Pediatric Osteosarcoma of Extremities: A 15-year Experience From a Tertiary Care Cancer Center in Upper Egypt
Bibliographic record
Abstract
AIM: To assess the outcome and determine predictors of survival in pediatric patients with osteosarcoma of the extremities treated with a unified chemotherapy protocol at a single institution over a 15-year period. MATERIALS AND METHODS: We performed a retrospective analysis of medical records of 48 pediatric patients with histologically verified osteosarcoma of the extremities diagnosed at South Egypt Cancer Institute and received treatment between January 2001 and December 2015. RESULTS: With a median follow-up of 61 months for the entire cohort, estimates of overall survival (OS) for 3- and 5-year were 50.9% and 42.1%, respectively. While the estimates of OS for 3- and 5-year in the nonmetastatic group were 79% and 65.2%, respectively. In the multivariable analysis, both metastatic disease at diagnosis and poor response to chemotherapy retained their statistical significance as independent predictors for event-free survival. Whereas for OS, a metastatic disease at diagnosis remained as the lone predictor of a dismal outcome, while a poor response to chemotherapy became marginally associated with an inferior outcome. CONCLUSIONS: In Upper Egypt, whereas slightly less than two thirds of children with localized osteosarcoma of extremities survives their disease, metastasis at presentation remains the key predictor of dismal survival outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".