Quantifying the Predictive Accuracy of a Polygenic Risk Score for Predicting Incident Cancer Cases : Application to the CARTaGENE Cohort

@article{Duhaze2020QuantifyingTP,
  title={Quantifying the Predictive Accuracy of a Polygenic Risk Score for Predicting Incident Cancer Cases : Application to the CARTaGENE Cohort},
  author={Julianne Duhaze and Rodolphe Jantzen and Yves Payette and Thibault de Malliard and Catherine Labb{\'e} and Nolwenn Noisel and Philippe Bro{\"e}t},
  journal={Frontiers in Genetics},
  year={2020},
  volume={11}
}
With the increasing use of polygenic risk scores (PRS) there is a need for adapted methods to evaluate the predictivity of these tools. In this work, we propose a new pseudo-R2 criterion to evaluate PRS predictive accuracy for time-to-event data. This new criterion is related to the score statistic derived under a two-component mixture model. It evaluates the effect of the PRS on both the propensity to experience the event and on the dynamic of the event among the susceptible subjects… 
1 Citations
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TLDR
This review summarises the potential use cases for seven common diseases where PRS has or could have clinical utility and summarises open questions regarding PRS usability, ancestry bias, and transferability, emphasising the need for the next wave of studies to focus on the implementation and health-economic value of PRS testing.

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