C. Modesto et al., Systemic onset juvenile chronic arthritis, polyarticular pattern and hip involvement as markers for a bad prognosis, CLIN EXP RH, 19(2), 2001, pp. 211-217
Objective
To explore all the common clinical and biological variables that are charac
teristic of Systemic onset Juvenile Chronic Arthritis (SoJCA) in order to d
etermine which of them are suitable as predictors of a ban articular outcom
e (persistence of inflammatory symptoms and/or established limitation of th
e range of motion (ROM)).
Material and methods
Clinical charts for 124 SoJCA patients were retrospectively reviewed. From
them, 91 were finally included in the study because they had all of the cli
nical and biological data at disease onset properly recorded. All have been
followed for at least 3 years since the beginning of the disease. Data col
lected at onset, and after 3 and 6 months of the disease included. 1) syste
mic symptoms; 2) joint involvement, using both the usual articular count an
d the value of an articular index (Helsinki Index = HI) which intentionally
excludes those joints that are not uniformly recorded in clinical charts;
and 3) biological data. HI was used to separate the patients into two group
s. When applied 3 years after the disease onset, HI greater than or equal t
o 10 represented a bad articular outcome while HI < 10 means a good prognos
is. SPSS for Window's 6.1 It as used for both the univariate and multivaria
te analyses.
Results
From the multivariate logistic regression analysis, two different "clusters
" of clinical data were found to be the best predictors of a bad articular
outcome. A bad prognosis was linked at onset with the presence of generaliz
ed lymphadenopathies, age < 8 years and an HI > 6; at six months a bad outc
ome M was linked with the presence of a polyarticular pattern plus hip invo
lvement.
Conclusion
Clinical parameters at the beginning of the disease were shown to be extrem
ely useful in predicting the articular outcome of SoJCA. Therefore, they co
uld constitute a good instrument to help clinicians tailor the best therapy
for their patients.