A retrospective, real-world population-based analysis of treatment patterns and outcomes in adult patients with relapsed/refractory acute myeloid leukemia in Alberta, Canada.
Bibliographic record
Abstract
e18505 Background: In order to describe the impact of future targeted therapies on treatment outcomes of patients (pts) with relapsed and/or refractory (RR) acute myeloid leukemia (AML), a better understanding of the clinical management pathway in these pts is needed. We therefore evaluated the treatment patterns and associated outcomes in a real-world cohort of pts with RR-AML using a population-based cancer registry and patient medical records. Methods: Pts newly diagnosed wih AML between January 2013 and December 2016, aged ≥ 18 years were identified from the provincial-wide Alberta Cancer Registry (ACR). Data for pts who met the criteria for RR-AML were assessed by hematologists and were extracted from medical records. RR-AML pts were then categorized as: receiving intensive therapy (IT); receiving non-intensive therapy (NIT); or treated with best-supportive care (BSC) following a diagnosis of RR-AML. Results: 572 AML pts were identified from the ACR, of which 199 met criteria for RR-AML and were included in the analysis (124 males, 75 females; median age at diagnosis of RR-AML 66.8 years; median follow-up 4.7 months). In this RR-AML cohort, 26 (13%) pts received ≥ 2 lines of prior therapy. Unadjusted median overall survival (mOS) was 5.3 months, with a 12-month overall survival rate of 29.6% (95% CI 29.0–30.3%) from the time of RR. Following RR, 46 (23%) pts received IT, 65 (33%) pts were treated with NIT, and 88 (44%) pts received BSC, with unadjusted mOS of 13.8, 9.4, and 2.1 months, respectively ( P < 0.001). When stratified by European LeukemiaNet risk classification at diagnosis, unadjusted mOS was 12.4, 4.7, and 4.0 months for favorable risk, intermediate risk, and adverse risk groups, respectively ( P < 0.01). Conclusions: This retrospective, real-world study in Alberta Canada confirms the poor prognosis reported to date in the RR-AML population. Notably, a large proportion of pts received BSC which was associated with dismal survival outcomes. These data also highlight that effective and tolerable alternatives to current treatment options are urgently needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".