Gastric cancer is the sixth most common cancer and the fourth most common cause of cancer-related death in Europe, causing 107,000 deaths annually. It is difficult to diagnose it at the pre-symptomatic stage, when treatment is most effective, based on a single diagnostic method. Due to that fact, individual databases or studies can be limited by default.
Data plays a key role in early diagnosis and saving lives. If data from diverse clinical and R&I activities is consolidated, harmonized, and shared with the purpose, it may detect early stages of cancer more successfully. That is why the Data Collaborative project was born, a new form of collaboration that may prevent gastric cancer through early diagnosis. The issue of data transparency is fundamental, both from the patient and technological point.
“Microsoft has engaged with Latvian scientists and partners to help build a framework where several product services can be developed, and data can be shared in a trustworthy manner. Our technology provides solutions that doctors and other professionals can use in the research while keeping patients’ data safe. We are glad that our technology can enable scientists to look for a better way for early diagnostics of gastric cancer”, says the director for Health Industry Sector at Microsoft CEE, Ruthy Kaidar.
With joined forces in making data more transparent in the health sector, Microsoft team collaborated with different scientists in Latvia as well as with partners such as StratejAI and came up with this interesting case that was piloted by the University of Latvia, a pioneer in gastric cancer research.
Professor of Medicine, Director of the Institute of Clinical and Preventive Medicine, University of Latvia, Marcis Leja, has a particular interest in the prevention and early detection of gastrointestinal cancer, particularly – gastric cancer.
“Information is multiplying. Nowadays, the number of studies is growing exponentially, and it requires huge data resources and data inspection so doctors could not be mistaken in some analyses. We see an increasing number of large data volumes. In medicine, decision-making is critical. If we have measurements that could be huge datasets, then evidence-based medicine is heading towards better diagnosis because a human brain is not able to process all this data,” explained Professor Leja.
The technology and the ideas behind data collaboratives are not new. A few hundred healthcare data collaboratives are already operational in Europe and North America. To align the project to the existing European data motion, Data Collaborative project is presented in the Gaia-X healthcare hub, and this is becoming one of the first transborder use cases in that scope.
“Our group of scientists, supported by Microsoft, is leading and managing the largest project in Europe on large data in gastric cancer. The project itself is aligned with Gaia-X guidelines and expert group recommendations. Thanks to Microsoft’s Azure Data Factory, Azure Data Bricks, Azure Synapse Analytics, Azure ML, and Power BI, we have results that are necessary to recommend population-based prevention strategies in entire Europe”, said the Professor.
There is convincing evidence that Helicobacter pylori bacteria (H.pylori) found in the stomach is responsible for gastric cancer in about 90% of the cases. Approximately half of the global population is infected, although there are significant differences present between the countries. It must be pointed out that the prevalence rates are decreasing, but not the absolute number of gastric cancer cases due to the increase of an aging population, also in Europe.
“Having a precise risk-score for primary prevention will lead to precise treatments for high-risk groups of patients and will allow earlier and better diagnostics. Working on endoscopies will also reasonably lead to an improvement in support of more AI-supported diagnosis,” claims Stefano Sedola, partner and founder of StartejAI.
When a patient is admitted to the study, the main benefit goes to society because the recommendations and standards and future patient treatment will rely on the data from those studies.
“Having this data, we could have sound conclusions that would be immediately applied in the healthcare system in our country – for instance, how procedures must be performed, what medical methods should be used, how artificial intelligence could be implied, on condition that these systems are set up. For the research purposes, or the purpose in this case, it is quite possible that they will remain and could also be used for practical healthcare purposes in the future,” observed Professor Leja.
Inspired and conceptually aligned with emerging approaches like the European Health Data Space and Gaia – X, this Latvian project is designed as a decision support tool for policymakers, healthcare organizations, specialists, and other stakeholders, as well as for citizen empowerment and their more intense involvement in the decision-making process.
Currently, the European recommendations are that each European country is obliged to have an accredited Comprehensive Cancer Center. The goal of the Data Collaborative project is that all the experts in the field develop and validate a scalable, data-agnostic, data-driven AI-powered trusted data collaborative system.