Background: The term prurigo has been used for many decades in dermatology without clear definition, and currently used terminology of prurigo is inconsistent and confusing. Especially, itch‐related prurigo remains unexplored regarding the epidemiology, clinical profile, natural course, underlying causes, available treatments and economic burden, although burdensome and difficult to treat.Objective: To address these issues, the multicentre European Prurigo Project (EPP) was designed to increase knowledge on chronic prurigo (CPG). In the first step, European experts of the EADV Task Force Pruritus (TFP) aimed to achieve a consensus on the definition, classification and terminology of CPG. Additionally, procedures of the cross‐sectional EPP were discussed and agreed upon.Methods: Discussions and surveys between members of the TFP served as basis for a consensus conference. Using the Delphi method, consensus was defined as an agreement ≥75% among the present members.Results: Twenty‐four members of the TFP participated in the consensus conference. Experts consented that CPG should be used as an umbrella term for the range of clinical manifestations (e.g. papular, nodular, plaque or umbilicated types). CPG is considered a distinct disease defined by the presence of chronic pruritus for ≥6 weeks, history and/or signs of repeated scratching and multiple localized/generalized pruriginous skin lesions (whitish or pink papules, nodules and/or plaques). CPG occurs due to a neuronal sensitization to itch and the development of an itch‐scratch cycle.Conclusion: This new definition and terminology of CPG should be implemented in dermatology to harmonize communication in the clinical routine, clinical trials and scientific literature. Acute/subacute forms of prurigo are separated entities, which need to be differentiated from CPG and will be discussed in a next step. In the near future, the cross‐sectional EPP will provide relevant clinical data on various aspects of CPG leading to new directions in the scientific investigation of CGP.

Background: Chronic nodular prurigo (CNPG) is a condition characterized by chronic itch, a prolonged scratching behaviour and the presence of pruriginous nodules. A comprehensive understanding of this condition, especially regarding its clinical characteristics and impact on quality of life is still lacking.Objectives: Aim of this pan‐European multicentre cross‐sectional study was to establish the clinical profile of CNPG, including its associated burden.Methods: Fifteen centres from 12 European countries recruited CNPG patients presenting at the centre or using the centres' own databases. Patients were asked to complete a questionnaire in paper or electronic format. Demography, current co‐morbidities, underlying disease, itch intensity, additional sensory symptoms, quality of life, highest burden and emotional experience of itch were assessed.Results: A total of 509 patients (210 male, median age: 64 years [52; 72]) were enrolled. Of these, 406 reported itch and CNPG lesions in the previous 7 days and qualified to complete the whole questionnaire. We recorded moderate to severe worst itch intensity scores in the previous 24 h. Scores were higher in patients with lower educational levels and those coming from Eastern or Southern Europe. Most patients experience itch often or always (71%) and report that their everyday life is negatively affected (53%). Itch intensity was considered to be the most burdensome aspect of the disease by 49% of the patients, followed by the visibility of skin lesions (21%) and bleeding of lesions (21%). The majority of patients was unaware of an underlying condition contributing to CNPG (64%), while psychiatric diseases were the conditions most often mentioned in association with CNPG (19%).Conclusions: This multicentre cross‐sectional study shows that itch is the dominant symptom in CNPG and reveals that the profile of the disease is similar throughout Europe.

Introduction : Information systems are a key success factor for medical research and healthcare. Currently, most of these systems apply heterogeneous and proprietary data models, which impede data exchange and integrated data analysis for scientific purposes. Due to the complexity of medical terminology, the overall number of medical data models is very high. At present, the vast majority of these models are not available to the scientific community. The objective of the Portal of Medical Data Models (MDM, https://medical-data-models.org ) is to foster sharing of medical data models. Methods : MDM is a registered European information infrastructure. It provides a multilingual platform for exchange and discussion of data models in medicine, both for medical research and healthcare. The system is developed in collaboration with the University Library of Münster to ensure sustainability. A web front-end enables users to search, view, download and discuss data models. Eleven different export formats are available (ODM, PDF, CDA, CSV, MACRO-XML, REDCap, SQL, SPSS, ADL, R, XLSX). MDM contents were analysed with descriptive statistics. Results : MDM contains 4387 current versions of data models (in total 10 963 versions). 2475 of these models belong to oncology trials. The most common keyword ( n = 3826) is ‘Clinical Trial’; most frequent diseases are breast cancer, leukemia, lung and colorectal neoplasms. Most common languages of data elements are English ( n = 328 557) and German ( n = 68 738). Semantic annotations (UMLS codes) are available for 108 412 data items, 2453 item groups and 35 361 code list items. Overall 335 087 UMLS codes are assigned with 21 847 unique codes. Few UMLS codes are used several thousand times, but there is a long tail of rarely used codes in the frequency distribution. Discussion : Expected benefits of the MDM portal are improved and accelerated design of medical data models by sharing best practice, more standardised data models with semantic annotation and better information exchange between information systems, in particular Electronic Data Capture (EDC) and Electronic Health Records (EHR) systems. Contents of the MDM portal need to be further expanded to reach broad coverage of all relevant medical domains. Database URL : https://medical-data-models.org

Background: Chronic pruritus (CP) is a subjective symptom, and it is necessary to assess its intensity with validated patient‐reported outcome tools in order to allow determination of the treatment course.Objectives: So far, the itch intensity scales were validated in small cohorts and in single languages. Here, we report the validation of the numerical rating scale, the verbal rating scale and the visual analogue scale for the worst and average pruritus intensity in the last 24h in several languages across Europe and across different pruritic dermatoses.Methods: After professional translation, the intensity scales were digitized for use as a tablet computer application. Validation was performed in clinics for Dermatology in Austria, France, Germany, Italy, Poland, Russia, Spain, Switzerland and Turkey.Results: A total of 547 patients with contact dermatitis, chronic nodular prurigo, psoriasis vulgaris, lichen planus or cutaneous T‐cell lymphoma were included. The intensity scales showed a high level of reproducibility and inter‐correlations with each other. The correlation with the Dermatology Life Quality Index was weak to strong in nearly all countries and dermatoses with the exception of France and patients with chronic nodular prurigo, for which no statistically significant correlations were found.Conclusions: The numerical rating scale, the verbal rating scale und the visual analogue scales are valid instruments with good reproducibility and internal consistency in German (Germany, Austria, Switzerland), French, Italian, Polish, Russian, Spanish and Turkish for different pruritic dermatoses. VAS worst was the best reproducible and consistent measuring instrument in all countries.

The volume and complexity of patient data – especially in personalised medicine – is steadily increasing, both regarding clinical data and genomic profiles: Typically more than 1,000 items (e.g., laboratory values, vital signs, diagnostic tests etc.) are collected per patient in clinical trials. In oncology hundreds of mutations can potentially be detected for each patient by genomic profiling. Therefore data integration from multiple sources constitutes a key challenge for medical research and healthcare. Semantic annotation of data elements can facilitate to identify matching data elements in different sources and thereby supports data integration. Millions of different annotations are required due to the semantic richness of patient data. These annotations should be uniform, i.e., two matching data elements shall contain the same annotations. However, large terminologies like SNOMED CT or UMLS don’t provide uniform coding. It is proposed to develop semantic annotations of medical data elements based on a large-scale public metadata repository. To achieve uniform codes, semantic annotations shall be re-used if a matching data element is available in the metadata repository. A web-based tool called ODMedit ( https://odmeditor.uni-muenster.de/ ) was developed to create data models with uniform semantic annotations. It contains ~800,000 terms with semantic annotations which were derived from ~5,800 models from the portal of medical data models (MDM). The tool was successfully applied to manually annotate 22 forms with 292 data items from CDISC and to update 1,495 data models of the MDM portal. Uniform manual semantic annotation of data models is feasible in principle, but requires a large-scale collaborative effort due to the semantic richness of patient data. A web-based tool for these annotations is available, which is linked to a public metadata repository.