Contributions
Abstract: P355
Type: Poster Sessions
Abstract Category: Clinical aspects of MS - Epidemiology
Background: Each medical care event (mce) with a diagnosis assigned to a patient is mandatory registered in the National Patient Registry (NPR). NPR includes all inpatient MS care events since 1969 and outpatient visits since 2001. Accurate evaluation of MS prevalence is a time consuming task. It involves validation of MS diagnosis and access to individual patient's records. Early symptoms of different neurological disorders can be misclassified with MS, and patients can possibly get a false MS diagnosis under the early clinical period.
Objectives: Evaluation of the actual MS prevalence using NPR data by analysing the frequency- and time- distribution of all reported MS diagnosis. Assessment of a fraction of false positive MS diagnosis in inpatient and outpatient care and analysis of its distribution in time.
Methods: NPR includes all the registrations of MS diagnosis (mce) based on a medical examination of a patient. Number of mce covers a range from 1 to over 100 per patient, dependently on MS duration. We analysed the actual mce-distribution using Gaussian fit with calculations of residuals of a fitted model. For the patients with 1 or 2 confirmations of MS diagnosis we investigated the time distribution. We checked when patients got MS-diagnosis without any further confirmation of MS in later years. Such diagnosis were considered as false positive MS-diagnosis and excluded from the final evaluations.
Results: We got 20814 living patients with reported MS diagnosis until 2013. The distribution of mce showed that the number of patients with 1 or 2 diagnosis extended strongly beyond the observed distribution for the rest of patients. This suggested that false positive MS diagnosis belong almost exclusively to the patients having only one confirmation of MS (61% misclassified) or two (20%). Analysis of a time distribution of a subgroup with mce=1 revealed, that for inpatient care, the number of patients with misclassified MS was stable with time with the mean of 27±7 patients per year and for outpatient care 101±12 per year. Total number of patients with misclassified MS in NPR was 2495 i.e.12% of all registered patients. They were excluded from the calculations of MS prevalence. The procedure resulted in 18320 prevalent MS patients in 2013 i.e. 191/100,000.
Conclusion: New method for evaluation of MS prevalence based on MS diagnosis registered in NPR appeared to be a robust one. It gave new insights on the level of false positive MS cases reported in early MS.
Disclosure: LS, AM and AF declare no conflict of interest.
JH received honoraria for serving on advisory boards for Biogen and Novartis and speaker´s fees from Biogen, MerckSerono, BayerSchering, Teva and SanofiGenzyme. He has served as P.I. for projects sponsored by, or received unrestricted research support from, Biogen, SanofiGenzyme, MerckSerono, TEVA, Novartis and BayerSchering. His MS research is funded by the Swedish Research Council and the Swedish Brain Foundation.
Abstract: P355
Type: Poster Sessions
Abstract Category: Clinical aspects of MS - Epidemiology
Background: Each medical care event (mce) with a diagnosis assigned to a patient is mandatory registered in the National Patient Registry (NPR). NPR includes all inpatient MS care events since 1969 and outpatient visits since 2001. Accurate evaluation of MS prevalence is a time consuming task. It involves validation of MS diagnosis and access to individual patient's records. Early symptoms of different neurological disorders can be misclassified with MS, and patients can possibly get a false MS diagnosis under the early clinical period.
Objectives: Evaluation of the actual MS prevalence using NPR data by analysing the frequency- and time- distribution of all reported MS diagnosis. Assessment of a fraction of false positive MS diagnosis in inpatient and outpatient care and analysis of its distribution in time.
Methods: NPR includes all the registrations of MS diagnosis (mce) based on a medical examination of a patient. Number of mce covers a range from 1 to over 100 per patient, dependently on MS duration. We analysed the actual mce-distribution using Gaussian fit with calculations of residuals of a fitted model. For the patients with 1 or 2 confirmations of MS diagnosis we investigated the time distribution. We checked when patients got MS-diagnosis without any further confirmation of MS in later years. Such diagnosis were considered as false positive MS-diagnosis and excluded from the final evaluations.
Results: We got 20814 living patients with reported MS diagnosis until 2013. The distribution of mce showed that the number of patients with 1 or 2 diagnosis extended strongly beyond the observed distribution for the rest of patients. This suggested that false positive MS diagnosis belong almost exclusively to the patients having only one confirmation of MS (61% misclassified) or two (20%). Analysis of a time distribution of a subgroup with mce=1 revealed, that for inpatient care, the number of patients with misclassified MS was stable with time with the mean of 27±7 patients per year and for outpatient care 101±12 per year. Total number of patients with misclassified MS in NPR was 2495 i.e.12% of all registered patients. They were excluded from the calculations of MS prevalence. The procedure resulted in 18320 prevalent MS patients in 2013 i.e. 191/100,000.
Conclusion: New method for evaluation of MS prevalence based on MS diagnosis registered in NPR appeared to be a robust one. It gave new insights on the level of false positive MS cases reported in early MS.
Disclosure: LS, AM and AF declare no conflict of interest.
JH received honoraria for serving on advisory boards for Biogen and Novartis and speaker´s fees from Biogen, MerckSerono, BayerSchering, Teva and SanofiGenzyme. He has served as P.I. for projects sponsored by, or received unrestricted research support from, Biogen, SanofiGenzyme, MerckSerono, TEVA, Novartis and BayerSchering. His MS research is funded by the Swedish Research Council and the Swedish Brain Foundation.