Outcomes after relapse for adolescent and young adult patients with ALL: Results from the Children's oncology group
Bibliographic record
Abstract
Abstract Background Outcomes for adolescents and young adults (AYAs) with acute lymphoblastic leukemia (ALL) are improving, yet little is known specifically about their outcomes after relapse. A recent study from the Children's Oncology Group (COG) identified risk factors for overall survival (OS) after relapse for patients with ALL enrolled on frontline clinical trials from 1996 to 2014 [Rheingold et al Leuk (2024) 38: 2382]. Here we report relapse outcomes for the AYAs enrolled on these trials. Methods Patients with de novo B- or T-ALL enrolled on twelve frontline clinical trials were reviewed retrospectively. AYA patients (aged ≥15 years at initial diagnosis) who relapsed were analyzed. Univariate and multivariate Cox regression models assessed the impact of patient and disease characteristics on OS following relapse. Statistical significance was set at p <0.05. Analyses were performed using SAS software (version 9.4). Results Among 16,115 patients enrolled, 2,053 (12.7%) relapsed, including 257 AYAs between the ages of 15 and 29 at initial diagnosis. The OS rate at 5 years (± standard error) after relapse for AYAs was 27.7 ± 3.0%, versus 37.9 ± 2.8% for 10-14 year-olds and 57.9 ± 1.4% for 1-9 year-olds (p <0.001). In multivariable analysis, neither race, white blood cell count (WBC) >100,000/µL at initial diagnosis, nor minimal residual disease (MRD) at the end of initial induction were significantly associated with OS post relapse. However, traditional relapse risk stratification measures, such as isolated central nervous system (CNS) relapse and longer time from initial diagnosis to relapse correlated with better outcomes in AYAs (p<0.001). The 217 AYAs with B-ALL had a 5-year post-relapse OS of 27.7 ± 3.3% compared to 40.9 ± 3.0% for 10-14 year-olds and 59.7 ± 1.5% for 1-9 year-olds (p <0.001). B-ALL AYAs with isolated CNS relapse had better outcomes compared to AYAs with an isolated bone marrow (BM) relapse (hazard ratio (HR) [95% confidence interval (CI)] = 0.38 [0.23, 0.66], p <0.001). For AYAs with B-ALL, time from initial diagnosis to relapse was also significantly associated with OS post relapse, with a longer duration of initial remission (18-35 months or ≥36 months) associated with improved outcomes (HR [95% CI] = 0.37 [0.24, 0.58] and 0.18 [0.11, 0.28], respectively, p <0.0001 in both cases). There was a trend towards worse 5-year post-relapse OS for B-ALL AYAs of Hispanic ethnicity of all races (19.9 ± 5.4%), end of initial induction (EOI) MRD ≥0.1% (17.8±4.4%), and presenting WBC >100,000/µL (12.4 ± 5.2%), but these factors did not reach statistical significance. T-ALL data are limited by small sample size (40 patients), but similar trends emerged. The 5-year post-relapse OS for AYAs was 29.0 ± 7.7%, while the OS for 10-14 year-olds was 18.1 ± 6.0% and for 1-9 year-olds was 43.0 ± 4.3% (p <0.001). An initial WBC >100,000/µL correlated with worse OS post relapse compared to an initial WBC <50,000/µL (HR [95% CI] = 8.23 [1.68, 40.17], p=0.009). T-ALL AYAs with an isolated CNS relapse again tended to have better outcomes compared to AYAs with an isolated BM relapse (HR [95% CI] = 0.16 [0.02, 1.09], p=0.062), but there was not a significant difference in outcomes for AYAs with either combined or isolated (with or without CNS involvement) BM relapse (HR [95% CI] = 1.76 (0.32, 9.58), p = 0.51). While not statistically significant, Hispanic ethnicity and non-White race, MRD at the end of initial induction ≥0.1%, and time <36 months from initial diagnosis to relapse appeared to be associated with inferior outcomes. Conclusion AYA patients with ALL have poor outcomes after relapse, and current COG and other cooperative group studies stratify patients age ≥18 years at the time of relapse as high risk. Our data indicate that age at the time of diagnosis is also correlated with post-relapse outcomes, with patients ≥15 years at the time of diagnosis faring poorly after relapse. This suggests that perhaps age at the time of diagnosis should be considered in relapse risk stratification as well, and further work with this data set can focus on not only age at diagnosis, but also age at the time of relapse. Current frontline and relapse treatment studies are now focusing on the incorporation of immunotherapies which may lead to improved outcomes, but our findings highlight the need for continued attention to AYAs as a particularly high-risk population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".