Rare neurodegenerative diseases are characterized by high heterogeneity and high clinical complexity, as well as low incidence and prevalence, thus making tracking small numbers of incident cases in the general population very challenging. Since it is not possible to use classical cohort studies to estimate the incidence of these rare diseases, we can "reconstruct" a theoretical cohort using case information from a well-defined geographic region collected through a surveillance system. The incidence rate is estimated as the ratio between the number of individuals at risk who were diagnosed with the disease of interest during the study period and the estimated overall amount of time individuals in the reference population spent at risk during the study period. If a series of assumptions are met, the approximate incidence proportion of a closed theoretical cohort without competing events and with the same follow-up duration can be calculated by multiplying the incidence rate with the length of the study time. This rationale relies on the presence of an effective referral system, which links all levels of the healthcare system together in the region, from general practitioners to specialized clinical centers. The reconstructed cohort design is a valid and cost-effective method to collect data on the incidence of rare neurodegenerative diseases and represents the theoretical framework for building up population-based registries.
