The Gestalt of Early Arthritis in Europe: Beyond expert opinion alone


Research in rheumatology has successfully focused on early diagnosis and early intervention, resulting in reduced burden of disease. However, the ‘early aggressive’ approach may also have ‘side effects’: overdiagnosis/overtreatment. Disentangling early arthritis (EA) patients with a ‘full blown disease’ prognosis and those who may fare a milder course or even go into spontaneous remission is a real challenge at presentation. Expert-based classification criteria have been revised to capture these early patients better but suffer from circularity. We propose an analytical, non-expert-based, approach that allows us to gain a more unbiased insight into the concept of EA, by investigating EA’s ‘latent constructs’ (latent class analysis) and how these constructs change over time (latent transition analysis).

Facts and figures

Project lead
R Landewé
University of Amsterdam
FOREUM research grant: € 226'186

Meet the team

R Landewé
University of Amsterdam
D van Schaardenburg
University of Amsterdan
A van der Helm-van Mil
UMC Leiden
S Ramiro
Leiden University
SA Bergstra
Leiden University
B Combe
University of Montpellier
A Sepriano
Nova Medical School
M de Wit
E Frazão Mateus
A Kent
B T van Dijk
Leiden University Medical Centre


  • To identify the latent EA phenotypes by using an analytical technique that circumvents expert opinion.
  • To assess if (and how) EA patients change latent phenotypes over time.
  • To assess if there are prognostic dissimilarities between different latent EA phenotypes.
  • To assess how the 2010 EULAR-ACR RA classification criteria capture the latent EA phenotypes.

Patient voice

A patients’ advisory group (PAG) consisting of 3 experienced patient research partners will be involved in all steps of the project, including study concept, data interpretation and participation in meetings. The study Principal Investigator (PI) and the Study Coordinator (SC), will work as the bridge between the PAG and the remaining collaborators. Members of the PAG will present the project main findings in the PARE conference with close support by the PI and SC, and their contribution recognized by authorship in publications.


Task 1: Database extraction and management (year 1 and 2)
Task 2: Data analysis and interpretation (year 1, 2 and 3)
Task 3: Abstract presentation (EULAR and PARE) (year 3)
Task 4: Mansurcript writing (year 3)
Task 5: Smartphone app. design and evaluation (year 3)