Abstract

Prognostic modelling in IBD

Best Pract Res Clin Gastroenterol. 2023 Dec:67:101877.doi: 10.1016/j.bpg.2023.101877. Epub 2023 Nov 29.

 

Peter Rimmer 1Tariq Iqbal 2

 
     

Author information

1Queen Elizabeth Hospital Birmingham, B15 2TH, UK; University of Birmingham, College of Medical and Dental Science, UK. Electronic address: Peter.Rimmer@uhb.nhs.uk.

2Queen Elizabeth Hospital Birmingham, B15 2TH, UK; University of Birmingham, College of Medical and Dental Science, UK. Electronic address: T.h.iqbal@bham.ac.uk.

Abstract

In the ideal world prognostication or predicting disease course in any chronic condition would allow the clinician to anticipate disease behaviour, providing crucial information for the patient and data regarding best use of resources. Prognostication also allows an understanding of likely response to treatment and the risk of adverse effects of a treatment leading to withdrawal in any individual patient. Therefore, the ability to predict outcomes from the onset of disease is the key step to developing precision personalised medicine, which is the design of medical care to optimise efficiency or therapeutic benefit based on careful profiling of patients. An important corollary is to prevent unnecessary healthcare costs. This paper outlines currently available predictors of disease outcome in IBD and looks to the future which will involve the use of artificial intelligence to interrogate big data derived from various important 'omes' to tease out a more holistic approach to IBD.

© Copyright 2013-2024 GI Health Foundation. All rights reserved.
This site is maintained as an educational resource for US healthcare providers only. Use of this website is governed by the GIHF terms of use and privacy statement.