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Rheumatology Advance Access originally published online on May 20, 2008
Rheumatology 2008 47(7):942-945; doi:10.1093/rheumatology/ken195
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© The Author 2008. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

EDITORIALS

Predicting outcome in ankylosing spondylitis

D. J. Pradeep1, A. Keat2 and K. Gaffney1

1Department of Rheumatology, Norfolk and Norwich University Hospital, Norwich and 2Department of Rheumatology, Northwick Park Hospital, Harrow, UK

Correspondence to: D. J. Pradeep, Department of Rheumatology, Norfolk and Norwich University Hospital, Norwich, UK. E-mail: john.pradeep@nnuh.nhs.uk

The first 150 words of the full text of this article appear below.

Introduction

Ankylosing spondylitis (AS) has an estimated prevalence of 0.2–0.86% for adult Caucasian populations of western European extraction [1]. The ability of anti-TNF treatment to dramatically suppress symptoms in AS [2–4] and improve quality of life [5–7] is now beyond doubt. However, the high costs and potentially serious side-effects [8], combined with uncertainties over any long-term ‘disease modifying’ effects [9] make careful selection of patients for treatment absolutely critical if needless toxicity and expense are to be avoided. Inevitably, funding bodies are reluctant to commit huge funds to this relatively obscure and formerly ‘cheap’ disease; therefore, it is encumbent on rheumatologists to avoid exposing patients who will do well without biologic therapy to unnecessary risk.

In practice, most patients do well on anti-TNF treatment, However there are very few guides to long-term prognosis [10]. Current approaches to patient selection . . . [Full Text of this Article]

The natural history of AS

What outcomes should be measured and predicted?

What evidence is already available?

Demographic factors
Musculoskeletal features
Extra-articular factors
Disease activity and functional disability
Socio-economic and lifestyle factors
Family and genetic markers
Susceptibility to AS
Genetics and disease severity
Imaging
Laboratory parameters
Predicting the outcome of biologic treatment

Conclusions


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