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Record W2010936602 · doi:10.1016/j.bbmt.2014.01.027

Allogeneic Hematopoietic Cell Transplantation May Alleviate the Negative Prognostic Impact of Monosomal and Complex Karyotypes on Patients with Acute Myeloid Leukemia

2014· article· en· W2010936602 on OpenAlexafffund
Robert J. Guo, Eshetu G. Atenafu, Kate Craddock, Hong Chang

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2014
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity Health Network
FundersUniversity Health Network
KeywordsMedicineInternal medicineMyeloid leukemiaUnivariate analysisTransplantationOncologyHematopoietic stem cell transplantationLeukemiaKaryotypeMyeloidGastroenterologyMultivariate analysis

Abstract

fetched live from OpenAlex

Monosomal karyotype (MK) and complex karyotype (CK) are well known to be associated with a very poor clinical outcome in patients with acute myeloid leukemia (AML). However, whether or not the prognostic impact of MK and CK remains relevant for patients who have undergone allogeneic hematopoietic cell transplantation (allo-HCT) is still unclear. We retrospectively analyzed the status of MK and CK, as well as other clinical laboratory features, in 148 allo-HCT AML patients at our institution and correlated with their event-free survival (EFS) and overall survival (OS) after transplantation. MK and CK were identified in 14 (9%) and 19 (13%) cases, respectively. On univariate analysis, only age (≥60 years) and WBC count (≥15 × 10(9)/L) were significant adverse predictors for EFS (P < .001 and P = .017, respectively) and OS (P = .002 and P = .021, respectively). MK, CK, and other relevant parameters analyzed did not affect the clinical outcome. Multivariable analysis confirmed that both older age and high WBC count were independent prognostic factors for a shorter OS (P = .001 and P = .003, respectively) and a shorter EFS (P < .001 and P = .001, respectively). Our results indicate that neither MK nor CK are high-risk factors in AML patients undergoing allo-HCT.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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.

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".

Quick stats

Citations21
Published2014
Admission routes2
Has abstractyes

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