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PB2331 IMPACT OF PRETRANSPLANT CHEMOTHERAPY, GRAFT VERSUS HOST DISEASE PROPHYLAXIS, GENDER AND RISK GROUP ON ALLOGENEIC REDUCED INTENSITY CONDITIONING TRANSPLANTS FOR ELDERLY ACUTE MYELOID LEUKEMIA PATIENTS

2019· article· en· W2949825634 on OpenAlexaff
Thomas Kiss, Malin Nicklasson, Jaime D. Blais, Elisabeth Wallhult, Mats Brune

Bibliographic record

VenueHemaSphere · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsMedicineBusulfanInternal medicineFludarabinePopulationTransplantationMyeloid leukemiaChemotherapySurgeryGraft-versus-host diseaseRegimenOncologyHematopoietic stem cell transplantationCyclophosphamide

Abstract

fetched live from OpenAlex

Background: Allogeneic reduced intensity conditioning transplant (RICT) has become an accepted treatment modality for patients (pts) age ≥50 years with acute myeloid leukemia (AML). Reports on patient and transplant related factors that may influence outcome in this population are rare. Aims: To analyze the possible impact of number of chemotherapy courses, recipient gender, choice of graft versus host disease (GVHD) prophylaxis and disease risk on the outcome of elderly pts with AML in CR1 receiving an allogeneic RICT. Methods: Patients were allografted from a matched sibling donor (MSD) as part of a multinational, prospective, controlled study (NCT00342316) which aimed to compare RICT and chemotherapy in an elderly population. Patients with a median age of 63 years (yrs) (52‐70) were transplanted between 2004 and 2015. Fifty‐eight pts (29 females, 29 males) were allografted using a RICT regimen: fludarabine (150‐180 mg/m 2 ) and busulfan (8 mg/kg orally or 6.4 mg/kg iv.) in 93%. Peripheral blood stem cells were given in 54 pts (93%). Median follow up was 36 months (2‐149). Prespecified high risk criteria were poor risk cytogenetics, secondary or therapy related AML, or blasts ≥15% after induction 1. Results: Overall survival (OS) at study termination was 36%. Twenty‐four (41%) pts relapsed. Acute GVHD grade 2 to 4 was noted in 28%, chronic extensive GVHD in 36%. Twenty‐one pts (36%) received up to 2 chemotherapy courses prior to transplant and 36 (62%) received more than 2 courses. Data was missing in 1 patient. These groups were well balanced with respect to age (63 years in both groups), gender and risk category. Neither OS, 38% versus 36%, nor relapse rate (RR), 38% versus 42% were significantly different. Data on GVHD prophylaxis was available on 57 pts, the two main immunosuppressive treatments were cyclosporine/methotrexate given to 29 pts, whereas 20 pts received cyclosporine/MMF based regimens. Age, gender, risk group distribution, number of chemotherapy regimens and performance status prior to transplant were not different in these two groups. OS was 38% versus 40% (not significant). There was no difference in either RR or acute or chronic GVHD between these two groups. Twenty‐nine of 58 (50%) pts were female. Median age of females was 62 yrs, of males 63 yrs (p = 0.275). There were no differences regarding disease risk between female and male groups, or between numbers of chemotherapy regimens. OS of female patients was 45% versus 28% in male patients (p = 0.17). Thirty‐eight pts were considered intermediate and 20 high risk. Median age was slightly higher in the high risk group, 64 vs 61 yrs (p = 0.042), and high‐risk pts received a higher number of chemotherapy courses. There was a trend to better OS in the intermediate risk group compared with the high risk group, 45% versus 20%, respectively (p = 0.087). RR was 34 versus 55%, which did not reach statistical significance. Summary/Conclusion: In our cohort of elderly patients with AML in CR1 receiving a RICT transplant from related donors, the number of pretransplant chemotherapy regimens, choice of graft versus host disease prophylaxis, patients gender, and comparison of high versus intermediate risk groups did not appear to impact on OS. Relapse rates in all patient groups were high, possibly masking any survival difference between the groups.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.276
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 teacher head, not a consensus.

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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Citations0
Published2019
Admission routes1
Has abstractyes

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