Team Sanfilippo Foundation

Abstract Background Generalized pairwise comparisons (GPC) can be used to assess the Net Benefit of new treatments for rare diseases. We show the potential of GPC through simulations based on data from a natural history study in mucopolysaccharidosis type IIIA (MPS IIIA). Methods Using data from a historical series of untreated children with MPS IIIA aged 2 to 9 years at the time of enrolment and followed for 2 years, we performed simulations to assess the operating characteristics of GPC to detect potential (simulated) treatment effects on a multi-domain symptom assessment. Two approaches were used for GPC: one in which the various domains were prioritized, the other with all domains weighted equally. The Net Benefit was used as a measure of treatment effect. We used increasing thresholds of clinical relevance to reflect the magnitude of the desired treatment effects, relative to the standard deviation of the measurements in each domain. Results GPC were shown to have adequate statistical power (80% or more), even with small sample sizes, to detect treatment effects considered to be clinically worthwhile on a symptom assessment covering five domains (expressive language, daily living skills, and gross-motor, sleep and pain). The prioritized approach generally led to higher power as compared with the non-prioritized approach. Conclusions GPC of prioritized outcomes is a statistically powerful as well as a patient-centric approach for the analysis of multi-domain scores in MPS IIIA and could be applied to other heterogeneous rare diseases.