Searching for a prognostic index in lupus nephritis

寻找狼疮性肾炎的预后指标

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Abstract

BACKGROUND: Currently we do not have an ideal biomarker in lupus nephritis (LN) that should help us to identify those patients with SLE at risk of developing LN or to determine those patients at risk of renal progression. We aimed to evaluate the development of a prognostic index for LN, through the evaluation of clinical, analytical and histological factors used in a cohort of lupus. We have proposed to determine which factors, 6 months after the diagnosis of LN, could help us to define which patients will have a worse evolution of the disease and may be, more aggressive treatment and closer follow-up. METHODS: A retrospective study to identify prognostic factors was carried out. We have included patients over 18 years of age with a clinical diagnosis of systemic lupus erythematosus (SLE) and kidney involvement confirmed by biopsy, who are followed up in our centre during the last 20 years. A multi-step statistical approach will be used in order to obtain a limited set of parameters, optimally selected and weighted, that show a satisfactory ability to discriminate between patients with different levels of prognosis. RESULTS: We analysed 92 patients with LN, although only 73 have been able to be classified according to whether or not they have presented poor renal evolution. The age of onset (44 vs. 32; p = 0.024), the value of serum creatinine (1.41 vs. 1.04; p = 0.041), greater frequency of thrombocytopenia (30 vs. 7%; p = 0.038), higher score in the renal chronicity index (2.47 vs. 1.04; p = 0.015), proliferative histological type (100%) and higher frequency of interstitial fibrosis (67 vs. 32%; p = 0.017) and tubular atrophy (67 vs. 32%; p = 0.018) was observed between two groups. The multivariate analysis allowed us to select the best predictive model for poor outcome at 6 months based on different adjustment and discrimination parameters. CONCLUSION: We have developed a prognostic index of poor renal evolution in patients with LN that combines demographic, clinical, analytical and histopathological factors, easy to use in routine clinical practice and that could be an effective tool in the early detection and management.

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