Multi-Gene Panel Testing for Hereditary Cancer Predisposition Among Patients Sixty-Five Years and Above Diagnosed With Breast Cancer
Bibliographic record
Abstract
Background: The availability and affordability of germline genetic testing (GGT) has resulted in a broader utilization in daily clinical practice. However, adherence to testing guidelines is low, especially among older patients, where testing is often not offered. Methods: In this study, consecutive, newly diagnosed patients with breast cancer (BC) aged ¡Ý 65 years and eligible for GGT, as per the National Comprehensive Cancer Network (NCCN) guidelines (version 1, 2021), were invited to participate, from March 2021 to December 2022. Patients were offered a restricted (two- or 20-gene panel), or an expanded 84-gene panel. Results: During the study period, 204 patients were enrolled. The mean (standard deviation (SD)) age at BC diagnosis was 70.5 (5.13) years, ranging 65 - 81 years. All patients were Arab and the majority were Jordanian. The majority (n = 188, 92.2%) had early-stage (stages I and II) disease. One hundred three (50.5%) patients were tested with a restricted two-gene (n = 13) or 20-gene (n = 90) panel, while the remaining 101 (49.5%) patients had an expanded 84-gene panel. Family history of close blood relative(s) with BC was the most common indication for testing (n = 110, 53.9%). Among the entire study cohort, 22 (10.8%) had pathogenic/likely pathogenic germline variants (PGVs) and another 97 (47.5%) had ¡Ý 1 variants of uncertain significance (VUS). PGV rates were significantly higher with the expanded panel (14.9%) compared to restricted testing (6.8%) (P = 0.032). Similarly, VUS rates were significantly higher with the expanded panel (64.4%) compared to the restricted panel (31.1%) (P < 0.001). The most prevalent genes with PGVs were BRCA1/2 (31.3% of all PGV-positive patients), CHEK2 (23.1%) and ATM (19.2%). Conclusion: GGT should not be overlooked in older BC patients, as this study demonstrates that > 10% of patients have PGVs, largely in potentially actionable genes. World J Oncol. 2024;15(5):777-783 doi: https://doi.org/10.14740/wjon1919
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".