46.1 Calibration Example Model

To illustrate calibration, we will focus on a series of similar Healthcare Example Models starting with MarkovCalibration_1a_Fixed_PreCal.trex.

Prior to calibration, all the progression and death probabilities have been set as fixed values of 0.1. Therefore, we cannot expect model progression and model outputs to align with the clinical data (target data). Calibration attempts to bring the model outputs in line with the clinical data.

The model contains clinical survival tables (Kaplan-Meier tables) for each strategy.

Prior to calibration, model survival (outputs) does not match clinical survival tables. Model and clinical survival for the Cetuximab (Cet) strategy is shown below in the Markov Plot.

In the next sections, we will run calibration and use the calibrated inputs to generate more accurate results. This should result in the model outputs (red and blue curves) better matching the target survival values (pink and purple curves).

We will start with the model above then move to more advanced models/calibration.