A clinical prediction rule combining routine assessment and power Doppler ultrasonography for predicting progression to rheumatoid arthritis from early-onset undifferentiated arthritis.
OBJECTIVE
The ability to predict the development of rheumatoid arthritis (RA) in patients with an early-onset undifferentiated arthritis (UA) is highly required if the remission or an adequate response to the treatment are the main goal. The aim of the study was to develop a predictive rule combining clinical variables, serological biomarkers and power Doppler ultrasonography (PDUS) for the progression from an early-onset UA to RA in daily rheumatological practice.


METHODS
A prediction rule was developed after a 12 months study of 149 adult patients with a recent-onset UA. The combination of routine assessment variables and PDUS findings was investigated. Logistic regression analysis was performed to identify the independent factors for the development of RA and global predictive score was calculated. The score of the predictive rule ranged from 0 to 10. The area under the receiver operating characteristic curve was used to evaluate the diagnostic performance of the rule. The post-test probability (post-TP) was evaluated using the Bayes theorem.


RESULTS
Sixty-two patients (41.6%) developed a RA. The rule demonstrated excellent discriminative ability, with an AUC of 0.919 (p=0.0001). With the optimal cut-off point of 5, sensitivity was 89.9%, specificity was 88.6% and positive likelihood ratio was 7.89. If a threshold of 6.5 was applied a higher value of specificity (97.7%) was obtained, but sensitivity (47.6%) decreased. The post-TP value of the two different cut-off points mentioned above were 62% and 80%, respectively.


CONCLUSIONS
Our predictive rule, which includes PDUS assessment, revealed an excellent discriminative ability for assessing the likelihood of development of RA in patients with an early-onset UA. Further studies are required to confirm the results and to tailor a therapeutic approach in patients with an early-onset UA.
Salaffi
F
F
Department of Molecular Pathology and Innovative Therapies, Clinica Reumatologica, Università Politecnica delle Marche, Ancona, Italy. fsalaff@tin.it
Ciapetti
A
A
Gasparini
S
S
Carotti
M
M
Filippucci
E
E
Grassi
W
W
D000293:Adolescent; D000328:Adult; D000368:Aged; D001172:Arthritis, Rheumatoid / Q000097:blood / Q000175:diagnosis* / Q000503:physiopathology; D015415:Biomarkers / Q000097:blood; D004185:Disability Evaluation; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D050823:Hand Joints / Q000000981:diagnostic imaging / Q000473:pathology* / Q000503:physiopathology; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010146:Pain / Q000503:physiopathology; D011237:Predictive Value of Tests; D012372:ROC Curve; D011795:Surveys and Questionnaires; D018608:Ultrasonography, Doppler / Q000379:methods*; D055815:Young Adult
D015415:Biomarkers