Genotype–phenotype correlations in paediatric and adolescent phaeochromocytoma and paraganglioma: a cross-sectional study
Bibliographic record
Abstract
Phaeochromocytoma (PC) and paraganglioma (PGL) syndromes associated with germline pathogenic variants are associated with high morbidity and mortality. Establishing genotype–phenotype correlations within a young population is challenging due to their rare occurrence. Objective To describe genotype–phenotype correlations in paediatric and adolescent patients diagnosed with PC/PGL. To establish the incidence of PC/PGL in a young population and prevalence of germline pathogenic variants within this group. Study design We conducted a cross-sectional study of patients diagnosed with a PC/PGL aged 0–21 years old who were reviewed within Familial Cancer Services within New South Wales and the Australian Capital Territory, Australia. Results A germline pathogenic variant was detected in 80% (24/30) of patients;SDHB: n=12,VHL: n=11, andMAX: n=1. Only patients harbouring a germline pathogenic variant reported a family history of syndromic tumours, those with apparently sporadic disease did not (62.5% versus 0%, p=0.02). All patients withVHLpresented with an adrenal tumour compared with 25% of those withSDHB(100% versus 25%, p=0.01). Occurrence of multiple primary PC/PGL was seen in patients withVHLhowever was absent in patients withSDHB(36% versus 0%, p=0.03). Incidence rate of paediatric PC/PGL was 0.45 cases per million person years. Conclusions PC/PGL diagnosed in children and adolescents were strongly associated with germline pathogenic variants inVHLorSDHB. These patients should be referred to specialist services for family counselling and genetic testing along followed by investigations for the detection of bilateral, multifocal or metastatic disease, and lifelong surveillance for recurrent disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".