Long-term outcome in rheumatoid arthritis: a simple algorithm

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Arthritis Rheum 2002 Aug15;47(4):383-90

Long-term outcome in rheumatoid arthritis: a simple algorithm of

baseline parameters can predict radiographic damage, disability, and

disease course at 12-year follow-up.

Drossaers-Bakker KW, Zwinderman AH, Vlieland TP, Van Zeben D, Vos K,

Breedveld FC, Hazes JM.

Leiden University Medical Center, Leiden, The Netherlands.

W.Drossaers@...

OBJECTIVES: To predict the long-term outcome of rheumatoid arthritis

(RA) with respect to radiographic damage, disability, and disease course

using baseline variables, and to construct decision trees identifying

patients on an individual level at the extremes of the outcome spectrum

of these 3 dimensions. METHODS: The 12-year outcome of 112 female RA

patients from a prospective inception cohort was assessed by measuring

the tertiles of radiographic damage (measured by the modified Sharp/van

der Heijde method, SHS), disability (measured by the Health Assessment

Questionnaire, HAQ), and severe disease course as defined by patients

with either the 33% highest cumulative disease activity (area under the

curve of all observed disease activity scores) or the highest tertile of

radiographic damage. Patients in the lowest (mild) and highest tertile

(severe) of each outcome measure were identified. All baseline

parameters known to be associated with each outcome (demographic and

socioeconomic parameters; disease duration; disease activity measures;

laboratory measures including rheumatoid factor, HLA typing, percentage

agalactosyl IgG, functional and radiographic measures) were entered into

cross-validated stepwise logistic regression models to find the best

predictive combination of baseline parameters for each of the outcomes.

Using the results of the logistic regression models, simple decision

trees were constructed to categorize patients at an individual level in

a particular prognostic group. RESULTS: After 12 years, the lowest and

highest tertiles were, respectively, 42.3 and 189 for the SHS and 0.37

and 1.25 for the HAQ. Fifty-five patients had a severe disease course.

Mild and severe radiographic damage could be predicted with an accuracy

of 90% and 85%, respectively. Mild and severe HAQ could be predicted

with an accuracy of 90% and 84%, respectively, and severe disease course

with an accuracy of 81%. The baseline variables found to be predictive

of all 3 outcome measures were very similar and consisted of

combinations of the following baseline parameters: swollen joint count

(SJC), Ritchie score, rheumatoid factor (RF), the presence of erosions,

and the HAQ score. Additional knowledge of the HLA typing hardly

improved the accuracy of the prediction. To predict outcome at the

individual level, simple decision trees were constructed using the RF,

HAQ, SJC, and presence of erosions at baseline.

CONCLUSION: The present study shows that prediction of outcome in

long-term RA is possible and can be done using widely available baseline

parameters.

PMID: 12209484