The choice of primary and secondary endpoints for the individual studies of a research and development program is a classical biometric problem. Far-reaching decisions have to be made on the basis of incomplete information. Early studies in a program usually have functional or symptom-driven endpoints; the larger subsequent trials will usually focus on quality of life, morbidity or mortality. For program acceleration and cost reduction surrogate parameters are welcome. Unfortunately, there are only a few generally accepted surrogates for morbidity or mortality. At first glance, risk scores seem to be a suitable means for filling this gap. They are easily calculated, comprehensive and thus form a solid base for shared decision-making. However, further reasoning reveals that risk scores do not meet the usual standards for surrogates. What is more, a treatment targeting the reduction of a risk score cannot be considered an evidence-based intervention, which is due to a lack of randomized trials that compare risk score reduction to conventional interventions focussing on isolated risk factors. Thus, risk scores are unsuitable for primary endpoints, whereas they play an important role as comprehensive explanatory variables in study evaluation, i.e., for the description of population characteristics and as potential control variables or effect modifiers.
