Validation of a Predictive Model for Indentifying An Increased Risk for Thromboembolism in Children with Acute Lymphoblastic Leukemia: Results of a Multicenter Cohort Study
Bibliographic record
Abstract
Abstract Children with acute lymphoblastic leukemia (ALL) are at increased risk for venous thromboembolism (VTE), however, not all children experience a VTE. Developing a predictive model for determining children at increased risk would be beneficial in targeting interventional studies to only high risk groups. A recent meta-analysis of studies in VTE in children with ALL identified four potential risk factors: treatment with Escherichia coli asparaginase (CASP), concomitant use of steroids, presence of central venous lines and thrombophilic genetic abnormalities. As VTE in childhood ALL is well recognized as serious clinical problem and due to the lack of studies on prevention, the standard of practice varies and some centres use enoxaparin prophylaxis for these children. However, the risks and benefits of the intervention are unknown. The aim of the study was to develop a simple model for predicting ALL-chemotherapy-associated VTE using baseline clinical and laboratory variables, and to evaluate, on an explorative basis, the increasing off-label use of enoxaparin for VTE prophylaxis in ALL children. For development of the risk model the predictive variables were scored as follows: treatment with CASP (5000–10000/m2) in combination with prednisone or dexamethasone, presence of central venous lines, thrombophilic genetic abnormalities, e.g. positive family history for VTE or identification of a single thrombophilic trait (1 point each), or carrier status of combined thrombophilic traits (2 points). A definition of VTE risk by score was low (1–2) and high (□ 3). The risk score was than prospectively validated in an independent cohort of 136 newly recruited patients enrolled into the German database. Seven patients were excluded (lost to follow-up n=2; death n=2, secondary malignancy, VTE before ALL-onset, infant < 12 months of age: each n=1). The cumulative VTE rates at 3.5 months in the validation cohorts were 3.6% (95% CI 1%–9%) in the low-risk group (4 of 112), and 47% (95%CI 23%–72%) in the high-risk category (8 of 17). In multivariate analysis [Cox regression] the high risk group was significantly associated with VTE when compared to the low risk group even after adjusting for age at ALL-onset, duration of CASP administration, steroid administered (prednisone/dexamethasone), and presence or absence of enoxaparin prophylaxis [hazard/95%CI: 4.16/1.13–15.34]. The negative predictive value for VTE was 96.3% [95%CI: 92.9–99.8]. Early enoxaparin prophylaxis reduced the absolute VTE-risk about 60% [95%CI: 23–96]. Therefore, the model can identify ALL-children with an increased risk for symptomatic VTE.
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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 | 0.034 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".