Incidence and socioeconomic factors in older adults with acute myeloid leukaemia: Real‐world outcomes from a population‐based cohort
Bibliographic record
Abstract
OBJECTIVES: Acute myeloid leukaemia (AML) is a disease of older adults, who are vulnerable to socio-economic factors. We determined AML incidence in older adults and the impact of socio-economic factors on outcomes. METHODS: We included 3024 AML patients (1996-2016) identified from a population-based registry. RESULTS: AML incidence in patients ≥60 years increased from 11.01 (2001-2005) to 12.76 (2011-2016) per 100 000 population. Among 879 patients ≥60 years in recent eras (2010-2016), rural residents (<100 000 population) were less likely to be assessed by a leukaemia specialist (39% rural, 47% urban, p = .032); no difference was seen for lower (43%, quintile 1-3) vs. higher (47%, quintile 4-5) incomes (p = .235). Similar numbers received induction chemotherapy between residence (16% rural, 18% urban, p = .578) and incomes (17% lower, 17% high, p = 1.0). Differences between incomes were seen for hypomethylating agent treatment (14% low, 20% high, p = .041); this was not seen for residence (13% rural, 18% urban, p = .092). Among non-adverse karyotype patients ≥70 years, 2-year overall survival was worse for rural (5% rural, 12% urban, p = .006) and lower income (6% low, 15% high, p = .017) patients. CONCLUSIONS: AML incidence in older adults is increasing, and outcomes are worse for older rural and low-income residents; these patients face treatment barriers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".