Multisite 11-year experience of less-intensive vs intensive therapies in acute myeloid leukemia
Bibliographic record
Abstract
Less-intensive induction therapies are increasingly used in older patients with acute myeloid leukemia (AML). Using an AML composite model (AML-CM) assigning higher scores to older age, increased comorbidity burdens, and adverse cytogenetic risks, we defined 3 distinct prognostic groups and compared outcomes after less-intensive vs intensive induction therapies in a multicenter retrospective cohort (n = 1292) treated at 6 institutions from 2008 to 2012 and a prospective cohort (n = 695) treated at 13 institutions from 2013 to 2017. Prospective study included impacts of Karnofsky performance status (KPS), quality of life (QOL), and physician perception of cure. In the retrospective cohort, recipients of less-intensive therapies were older and had more comorbidities, more adverse cytogenetics, and worse KPS. Less-intensive therapies were associated with higher risks of mortality in AML-CM scores of 4 to 6, 7 to 9, and ≥10. Results were independent of allogeneic transplantation and similar in those age 70 to 79 years. In the prospective cohort, the 2 groups were similar in baseline QOL, geriatric assessment, and patient outcome preferences. Higher mortality risks were seen after less-intensive therapies. However, in models adjusted for age, physician-assigned KPS, and chance of cure, mortality risks and QOL were similar. Less-intensive therapy recipients had shorter length of hospitalization (LOH). Our study questions the survival and QOL benefits (except LOH) of less-intensive therapies in patients with AML, including those age 70 to 79 years or with high comorbidity burdens. A randomized trial in older/medically infirm patients is required to better assess the value of less-intensive and intensive therapies or their combination. This trial was registered at www.clinicaltrials.gov as #NCT01929408.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".