Session Type: Poster Session (Sunday)
Session Time: 9:00AM-11:00AM
Background/Purpose: To predict prognosis of patients with rheumatoid arthritis (RA) from the location and the size of affected joints.
Methods: Data of 7,776 patients with RA, who were serially registered from 2016 to 2017 without data missing, were extracted from the National Database of Rheumatic Diseases in Japan (NinJa). The joint index (JI) was calculated as the sum of the number of tender and swollen joints divided by the number of evaluable joints in four categories, i.e., upper/large, upper/small, lower/large, and lower/small (Nishiyama S, et al. Proposing a method of regional assessment and a novel outcome measure in rheumatoid arthritis. Rheumatol Int 32:2569-2571. doi 10.1007/s00296-011-2058-9). Next, the joint index vector V (x, y, z) was calculated as x = JIUL + JIUS, y = JILL + JILS, and z = JIUL + JILL – JIUS – JILS, where JIUL, JIUS, JILL, and JILS indicate the joint indices of the upper/large, upper/small, lower/large, and lower/small joint categories, respectively. Patients were classified into four groups by |Vxy| (= √(x2+y2)) and z values (G1: |Vxy|≦0.1, G2: |Vxy| >0.1 & |z|≦0.2, G3: |Vxy| >0.1 & z < -0.2, G4: |Vxy| >0.1 & z >0.2). Transformation matrix was computed using serial registration data of patients with RA who were treated with MTX from the NinJa database from 2013 to 2014 (Nishiyama S, et al. Joint index vector: a novel assessment measure for stratified medicine in patients with rheumatoid arthritis. Journal of Big Data 2018;5:37. https://doi.org/10.1186/s40537-018-0148-1).
Results: SDAI was the highest in patients of the G3 (small-dominant joint involvement group) and HAQ-DI was the worst in patients of the G4 (large-dominant joint involvement group) independent of registration year (Fig.1). Groups in 2017 were predicted from the vectors estimated using the transformation matrix applied on 4,811 MTX users in 2016, and then 456 patients were classified as the predicted G4. The rest of 4,355 patients had lower SDAI and better HAQ-DI than patients of the predicted G4 (Fig. 2). The concordance rate of the G4 or the others between the predicted group and the real group in 2017 was 82.8%. In 1,001 patients of the G4 in 2016, 452 were predicted to be in the G4 next year, whose SDAI (mean±standard error: 9.90±0.30) and HAQ-DI (0.95±0.04) were significantly higher than those of the rest of 549 patients (7.12±0.22 and 0.67±0.03, respectively).
Conclusion: Classification of RA patients according to the joint index vector which has the affected joints information of the location and the size discriminated patients with a relatively poor prognosis from those with lower SDAI and better HAQ-DI.
To cite this abstract in AMA style:Nishiyama S, Sawada T, Tohma S. Location and Size of Affected Joints Are Useful to Predict Prognosis of Patients with Rheumatoid Arthritis [abstract]. Arthritis Rheumatol. 2019; 71 (suppl 10). https://acrabstracts.org/abstract/location-and-size-of-affected-joints-are-useful-to-predict-prognosis-of-patients-with-rheumatoid-arthritis/. Accessed .
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