Breast cancer germline multigene panel testing in mainstream oncology based on clinical–public health utility: ESMO Precision Oncology Working Group recommendations
Bibliographic record
Abstract
BACKGROUND: With widening therapeutic indications, germline genetic testing is offered to an increasing proportion of patients with breast cancer (BC) via mainstream oncology services. However, the gene set tested varies widely from just BRCA1/BRCA2 through to 'pan-cancer' panels of nearly 100 genes. If a germline pathogenic variant (GPV) is detected, the BC proband and other family GPV-carriers may be offered interventions such as risk-reducing surgery and intensive surveillance over decades for the various cancers linked to that gene. METHODS: The European Society for Medical Oncology (ESMO) Precision Oncology Working Group established an international expert working group (EWG) in BC germline genetics. This EWG firstly established a framework of criteria by which to evaluate each breast cancer susceptibility gene (BCSG) for potential inclusion on a breast cancer multigene panel test (BC-MGPT) for universal mainstream testing for BC cases. Next, the EWG scored BCSGs for impact regarding (i) BC risk estimation, (ii) clinical actionability and (iii) cancer-related mortality. RESULTS: The group agreed that they would constitute a BC-MGPT based on net clinical-public health utility, as quantified by likelihood of impact on cancer-related mortality. Judged as of high or moderate impact on this basis were six BCSGs: BRCA1, BRCA2, PALB2, RAD51C, RAD51D and TP53 (for BC diagnosed <40 years of age), with possible addition of BRIP1. While potentially informative for BC risk estimation, CHEK2 and ATM were judged to offer insufficient evidence for improving cancer-related mortality. The EWG recommended strongly against inclusion of 'syndromic' genes such as STK11, PTEN, NF1 and CDH1. CONCLUSIONS: With expanded germline testing in patients with BC (and cascade testing into families), the number and nature of resultant GPV-carriers identified will be dictated by the genes included on the upfront BC-MGPT. The potential harms, opportunity and economic costs of decades of surveillance of multiple organs and risk-reducing surgeries for GPV-carriers should be justified by strong evidence of meaningful improvement in cancer-related mortality (or health-related quality of life).
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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 | 0.117 | 0.135 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.012 | 0.008 |
| Research integrity | 0.023 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".