Evaluating Asparaginase Toxicity in Hispanic Patients With Acute Lymphoblastic Leukemia in a Large Safety-Net Hospital
Bibliographic record
Abstract
Background: Acute lymphoblastic leukemia (ALL) is relatively rare in adults with poor rates of long-term remission. Chemotherapy protocols for adults have been adapted from pediatric protocols, including asparaginase. While asparaginase has shown significant efficacy in pediatric patients, its use in adults is limited due to hepatotoxicity, pancreatitis, and thrombosis. This study seeks to review the toxicity profile in Hispanic adults at a large safety-net hospital. Methods: We performed a chart review of patients over the age of 18 with ALL treated with asparaginase. Data were collected between the years of 2015 and 2021 and included demographics, laboratory parameters on diagnosis, treatment details, and information on complications related to treatment. Results: A total of 14 Hispanic patients diagnosed with ALL and treated with asparaginase from January 2016 to November 2021 were included in this study. Our patient population had an average body mass index (BMI) of 34 (standard deviation (SD) 8.7), with the majority (64%) classified as obese (BMI ≥ 30). Twelve patients (86%) were Philadelphia chromosome negative. The incidence of grade 3 to 4 hyperbilirubinemia (> 3 times the upper limit of normal (ULN) for serum bilirubin) was six out of 14 patients (43%). The incidence of grade 3 to 4 transaminitis (> 5 times the ULN for alanine aminotransferase (ALT) or aspartate aminotransferase (AST) levels) was 13 out of 14 patients (93%). Thrombosis occurred in six out of 14 patients (43%), with one patient experiencing disseminated intravascular coagulation (DIC). Conclusions: Our cohort of Hispanic adults experienced transaminitis and hyperbilirubinemia at a high rate (93%). The higher incidence noted in our patients with class III obesity is in line with recent expert recommendations for dose reduction of asparaginase in patients with severe obesity. Our study suggests that our Hispanic population is at higher risk for developing hepatotoxicity after asparaginase use, though this could also be related to the high prevalence of obesity in our population. This is important for future care in selecting candidates for asparaginase therapy including those who may be at higher risk for adverse events.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".