This work studies three differential equation models of the leukemia cell cycle: a population balance model (PBM) using intracellular protein expression levels as state variables representing phase progress; a delay differential equation model (DDE) with temporal phase durations as delays; and an ordinary differential equation model (ODE) of phase-to-phase progression. In each type of model, global sensitivity analysis determines the most significant parameters while parameter estimation fits experimental data. To compare models based on the output of their structural properties, an expected behavior was defined, and each model was coupled to a pharmacokinetic/pharmacodynamic model of chemotherapy delivery. Results suggest that the particular cell cycle model chosen highly affects the simulated treatment outcome, given the same steady state kinetic parameters and drug dosage/scheduling. The manuscript shows how cell cycle models should be selected according to the complexity, sensitivity, and parameter availability of the application envisioned.