Identification of prognostic factors in childhood T‐cell acute lymphoblastic leukemia: Results from DFCI ALL Consortium Protocols 05‐001 and 11‐001
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: While outcomes for pediatric T-cell acute lymphoblastic leukemia (T-ALL) are favorable, there are few widely accepted prognostic factors, limiting the ability to risk stratify therapy. DESIGN/METHODS: Dana-Farber Cancer Institute (DFCI) Protocols 05-001 and 11-001 enrolled pediatric patients with newly diagnosed B- or T-ALL from 2005 to 2011 and from 2012 to 2015, respectively. Protocol therapy was nearly identical for patients with T-ALL (N = 123), who were all initially assigned to the high-risk arm. End-induction minimal residual disease (MRD) was assessed by reverse transcription polymerase chain reaction (RT-PCR) or next-generation sequencing (NGS), but was not used to modify postinduction therapy. Early T-cell precursor (ETP) status was determined by flow cytometry. Cases with sufficient diagnostic DNA were retrospectively evaluated by targeted NGS of known genetic drivers of T-ALL, including Notch, PI3K, and Ras pathway genes. RESULTS: ) was associated with superior disease-free survival (DFS). Pathogenic mutations of the PI3K pathway were mutually exclusive of ETP phenotype and were associated with inferior 5-year DFS and OS. CONCLUSIONS: Together, our findings demonstrate that ETP phenotype, end-induction MRD, and PI3K pathway mutation status are prognostically relevant in pediatric T-ALL and should be considered for risk classification in future trials. DFCI Protocols 05-001 and 11-001 are registered at www.clinicaltrials.gov as NCT00165087 and NCT01574274, respectively.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".