Can experienced clinicians predict the outcome of lupus nephritis?

The ability of four experienced clinicians to predict short-term outcome (serum creatinine level at 1 year) and long-term outcome (renal insufficiency) was evaluated in 87 patients with lupus nephritis. The correlational agreement and the accuracy of their predictions were contrasted with the actual outcomes observed and with statistically generated prognostic regression models. In contrast to previously published data, all four clinicians predicted both short-term outcomes (P < 0.001) and long-term outcomes (P < 0.02) well. The clinicians' predictions approximated that of a statistically generated computer model for both agreement and accuracy for renal function at 1 year. The four clinicians identified nearly identical clinical variables as important in determining prognosis. Provision of biopsy data to the clinicians improved short-term and long-term prediction slightly. The value of the statistical models was 'validated' by demonstrating that three of the four clinical variables identified by the models, but not by the clinicians, could enhance clinical prediction (P < 0.05). In addition, the extent of tubulo-interstitial involvement on biopsy, a predictor that has recently received increased attention, could improve the long-term clinical predictions of all four clinicians (P < 0.05).

Predictors of one year outcome in lupus nephritis: the importance of renal biopsy.

The short-term prognosis of lupus nephritis was evaluated by assessing serum creatinine 12 months after renal biopsy in 87 patients with lupus nephritis. On univariate analysis, significant clinical and laboratory predictors of this outcome included clinical signs of renal injury (serum creatinine, 24-hour urinary protein, prolonged renal disease, nephrotic syndrome, serum albumin), as well as thrombocytopenia, older age, and coexisting illness or hypertension at the time of biopsy. On renal biopsy, diffuse proliferative nephritis, higher activity, chronicity, or tubulointerstitial scores, or subendothelial or subepithelial electron dense deposits predicted a higher serum creatinine 12 months after biopsy. A clinical predictive model was developed which included as independent predictors serum creatinine, age, platelet count and 24-hour urinary protein. Any one of three biopsy variables added information to the clinical prediction model: a marked quantity of subendothelial deposits (p = 0.02), a higher activity index score (p = 0.02), or the presence of diffuse proliferative lupus nephritis (p = 0.05). However, the relative predictive accuracy of the clinical model did not improve with the addition of any of the biopsy variables. The value of renal biopsy in lupus nephritis is discussed based on the ability of biopsy information to confirm the prognosis, to add new predictive information for a group of subjects, and to improve predictive accuracy for individual patients.

Cluster analysis of an insulin-dependent diabetic cohort towards the definition of clinical subtypes.

Clinical and biochemical data on 111 consecutive insulin-dependent diabetic children enrolled in a longitudinal prospective study were analyzed to determine if more than one clinical expression of Type I diabetes exists. Use of multivariate statistical methods, including Correspondence Analysis, kappa-means clustering and RECPAM (RECursive Partition and AMalgamation), show that there are two well differentiated clinical expressions of IDDM each characterized by a cluster. One is characterized by later age, less severe onset, longer symptom duration, less beta-cell disappearance after 12 months, more females; the other by earlier age, more sudden and severe onset, DR 3/4, earlier disappearance of beta-cell function and more males. RECPAM analysis provides further insight into the structure of the two clusters. An other RECPAM tree identifies low, medium and high risk groups of disappearance of beta-cell function at 12 months after diagnosis.