Dataset of the meta-analysis on seasonality of polymyalgia rheumatica and giant cell arteritis onset

Published: 01-08-2020| Version 1 | DOI: 10.17632/63n4mxv2kr.1
Elvis Hysa


Onset symptoms of polymyalgia rheumatica (PMR) and giant cell arteritis (GCA) were collected through relevant papers found in the scientific literature. Since we wanted to determine whether there is a seasonal aggregation for these disorders, only papers reporting semestral, seasonal or monthly onset symptoms were included in the meta-analysis. Data were organized in hierarchical order yielding 9 tables, which first considered both diseases together, and then each disease separately, in relationship to the times of the year divided as 6-month periods, seasons or months. Meta-analysis of incidence variations with semester, season, or month was performed on the natural logarithm of IRRs, which was calculated, for each comparison, as a ratio between the cold period versus the warm period. The main meta-analysis regarded the comparison between the warm and cold semesters in all PMR and GCA patients considered. Secondary meta-analyses regarded any other possible combination. Fixed and random effects meta-analysis weighed by the inverse variance were also performed and the results were graphically represented as forest plots. Heterogeneity was determined by Cochrane’s Q and the I2 statistic while publication bias was assessed by funnel plots and Egger tests. Different sensitivity analyses were performed with the evaluation of pooled data obtained by repeating the meta-analyses after removing one paper at a time. This process was performed to observe whether disproportionate studies could have a disproportionate influence on the result of the meta-analysis. All statistical analyses were performed using R version 3.5. The meta package (version 4.9) was used to produce the pooled estimates and forest plots.