AUTHOR=Duhazé Julianne , Jantzen Rodolphe , Payette Yves , De Malliard Thibault , Labbé Catherine , Noisel Nolwenn , Broët Philippe 

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

JOURNAL=Frontiers in Genetics

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.00408

DOI=10.3389/fgene.2020.00408

ISSN=1664-8021

ABSTRACT=With the increasing use of polygenic risk scores (PRS) there is a need of 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.
Simulation results show that our index has good properties. We compared our index to other implemented pseudo-R² for survival data. Along with our index, two other indices have comparable good behavior when the PRS has a non-null propensity effect, and our index is the only one to detect when the PRS have only a dynamic effect. We evaluated the five-year predictivity of a 18 single nucleotide polymorphism PRS for incident breast cancer cases on the CARTaGENE cohort using several pseudo-R² indices.
We report that our index had the highest predictive accuracy underlying that this PRS summarized both a propensity and a dynamic effect.
In conclusion, our proposed pseudo-R² is easy to implement and well suited to evaluate PRS for predicting incident events in cohort studies.