Selecting the minimum prediction base of historical data to perform 5-year predictions of the cancer burden: The GoF-optimal method

摘要

Background: Predicting the future burden of cancer is a key issue for health services planning, where a method for selecting the predictive model and the prediction base is a challenge. A method, named here Goodness-of-Fit optimal (GoF-optimal), is presented to determine the minimum prediction base of historical data to perform 5-year predictions of the number of new cancer cases or deaths.