Treatment‐related mortality in children with acute lymphoblastic leukemia in Central America
Bibliographic record
Abstract
BACKGROUND: The objectives of this study were to describe the incidence, timing, and predictors of treatment-related mortality (TRM) among children with acute lymphoblastic leukemia (ALL) in El Salvador, Guatemala, and Honduras. METHODS: Patients aged <20 years who were diagnosed with ALL between January 2000 and March 2008, who received treatment in any of the 3 countries, and who started induction chemotherapy were included in the study. Almost all patients were treated on the El Salvador-Guatemala-Honduras II protocol, which was based on the St. Jude Total XIII and XV protocols. Biologic, socioeconomic, and nutritional variables were examined as predictors of TRM. RESULTS: Of 1670 patients, TRM occurred as a first event in 156 children (9.3%); TRM occurred during remission induction therapy in 92 of 156 children (59%), between remission induction and maintenance therapy in 27 of 156 children (17%), and during maintenance therapy in 37 of 156 children (24%). Although the TRM rate decreased in patients who were diagnosed after July 1, 2004 (11.2% vs 7.9%; P = .02), the rate of induction death did not change (5.2% vs 5.8%; P = .58). Independent predictors of induction death included higher risk ALL (odds ratio [OR], 1.84; 95% confidence interval [CI], 1.03-3.27; P = .04), lower initial platelet counts (OR per 10 × 10(9) /L, 0.94; 95% CI, 0.89-0.98; P = .005), and longer travel time to the clinic (OR, 1.06 per hour; 95% CI, 1.01-1.14; P = .03). CONCLUSIONS: In Central America, TRM remains an important cause of treatment failure in children with ALL. A large proportion of TRM occurs in maintenance, although this proportion has decreased over time. Supportive care interventions should especially target children who present with low platelet counts. Further study on transfusion ability and the location of induction deaths is required.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".