Evaluating the Clinical Impact of a Genomic Classifier in XXXX Using Individualized Decision Analysis.

@entity1 @entity137 @entity263 @entity5 @entity10281 @entity3 @entity8447 @entity204
BACKGROUND: Currently there is controversy surrounding the optimal way to treat @entity1 with @entity263 in the @entity10281 . Adjuvant therapies carry possible benefits of improved curative results, but there is uncertainty in which @entity1 should receive adjuvant therapy. There are concerns about giving @entity137 to a whole population for the benefit of only a subset. We hypothesized that making @entity8447 treatment decisions using genomics-based risk prediction estimates would improve @entity5 and quality of life outcomes. METHODS: We developed a state-transition model to simulate outcomes over a 10 year horizon for a cohort of @entity8447 @entity1 . Outcomes included @entity5 progression rates at 5 and 10 years, overall survival, and quality-adjusted survival with reductions for treatment, side effects, and @entity5 stage. We compared outcomes using population-level versus individual-level risk of @entity5 progression, and for genomics-based care versus usual care treatment recommendations. RESULTS: Cancer progression outcomes, expected life-years (LYs), and expected quality-adjusted life-years (QALYs) were significantly different when individual genomics-based @entity5 progression risk estimates were used in place of population-level risk estimates. Use of the genomic classifier to guide treatment decisions provided small, but statistically significant, improvements in model outcomes. We observed an additional 0.03 LYs and 0.07 QALYs, a 12% relative increase in the 5-year recurrence-free survival probability, and a 4% relative reduction in the 5-year probability of @entity3 or @entity204 . CONCLUSIONS: The use of genomics-based risk prediction to guide treatment decisions may improve outcomes for @entity263 @entity1 . This study offers a framework for individualized decision analysis, and can be extended to incorporate a wide range of personal attributes to enable delivery of @entity1 -centered tools for informed decision-making.
