Renal Liposarcoma in a Patient Undergoing Radiotherapy in Childhood: A Case Report
Bibliographic record
Abstract
Soft tissue sarcomas are rare neoplasms, which account for less than 1% of adult malignancies. In addition, they account for only 2% of renal cancers. The main mesenchymal lesions of the kidney are benign and difficult to differentiate with well-differentiated sarcomas. The aim of this report was to present the experience of the Hospital Sao Paulo (HU/UNIFESP) in a case of well-differentiated liposarcoma, which affected the kidney of a young adult who has been treated with radiotherapy in childhood, as well as to raise the relevant literature. A 26-year-old male patient with a history of prostate rhabdomyosarcoma that has been submitted to surgical resection and adjuvant radiotherapy 23 years ago in the childhood was presented. He was asymptomatic during 22 years, then he developed back pain, and underwent investigation and one tumor was detected in the right kidney. Radical nephrectomy was performed with complete resection of the lesion and he is currently without evidence of disease recurrence. Renal liposarcoma usually has good prognosis and the treatment is based almost exclusively on tumor resection. The differentiation between primary renal or retroperitoneal site is important for the prognostic assessment of the disease. There is a relationship between exposure to radiation in childhood and the development of second malignancy in adulthood, especially soft tissue sarcomas. Metastases are rare in well-differentiated forms of the disease. Recurrences can be observed in 30% of all cases and have been described after 13 years of initial diagnosis, which justifies the extended follow-up of these patients. J Med Cases. 2014;5(10):538-540 doi: http://dx.doi.org/10.14740/jmc1933w
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".