Visualising the past to plan the future: a network analysis of the largest European dermatology conference

Abstract

Visualising the past to plan the future: a network analysis of the largest European dermatology conference Background: The annual conference of the European Academy of Dermatology and Venereology is one the largest dermatology conferences worldwide. Objectives: Network analysis can be used for in-depth insight into trending topics and underlying trends at the congress. Materials & Methods: Network analysis was employed to assess the entirety of the submitted abstracts to the congress in 2019. The data were processed, analysed, and visualised using easy-to-understand network graphs. Topics were then compared to their respective global burden (Disease Adjusted Life Years [DALYs]) and the number of respective publications on PubMed in the year 2018. Results: Overall, 1,280 lecture titles and 1,941 poster titles were included in the final analysis. The most frequently used terms were "patients" (n = 473), "treatment" (n = 301), and "psoriasis" (n = 335). Relative to DALYs, "psoriasis" (+21.9%) among others, was rather over-represented, while "fungal skin diseases" (-7.6%) and "urticaria" (-6.4%) were under-represented. Compared to the relative number of PubMed publications in 2018, "psoriasis" (+20.3%), "acne" (+7.9%), and "alopecia" (+3.1%) were over-represented, while "melanoma" (-22.5%), "dermatitis" (-4.2%) and "pruritus" (-3.4%) were rather under-represented. Conclusion: The network analysis showed that the congress was a patient and therapy-centred event. An explanation for the particular focus on chronic inflammatory skin diseases and melanoma would be the introduction of new therapies at the congress. To delineate trends over time, a longitudinal network analysis including several congresses should be conducted and could be used to determine additional topics to be included in future events

Munich atopy prediction study (MAPS): protocol for a prospective birth cohort addressing clinical and molecular risk factors for atopic dermatitis in early childhood

“…To visualise, analyse and structure the data, network analysis will be used to identify potential clusters within the large data sets. 31 Overall, the study aims to better understand the underlying mechanisms of AD and the interaction of various risk factors in infants to improve patient care and disease management.…”

“…Combined with the already existing studies on individual risk factors on AD, we hope to expand on the evidence currently available in the literature and to identify areas which are hardly studied. To visualise, analyse and structure the data, network analysis will be used to identify potential clusters within the large data sets 31. Overall, the study aims to better understand the underlying mechanisms of AD and the interaction of various risk factors in infants to improve patient care and disease management.…”