Evaluation of Overall Survival (OS) and Event-Free Survival (EFS) of Paediatric Sarcoma Patients at a Single Institution
Bibliographic record
Abstract
Aims: To evaluate OS and EFS of paediatric sarcoma patients with an interest in comparing metastatic cases with non-metastatic cases, and compiling statistics on treatment methods. Methods: Information was obtained from patient notes in the Schiehallion ward. These contained information about diagnosis, treatment, prognostic indicators, and outcomes for each patient. Results: 56 patients, 2001-2008. Osteosarcoma: 11 patients, 7♂, 4♀; age range: 4-16; = 10; OS = 64%, EFS = 55%; Primary site of disease: Femur (47%), Tibia (41%), Humerus (5.5%), Scapula (5.5%), Other (1%); Metastatic Rate = 27% (OS = 0%). Ewing’s sarcoma: 24 patients, 10♂, 14♀; age range: 1-16, = 12; OS = 71%, EFS = 58%; Primary site of disease: Pelvis (29%), Femur (22%), Paraspinal (16%), Chest Wall (10%), Tibia (10%), Other (13%); Metastatic Rate = 21% (OS = 40%; EFS = 40%); Alveolar rhabdomyosarcoma: 10 patients; OS= 80%, EFS = 60%; Metastatic Rate = 20% (OS = 100%; EFS = 100%). Embryonal rhabdomyosarcoma: 11 patients; OS = 73%, EFS = 73%; Metastatic Rate = 0%. Conclusions: Our results reflect access to an experienced and innovative paediatric sarcoma service with close links to a national Sarcoma MDT. The data falls in line with other studies in terms of age of onset, location of primary tumour, metastatic rate, site of metastases, and prognosis for all cancer types. Limb salvage surgery is greatly favoured over amputation for both osteosarcoma and Ewing’s sarcoma. Females have a more favourable prognosis in osteosarcoma and a slightly poorer prognosis in Ewing’s sarcoma. Yorkhill’s overall survival rates are currently better than the UK-wide statistic for three of the four tumours examined.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".