Results of a Randomized Augmented Intensification Phase in Acute Lymphoblastic Leukemia in Children in Argentina: GATLA 2010 ALL IC Trial
Bibliographic record
Abstract
BACKGROUND: Intensified postinduction therapy improves outcomes for high-risk pediatric patients with acute lymphoblastic leukemia (ALL) in high-income countries. However, benefits are uncertain in middle-income countries where supportive care is often limited. The primary objective was to determine if augmented protocal I phase B (IB) reduced the 5-year cumulative incidence of relapse compared with standard IB among newly diagnosed pediatric patients with intermediate- and high-risk (IR and HR) ALL in a middle-income country. METHODS: This was a randomized, phase III multicenter study conducted in 30 centers from GATLA group in Argentina, as part of International BFM study group ALLIC. We included newly diagnosed pediatric patients with ALL 1-18 years of age with IR or HR B- and T-precursor ALL. Only patients who were in complete remission at end induction were randomized to augmented IB versus standard IB. Augmented IB consisted of cyclophosphamide, cytarabine, 6-mercaptopurine, vincristine, E. coli l-asparaginase and intrathecal methotrexate. Standard IB consisted of cyclophosphamide, 6-mercaptopurine, cytarabine, and intrathecal methotrexate. The primary outcome was the cumulative incidence of relapse. RESULTS: There were 1060 patients randomized to standard IB (n = 527) and augmented IB (n = 533). The 5-year cumulative incidence of relapse (±standard error) was not significantly different by group (22.6 ± 0.2 vs. 22.3 ± 0.1%; p = 0.97) for standard IB and augmented IB, respectively. Treatment-related mortality (TRM) was 6.5 ± 0.1 and 7.5 ± 0.1%; p = 0.45, respectively. CONCLUSIONS: Among newly diagnosed pediatric patients with IR and HR ALL treated in Argentina, postinduction intensification with augmented IB did not improve outcomes compared with standard IB. Standard IB should be used for these patients. Future trials should focus on reducing TRM.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".