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Post hoc analysis of association between treatment response and various indicators of efficacy and safety in a randomized phase III trial of decitabine in older patients with acute myeloid leukemia.

2012· article· en· W2598038468 on OpenAlexaff
Mark D. Minden, Chris Arthur, Jiří Mayer, Mark M. Jones, Peter G. Tarassoff, Hagop M. Kantarjian

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineDecitabineInternal medicineCytarabineMyeloid leukemiaPost-hoc analysisGastroenterologyAzacitidineNeutropeniaSurgeryChemotherapy

Abstract

fetched live from OpenAlex

6627 Background: In a recent, large phase III trial (NCT00260832; Kantarjian, JCO; in press), 485 patients ≥65y with newly diagnosed acute myeloid leukemia (AML) received, every 4 wks, treatment choice (TC) of either supportive care or cytarabine (20 mg/m2 subcutaneous injection, 10 consecutive days) or decitabine (DAC) 20 mg/m2 (1-h intravenous [IV] infusion, 5 consecutive days). This post hoc analysis investigated relationships between response to treatment and indicators of efficacy and safety. Methods: Response was defined as morphologic complete remission (CR), or CR with incomplete blood count recovery (CRi) or partial response (PR). Transfusions (red blood cell [RBC] or platelets [PLT]), IV antibiotic use, and dose modifications were tabulated for responders and nonresponders to DAC or TC during the treatment period. Results: Fewer responders than nonresponders had dose modifications (30.4% vs 64.5%, respectively; P<.0001). Antibiotic use and transfusions were similar in both groups. Overall survival for responders was 16.1–18.5 mo vs 4.2–4.9 mo for nonresponders. Conclusions: These data suggest that response to DAC or TC treatment predicts clinically relevant benefits, with fewer dose modifications in older patients with newly diagnosed AML. The number of transfusions and antibiotic use was impacted by the longer survival time of responders vs nonresponders. Data on the impact of early response are being analyzed. [Table: see text]

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)0.014
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.420
Teacher spread0.389 · 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 designMeta-analysis
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
Published2012
Admission routes1
Has abstractyes

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