Trends and Perspectives for Dermatological Research in Europe: An Abstract Title Analysis of ESDR and IID Congresses 2010–2019

Abstract

To better understand and interpret the trends in cutaneous research, we carried out a network analysis of all the titles of the submitted abstracts of the annual meetings of the European Society of Dermatological Research (ESDR), including the International Investigative Dermatology (IID) meetings between 2010 and 2019. Network analysis is a data science tool to process, analyze, and visualize big sets of data. As expected, psoriasis was the frontrunner in each of the annual meetings, followed by dermatitis and melanoma. Interestingly, alopecia, acne, squamous cell carcinoma, pruritus, basal cell carcinoma, and hidradenitis suppurativa were among the next most frequently named diseases and/or terms. We also looked at diversity to assess how broad the interest of the submitting community is and to identify whether "blockbusters" such as psoriasis and atopic dermatitis expand in expense of other interests. In contrast to our expectations, the diversity of submissions to the ESDR annual meetings remained high over the 10 years of our observation period. Interestingly, the diversity increased in the years of the IID, indicating an outreach to other research areas worldwide compared with the ESDR meetings. This is true for both 2013 in Edinburgh, UK, and 2018 in Orlando, USA. During these meetings, this rise in diversity was associated with a relative decrease of the three most often named diseases. Network analysis thus may be a useful tool for research societies like the ESDR to identify trends and allocate resources such as reviewers and sessions accordingly. In addition, it can serve as quality control monitoring whether the ESDR continues to offer a platform for all researchers in cutaneous biology or implements or focuses on emerging fields.

Websearch-Daten als Gesundheitsdaten?

“…Große Möglichkeiten birgt aber auch die Digitalisierung im Gesundheitswesen selbst. Überdies wurde in den letzten Jahren in der Medizin auch zunehmend die Nützlichkeit von Netzwerkanalysen [ 2 ] zur Visualisierung und Analyse von komplexen Daten jeglicher Art erkannt. Ziel ist es, diese Daten unter Einhaltung der rechtlichen Grundlagen zusammenzubringen und zu analysieren.…”

Netzwerkanalysen als nützliche Ergänzung konventioneller Statistik

“…Auf dieselbe Weise konnten Netzwerkanalysen und -graphen auch dazu genutzt werden, um Themenschwerpunkte automatisiert aus über 100 Seiten langen Programmheften dermatologischer Fachkongresse herauszuarbeiten [ 3 – 6 ]. Dies bringt potenziellen Kongressinteressenten den Vorteil, Themengebiete schon vor der Kongressanmeldung überblicken zu können.…”

A network analysis of the EADV 2019 conference

“…Because of the sheer volume, it is hard to grasp which topics were especially focused on and which, conversely, were rather underrepresented. An upcoming computational method to process, analyse and visualize big data of any size to make it accessible for interpretation is network analysis, which is widely used in social and political sciences 2,3 but rarely in the medical field 4,5 . To gain an in‐depth insight into the EADV 2019, its collaborators and themes, we performed a network analysis based on the titles of all lectures and posters.…”

“…An upcoming computational method to process, analyse and visualize big data of any size to make it accessible for interpretation is network analysis, which is widely used in social and political sciences 2,3 but rarely in the medical field. 4,5 To gain an in-depth insight into the EADV 2019, its collaborators and themes, we performed a network analysis based on the titles of all lectures and posters. Data were extracted from the official program pdf file using tabula v1.2.1 open-source software 6 and then preprocessed using custom-written python code.…”