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Record W3216633465 · doi:10.1182/blood-2021-151862

Supermobilizers with High CD34 + Cell Collection for Autologous Transplant and Impact on Survival Outcomes in Multiple Myeloma

2021· article· en· W3216633465 on OpenAlexaff
Eyal Lebel, Katherine Lajkosz, Esther Masih‐Khan, Donna Reece, Suzanne Trudel, Rodger E. Tiedemann, Anca Prica, Vishal Kukreti, Christine I. Chen

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineMultiple myelomaBortezomibCD34Autologous stem-cell transplantationLenalidomideCyclophosphamideTransplantationInternal medicineVincristineLeukapheresisOncologyUrologyStem cellDexamethasoneSurgeryChemotherapyBiology

Abstract

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Abstract Introduction: Autologous stem cell transplantation (ASCT) is standard therapy for selected patients with newly diagnosed multiple myeloma (MM). Studies in MM and lymphoma have suggested that ability to mobilize and collect a higher yield of CD34 + cells predicts for improved survival outcomes, perhaps reflecting better bone marrow reserve (Bolwell 2007, Raschle 2011). We aimed to validate this hypothesis by correlating high CD34 + cell collection ("supermobilizers") and survival outcomes in a large myeloma cohort with long follow-up. Methods: We retrospectively reviewed MM patients (pts) who underwent ASCT at our centre 2000-2010, correlating number of CD34 + cells collected with post-transplant progression-free survival (PFS) and overall survival (OS). Stem cells were mobilized using cyclophosphamide 2.5 g/m 2 IV (day 1), G-CSF 10 ug/kg/day SC (starting on day 4), and leukapheresis (day 11), targeting 4x10 6/kg but accepting a minimum of 2x10 6/kg to support a single transplant. Using a cut-off used in previous studies, pts were categorized as "supermobilizers" if ≥8x10 6/kg CD34+ cells were collected. Results: 621 pts were analyzed. Most pts (422/605; 70%) received high dose dexamethasone (HDD) alone or in combination with vincristine and adriamycin (VAD) for pre-transplant induction therapy (pre-dating the novel agent era) with only 18% (110/605) receiving more contemporary bortezomib-based induction (mostly cyclophosphamide, bortezomib and dexamethasone; CyBORD). The median number of CD34 + cells collected for all pts was 13.9x10 6/kg (range 2.1-61.8). The median CD34 + cells re-infused was 6.2x10 6/kg (range 2.1-25), as some cells were reserved for 2 nd ASCT, but median CD34+ cells collected correlated with CD34 + cells infused (Pearson coefficient 0.81, p<0.001). At a median follow-up of 74 months (m), we were surprised to report an inferior PFS of 24.1m for the supermobilizers collecting ≥8x10 6/kg vs 33.7m for the <8 group (p=0.038, Figure 1a), without differences in OS (p=0.612, Figure 1b). No further discrimination in PFS was observed when using a more extreme supermobilizer cut-off of 15x10 6/kg. To further understand the counterintuitive result of shorter PFS with higher mobilization capacity, we explored the continuous relationship between CD34 + cells and PFS, identifying another optimal cut-off of 4.5x10 6/kg. Pts collecting in the mid-range (4.5-8; n=129) achieved the best PFS of 34.5m, significantly improved over 24.1m in the ≥8 group (n=478) and 11.4m in the small group at the extreme lower collection range (n=14; ≤4.5x10 6/kg)(Figure 1c). A similar pattern was seen with OS (Figure 1d). Clinical and laboratory parameters that may impact both collection capacity and survival, such as age, ISS, and kidney dysfunction, were investigated as confounders but were similar between collection groups and did not predict for PFS in multivariable analyses. Treatment variables, however, differed between groups: the lower collection groups more often received bortezomib-based induction (29%, 31% and 14% in the ≤4.5, 4.5-8 and ≥8 groups, respectively, p<0.001) resulting in deeper responses pre-transplant (VGPR 50% in the ≥8 group vs 43% in the 4.5-8 group, p=0.024) (Table 1). Use of maintenance therapy post-ASCT also differed (50%, 40% and 28% in the ≤4.5, 4.5-8 and ≥8 groups, respectively, p=0.006). Discussion: In this large cohort of 621 MM patients, we report that "supermobilizers" who collected ≥8 x 10 6 CD34 + cells/kg exhibit inferior PFS from transplant than those with less robust mobilization. We suspected that this unexpected observation was due to confounding variables, and identified differences in treatment, primarily greater use of bortezomib-based induction and post-transplant maintenance therapy in the lower collection group. This group was able to achieve deeper responses (≥VGPR) even before transplant than the supermobilizer group, leading to improved PFS. Although bortezomib is routinely used as induction therapy pre-transplant currently and is not felt to be stem cell toxic, it may impair mobilization to a lesser degree, leading not to abject failure of collection but lowered capacity to achieve "supermobilizer" status. Although more research is needed to validate this hypothesis, we can at minimum conclude that high stem cell collection does not appear to predict for a long-term survival advantage. Figure 1 Figure 1. Disclosures Reece: Millennium: Research Funding; Sanofi: Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Research Funding; GSK: Honoraria; BMS: Honoraria, Research Funding. Trudel: Amgen: Honoraria, Research Funding; BMS/Celgene: Consultancy, Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Genentech: Research Funding; Sanofi: Honoraria; Pfizer: Honoraria, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Roche: Consultancy. Prica: Astra-Zeneca: Honoraria; Kite Gilead: Honoraria. Chen: Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astrazeneca: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; 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)0.002
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 score0.002
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.283
Teacher spread0.262 · 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
Published2021
Admission routes1
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