A recent study claimed that genome-wide polygenic scores (GPSs) for five common diseases could identify individuals with risk equivalent to monogenic mutations. Receiver operator curve analyses were reported to have areas under the curve (AUCs) ranging from 0.63 for inflammatory bowel disease up to 0.81 for coronary artery disease (CAD). The GPS for CAD identified 8% of the population at threefold increased risk, which it was claimed was comparable to the excess risk from monogenic mutations. Attempts were made to model the distribution of GPS for CAD to match the information provided. Models were based on the reported distribution of prevalence and GPS and were fitted to the reported results using linear approximations to the distributions and using simulations of a liability-threshold model. It was impossible to produce a compatible model which produced an AUC as high as 0.81 and the most plausible estimate was that the true AUC was only 0.65. The reported distributions in cases and controls largely overlap so that they are not compatible with an AUC of 0.7 or more. The true AUC of the GPS for these diseases is much lower than claimed. Furthermore, the literature robustly demonstrates that true CAD risk associated with monogenic mutations is much higher than the threefold increase which was claimed. Together, these findings cast doubt on the clinical utility of the GPS.