Genetic risk assessment for hereditary renal cell carcinoma: Clinical consensus statement
Bibliographic record
Abstract
BACKGROUND: Although renal cell carcinoma (RCC) is believed to have a strong hereditary component, there is a paucity of published guidelines for genetic risk assessment. A panel of experts was convened to gauge current opinions. METHODS: A North American multidisciplinary panel with expertise in hereditary RCC, including urologists, medical oncologists, clinical geneticists, genetic counselors, and patient advocates, was convened. Before the summit, a modified Delphi methodology was used to generate, review, and curate a set of consensus questions regarding RCC genetic risk assessment. Uniform consensus was defined as ≥85% agreement on particular questions. RESULTS: Thirty-three panelists, including urologists (n = 13), medical oncologists (n = 12), genetic counselors and clinical geneticists (n = 6), and patient advocates (n = 2), reviewed 53 curated consensus questions. Uniform consensus was achieved on 30 statements in specific areas that addressed for whom, what, when, and how genetic testing should be performed. Topics of consensus included the family history criteria, which should trigger further assessment, the need for risk assessment in those with bilateral or multifocal disease and/or specific histology, the utility of multigene panel testing, and acceptance of clinician-based counseling and testing by those who have experience with hereditary RCC. CONCLUSIONS: In the first ever consensus panel on RCC genetic risk assessment, 30 consensus statements were reached. Areas that require further research and discussion were also identified, with a second future meeting planned. This consensus statement may provide further guidance for clinicians when considering RCC genetic risk assessment. LAY SUMMARY: The contribution of germline genetics to the development of renal cell carcinoma (RCC) has long been recognized. However, there is a paucity of guidelines to define how and when genetic risk assessment should be performed for patients with known or suspected hereditary RCC. Without guidelines, clinicians struggle to define who requires further evaluation, when risk assessment or testing should be done, which genes should be considered, and how counseling and/or testing should be performed. To this end, a multidisciplinary panel of national experts was convened to gauge current opinion on genetic risk assessment in RCC and to enumerate a set of recommendations to guide clinicians when evaluating individuals with suspected hereditary kidney cancer.
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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 | 0.123 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".