Irrespective of predictive power, there are a number of benefits of such genetic prediction over classical alternatives. For instance, unlike classical risk prediction, genetic risk prediction is highly stable over time, as a person's genetic sequence is essentially constant throughout their life. Some currently used clinical biomarkers, in contrast, are powerful predictors of disease risk in the near term but less valuable in assessing lifetime risk. A study in type 2 diabetes (35) showed that the AUC for clinical predictors declines from 0.76 to 0.64 as mean follow-up time increases from 16 to 28 years, but genetic prediction improves from 0.57 to 0.62 over the same timescale (see also the lipid level example above). This allows risk prediction to be performed on a much longer time scale than is currently plausible. Such stable risk stratification could be especially important when the proposed interventions are more effective if started at an early age, or continued over a long time period.
