Disease stratification in GCA and PMR: state of the art and future perspectives.
Alessandro TomelleriKornelis S M van der GeestMuhammad Asim KhurshidAlwin SebastianFiona CoathDaniel RobbinsBarbara PierscionekChristian DejacoEric MattesonYannick van SleenBhaskar DasguptaPublished in: Nature reviews. Rheumatology (2023)
Giant cell arteritis (GCA) and polymyalgia rheumatica (PMR) are closely related conditions characterized by systemic inflammation, a predominant IL-6 signature, an excellent response to glucocorticoids, a tendency to a chronic and relapsing course, and older age of the affected population. This Review highlights the emerging view that these diseases should be approached as linked conditions, unified under the term GCA-PMR spectrum disease (GPSD). In addition, GCA and PMR should be seen as non-monolithic conditions, with different risks of developing acute ischaemic complications and chronic vascular and tissue damage, different responses to available therapies and disparate relapse rates. A comprehensive stratification strategy for GPSD, guided by clinical findings, imaging and laboratory data, facilitates appropriate therapy and cost-effective use of health-economic resources. Patients presenting with predominant cranial symptoms and vascular involvement, who usually have a borderline elevation of inflammatory markers, are at an increased risk of sight loss in early disease but have fewer relapses in the long term, whereas the opposite is observed in patients with predominant large-vessel vasculitis. How the involvement of peripheral joint structures affects disease outcomes remains uncertain and understudied. In the future, all cases of new-onset GPSD should undergo early disease stratification, with their management adapted accordingly.
Keyphrases
- giant cell
- multiple sclerosis
- physical activity
- healthcare
- stem cells
- oxidative stress
- rheumatoid arthritis
- high resolution
- current status
- risk assessment
- type diabetes
- liquid chromatography
- mass spectrometry
- preterm infants
- acute respiratory distress syndrome
- health information
- climate change
- machine learning
- hepatitis b virus
- artificial intelligence
- drug induced
- intensive care unit
- molecularly imprinted