New approaches to the treatment of dense deposit disease
New approaches to the treatment of dense deposit disease
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DOI：
10.1681/asn.2007030356
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发表时间：
2007-09-01
影响因子：
13.6
通讯作者：
Zipfel, Peter F.
中科院分区：
文献类型：
--
作者：
Smith, Richard J. H.;Alexander, Jessy;Zipfel, Peter F.
临床治疗方案的开发通常依赖于注重随机对照试验的循证指南。对于罕见的肾脏疾病，这种严格的要求可能是一个巨大的挑战。致密沉积病(DDD；又称膜增生性肾小球肾炎II型)是一种典型的罕见疾病。它每百万只影响2到3个人，并在10年内导致50%的受影响儿童发生肾功能衰竭。本文以病理生理学为基础，提出了一种诊断和治疗DDD患者的算法。诊断试验应评估补体的替代途径以发现异常。治疗选择包括积极控制血压和减少蛋白尿，在病理生理学、动物数据和人体研究的基础上，血浆输注或交换、利妥昔单抗、舒洛地特和尤利珠单抗是额外的选择。治疗成功的标准应该是防止进展，这取决于肾功能的维持或改善。第二个标准应该是通过C3/C3d比率和C3NeF水平来衡量替代补体途径的活动水平的正常化。结果应该报告给中央资料库，现在所有临床医生都可以访问。随着对DDD认识的加深，新的治疗方法应该被整合到现有的DDD治疗方案中，并使用开放标签的贝叶斯研究设计进行评估。
The development of clinical treatment protocols usually relies on evidence-based guidelines that focus on randomized, controlled trials. For rare renal diseases, such stringent requirements can represent a significant challenge. Dense deposit disease (DDD; also known as membranoproliferative glomerulonephritis type II) is a prototypical rare disease. It affects only two to three people per million and leads to renal failure within 10 yr in 50% of affected children. On the basis of pathophysiology, this article presents a diagnostic and treatment algorithm for patients with DDD. Diagnostic tests should assess the alternative pathway of complement for abnormalities. Treatment options include aggressive BP control and reduction of proteinuria, and on the basis of pathophysiology, animal data, and human studies, plasma infusion or exchange, rituximab, sulodexide, and eculizumab are additional options. Criteria for treatment success should be prevention of progression as determined by maintenance or improvement in renal function. A secondary criterion should be normalization of activity levels of the alternative complement pathway as measured by C3/C3d ratios and C3NeF levels. Outcomes should be reported to a central repository that is now accessible to all clinicians. As the understanding of DDD increases, novel therapies should be integrated into existing protocols for DDD and evaluated using an open-label Bayesian study design.