Recessive Ataxia Differential Diagnosis Algorithm (RADIAL) Versus Specific Niemann-Pick Type C Suspicion Indices: A...

Early diagnosis of Niemann-Pick disease type C (NPC) is crucial to slow the progression of neurological manifestations. Different tools were developed to aid diagnosis of NPC, but to date, no study has compared their performance. We aimed to compare the RADIAL algorithm, intended for the differential diagnosis of autosomal recessive cerebellar ataxias (ARCAs) and NPC-specific suspicion indices (SIs). This study was a retrospective analysis of data from 834 patients with molecularly confirmed ARCAs, including 57 NPC cases (RADIAL cohort). We aimed to compare the algorithm performance of RADIAL (Top 1 and Top 3) with that of four SIs (Original, Refined, 2/3 and 2/7) in discriminating NPC cases and non-NPC cases. We also identified ARCAs closely related to NPC as those with low specificity to detect non-NPC cases and described differential and overlapping features with NPC. Overall, excellent sensitivity and specificity (> 0.90) were achieved with both RADIAL and SI tools for NPC cases. The highest sensitivity was attained with the 2/7 SI, Refined SI and Top 3 RADIAL algorithms. Top 1 and Top 3 RADIAL were the most specific tools, followed by the Original SI. The individual comparison of each ARCA revealed that Wilson disease, PLA2G6-associated neurodegeneration, and hypomyelinating leukodystrophy (POLR3A) are frequent NPC false positives (PLA2G6 and POL3A only with the SIs). Both RADIAL and SI diagnostic approaches showed strong discriminatory potential and may be useful screening tools in different clinical contexts.