THE TIME-DEPENDENCE OF LONG-TERM PREDICTION IN LUPUS NEPHRITIS

Objective. To assess the clinical, laboratory, and renal biopsy predictors of long-term outcome in lupus nephritis and to investigate the time-dependence of these predictors. Methods. Eighty-seven lupus nephritis patients were studied retrospectively for the outcomes renal failure and fatality due to renal involvement. In addition to a conventional Cox model analysis, a new generalized time-dependent analytic approach was developed and used to assess the time dependence of a predictor variable's importance. Results. The mean followup time was 11.9 years. Renal failure (n = 19) was significantly predicted by measures of renal function (abnormal serum creatinine levels, proteinuria, duration of prior renal disease) and immunologic activity (elevated DNA binding, hypocomplementemia, and thrombocytopenia), by overall lupus disease activity measures (le Riche index, Lupus Activity Criteria Count), and by the activity index, the tubulointerstitial index, and the amount of subepithelial deposits on renal biopsy. In general, the laboratory predictors were significantly better prognostic markers in the early years after biopsy, the disease activity measures were best in the later years, and the biopsy variables were significant predictors over the entire observation period. In contrast to the renal failure outcome, the best predictors for death not directly related to lupus nephritis (n = 17) were the extent of comorbid diseases (principally vascular diseases), older age, and the chronicity index. All three predicted well over the extended observation period. Conclusion. The major predictor variables for renal outcomes and nonrenal outcomes are distinct. The time-dependence of the predictive ability of some variables may be important in managing individual patients. The new generalized time-dependent analytic technique may have widespread application in studies to identify prognostic factors for established disease or risk factors for the development of disease.