Population-based registers are widely used in epidemiological studies. We aimed to estimate the validity of multiple sclerosis (MS) diagnoses registered in the Swedish National Patient Register (NPR) by two sequential register-based case-definition algorithms. Prevalent MS patients aged 16-64 years were identified from the in-and specialised out-patient NPR in 2001-2013, using International Classification of Diseases code G35. These identified MS diagnoses were validated through two sequential register-based case-definition algorithms, as the 'gold-standard' reference, by linking individual-level data longitudinally to other nationwide registers. The primary algorithm first sought to corroborate the MS diagnoses with MS-specific information in other nationwide registers. The exploratory secondary algorithm identified individuals with MS-related information in other registers and those who were unable to be followed sufficiently. Through multi-register linkage, we estimated the number of confirmed and uncertain individuals with an MS diagnosis recorded in the NPR. A total of 19,781 individuals (mean age at first visit 45.2 years; 69.5% women) had at least one MS diagnosis recorded in the NPR during 2001-2013. Using the two case-definition algorithms, 92.5% (n = 18,291) of the MS diagnoses recorded in the NPR were confirmed, while 7.5% (n = 1490) remained uncertain. Our findings indicate that a very high percentage of patients coded with an MS diagnosis in the Swedish NPR actually have MS, and supports the use of the NPR as a viable source to identify individuals with an MS diagnosis for population-based research. This exploratory methods paper suggests an alternative novel method to verify individuals' diagnoses in register-based settings.