Infectious Complications During Reinduction in Children with Relapsed Acute Lymphoblastic Leukemia: A Descriptive Analysis
Bibliographic record
Abstract
Children with relapsed acute lymphoblastic leukemia (ALL) face higher rates of infection and treatment-related mortality than at initial diagnosis. Although immunotherapy is increasingly used in the relapsed setting, combination intensive chemotherapy remains the standard approach for reinduction. Serious infections during this phase can delay or preclude curative therapy. We aimed to describe the incidence and pattern of infections during reinduction in this high-risk population. In this single-center retrospective study, we reviewed charts of patients with relapsed ALL treated with combination chemotherapy reinduction at British Columbia Children’s Hospital between 2006 and 2022. Forty-three patients were included (median age 10.2 years at relapse). Most (90%) received a standard four-drug reinduction. Median duration of severe neutropenia was 20.8 days. About half (51%) experienced at least one infection, including 16% with confirmed or probable fungal infection. Infection was associated with significantly longer hospitalization (median 17 vs. 7 days; p = 0.006). While no predictors reached statistical significance, hyperglycemia and neutropenia ≥ 21 days were associated with higher odds of infection. Overall survival did not differ significantly by infection status (log-rank p = 0.43). Infectious complications remain common during reinduction chemotherapy for relapsed ALL despite advances in supportive care. While pharmacologic and clinical strategies may reduce risk, safer and more targeted reinduction approaches are urgently needed to optimize outcomes in this vulnerable group.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".