Genetic spectrum in a Canadian cohort of apparently sporadic pheochromocytomas and paragangliomas: New data on multigene panel retesting over time
Bibliographic record
Abstract
OBJECTIVE: Pheochromocytomas (PHEOs) and paragangliomas (PGLs), collectively known as PPGLs, are tumours with high heritability. The prevalence of germline mutations in apparently sporadic PPGLs varies depending on the study population. The objective of this study was to determine the spectrum of germline mutations in a cohort of patients with apparently sporadic PPGLs over time. DESIGN: We performed a retrospective review of patients with apparently sporadic PPGLs who underwent genetic testing at our referral centre from 2005 to 2020. PATIENTS: We included patients with apparently sporadic PPGLs who underwent genetic testing at our referral center. MEASUREMENTS: Genetic analysis included sequential gene sequencing by Sanger method or next generation sequencing (NGS) with a multigene panel. RESULTS: The prevalence of germline mutations was 26.2% (43/164); 40.0% (30/75) in PGLs and 14.6% (13/89) in PHEOs. We identified four novel pathogenic variants (two SDHB and two SDHD). Patients carrying germline mutations were younger (38.7 vs. 49.7 years old) than patients with no identified germline mutations. From 2015 to 2020, we performed NGS with a multigene panel on 12 patients for whom the initial genetic analysis was negative. Germline mutations in previously untested genes were found in four (33.3%) of these patients (two MAX and two SDHA), representing 9.3% (4/43) of the mutation carriers. CONCLUSION: The prevalence of germline mutations in our cohort of patients with apparently sporadic PPGLs was 26.2%. Genetic re-evaluation over time using multigene sequencing by NGS assay in a subgroup of patients leads to an increase in the detection of mutations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".