Germline Cancer Susceptibility Gene Testing in Unselected Patients With Colorectal Adenocarcinoma: A Multicenter Prospective Study
Bibliographic record
Abstract
BACKGROUND & AIMS: Hereditary factors play a role in the development of colorectal cancer (CRC). Identification of germline predisposition can have implications on treatment and cancer prevention. This study aimed to determine the prevalence of pathogenic germline variants (PGVs) in CRC patients using a universal testing approach, association with clinical outcomes, and the uptake of family variant testing. METHODS: We performed a prospective multisite study of germline sequencing using a more than 80-gene next-generation sequencing platform among CRC patients (not selected for age or family history) receiving care at Mayo Clinic Cancer Centers between April 1, 2018, and March 31, 2020. RESULTS: Of 361 patients, the median age was 57 years (SD, 12.4 y), 43.5% were female, 82% were white, and 38.2% had stage IV disease. PGVs were found in 15.5% (n = 56) of patients, including 44 in moderate- and high-penetrance cancer susceptibility genes. Thirty-four (9.4%) patients had incremental clinically actionable findings that would not have been detected by practice guideline criteria or a CRC-specific gene panel. Only younger age at diagnosis was associated with the presence of PGVs (odds ratio, 1.99; 95% CI, 1.12-3.56). After a median follow-up period of 20.7 months, no differences in overall survival were seen between those with or without a PGV (P = .2). Eleven percent of patients had modifications in their treatment based on genetic findings. Family cascade testing was low (16%). CONCLUSIONS: Universal multigene panel testing in CRC was associated with a modest, but significant, detection of heritable mutations over guideline-based testing. One in 10 patients had changes in their management based on test results. Uptake of cascade family testing was low, which is a concerning observation that warrants further study.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".