47 Narcolepsy Type 1 2013 Incidence Peak and definite). All 148 patients with a “possible” or “probably” NT1 diagnostic certainty were excluded. 2. A total of 33 patients with missing information regarding the year of EDS onset were excluded. 3. A total of 250 patients with an onset of EDS before 1995 were excluded. 4. Only countries with more than 30 entered patients were included. Patients from Austria (n = 13), Poland (n = 14), Portugal (n = 18), Scotland (n = 1), Slovakia (n = 9) were thus excluded. In total, 508 patients (f = 230, m = 278, mean age of EDS onset [mean± standard deviation]: 22.01 ± 12.79 years) from Czech Republic (n = 31), Finland (n = 42), France (n = 114), Germany (n = 84), Italy (n = 90), the Netherlands (n = 58), Spain (n = 53), and Switzerland (n = 36) were included. The latest onset of EDS in these patients was in 2016. We chose the year of EDS onset as disease onset, as EDS in general is the first symptom of narcolepsy to develop. To replicate whether the incidence of NT1 in 2009–2011 was statistically increased compared to other years in the European population, we used the same data modelling approach (i.e. autoregressive integrated moving average [ARIMA] model) as previously described in a Chinese study by Fang Han et al. [60]. ARIMA models used the data of 1995–2008 to forecast the numbers of NT1 in 2009–2011 with 95% predictive confidence intervals (CIs). Then the ratios between the real and the predicted numbers of patients (i.e. R = real number/predictive number) and their 95% predictive CIs were calculated in 2009–2011, respectively. The incidence of NT1 was considered as R-fold significantly increased if the bottom of the 95% predictive CIs of R was larger than 1. ARIMA models are suitable to fit the time series data and to forecast future data points in that series. However, ARIMA cannot use the data after the 2009 pH1N1 episode to predict the numbers in 2009–2011. We therefore used locally estimated scatterplot smoothing (LOESS) methods [142], another model that allows us to exploit the entire dataset, both before and after 2009–2010 pH1N1 to predict the numbers of cases in 2009–2011. Similarly as the aforementioned analyses done with ARIMA models, we then predicted the numbers of NT1 onset in 2009–2011 using the LOESS models and calculated the ratios between the real and predicted numbers of patients and their 95% predictive CIs. In addition, we divided the database into two subgroups: children and adolescent cases (age of starting EDS ≤18 years, n = 256, f = 127, m = 129) and adult cases (age of starting EDS >18 years, n = 252, f = 103, m = 149), and repeated the LOESS modelling in the two subgroups to further investigate 2
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