Impact of baseline clinical and laboratory features on the risk of thrombosis in children with acute lymphoblastic leukemia: A prospective evaluation
Bibliographic record
Abstract
BACKGROUND: Children with acute lymphoblastic leukemia (ALL) have increased risk of thromboembolism (TE). However, the predictors of ALL-associated TE are as yet uncertain. OBJECTIVE: This exploratory, prospective cohort study evaluated the effects of clinical (age, gender, ALL risk group) and laboratory variables (hematological parameters, ABO blood group, inherited and acquired prothrombotic defects [PDs]) at diagnosis on the development of symptomatic TE (sTE) in children (aged 1 to ≤18) treated on the Dana-Farber Cancer Institute ALL 05-001 study. PROCEDURES: Samples collected prior to the start of ALL therapy were evaluated for genetic and acquired PDs (proteins C and S, antithrombin, procoagulant factors VIII (FVIII:C), IX, XI and von Willebrand factor antigen levels, gene polymorphisms of factor V G1691A, prothrombin gene G20210A and methylene tetrahydrofolate reductase C677T, anticardiolipin antibodies, fasting lipoprotein(a), and homocysteine). RESULTS: Of 131 enrolled patients (mean age [range] 6.4 [1-17] years) 70 were male patients and 20 patients (15%) developed sTE. Acquired or inherited PD had no impact on the risk of sTE. Multivariable analyses identified older age (odds ratio [OR] 1.13; 95% confidence interval [CI]: 1.01, 1.26) and non-O blood group (OR 3.64, 95% CI: 1.06, 12.51) as independent predictors for development of sTE. Patients with circulating blasts had higher odds of developing sTE (OR 6.66; 95% CI: 0.82, 53.85). CONCLUSION: Older age, non-O blood group, and presence of circulating blasts, but not PDs, predicted the risk of sTE during ALL therapy. We recommend evaluation of these novel risk factors in the development of ALL-associated TE. If confirmed, these easily accessible variables at diagnosis can help develop a risk-prediction model for ALL-associated TE.
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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 | 0.002 | 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 | 0.001 |
| 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".