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Updated: Jul 16, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Calibrating variant curation by clinical context based on factors that influence patients' tolerance of uncertainty
Alison H Trainer1, Erin Goode2, Cass N Hoskins2
1Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Department of Medicine, University of Melbourne, Melbourne, VIC, Australia; Department of Genomic Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.
Purpose:
Shared decision making manages genomic uncertainty by integrating molecular and clinical uncertainties with patient values to craft a person-centered management plan. Laboratories seek genomic report consistency, agnostic to clinical context. Molecular reports often mask laboratory-managed uncertainties from clinical decision making. Better integration of these uncertainty management strategies requires a nuanced understanding of patients' perceptions and reactions to test uncertainties. We explored patients' tolerance to variant uncertainty in 3 parameters: (1) relative causal significance, (2) risk accuracy, and (3) classification validity.
Method:
Deliberative forums were undertaken with 18 patients with predictive testing experience. Uncertainty deliberations were elicited for each parameter. A thematic framework was first developed, and then mapped to whether they justified tolerance to more or less parameter-specific uncertainty.
Results:
Six identified themes mapped to clinical and personal domains. These domains generated opposing forces when calibrating uncertainty. Personal themes justified tolerance of higher uncertainty and clinical themes lower uncertainty. Decision making in uncertainty focused on reducing management regret. Open communication increased tolerance of classification validity and risk accuracy uncertainty. Using these data, we have developed a nascent clinical algorithm integrating molecular uncertainty with clinical context through a targeted communication framework.
Conclusion:
Maximizing test utility necessitates context-specific recalibration of uncertainty management and communication.
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