51. Measuring disease activity
- Author
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Joan T. Merrill
- Subjects
medicine.medical_specialty ,Pathology ,Systemic lupus erythematosus ,business.industry ,Disease ,medicine.disease ,Clinical trial ,Epidemiology ,Clinical endpoint ,Relevance (law) ,Medicine ,Outcomes research ,skin and connective tissue diseases ,business ,Intensive care medicine ,Quality assurance - Abstract
Clinical trials for systemic lupus erythematosus (SLE) currently depend on outcome measures that were originally developed for epidemiological or outcomes research and never optimized to discriminate treatment effects. Because these systems were devised to encompass simultaneous assessment of multiple organs, their interpretation can be complicated, requiring specialized training. Not surprisingly, there has been minimal adaptation of these disease activity scales in clinical practice, leaving clinicians without practical or reproducible methods for tracking progress, justifying treatment approvals, or documenting quality assurance. This chapter focuses on two of the most widely used SLE measures, the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and the British Isles Lupus Assessment Group (BILAG) index. Definitions and scoring rules for these instruments were originally conceived through expert consensus, followed by formal validation studies to test reliability of their use over time and between clinicians. Both the SLEDAI and BILAG have demonstrated reliability, relevance, and sensitivity to change in disease severity, but when these mature, well-validated instruments began to be applied in registrational trials of investigational treatments, significant pitfalls were recognized. Subsequent accommodations in how the instruments are applied to study endpoints has led to more interpretable results in some recent trials, but continue to illuminate ongoing obstacles to successful treatment development, and to the ability, in clinic, to accurately track progress in a complex patient population. The solution may lie in the development of a measure that is not first keyed to established algorithms, then later tested for validity, but is originally scaled to live patient outcomes in the clinic to discriminate real world, clinically significant disease changes from minor fluctuations.
- Published
- 2021
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