Dataset Information

Effects of alternative remission criteria on outcome of pediatric proliferative lupus nephritis: a multi-center retrospective study of pediatric proliferative lupus nephritis.

ABSTRACT:

Objectives

To observe the induction efficacy of mycophenolate mofetil and cyclophosphamide under different complete remission (CR) criteria in children with proliferative lupus nephritis, and to further explore the factors influencing the judgment of remission.

Methods

From 2003 to 2019, children who diagnosed proliferative lupus nephritis underwent induction therapy of MMF or CYC in three hospitals were consecutively collected. Based on this population, we compared CR rates between two groups under six CR criteria selected from related recommendations and clinical trials. Then degrees and impact factors of disagreement among CR rates evaluated by selected criteria would be analyzed by Kappa test and multivariable logistic-regression models.

Results

A total of 161 children were included in this study, 27 patients received induction therapy of mycophenolate mofetil (MMF) and 134 patients recieved cyclophosphamide (CYC). Under different CR criteria, CR rates in MMF group fluctuated between 18.5%-74.1% and that in CYC group ranged from 16.4%-73.9%. Moreover, comparison between the two drugs in induction treatment under different criteria showed an opposite trend in efficacy. The results of six criteria were inconsistent, with pair-to-pair Kappa values ranging from 0.118 to 0.858. The most important factors leading to disagreement in judgment were urinary protein and urinary red blood cells.

Conclusions

The definition of complete response, especially the factors of the urinary protein and urinary red blood cells, significantly impacts the clinical judgment of children with lupus nephritis.

SUBMITTER: Chen L

PROVIDER: S-EPMC8205752 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction: Pediatric systemic lupus erythematosus (pSLE) patients often initially present with more active and severe disease than adults, including a higher frequency of lupus nephritis. Specific autoantibodies, including anti-C1q, anti-DNA and anti-alpha-actinin, have been associated with kidney involvement in SLE, and DNA antibodies are capable of initiating early stage lupus nephritis in severe combined immunodeficiency (SCID) mice. Over 100 different autoantibodies have been described in SLE patients, highlighting the need for comprehensive autoantibody profiling. Knowledge of the antibodies associated with pSLE and proliferative nephritis will increase the understanding of SLE pathogenesis, and may aid in monitoring patients for renal flare. Methods: We used autoantigen microarrays composed of 140 recombinant or purified antigens to compare the serum autoantibody profiles of new-onset pSLE patients (n=45) to healthy controls (n=17). We also compared pSLE patients with biopsy-confirmed class III or IV proliferative nephritis (n=23) and without significant renal involvement (n=18). We performed ELISA with selected autoantigens to validate the microarray findings. We created a multiple logistic regression model, based on the ELISA and clinical information, to predict whether a patient had proliferative nephritis, and used a validation cohort (n=23) and longitudinal samples (88 patient visits) to test its accuracy. Results: Fifty autoantibodies were at significantly higher levels in the sera of pSLE patients compared to healthy controls, including anti-B-cell activating factor (BAFF). High levels of anti-BAFF were associated with active disease. Thirteen serum autoantibodies were present at significantly higher levels in pSLE patients with proliferative nephritis than those without, and we confirmed five autoantigens (dsDNA, C1q, collagens IV & X and aggrecan) by ELISA. Our model, based on ELISA measurements and clinical variables, correctly identified patients with proliferative nephritis with 91% accuracy. Conclusions: Autoantigen microarrays are an ideal platform for identifying autoantibodies associated with both pSLE and specific clinical manifestations of pSLE. Using multiple regression analysis to integrate autoantibody and clinical data permits accurate prediction of clinical manifestations with complex etiologies in pSLE.