Comparing statistical methods for quantifying drug sensitivity based on in vitro dose-response assays

In vitro chemosensitivity assays are invaluable for assessing chemotherapeutic agents' effects on cancer cells. Yet the dose-response curves generated by those assays, usually approximated by four-parameter logistic (4PL) models, are oftentimes difficult to interpret, with no clear indication of which metric should be used to compare them. Here, five commonly used metrics, absolute and relative half-maximal inhibitory concentration (IC(50)), area under the dose-response curve (AUC) based on trapezoidal rule and a parametric approach, and the effect at the maximal concentrations (E(max)), were compared in both simulations and real-life scenarios to evaluate their use with 4PL curves. Despite the fact that IC(50) is the most widely used metric to analyze dose-response curves, this study demonstrated that it was not the most reliable of the metrics tested. Fitted AUC showed the best overall performance in both the simulation and real-life scenarios; trapezoidal AUC showed similar performance to fitted AUC in most cases.