The European project ORCHESTRA intends to create a new pan-European cohort to rapidly advance the knowledge of the effects and treatment of COVID-19. Establishing processes that facilitate the merging of heterogeneous clusters of retrospective data was an essential challenge. In addition, data from new ORCHESTRA prospective studies have to be compatible with earlier collected information to be efficiently combined. In this article, we describe how we utilized and contributed to existing standard terminologies to create consistent semantic representation of over 2500 COVID-19-related variables taken from three ORCHESTRA studies. The goal is to enable the semantic interoperability of data within the existing project studies and to create a common basis of standardized elements available for the design of new COVID-19 studies. We also identified 743 variables that were commonly used in two of the three prospective ORCHESTRA studies and can therefore be directly combined for analysis purposes. Additionally, we actively contributed to global interoperability by submitting new concept requests to the terminology Standards Development Organizations.

On May 3rd, 2022, the European Commission published its legislative proposal to create a European Health Data Space (EHDS) enabling citizens of the European Union to gain secure access to their electronic health data by establishing a market for digital health. This market will feature the primary and secondary use of electronic health records by digital products and services. The articles of the proposal address many aspects of ensuring health data interoperability. That includes the creation of a European Electronic Health Record Exchange Format for defined data categories including patient summaries and electronic prescriptions, the development of a central platform to provide a cross-border digital infrastructure and that each Member State institutes a digital health authority and a national point of contact. In addition, the Commission will define common specifications that electronic health record systems and medical devices will have to meet as interoperability requirements. In its current form, the proposal does not stipulate specific standards that need to be universally adopted to ensure semantic and syntactical interoperability. Considering that many datasets are not internationally harmonized and lack standardization, these specifications will need to be provided for example by existing standards like the International Patient Summary.

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Glycosaminoglycans are long polysaccharidic chains, which are mostly present in connective tissues. Modified GAG expression in tissues surrounding malignant cells has been shown to contribute to tumor progression, aggressive status and metastasis in many types of cancer. Ovarian cancer is one of the most lethal gynecological malignancies due to its late diagnosis because of the absence of clear symptoms and unavailability of early disease markers. We investigated for the first time GAG changes at the molecular level as a novel biomarker for primary epithelial ovarian cancer. To this end, serum of a cohort of 68 samples was digested with chondroitinase ABC, which releases chondroitin sulfate into disaccharides. After labeling and purification, they were measured by HPLC, yielding a profile of eight disaccharides. We proposed a novel GAG-based score named “CS- bio” from the measured abundance of disaccharides present that were of statistical relevance. CS-bio’s performance was compared with CA125, the clinically used serum tumor marker in routine diagnostics. CS-bio had a better sensitivity and specificity than CA125. It was more apt in differentiating early-stage patients from healthy controls, which is of high interest for oncologists.