Simulation model of disease incidence driven by diagnostic activity.

ABSTRACT: It is imperative to understand the effects of early detection and treatment of chronic diseases, such as prostate cancer, regarding incidence, overtreatment and mortality. Previous simulation models have emulated clinical trials, and relied on extensive assumptions on the natural history of the disease. In addition, model parameters were typically calibrated to a variety of data sources. We propose a model designed to emulate real-life scenarios of chronic disease using a proxy for the diagnostic activity without explicitly modeling the natural history of the disease and properties of clinical tests. Our model was applied to Swedish nation-wide population-based prostate cancer data, and demonstrated good performance in terms of reconstructing observed incidence and mortality. The model was

SUBMITTER: Westerberg M 

PROVIDER: S-EPMC7894333 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature