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A proposed algorithmic approach may be useful in the early detection of AS
Physicians’ perceptions of the spondyloarthropathies are changing. Ankylosing spondylitis (AS), the prototype of this group, has traditionally been considered a rare disease with few therapeutic options. In addition, diagnosis is difficult, sometimes delayed for decades, mainly owing to the lack of sensitivity of the traditional imaging method, radiography, to detect the hallmark of AS, sacroiliitis. Also, the widespread perception of these diseases as “innocuous” or having a good outcome has hampered the development of protocols for defining early disease and identifying those patients who would benefit from early treatment.
PROBLEMS OF AS
It is now clear that these assumptions are incorrect. Ankylosing spondylitis is more common than previously estimated, with some studies suggesting a prevalence as high as 1%.1 Importantly it affects people at a time when they are economically active (most commonly in the third decade), and the disease has a major impact on a person’s ability to work. Recent evidence from a survey from our group shows that a high proportion of patients with AS still in work have major problems suggesting imminent job loss.2 In addition, the assumption of a good clinical outcome has recently been challenged, with 70% of patients progressing to fusion of the spine by 10–15 years.3,4 Mortality is also increased by 1.5–4 times that of the general population,5and a …