Stata statistical software

Data from July 2007, the first month when surveillance was conducted in all 11 sites, through June 2013, were included in the analysis. We excluded patients for whom demographic data or laboratory results were missing, and patients who did not meet one of the case definitions. We used Pearson's chi square test to compare demographic and clinical variables between SARI and ILI patients. We used logistic regression to calculate odds ratios in bi-variate and multivariate analyses comparing influenza-positive and influenza-negative ILI patients, and influenza-positive and influenza-negative SARI patients. We used generalized linear models (GLM) to estimate relative risk when comparing fatal and non-fatal cases. Multivariable logistic regression and GLM models were constructed using factors that were significant at p<0.2 in the bi-variate analysis. SARI patients <5 years old and those ≥5 years old were analyzed separately because different case definitions were used for the two age groups. Findings were considered statistically significant if the p-value was <0.05. Data analyses were performed using Stata 12.1 (Stata Corp. 2011. Stata Statistical Software: Release 12. College Station, TX: Stata Corp LP).

Eligible participants were randomly assigned in three treatment arms with a 1:1:1 ratio to receive rapamycin 1 mg per square meter (m²) of body surface area a day (1 mg/m²/day) (21 patients), rapamycin 2 mg/m²/day (21 patients), or placebo (21 patients). The randomization schedule was computer generated by an unblinded statistician using STATA software (StataCorp. 2017. Stata Statistical Software: Release 15). Randomization was stratified by rate of disease progression as measured by monthly decline of the Revised ALS Functional Rating Scale (ALSFRS-R) from onset to screening visit, with a cut off set at http://www.css.euromed.it/en/) prepared the active formulation and the placebo complying the Good Manufacturing Practices of the European Union for active pharmaceutical ingredients and ICH Q7A guidelines. Trial drug was dispensed in kits with random four-digit identification numbers. Kits were sent in sequence to sites as each new participant was enrolled. Treatment under investigation and placebo were made indistinguishable to patients and neurologists.

All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS, version23) and Stata Statistical Software (STATA, version13.1). Discrete data, normally distributed and skewed distribution continuous data were presented as counts and percentages, means ± SD and medians with the accompanying inter-quartile ranges (IQR) respectively. The differences between groups were analyzed using Chi-square or Fisher’s exact test, student-t tests and the Mann-Whitney U test. Univariate and multivariate logistic regression analyses (using stepwise method) were performed to evaluate the magnitude and significance of the association. The choice of models was under the simple and feasible evaluation criterion of the Akaike information criterion (AIC). ROC and AUC analysis was performed to determine the sensitivity and specificity of PEG-IFN response and optimal cut-off was selected based on Youden Index (YI). A two-sided p value< 0.05 was considered statistically significant.