Lynch Syndrome Limbo: Patient Understanding of Variants of Uncertain Significance
Bibliographic record
Abstract
Providers and patients encounter challenges related to the management of Variants of Unknown Significance (VUS). A VUS introduces new counseling dilemmas for the understanding and psychosocial impact of uncertain genetic test results. This descriptive study uses Mishel's theory of uncertainty in illness to explore the experience of individuals who have received a VUS as part of the genetic testing process. Semi-structured interviews were conducted with 27 adult individuals who received a VUS for Lynch syndrome mismatch repair genes between 2002 and 2013. The interviews were transcribed and analyzed. Most individuals recalled their result and perceived various types of uncertainty associated with their VUS. Half of the participants appraised their variant as a danger and implemented coping strategies to reduce the threat of developing cancer. Mobilizing strategies to reduce their risk included vigilant cancer surveillance, information seeking and notifying relatives. The majority of participants were unaware of the possibility of a VUS before receiving their result and expected reclassification over time. These results provide insight into the ways healthcare providers can support patients who receive VUS for Lynch syndrome. Findings also provide direction for future work that can further explicate the impact of receiving a VUS.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".