Diagnosis of rheumatoid arthritis: multivariate analysis of biomarkers.
OBJECTIVE
To test if a combination of biomarkers can increase the classification power of autoantibodies to cyclic citrullinated peptides (anti-CCP) in the diagnosis of rheumatoid arthritis (RA) depending on the diagnostic situation.


METHODS
Biomarkers were subject to three inclusion/exclusion criteria (discrimination between RA patients and healthy blood donors, ability to identify anti-CCP-negative RA patients, specificity in a panel with major non-rheumatological diseases) before univariate ranking and multivariate analysis was carried out using a modelling panel (n = 906). To enable the evaluation of the classification power in different diagnostic settings the disease controls (n = 542) were weighted according to the admission rates in rheumatology clinics modelling a clinic panel or according to the relative prevalences of musculoskeletal disorders in the general population seen by general practitioners modelling a GP panel.


RESULTS
Out of 131 biomarkers considered originally, we evaluated 32 biomarkers in this study, of which only seven passed the three inclusion/exclusion criteria and were combined by multivariate analysis using four different mathematical models. In the modelled clinic panel, anti-CCP was the lead marker with a sensitivity of 75.8% and a specificity of 94.0%. Due to the lack in specificity of the markers other than anti-CCP in this diagnostic setting, any gain in sensitivity by any marker combination is off-set by a corresponding loss in specificity. In the modelled GP panel, the best marker combination of anti-CCP and interleukin (IL)-6 resulted in a sensitivity gain of 7.6% (85.9% vs. 78.3%) at a minor loss in specificity of 1.6% (90.3% vs. 91.9%) compared with anti-CCP as the best single marker.


CONCLUSIONS
Depending on the composition of the sample panel, anti-CCP alone or anti-CCP in combination with IL-6 has the highest classification power for the diagnosis of established RA.
Wild
Norbert
N
Department of Marker Discovery/Proteomics, Roche Professional Diagnostics, Roche Diagnostics GmbH, Penzberg, Germany. norbert.wild@roche.com
Karl
Johann
J
Grunert
Veit P
VP
Schmitt
Raluca I
RI
Garczarek
Ursula
U
Krause
Friedemann
F
Hasler
Fritz
F
van Riel
Piet L C M
PL
Bayer
Peter M
PM
Thun
Matthias
M
Mattey
Derek L
DL
Sharif
Mohammed
M
Zolg
Werner
W
D000974:Antibodies, Antinuclear / Q000032:analysis*; D001172:Arthritis, Rheumatoid / Q000175:diagnosis*; D015415:Biomarkers / Q000032:analysis*; D002956:Citrulline / Q000276:immunology; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010456:Peptides, Cyclic / Q000276:immunology*; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D000685:Serum Amyloid A Protein / Q000032:analysis
D000974:Antibodies, Antinuclear; D015415:Biomarkers; D010456:Peptides, Cyclic; D000685:Serum Amyloid A Protein; C487763:cyclic citrullinated peptide; D002956:Citrulline