New Approaches to the Treatment of Dense Deposit Disease

Abstract

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.

In the past two decades, the development of new clinical treatment protocols has revolved around evidence-based guidelines. Randomized, controlled trials have become the favored metric for assessing the effectiveness of novel interventions, with anything falling below this level of certainty running the danger of being discounted.1 For rare diseases, this requirement represents a significant challenge.

A rare disease makes the randomized, controlled study design impractical for numerous reasons: Sample size is small and geographically dispersed; the use of historical controls is often impossible; and randomization can be seen as unethical, especially in the face of significant disease morbidity.2 Because rarity, by definition, suggests an insubstantial public health care concern, one approach to this conundrum is to avoid rare diseases in favor of more common and substantial problems. However, this option is impractical because rare diseases, in aggregate, still represent a substantial health care problem in the developed world.

There are 5000 to 6000 rare diseases, most of which are genetic in origin, and with the continued separation of broad disease categories into smaller, well-defined entities, approximately 250 new rare diseases are described each year.3 For a disease to be considered rare in the United States, it must affect fewer than 200,000 citizens, reflecting a prevalence of approximately six per 10,000, whereas in Europe, the definition is slightly stricter: Up to five per 10,000.4 Thus, an estimated 25 million North Americans and 30 million Europeans are afflicted with rare diseases. How, then, are therapeutic advances to be developed for these populations? This article focuses on dense deposit disease (DDD; also known as membranoproliferative glomerulonephritis type II), which is rare even among rare diseases, and uses DDD as a model for how new treatment guidelines can be proposed on the basis of evidence derived from animal studies and genetic and molecular data and how outcomes can be followed using Bayesian analysis