Subependymal Giant Cell Astrocytoma: Diagnosis, Screening, and Treatment. Recommendations From the International Tuberous Sclerosis Complex Consensus Conference 2012
Bibliographic record
Abstract
BACKGROUND: Tuberous sclerosis complex is an autosomal dominant disorder predisposing to the development of benign lesions in different body organs, mainly in the brain, kidney, liver, skin, heart, and lung. Subependymal giant cell astrocytomas are characteristic brain tumors that occur in 10% to 20% of tuberous sclerosis complex patients and are almost exclusively related to tuberous sclerosis complex. Subependymal giant cell astrocytomas usually grow slowly, but their progression ultimately leads to the occlusion of the foramen of Monro, with subsequent increased intracranial pressure and hydrocephalus, thus necessitating intervention. During recent years, secondary to improved understanding in the biological and genetic basis of tuberous sclerosis complex, mammalian target of rapamycin inhibitors have been shown to be effective in the treatment of subependymal giant cell astrocytomas, becoming an alternative therapeutic option to surgery. METHODS: In June 2012, an International Tuberous Sclerosis Complex Consensus Conference was convened, during which an expert panel revised the diagnostic criteria and considered treatment options for subependymal giant cell astrocytomas. This article summarizes the subpanel's recommendations regarding subependymal giant cell astrocytomas. CONCLUSIONS: Mammalian target of rapamycin inhibitors have been shown to be an effective treatment of various aspects of tuberous sclerosis complex, including subependymal giant cell astrocytomas. Both mammalian target of rapamycin inhibitors and surgery have a role in the treatment of subependymal giant cell astrocytomas. Various subependymal giant cell astrocytoma-related conditions favor a certain treatment.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".