Update on Tumor Surveillance for Children with Hereditary Pheochromocytoma/Paraganglioma Syndromes
Bibliographic record
Abstract
Hereditary pheochromocytoma/paraganglioma syndromes (HPPS) are a collection of conditions caused by variants in genes producing subunits of the succinate dehydrogenase (SDH) complex or related proteins. These conditions are characterized by substantial lifetime risks for developing pheochromocytomas, paragangliomas, and other tumors. Affected individuals who develop these tumors may experience severe, acute, and chronic problems. Indeed, aggressive, malignant, and/or disseminated tumors may result in death. Tumor surveillance enables early intervention, which, in turn, should lead to improved clinical outcomes. However, the desire for intensive surveillance strategies must be balanced against medical and psychosocial risks. In 2017, consensus HPPS surveillance recommendations addressing germline predisposition to SDHA-, SDHAF2-, SDHB-, SDHC-, SDHD-, MAX-, and TMEM127 (collectively, SDHx+)-related tumors were published after the inaugural American Association for Cancer Research Childhood Cancer Predisposition Workshop. Based on the limited available clinical data at that time, these recommendations advocated a uniform approach to tumor surveillance in HPPS. Since then, several other groups have proposed alternative consensus surveillance guidelines. Although these surveillance approaches share some common elements, including recommendations tailored to emerging differences in tumor phenotype based on underlying specific SDHx+ genes, these approaches also vary significantly among each other. As clinical data continue to accrue, it is critical that surveillance strategies continue to be refined to address emerging genotype-phenotype differences. In this review, we provide a brief up-to-date clinical overview of HPPS and describe recently proposed tumor surveillance regimens. We then detail our updated consensus pediatric-focused tumor surveillance recommendations from the 2023 American Association for Cancer Research Childhood Cancer Predisposition Workshop.
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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 | 0.003 | 0.019 |
| 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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".