Diagnostic journey for individuals with fibrous dysplasia / McCune albright syndrome (FD/MAS)

Abstract

Background Reducing delayed diagnosis is a significant healthcare priority for individuals with rare diseases. Fibrous Dysplasia/ McCune Albright Syndrome (FD/MAS) is a rare bone disease caused by somatic activation mutations of NASA. FD/MAS has a broad clinical phenotype reflecting variable involvement of bone, endocrine and other tissues, distribution and severity. The variable phenotype is likely to prolong the diagnostic journey for patients further. Aim To describe the time from symptom onset to final diagnosis in individuals living with FDMAS. Methods We used the UK-based RUDY research database (www.rudystudy.org), where patients self-report their diagnosis of FD/MAS. Participants are invited to complete the diagnostic journey based on the EPIRARE criteria. Results 51 individuals diagnosed with FD/MAS were included in this analysis. Among them, 70% were female, and the median age was 51.0 years (IQR 34.5–57.5]. 12 (35%) individuals reported McCune Albright Syndrome, 11 (21.6%) craniofacial and 11(21.6%) for each of poly- and mono-ostotic FD and 6 (11.8%) did not know their type of FD/MAS. Pain was the commonest first symptom (58.8%), and 47.1% received another diagnosis before the diagnosis of FD/MAS. The median time to final diagnosis from the first symptom was two years with a wide IQR (1,18) and range (0–59 years). Only 12 (23.5%) of individuals were diagnosed within 12 months of their first symptoms. The type of FD/MAS was not associated with the reported time to diagnosis. Significant independent predictors of longer time to final diagnosis included older current age, younger age at first symptom and diagnosis after 2010. Conclusion Individuals with FDMAS have a variable time to diagnosis that can span decades. This study highlights the need for further research on how to improve diagnostic pathways within Orthopaedic and Ear, Nose and Throat (ENT)/Maxillofacial services. Our data provides a baseline to assess the impact of novel NHS diagnostic networks on reducing the diagnostic odyssey.