ArticleCancers2026
Evaluation of Costs, Efficiency and Performance of a Pilot Genetic Testing Traceback Program for Ovarian Cancer.
Article in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors.
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Abstract
BACKGROUND/
objectivesGuideline-issuing organizations recommend that women with ovarian cancer undergo genetic testing to identify genetic variants related to hereditary breast and ovarian cancer. The National Cancer Institute proposed the Traceback framework to conduct genetic testing on previously untested women and their at-risk relatives. We implemented a pilot Traceback program in three large healthcare systems: Geisinger (GE), Kaiser Permanente Washington (KPWA), and Kaiser Permanente Mid-Atlantic States (KPMAS). We evaluated the performance, cost, and efficiency of the implementation.
methodsWe developed three decision-analytic models representing implemented programs to evaluate performance and estimate direct implementation costs and efficiency from a healthcare system perspective using a bottom-up micro-costing approach based on real-world data. We generalize our findings by modeling hypothetical Traceback programs based on our implementation using national cost data and literature estimates.
resultsThe programs identified 450, 240, and 878 living ovarian cancer patients at GE, KPWA, and KPMAS, respectively. Of those, 224 (49.8%), 149 (62.1%), and 224 (25.5%) were previously untested, of which 18 (8.0%), 37 (24.8%), and 74 (33.0%) underwent genetic testing. The program costs were $41,564 (GE), $97,396 (KPWA), and $120,327 (KPMAS), with KPMAS showing the lowest cost per patient tested and cost per case detected ($1626, $17,190) versus ($2309, $41,564) (GE) and ($2632, $48,698) (KPWA).
conclusionsTraceback programs were feasible to implement and were associated with improved genetic testing uptake for ovarian cancer patients in this non-randomized pilot. Evaluable outcomes reflect proband testing; additional data and evaluations are needed for assessing cascade testing. Quantifying costs can inform decision-makers on resource allocation for similar programs.
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