The Utility of Second-Tier Genomic Sequencing for Hereditary Cancer Syndromes: A Mixed-Methods Study
Bibliographic record
Abstract
Background: Identification of patients with hereditary cancer syndromes (HCS) is important to detect high-risk patients who become eligible for surveillance and preventive surgeries that reduce cancer risk or detect it earlier, reducing morbidity and mortality. Standard panels only identify 10-20% of HCS patients. Genomic sequencing (GS) may identify more high-risk patients; however, evidence demonstrating utility of GS in HCS is lacking. Methods: This mixed-methods thesis aimed to explore the utility of second-tier GS for HCS. The first study explored clinician-reported utility of GS for HCS and other indications through a qualitative study using semi-structured interviews with Canadian clinicians with GS experience. Transcripts were thematically analyzed using constant comparison. The second study evaluated clinical utility of second-tier GS for HCS through chart review and survey conducted for cancer patients undergoing GS in an RCT. Charts were reviewed to extract diagnostic yield and management changes data. The final study explored patient-reported utility of cancer GS results by conducting a qualitative study using semi-structured interviews with patients who received second-tier GS as part of the aforementioned RCT. Transcripts were analyzed using constant comparison, similar to aim 1. Finally, a narrative approach was used to integrate quantitative and qualitative data. Results: All three studies suggest that GS provides limited utility above standard panels in HCS patients. The first qualitative study found that cancer clinicians attributed minimal utility from second-tier GS, who emphasized that the additional low/moderate penetrance results identified would not change management. The second study revealed that second-tier GS identified pathogenic results in 10% of patients, most in low/moderate penetrance genes with minimal actionability and at the cost of a high VUS rate of 90%. Findings from the third study indicated that patients centered their perceptions of utility of GS results on whether they changed management. Consequently, patients without management changes perceived anxiety and became hypervigilant, experiencing harms. Conclusions: As a second-tier test, GS provided limited utility for cancer patients and may be triggering harms. Our findings call for practice interventions to support patients receiving uninformative results from cancer genetic testing and for research to establish the utility of first-tier GS in HCS.
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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 | 0.099 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".