of the research study [15]. (3) The area under the receiver operating characteristic curve (AUC) [16], which takes a value from 0.5 to 1. This gives an overall summary of the predictive ability of the model. It is most easily interpreted as the probability that a randomly selected case will have a higher polygenic risk score than a randomly selected control. Such models can also include risk factors such as age and sex, which will increase the AUC values above that based on PRS alone. (4) The proportion of the population that has a k-fold increased odds (k = 2, 3, …), compared to the population disease risk. (5) Odds ratio of disease risk conferred by a 1-standard deviation increase in PRS. (6) Odds ratio of disease for an individual in the top PRS decile (or other quantiles) compared to individuals in a different part of the PRS distribution. The high-risk group may be compared to the lowest decile, a mid-quintile (e.g. 40–60%), or those outside the high-risk group (0–90%). Comparing the upper and lower tails maximises the odds ratio for impact but raises concerns about the arbitrariness of the quantile used.B: Individual level In a clinical setting, the focus
