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PS1043 OUTCOMES OF PATIENTS WITH RELAPSED OR REFRACTORY ACUTE MYELOID LEUKEMIA: A POPULATION‐BASED REAL‐WORLD STUDY

2019· article· en· W2950780445 on OpenAlexaffabout
Lalit Saini, Michelle Geddes, F.F. Liu, Dimas Yusuf, Kiersten Schwann, Alkarim Billawala, Christopher Westcott, Jessica A. Kurniawan, Winson Y. Cheung, Joseph Brandwein

Bibliographic record

VenueHemaSphere · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity of AlbertaUniversity of CalgaryWestern University
Fundersnot available
KeywordsMedicineCytarabineInternal medicineRefractory (planetary science)Myeloid leukemiaRegimenPopulationChemotherapy regimenIntensive careChemotherapyPediatricsSurgeryIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Patients (pts) with acute myeloid leukemia (AML) may be treated with intensive or non‐intensive chemotherapy. While some pts achieve complete remission (CR) after initial treatment, a significant proportion become refractory to initial treatment or relapse after the initial response. Aims: To understand treatment patterns and outcomes in pts with relapsed or refractory AML (RR‐AML) in a real‐world setting. Methods: The Alberta Cancer Registry and local databases of the University of Alberta Hospital and the Tom Baker Cancer Centre were interrogated to identify AML pts with RR‐AML aged ≥18 years treated from January 2013 to December 2016. Pts were considered to have refractory AML if they failed to achieve CR or achieved CR with incomplete count recovery (CRi) after 2 cycles of intensive chemotherapy, 6 cycles of azacytidine, or 4 cycles of low‐dose cytarabine. Based on the treatment regimen received following the diagnosis of RR‐AML, pts were grouped as receiving either intensive therapy (IT), non‐intensive therapy (NIT), or best supportive care (BSC) and were followed from relapse to date of death or last follow‐up. Results: Overall, 572 pts with AML were identified from the database search, 199 (124 males, 75 females) of whom met the eligibility criteria for RR‐AML and were included in this analysis. The median age at diagnosis of RR‐AML was 66.8 years; median follow‐up was 4.7 months. According to the European LeukemiaNet (ELN) 2010 classification, 34 pts (17%) had a favorable risk, 102 (51%) intermediate (Int) risk, 59 (30%) adverse risk profile and 4 (2%) with unknown status. After relapse or refractoriness (RR), 88 pts (44%) received BSC, 46 (23%) received IT with fludarabine, cytarabine + granulocyte colony‐stimulating factor (FLAG) (n = 5), FLAG + idarubicin (n = 29), or another regimen (n = 12), while 65 (33%) received NIT with azacitidine ± another agent (n = 49), low‐dose cytarabine ± another agent (n = 12), or an alternative regimen (n = 4). The unadjusted median overall survival (mOS) for the overall study cohort was 5.3 months from the time of RR with a 12‐month OS rate of 29.6% (95% CI 29.0–30.3). The mOS was 13.8, 9.4, and 2.1 months for IT, NIT, and BSC groups, respectively ( P < 0.001) (Figure). The mOS for pts aged <60 years was 8.3 vs 4.5 months for those ≥60 years ( P = 0.009). Following RR, 16 (8%) pts received an allogeneic stem cell transplant (ASCT), for whom median survival was not reached, vs 4.5 months in pts who did not undergo transplantation. The mOS for pts with an ELN favorable, Int‐I, Int‐II, and adverse risk profile was 12.4, 4.5, 4.7, and 4.0 months, respectively ( P = 0.002). In a multivariable Cox regression model incorporating age, ELN risk group, treatment intensity pre‐RR, number of treatment lines pre‐RR, best response pre‐RR, treatment intensity post‐RR, and ASCT post‐RR, treatment intensity post‐RR (NIT vs BSC: hazard ratio [HR] for mortality 0.32; 95% CI 0.23–0.48; IT vs BSC: HR for mortality 0.26; 95% CI 0.16–0.43) and best response pre‐RR (CR/CRi <12 months vs all others: HR for mortality 0.55, 95% CI 0.33–0.92) were significantly associated with OS. Summary/Conclusion: In a real‐world setting, a high proportion of pts only receive BSC, which is associated with very short survival. Treatment regimen post‐RR is the major predictor of survival, with non‐intensively and intensively treated pts having better outcomes compared to pts who received BSC. However, the overall outcomes of pts with RR‐AML remain poor regardless of treatment, and new therapies are urgently needed. image

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.299
Teacher spread0.282 · 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 routes2
Has abstractyes

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