Von Hippel–Lindau and Hereditary Pheochromocytoma/Paraganglioma Syndromes: Clinical Features, Genetics, and Surveillance Recommendations in Childhood
Bibliographic record
Abstract
Abstract Von Hippel–Lindau disease (vHL) is a hereditary tumor predisposition syndrome that places affected individuals at risk for multiple tumors, which are predominantly benign and generally occur in the central nervous system or abdomen. Although the majority of tumors occur in adults, children and adolescents with the condition develop a significant proportion of vHL manifestations and are vulnerable to delayed tumor detection and their sequelae. Although multiple tumor screening paradigms are currently being utilized for patients with vHL, surveillance should be reassessed as the available relevant clinical information continues to expand. We propose a new vHL screening paradigm similar to existing approaches, with important modifications for some tumor types, placing an emphasis on risks in childhood. This includes advancement in the timing of surveillance initiation and increased frequency of screening evaluations. Another neuroendocrine-related familial condition is the rapidly expanding hereditary paraganglioma and pheochromocytoma syndrome (HPP). The tumor spectrum for patients with HPP syndrome includes paragangliomas, pheochromocytomas, renal cancer, and gastrointestinal stromal tumors. The majority of patients with HPP syndrome harbor an underlying variant in one of the SHDx genes (SDHA, SDHB, SDHC, SDHD, SDHA, and SDHAF2), although other genes also have been described (MAX and TMEM127). Annual screening for elevated plasma or urine markers along with complete blood count and biennial whole-body MRI accompanied by focal neck MRI is recommended for older children and adults with HPP syndrome to detect tumors early and to decrease morbidity and mortality from HPP-related tumors. Clin Cancer Res; 23(12); e68–e75. ©2017 AACR. See all articles in the online-only CCR Pediatric Oncology Series.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".