The clinical and technical impact of the HarmonicSS project.

Competing interests: none declared. HARMONIsation and integrative analysis of regional, national and international Cohorts on primary Sjögren’s syndrome (HarmonicSS) is a European Union funded project focused on clinical unmet needs of primary Sjögren’s syndrome (pSS). The main goal of HarmonicSS was to bring together the most important clinical centres specialised in SS across Europe and gather the maximum quantitative and qualitive clinical data in order to address clinically significant questions related to SS. To accomplish such an ambitious vision, distinct scientific fields were engaged and the project consisted of 21 clinical and 13 technical partners. Therefore, HarmonicSS was designed and developed in both clinical and technical level with common denominator the harmonisation process which represents the core of the project (1). The harmonisation process aims to match and transform the heterogeneous terminology used by different clinical partners for the various aspects of the disease, into a common set of terms designated as reference model. The common “scientific language” of reference model offers the opportunity to align clinical information related to SS, ensuring an automated process which homogenize and thus “harmonise” clinical data. This initial step is absolutely necessary in order to handle and utilise SS related data in an optimal way, given that the common reference model can be further expanded and enriched, reflecting the “technical” plasticity provided by the infrastructure which hosts the HarmonicSS project. Apart from the harmonisation process itself, technical challenges such as data curation, federated analysis as well as legal issues related to GDPR and data sharing, have been achieved within the HarmonicSS project. The clinical aspects of the project are summarised as follows: a) to define distinct clinical phenotypes of the disease along with the prevalence of significant clinical, laboratory and histologic parameters in a totally harmonised cohort through integration analysis; b) to explore potential associations between the histopathology of labial minor salivary gland (LMSG) biopsy and the clinical phenotype of the disease; c) to validate old and discover novel biomarkers; d) to study and develop lymphoma classification and prediction models; and e) to employ data driven approaches contributing to the transition into the era of precision medicine. To successfully complete the clinical tasks, research activity was simultaneously developed in 3 levels, since it was not feasible to address complex scientific questions such as discovery of novel biomarkers requiring biologic samples or lymphoma classification models, by simple integration analysis. The first level of research accounts for data collection and analysis from single centres, the second level from spontaneous collaborations of more than one centres while the third level from the whole consortium, meaning all clinical partners/centres. Needless to say, that there are pros and cons for each level of analysis: the third level analysis is characterised by high statistical power but less quality of data (e.g., high rates of missing values, restrictions in matching procedure between study and control groups etc.) and limited number of involved variables as defined by the reference model. On the contrary, first and second level analysis characteristics include lower statistical power, better quality of data and more explored variables. Major progress and innovation were achieved from the technical point of view, towards the development of data governance mechanisms and data analytics services. More specifically, the data sharing assessment module provides functionalities for the upload of legal and ethical documents, the evaluation of GDPR compliance of these Editorial