Risk Factors Predisposing to Thromboembolism in Children with Cancer.
Bibliographic record
Abstract
Abstract Introduction: Cancer is a major risk factor in children with TE. However, information regarding epidemiology of TE in children with cancer is scant. We conducted a retrospective cohort study to define the epidemiology of TE in children with cancer and to identify potential risk factors. Methods: Records of children (≤18 years of age) with cancer diagnosed and treated at McMaster Children’s Hospital over past 15 years were reviewed for demographics, details of diagnosis and treatment of cancer and of TE, if any. We studied the effect of age (<10 years vs. ≥10 years), gender, type of cancer and presence or absence of intrathoracic disease (defined as mediastinal mass or any primary or metastatic pulmonary disease), type of central venous line (CVL) and CVL dysfunction (defined as persistent or recurrent difficulty of blood draw and/or infusion or documented CVL infection) on the risk of developing TE. Statistical analysis was performed using SPSS version 15. Results: Overall 49 of 606 children (8.1%) with cancer developed TE (Table 1). Due to very low prevalence of TE in children with brain tumors, regression analyses for risk factors was performed in children with non-CNS cancers. Children with ALL (OR 4.93, 95% CI 1.60, 11.52, p=0.004), lymphoma (OR 4.18, 95% CI 1.37, 12.71, p=0.01), and sarcoma (OR 4.42, 95% CI 1.42, 13.77, p=0.01) had increased risk of TE. Older patients (age ≥ 10 years) were at higher risk of developing TE compared to younger patients (OR 2.2; 95% CI 1.2,3.96; P<0.01). Subgroup analyses showed that patients with CVL-dysfunction (33.3% vs. 9.5%; p<0.0001, 95% CI; 10.1,37.5) and those with intrathoracic disease (17.6% vs.5.7%; p=0.028, 95% CI; 2.2, 21.7) were at significantly higher risk of TE compared to those without CVL dysfunction and intrathoracic disease. Conclusions: Overall TE is common in children with cancer. We have identified older age and type of cancer are the important risk factors predisposing to TE; children 10 years or older and those with lymphoreticular malignancy and sarcoma are at significantly higher risk of developing TE. In addition presence of mediastinal disease and CVL dysfunction increased the risk of TE. This is one of the largest comprehensive epidemiogical studies of TE in children with cancer identifying different risk factors. Prevalence of TE according to the tyep of cancer Type of Cancer N Patients with TE % with TE (95% CI) ALL 185 26 14.5 (9.39, 19.91) Brain Tumors 131 1 0.8 (0.02, 4.20) Lymphoma 72 9 12.5 (5.88, 22.41) Sarcoma 70 10 14.3 (7.07, 24.71) AML 51 3 5.9 (1.23, 16.24) Neuroblastoma 45 1 2.2 (0.05, 11.77) Wilms’ Tumor 43 1 1.3 (0.06, 12.3) Other 9 0 - Total 606 49 8.1 (6.1, 10.5)
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".