Meta-analysis as a Diagnostic Tool for Predicting Disease Onset and/or Activity in Systemic Lupus Erythematosus

Systemic lupus erythematous (SLE) is a relatively rare disorder with prevalence rates between 5 and 50 per 100,000 population. This means performing any epidemiological analysis in a specific research center is difficult, due to the low number of cases within any one location. There is a need for biomarkers and diagnostic aids to monitor SLE disease activity and severity prior, during, and after treatment. Many specialist lupus clinics worldwide have published trials following in detail small numbers of patients that have been monitored for a disease biomarker, e.g., an autoantibody against a self-molecule in prospective and retrospective studies. They have then attempted to correlate autoantibody levels against an autoantigen with disease activity, e.g., nephritis development. The results are often inconclusive with the conclusion “the autoantibody may be useful in monitoring disease activity.” Meta-analysis is a statistical technique that can be used for combining the findings of multiple studies to add power to any tentative conclusion proposed by individual studies. Here, we describe a method for analyzing biomarkers of interest as predictors of disease activity, using anti-C1q autoantibodies as an example.