Healthcare resource utilization trends in patients with acute myeloid leukemia ineligible for intensive chemotherapy receiving first‐line systemic treatment or best supportive care: A multicenter international study
Bibliographic record
Abstract
OBJECTIVES: This retrospective chart review examined real-world healthcare resource utilization (HRU) in patients with AML ineligible for intensive therapy who received first-line systemic therapy or best supportive care (BSC). METHODS: Data were collected anonymously on patients with AML who initiated first-line hypomethylating agents (HMA), low-dose cytarabine (LDAC), other systemic therapy, or BSC. HRU endpoints included hospitalizations, outpatient consultations, transfusions, and supportive care. RESULTS: Of 1762 patients included, 46% received HMA, 11% received LDAC, 17% received other systemic therapy, 26% received BSC; median treatment durations were 118, 35, 33, and 57 days, respectively. Most patients were hospitalized, most commonly for treatment administration, transfusion, or infection (HMA 82%, LDAC 93%, other systemic therapy 83%, BSC 83%). A median number of hospitalizations were 2-6 across systemic groups and two for BSC, with median durations of 8-18 days. Transfusion rates and outpatient consultations were highest for HMA (80% and 79%) versus LDAC (57% and 53%), other systemic therapy (57% and 63%), and BSC (71% and 66%). Antivirals/antibiotics and antifungals were used more frequently than growth factors (72-92%, 34-63%, and 7-27%, respectively). CONCLUSION: Patients with AML ineligible for intensive therapy have high HRU; novel therapies are needed to alleviate this burden.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".