OBJECTIVES: This study aimed at estimating the probability of switching among lines of treatment(s) for HER2+ metastatic breast cancer (mBC) to better assess the clinical impact of sequential therapy on disease progression.  METHODS: Individual patient data (IPD) were reconstructed for treatment lines composing four treatment sequences. Parametric models were tested to select the model that best fits the IPD. The transitional probability equations, used for disease progression modeling, were obtained by substituting the parameters of the general equation for transitional probabilities by the parameters estimated from fitted distributions.   RESULTS: The log-logistic model best fitted the reconstructed data for progression-free and overall survival curves for each line of treatment. The shapes and scales of the log-logistic models were used to develop the transitional probability equations for the HER2+ mBC simulation model.  CONCLUSIONS: The results of this study can be used as input in model-based economic evaluations of sequential therapy for HER2+ mBC.