OBJECTIVES : Cystinuria, a rare autosomal recessive genetic disease, is characterized by high urine concentrations of cysteine, leading to cystine stones in the kidneys, ureter, and bladder. Due to associated conditions and non-specific symptoms it may be under-reported and undiagnosed. This analysis aims to estimate the prevalence of cystinuria, the use of healthcare resources and pathway of patients in the UK.

METHODS : A retrospective analysis was carried out using the CPRD GOLD UK database and linked HES data to identify diagnosed, potentially undiagnosed or miscoded patients. First patient records with at least one event of cystinuria recorded between January 1987 and November 2017 were obtained. This population was analysed on the following aspects: demographics, GP consultations, specialist referrals, treatment patterns, outpatient visits, hospitalisations. Then records of patients without a diagnosis of cystinuria but with associated conditions were analysed. Algorithms based on a sequence of inclusion criteria were developed and validated by clinical experts to identify suspected cystinuria cases. Prevalence rates for 2017 were calculated.

RESULTS : 170 patients diagnosed with cystinuria were identified in the database, of whom 96 had a linkage to hospital data. Health records of diagnosed patients revealed that the most prescribed drugs other than for renal conditions were for pain management and infections, patients frequently visited specialists in urology, nephrology and general surgery and hospitalisations were on average inferior to 3 days. A total of 50 patients were identified as having suspected cystinuria via the algorithm. The prevalence of cystinuria was estimated to between 0.48 and 0.62 per 10,000.

CONCLUSIONS : The study adds to the literature by providing a new estimate of cystinuria prevalence in the UK and further shows that there are patients being undiagnosed or miscoded. However, the clinical criteria may not be specific enough to capture all the suspected patients through algorithms.