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Record W2913197449 · doi:10.1182/blood-2018-99-116795

Reduced Intensity Conditioning (RIC) Regimens Hematopoietic Cell Transplantation (HCT) for Acute Myeloid Leukemia (AML): A Comparison of Fludarabine/Busulfan (FB) and Fludarabine/Melphalan (FM) Based Regimens from the CIBMTR

2018· article· en· W2913197449 on OpenAlexaff
Rajneesh Nath, Zheng Zhou, Jan Černý, Hailin Wang, Khalid Bo-Subait, Zartash Guth, Gulrayz Ahmed, Muhammad Wagas Khan, Gerhard Hildebrandt, Hassan B. Alkhateeb, Moussab Damlaj, Mrinal M. Patnaik, Brenda M. Sandmaier, Daniel J. Weisdorf, Marcos de Lima, Mark R. Litzow, Wael Saber

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineFludarabineInternal medicineBusulfanMelphalanTransplantationAlemtuzumabOncologyGastroenterologyProportional hazards modelSurgeryHematopoietic stem cell transplantationCyclophosphamideChemotherapy

Abstract

fetched live from OpenAlex

Abstract Background: There is limited data comparing the outcomes of the two most common (FM or FB) RIC regimens in AML. Previous smaller retrospective studies suggest increased non-relapse mortality (NRM) but decreased relapse with FM based RIC with a variable effect on overall survival as compared to FB. Methods: AML patients aged ≥18 years who had their 1st allo HCT using FM or FB (iv Bu only) RIC between 2001-2015 who had data reported to CIBMTR were studied. Patients with cord blood or identical twin donors, TBI as a part of conditioning, GVHD prophylaxis with T cell depletion/CD34 selection or post HCT Cyclophosphamide were excluded. Primary endpoint was overall survival (OS), and secondary endpoints included non-relapse mortality (NRM), relapse, leukemia free survival (LFS) and acute and chronic GVHD. Cox proportional hazards multivariable regression was used to compare the two RIC regimens while adjusting for significant patient, disease and transplant related factors. Major subgroup analysis included patients in CR pre-HCT. Results: 622 patients received FB and 791 had FM RIC. Median age of the FM group was 59 years, range (18 to 76) and median age of FB group was 61 years, range (18- 77). Compared to FB RIC regimen, FM group had more patients with active disease (36% vs 18%), with mismatched donors (24% vs 15%), with bone marrow grafts (19% vs 9%), HCT before 2005 (29% vs 12%) and without ATG/alemtuzumab (58 % vs 48%); but fewer patients in CR1 (46% vs 62%) and matched sibling donor grafts (21% vs 30%). There was significantly increased NRM in the FM vs FB within 3 mo post HCT (hazard ratio (HR)=3.85 (95% confidence intervals [CI] 2.46-6.03), but not beyond 3 mo FM vs FB , HR= 1.14 (95% CI 0.88-1.47). There was significantly decreased relapse for FM vs FB, (HR=0.65 (0.55-0.76), p<0.001) and a marginally superior LFS for FM vs FB, (HR=0.89 (95% CI 0.78-1.00), p=0.05). There was a lower OS FM vs FB within 3 mo post HCT (HR=1.82 (95% CI 1.36-2.45), p<0.001) but similar OS for FM vs FB beyond 3 mo post HCT (HR=0.87 (95% CI 0.76-1.00), p=0.05). Analysis restricted to only patients in CR pre-HCT showed similar results: equivalent survival, higher early NRM and lower relapse with FM. Conclusion: The current study of this large CIBMTR AML transplant cohort has showed that in these two most common RIC regimens for allogeneic HCT, long-term survival with FM was similar to FB. While the FM regimen showed higher early NRM, it was associated with lower risks of relapse. Further analysis to evaluate FB and FM regimens in relationship to comorbidities, comprehensive geriatric assessments, and presence of minimal residual disease is warranted to better define the relative efficacy of these two RIC regimens in AML. Disclosures Weisdorf: Pharmacyclics: Consultancy; Seattle Genetics: Consultancy; SL Behring: Consultancy; FATE: Consultancy; Equillium: 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.301
Teacher spread0.278 · 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
Published2018
Admission routes1
Has abstractyes

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