Longer Time to the Start of Continuation Therapy Is Associated with Improved Survival In High Risk Pediatric Acute Lymphoblastic Leukemia (ALL): A Report From the Children's Oncology Group (COG)
Bibliographic record
Abstract
Abstract Abstract 3223 Background: Delays in treatment are common in pediatric ALL and may occur more often in high risk ALL (HR-ALL). Delays during maintenance therapy have adverse impact on survival, but the significance of delays prior to maintenance is unknown (Schmiegelow, et al, American Journal of Pediatric Hematology Oncology 1990 and Dibenedetto et al, Pediatric Hematology Oncology 1994). We studied the effect of delays in therapy prior to maintenance by analyzing data from two HR-ALL clinical trials, CCG1961 and POG9906. The objective was to determine the association between time to maintenance (TTM) from starting induction therapy and event-free survival (EFS) in children with high-risk ALL. Methods: CCG1961 enrolled 2078 patients from September 1996 to May 2002 with B- and T-lineage ALL with high-risk features, defined as those aged 1–9 years with initial white blood cell count (WBC) ≥ 50,000/μl, any patient aged ≥ 10 years and ≤ 21 years, and those with central nervous system (CNS) leukemia or overt testicular leukemia. Rapid early responders (RERs), those with < 25% blasts in the bone marrow on day 7 of therapy, were randomized to receive standard or augmented BFM therapy with either a single interim maintenance and delayed intensification phase (SDI) or two interim maintenance and delayed intensification (DDI) courses as outlined in Table 1. Slow early responders (SERs) were randomized to augmented BFM with DDI with either doxorubicin or idarubicin and cyclophosphamide in the DI courses. POG9906 enrolled 276 patients from March 2000 to April 2003 with high-risk B-precursor ALL, defined as all patients with CNS disease, testicular disease, MLL rearrangement, age ≥ 16 years, or WBC ≥ 100K. In addition, it included selected patients aged 12–15 with high-risk disease based on the Shuster criteria for age and initial WBC. Patients with favorable cytogenetic features (ETV6-RUNX1 fusion or trisomy of chromosomes 4 and 10) were excluded unless they had CNS or testicular leukemia. Patients were treated with augmented BFM with DDI. Patients who made it to start of maintenance are included in this report. TTM was calculated as time from start induction until start of maintenance therapy. Expected TTM for those with B-lineage ALL is shown in Table 1. TTM was dichotomized by plotting the Akaike information criterion (AIC) versus all possible cutoff values of TTM and identifying the cut-point which best discriminated between groups who did and did not fail. The identified threshold was then examined as a predictor of EFS using the Kaplan Meier method and log rank test. The outcomes were 5-year EFS for CCG1961 and 4-year EFS for POG9906. Results: Among the B-lineage patients, longer TTM was significantly associated with improved EFS in CCG1961 Std BFM DI and SER Aug BFM Doxo arms, as well as on POG 9906. For example, in Std BFM DI, 5-year EFS was 83% in those with longer TTM and 71.9% in those with shorter TTM (P=.036). Among the T lineage cohort enrolled on CCG1961, similar results were seen with longer TTM being significantly associated with improved EFS in Std BFM DDI and SER Aug BFM Ida, and a trend toward improved EFS with longer TTM in each of the other arms. Conclusions: These data suggest that longer TTM may be associated with superior EFS in pediatric high-risk ALL. Multiple factors may contribute to this association. For instance, pharmacogenetic differences resulting in more treatment toxicity and delays may also be associated with more potent anti-leukemic effects, or patients with infectious complications may have an endogenous immune response that also has an anti-leukemia effect. Further research is needed to validate the association between TTM and EFS and to characterize the timing and causes of these delays in protocol therapy. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".