Central Venous Line Dysfunction is an Independent Predictor of Poor Survival in Children With Cancer
Bibliographic record
Abstract
Central venous line (CVL) dysfunction (mainly from thrombotic occlusion) is a frequent, but relatively less-studied complication compared with infection and thromboembolism (TE). In adults with cancer, TE results in poor outcome. We evaluated the impact of CVL-dysfunction and TE on overall survival (OS) and event-free survival (EFS) in children with noncentral nervous system cancer (n=358). CVL-dysfunction was defined as persistent or recurrent difficulty of blood draw and/or infusion. Event was defined as cancer relapse, second malignancy, or death due to any cause. OS and EFS were estimated using Kaplan-Meier method and survival curves compared using log-rank test. Hazard ratios (HR) were calculated using the Weibull regression model. Diagnosis of TE (n=43, 12%) had no effect on the OS and EFS. Children with CVL-dysfunction (n=74, 21%) had shorter 5- and 10-year EFS compared with children without CVL-dysfunction (P=0.029 and P=0.027). Multiple regression analyses, adjusting for age, sex, diagnostic era, TE, and cancer type identified CVL-dysfunction as an independent determinant of 5-year OS (HR 1.87; 95% confidence interval, 1.02-3.42; P=0.043) and EFS (HR 1.96; 95% confidence interval, 1.23-3.41; P=0.018). Although the etiology of adverse impact of CVL-dysfunction on survival is unknown, its prevention and prompt treatment may improve outcome from cancer in children. Further prospective studies are recommended.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".