OBJECTIVES: Tay-Sachs disease (TSD) is a rare autosomal recessive disorder causing progressive neurodegeneration due to HEXA deficiency. Infantile, juvenile, and late-onset subtypes are described based on the age of symptom onset. Despite genotype variability between certain ethnicities, there are well-established associations between common mutations and subtypes. Limited published evidence is available on prevalence for large regions of the world, especially for the late-onset subtype, which may be underdiagnosed. This prevents a realistic estimate of the current disease burden. The objective of this study was to develop an epidemiological model of the prevalence and patient pool per TSD subtype at the global, regional, and country levels.

METHODS: A literature review of epidemiology data was performed using MEDLINE/PubMed. Studies were screened for the potential to offer the best available evidence on model inputs, resulting in 99 studies. A data triangulation approach was used to combine evidence on carrier frequency, genotype, modifying factors, (birth) prevalence, survival, and onset from multiple sources. Consanguinity and ethnicity rates were applied at the country level. Point prevalence was calculated and a deterministic sensitivity analysis was used to generate a range for the late-onset subtype, reflecting the uncertainty in birth prevalence.

RESULTS: The global prevalence of TSD was estimated to range from 0.17 to 0.24 per 100,000. The point prevalence per 100,000 was estimated at 0.02 for infantile and juvenile and ranging from 0.14 to 0.20 for late-onset. This resulted in an estimated pool of 34 infantile, 48 juvenile, and 452 to 679 late-onset symptomatic cases in the EU5.

CONCLUSIONS: This is the first reported epidemiological model of TSD at the subtype and country level. By combining limited evidence, the estimates better capture the unmet need of the late-onset subtype. This method can be applied in other rare genetic diseases to quantify uncertainty and inform clinical program planning and health economic modelling.