Journal article

Statistical models for respiratory disease diagnosis and prognosis

Rory Wolfe, John Carlin

RESPIROLOGY | WILEY | Published : 2015

Abstract

Risk prediction equations are used in a variety of healthcare settings to provide prognosis for patients with various respiratory conditions. This article provides a review of statistical methods for the development, evaluation and implementation of respiratory disease prediction models. We also consider a second, closely related application of these methods: the creation of equations that describe normal lung function in a particular population and the use of such equations in the diagnosis of abnormal lung function. The methods are illustrated with examples of models that have been developed for use in respiratory medicine and research.

Grants

Awarded by NHMRC Centre of Research Excellence grant


Funding Acknowledgements

This work was supported under a NHMRC Centre of Research Excellence grant, ID#1035261, awarded to the Victorian Centre for Biostatistics (ViCBiostat). We thank Michael Abramson and Christian Schindler for providing comments that helped to improve this article.