scholarly journals Risk Stratification and Clinical Utility of Polygenic Risk Scores in Ophthalmology

2021 ◽  
Vol 10 (6) ◽  
pp. 14
Author(s):  
Ayub Qassim ◽  
Emmanuelle Souzeau ◽  
Georgie Hollitt ◽  
Mark M. Hassall ◽  
Owen M. Siggs ◽  
...  
2021 ◽  
Vol 51 ◽  
pp. e234
Author(s):  
Huyen Nguyen ◽  
Tiahna Moorthy ◽  
Jehannine Austin ◽  
Jordan Smoller ◽  
Laura Hercher ◽  
...  

2020 ◽  
Vol 11 ◽  
Author(s):  
Silvia Biere ◽  
Thorsten M. Kranz ◽  
Silke Matura ◽  
Kristiyana Petrova ◽  
Fabian Streit ◽  
...  

2018 ◽  
Vol 19 (9) ◽  
pp. 581-590 ◽  
Author(s):  
Ali Torkamani ◽  
Nathan E. Wineinger ◽  
Eric J. Topol

2020 ◽  
Author(s):  
Stuart G Baker

Abstract There is growing interest in the use of polygenic risk scores based on genetic variants to predict cancer incidence. The type of metric used to evaluate the predictive performance of polygenic risk scores plays a crucial role in their interpretation. I compare three metrics for this evaluation: the area under the Receiver Operating Characteristic curve (AUC), the probability of cancer in a high-risk subset divided by the prevalence of cancer in the population, which I call the subset relative risk (SRR), and the minimum test tradeoff (MTT), which is the minimum number of gene variant ascertainments (one per person) for each correct prediction of cancer to yield a positive expected clinical utility. I show that SRR is a relabeling of AUC. I recommend MTT for the evaluation of polygenic risk scores because, unlike AUC and SRR, it is directly related to the expected clinical utility.


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