Survival and Late Mortality in Long-Term Survivors of Pediatric CNS Tumors
Bibliographic record
Abstract
PURPOSE: To describe the pattern of survival and late mortality among contemporary long-term survivors of pediatric CNS tumor. PATIENTS AND METHODS: The study population comprised 643 pediatric patients with primary CNS tumor treated at St Jude Children's Research Hospital (Memphis, TN) from 1985 to 2000 who survived > or = 5 years from diagnosis. Patients were classified according to primary tumor type, location of tumor, and survival. Cause of death was obtained from the medical record and categorized as progression, malignant transformation, second malignancy, medical complication, or external cause. RESULTS: Overall survival estimates for patients who survived at least 5 years postdiagnosis was 91.3% +/- 2% and 86% +/- 3% at 10 and 15 years postdiagnosis, respectively. A significant difference in the survival rates according to original tumor type (P = .001) was seen. Sixty-six (10%) of 643 patients experienced late mortality: 38 patients (58%) died of progressive disease while 14 patients (21%) died of second malignant tumor. Twelve patients (18%), predominantly with diencephalic tumor location, died of a specific medical cause: cardiovascular disease (n = 2), cerebrovascular accident (n = 1), metabolic collapse and/or sepsis (n = 7), respiratory failure (n = 1), or shunt malfunction (n = 1). CONCLUSION: Late mortality occurs in a substantial number of long-term survivors of pediatric CNS tumors and is most influenced by the initial tumor histopathology. Progressive disease remains the most common cause of death within the first decade of diagnosis. Teenage patients requiring treatment for panhypopituitarism may be especially vulnerable and deserve significant medical surveillance.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".