449 in CC+GF with median follow-up of 42 and 46 months respectively. The most common mobilizing CC regimen was single agent cyclophosphamide (71%). GF and CC+GF groups were similar but there were more patients in GF with only one prior line of therapy, lenalidomide exposure and CR at the time of transplant and more patients in CC+GF with low HCT co-morbidity index, prior thalidomide exposure and planed second autologous transplant (Table 1). Median number of days for auto-HC collection was 2 (IQR 1-3) in GF and 1 (IQR 1-3) in CC+GF (P<0.001). There were fewer days between collection and transplant (median 16 vs. 18, P<0.001) and fewer CD34+ cells (x 106/kg) infused at transplant (median 3.9, IQR=3.1-4.8, vs. 5.1, IQR 3.5-6.9, P<0.001) in GF than in CC+GF. Kinetics of neutrophil engraftment (> 0.5 x 109/L) was similar between groups (13 vs. 13 days, P=0.69) while platelet engraftment (> 20 x 109/L) was faster in CC+GF (median 19 vs. 18 days, P=0.006). There was no difference between groups in number of hospitalization days (14 vs. 14, P=0.7). In univariate analysis, there was no significant difference between the two groups in OS, PFS, or TRM. In multivariate analysis, stage III at diagnosis and Karnofsky status <90 but not modality of mobilization were associated with worse PFS. Similarly HCT-CI >2, Stage III at diagnosis and immunoglobulin isotype (IgG/IgA/Others), but not mobilization were associated with OS. Adjusted 3-years PFS was 43% (95% C.I. 38-48) in GF and 40% (95% C.I. 35-45) in CC+GF, P=0.33 (Figure). Adjusted 3-years OS was 82% (95% C.I. 78-86) vs 80% (95% C.I. 75-84), P=0.43 and adjusted 5-year OS was 62% (95C.I. 54-68) vs. 60% (95% C.I. 52-67), P=0.76, for GF and CC+GF respectively (Figure). Conclusions: MM patients undergoing AHPCT have similar outcomes irrespective of the use of cytotoxic chemotherapy mobilization. We found no evidence that chemotherapy mobilization contributes to disease control in MM. Table Characteristics of patients and treatments GF CC+GF P N=519 N=449 Lines of therapy <0.001 1 382 (74) 265 (59) 2 113 (22) 136 (30) >2 24 (5) 48 (11) Prior therapy <0.001 Thalidomide+Bortezomb+-Steroid 74 (14) 92 (20) Lenalidomide+Bortezomb+-Steroid 121 (23) 48 (11) Thaildomide+-Steroid 85 (16) 106 (24) Bortezomib+-Steroid 132 (25) 136 (30) Lenalidomide+-Steroid 107 (21) 67 (15) Disease status at HCT 0.05 CR 84 (16) 48 (11) PR 407 (78) 378 (84) MR/NR/SD 28 (5) 23 (4) HCT-CI 0.006 0 227 (44) 227 (51) 1-2 147 (29) 134 (30) >2 145 (28) 88(20) Time from diagnosis to HCT <0.001 <6 mo 221 (43) 140 (31) 6-12 mo 298 (57) 309 (69) Year of HCT 0.03 2007-2008 289 (56) 272 (61) 2009-2010 105 (20) 100 (22) 2011-2012 125 (24) 77 (17) Melphalan dose 0.40 140-180 mg/m2 71 (14) 70 (16) >180 mg/m2 448 (86) 379 (84) Transplant type 0.02 Single transplant 417 (80) 331 (74) Multiple Transplants Planned 2ndAuto (0-6 mo) 42 (8) 63 (14) Planned 2ndAuto (>6 mo) 5 (1) 6 (1) Use of maintenance agent 198 (38) 176 (39) 0.29 Figure 1 Figure 1. Disclosures Costa: Sanofi: Honoraria.

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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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.257
Teacher spread0.248 · 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
Published2014
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