Paediatric Parameningeal Rhabdomyosarcoma: A Case Report Post-multimodal Treatment
Bibliographic record
Abstract
Rhabdomyosarcoma is the most common soft tissue sarcoma of childhood, representing 5% of all childhood cancers. We are reporting an interesting case of parameningeal rhabdomyosarcoma in a child who underwent multimodal treatment. A 7 year old boy presented to our clinic with a history of bad breath, nasal obstruction and recurrent epistaxis from the left nostril for 3 months. On examination he had mild left proptosis with normal eye vision and movements, reddish left nasal mass with a smooth surface. Paranasal CT scan showed slightly enhancing soft tissue mass 72×77 mm in the nasal cavity that deviated the nasal septum to the right, extending to the nasopharynx posteriorly and to the maxillary and ethmoidal sinuses with another mass 11×16 mm extension into the orbit. Biopsy was taken and histology showed embryonal rhabdomyosarcoma. An extensive tumour debulking was done folwed by chemotherapy (vincristine, dactinomycin and cyclophosphamide) and 50 grays of radiotherapy. A surveillance CT scan a month after treatment revealed over 90% tumour reduction. All patients with metastatic disease (group IV, stage 4) are considered high risk, except children and adolescents younger than 14 years with embryonal rhabdomyosarcoma. Advances into the multimodality management have dramatically improved survival in PM-RMS from approximately 25% to 75%.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".