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Azacitidine Has Limited Activity in Patients with MDS and AML

2011· article· en· W2525872647 on OpenAlexaff
Karen Yee, Symron Bansal, Joseph Brandwein, Mark D. Minden, Aaron D. Schimmer, Vikas Gupta, Arsenia Dharman, Christine Cserti‐Gazdewich, Andre C. Schuh

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsToronto General HospitalUniversity Health NetworkPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineAzacitidineCytarabineInternal medicineChemotherapy regimenChemotherapyOncology

Abstract

fetched live from OpenAlex

Abstract Abstract 5057 Background: The multicenter, randomized AZA-001 trial demonstrated that azacitidine (AZA) significantly improved overall survival in patients with intermediate-2/high risk MDS (including patients with AML < 30 % marrow blasts), compared with conventional care regimens, including supportive care, low dose cytarabine (LDAC) and intensive chemotherapy (Lancet Oncol 2009;10:223–32). Recent data has suggested that AZA may have limited efficacy in the “real life” situation (Hematol Oncol 2011Mar8; Epub ahead of print). This retrospective analysis evaluates the responses and outcomes of patients with MDS and AML < 30% marrow blasts who received AZA at the Princess Margaret Hospital. Methods: Between July 2009 and July 2011, 87 patients received AZA at the Princess Margaret Hospital. This analysis is restricted to patients with MDS and AML < 30% marrow blasts (n = 60), excluding AML with > 30% blasts (n = 6), MDS/myeloproliferative neoplasm (n = 1), and patients previously treated with intensive chemotherapy and/or alloSCT within the last 5 years (n = 20). Azacitidine was planned to be administered subcutaneously at the dose-schedule of 75 mg/m2/d for 6 days every 28 days. However, 8 patients received subsequent cycles of AZA in local centers at the dose schedule of 75 mg/m2/d for 5 days, 2 days off, followed by 75 mg/m2/d for 2 days (AZA 5-2-2). Results: Median age was 73 (range, 43 to 87), and 63% were male. Twenty-three patients (38%) had secondary or therapy-related MDS or AML. Two patients had received a prior organ transplant (heart and liver). Forty-two patients (70%) had MDS (7 RCMD, 10 RAEB-1, 17 RAEB-2, 3 CMML-1, 5 CMML-2). Cytogenetic risk (by IPSS criteria) was good in 19 (32%), intermediate in 6 (10%), and poor in 33 (55%) patients, respectively. Karyotype analysis failed in 2 patients (3%). IPSS was intermediate-1 in 4 (7%), intermediate-2 in 32 (53%), and high in 24 (40%) of the patients. Median baseline hemoglobin level, absolute neutrophil count and platelet count were 90.5 g/L, 0.9 × 109/L, and 44.5 × 109/L, respectively. Median prior therapies was 0 (range, 0–2) with 5, 3, 1, and 1 patients having previously received erythropoiesis-stimulating agent, hydroxyurea, LDAC, and decitabine, respectively. The median number of AZA cycles administered was 5.5 (range, 0–19). The best response was CR in 4 (7%), marrow CR in 8 (13%), and hematologic improvements in platelets, neutrophils, and erythroid in 15 (25%), 9 (15%), and 5 (8%) patients, respectively. Fifteen patients remain on treatment. Treatment discontinuation was mostly due to disease progression, lack of response, and/or intercurrent illness/infection, with 7 (12%) patients stopping therapy to proceed to an alloSCT. Twenty patients have died. Median overall survival was 36.7 weeks (range, 4.4 weeks-86.6+ weeks). Conclusions: Azacitidine has limited efficacy in this group of patients. Optimal therapy for this patient population still needs to be determined. Disclosures: Yee: Celgene: Honoraria. Schuh:Celgene: Honoraria.

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)0.002
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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.243
Teacher spread0.210 · 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
Published2011
Admission routes1
Has abstractyes

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