Overlooking the obvious? On the potential of treatment alterations to predict patient-specific therapy response

Abstract

Prognostic or therapeutic classification of diseases is often based on clinical or genetic characteristics at diagnosis or response landmarks determined at a certain time point of treatment. On the other hand, there are more and more means, such as molecular markers and sensor data, that allow for quantification of disease or therapeutic parameters over time. Although a general value of time-resolved disease monitoring is widely accepted, the full potential of using the available information on disease and treatment dynamics in the context of outcome prediction or individualized treatment optimization still seems to be, at least partially, overlooked. Within this Perspective, we summarize the conceptual idea of using dynamic information to obtain a better understanding of complex pathophysiological processes within their particular "host environment," which also allows us to intrinsically map patient-specific heterogeneity. Specifically, we discuss to which extent treatment alterations can provide additional information to understand a patient's individual condition and use this information to further adapt the therapeutic strategy. This conceptual discussion is illustrated by using examples from myeloid leukemias to which we recently applied this concept using statistical and mathematical modeling.