Role of Genetic Testing for Inherited Prostate Cancer Risk: Philadelphia Prostate Cancer Consensus Conference 2017
Bibliographic record
Abstract
Purpose Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-driven working framework for comprehensive genetic evaluation of inherited PCA in the multigene testing era addressing genetic counseling, testing, and genetically informed management. Methods An expert consensus conference was convened including key stakeholders to address genetic counseling and testing, PCA screening, and management informed by evidence review. Results Consensus was strong that patients should engage in shared decision making for genetic testing. There was strong consensus to test HOXB13 for suspected hereditary PCA, BRCA1/2 for suspected hereditary breast and ovarian cancer, and DNA mismatch repair genes for suspected Lynch syndrome. There was strong consensus to factor BRCA2 mutations into PCA screening discussions. BRCA2 achieved moderate consensus for factoring into early-stage management discussion, with stronger consensus in high-risk/advanced and metastatic setting. Agreement was moderate to test all men with metastatic castration-resistant PCA, regardless of family history, with stronger agreement to test BRCA1/2 and moderate agreement to test ATM to inform prognosis and targeted therapy. Conclusion To our knowledge, this is the first comprehensive, multidisciplinary consensus statement to address a genetic evaluation framework for inherited PCA in the multigene testing era. Future research should focus on developing a working definition of familial PCA for clinical genetic testing, expanding understanding of genetic contribution to aggressive PCA, exploring clinical use of genetic testing for PCA management, genetic testing of African American males, and addressing the value framework of genetic evaluation and testing men at risk for PCA-a clinically heterogeneous disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.049 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".