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Allogeneic Stem Cell Transplantation for Multiple Myeloma: a Single Center Experience

2016· article· en· W2751006050 on OpenAlexaff
Amarilis Figueiredo, Harold Atkins, Natasha Kekre, Andrea Kew, Arleigh McCurdy

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of OttawaOttawa Hospital
Fundersnot available
KeywordsMedicineMultiple myelomaTransplantationSurgeryInternal medicineSingle CenterMelphalanAutologous stem-cell transplantationStem cellMedian follow-upRetrospective cohort studyCohortOncologyChemotherapy

Abstract

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Abstract Introduction The use of allogeneic stem cell transplantation (Allo-SCT) in patients with multiple myeloma (MM) remains controversial, but it offers prolonged disease free survival in some patients. It is unclear which patients should undergo Allo-SCT, what conditioning regimen should be used, and what the timing of the transplant should be in the course of the disease. Therefore, we sought to contribute our center's experience to the growing body of literature. Methods We performed a retrospective observational cohort study of all patients who underwent Allo-SCT for multiple myeloma at our center between January 1, 1992 and May 31, 2016. Categorical variables were compared using Pearson's chi-square test and the Kaplan-Meier method was used for the overall survival curves. Results Thirty-four patients underwent Allo-SCT for multiple myeloma and were included in this analysis. The median age was 40 years and 21 (62%) were male. Nineteen patients (56%) underwent Allo-SCT as upfront therapy, 1 (3%) underwent tandem autologous stem cell transplant (auto-SCT) followed by Allo-SCT, and 14 (41%) had salvage Allo-SCT at the time of relapse. Twenty-four (70.5%) patients had a matched related donor, 1 (3%) had a mis-matched related donor, 8 (23.5%) had matched unrelated donor and matching in 1 (3%) was not available. Myeloablative conditioning was given in 18 patients (52.9%) and non-myeloablative conditioning in 13 (38.2%) with 3 (8.8%) missing. The conditioning regimens included: 5 (15%) Flu-Mel, 7(20.6%) Flu-Bu, 13 (38%) Bu-Cy ± TBI, 6 (17.6%) MelVPTBI, and 3 (8.8%) were missing. Median overall survival (OS) for all patients was 72.5 months from diagnosis (figure 1) and 26.5 months from the time of Allo-SCT. For the 19 patients who had upfront Allo-SCT, median OS from diagnosis was 7.4 years compared to 5.3 years for those having salvage Allo-SCT (figure 2). However, in the upfront group 6 (32%) were alive 10 years post Allo-SCT and the survival curve reaches plateau, whereas in the salvage group, no patient was alive after 8 years post Allo-SCT. There was no difference in median survival between myeloablative and non myeloablative conditioning (2.9 versus 1.33 years, p=0.925). There have been 20 deaths in our cohort (59%); 5 (14.7%) from transplant related mortality within 1 year, 9 (26.5%) from disease progression, and 6 (17.6%) transplanted remotely whose cause of death is unknown. Conclusions Our data suggest that Allo-SCT offers prolonged disease free survival in some patients. In our small cohort, a greater proportion of patients undergoing upfront Allo-SCT achieved long term survival, raising the possibility that this group of patients may benefit more from Allo-SCT. Further prospective studies are needed to clarify the role of Allo-SCT in MM. Disclosures Kew: Celgene: Honoraria. McCurdy:Celgene: 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)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.036
GPT teacher head0.284
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
Published2016
Admission routes1
Has abstractyes

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