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Impact of the Intensity of Conditioning Therapy On the Outcomes of Patients Aged 40 to 60 Years with Acute Myeloid Leukemia/Myelodysplastic Syndrome Undergoing Allogeneic Hematopoietic Cell Transplantation.

2009· article· en· W2582263258 on OpenAlexaff
Murtadha Al‐Khabori, Mohamed Elemary, Gordon Guyatt, Ahmed Galal, John Kuruvilla, Jeffrey H. Lipton, Hans A. Messner, Vikas Gupta

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversitySt. Joseph's HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineInternal medicineTransplantationMyeloid leukemiaHematopoietic stem cell transplantationAlemtuzumabPopulationLeukemiaMyelodysplastic syndromesOncologyGraft-versus-host diseaseAcute leukemiaSurgeryBone marrow

Abstract

fetched live from OpenAlex

Abstract Abstract 1202 Poster Board I-224 Introduction: The eligibility of patients to undergo allogeneic hematopoietic cell transplantation (AHCT) is limited by age, co-morbid conditions and performance status. Utilizing reduced and minimal intensity conditioning regimens, older and less fit patients could benefit from this modality with the graft versus leukemia effect. Methods: We performed a retrospective analysis of adults aged 40-60 years with acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS) undergoing AHCT at our center from January 2002 to June 2008. The objective of the study is to compare the overall (OS), relapse free (RFS), acute GvHD free and chronic GvHD free survival between the different conditioning regimens. The regimens are classified according to the definition of CIBMTR as conventional intensity (CIC) or reduced intensity (RIC). High risk disease is defined as patients meeting one of the following criteria: AML with poor risk cytogenetics, secondary AML with preceding hematologic disorder, AML in second complete remission or AML/MDS with preceding malignancy. Results: There are 106 patients eligible for the study (CIC 67, RIC 39); 56 patients with de novo AML, 22 with MDS and 28 with secondary AML. High risk disease comprised 64% of our study population. The baseline characteristics between the two groups including performance status (Karnofsky Performance Score; CIC 81%, RIC 83%, p=0.08) are not different except for age (mean in years; CIC 50.2, RIC 52.9, p=0.03), graft versus host disease (GvHD) prophylaxis (cyclosporine/alemtuzumab; CIC 16%, RIC 57%, p<0.001), donor type (unrelated donor; CIC 30%, RIC 54%, p=0.04) and Seattle co-morbidity index score (score of ≥3; CIC 12%, RIC 31%, p=0.03). The median follow up duration for all patients was 1.93 years. There is no statistically significant difference in the OS between the two groups (median OS in years; CIC 1.93, RIC 2.59, Log-rank p=0.62). Furthermore, RFS between the two groups were similar (median RFS was not reached in either groups, Log-rank p=0.86). Using Cox-model adjusting for important prognostic factors at baseline (age, disease risk, donor type, performance status, Co-morbidity index score and type of conditioning regimen), only performance status and disease risk are significant for both OS (HR 0.906 [p=0.01] and 2.13 [p=0.04] respectively) and RFS (HR 0.854 [p=0.04] and 6.931 [p=0.007] respectively). The acute GvHD and chronic GvHD free survival curves are not significantly different in the two groups (Log-rank p values are 0.66 and 0.16 respectively). Conclusion: Despite inferior baseline characteristics in the patients receiving RIC, the outcomes were similar. Disease biology rather than intensity of the conditioning therapy is the determinant of overall survival and relapse risk after AHCT in patients aged 40-60 years with AML/MDS. Prospective randomized studies are needed to determine the superiority of RIC in patients who are deemed suitable to undergo CIC. Disclosures: No relevant conflicts of interest to declare.

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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.012
GPT teacher head0.260
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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Citations0
Published2009
Admission routes1
Has abstractyes

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