Uncovering the natural history of prostate cancer in data from millions of patient lives across the globe
Prostate cancer is a major disease affecting more than 2 million men in Europe alone, and has now become the most common cancer in men. Clinical management of this complex disease is challenging and involves difficult trade-offs, since in reality prostate cancer consists of a spectrum of diseases ranging from low-risk to very aggressive forms. Therefore, doctors and patients have to make difficult decisions on how to treat the disease and in some case on whether or not to treat the disease, which also involves risk.
Unfortunately, there is still surprisingly little data at scale on what the ‘natural history’ (progression of the disease in absence of treatment) is and how co-morbidities (other life-threatening medical conditions) influence the life expectancy of patients diagnosed with prostate cancer. It would greatly aid shared-decision making between clinicians and patients to have a better understanding of which patients will pass away as a result of prostate cancer versus other causes, to establish where treatment would be most effective and to avoid unnecessary interventions for patients.
To achieve this clinicians and researchers are joining forces in a virtual studyathon to explore the natural history of prostate cancer in a large dataset of patients from across the globe. The aim of the studyathon is to support clinicians and researchers with better data on the possible outcomes of different treatment options and to explore the potential to generate and validate more accurate prediction algorithms based on data from Europe, the USA and other parts of the globe.
New big data approaches pioneered by OHDSI and EHDEN are changing the way in which medical evidence is generated through systematic large-scale data analysis in health data sources globally. In particular, a studyathon is a focused event in which a large-scale study, which traditionally takes many months to complete, is executed and completed in a few days. This approach has recently successfully been applied to studies in rheumatoid arthritis, hypertension and COVID-19 (see links below), and we now aim to do the same for prostate cancer. Movember is supporting this project too with project design ideas drawn from their experiences in multidisciplinary, global collaboration.
Via PIONEER and EHDEN, datasets with healthcare records for more than 1 million patients with prostate cancer are already accessible for the studyathon, but we are seeking additional data sources with longitudinal data, especially those converted to the OMOP Common Data Model to join this effort. Clinicians, epidemiologists and other researchers interested in this question are also invited to take part.
The studyathon itself will be a 5-day virtual event on 8-12 March 2021, with sessions every day focused on literature review, phenotype definition, analytics and results interpretation, and will follow the OHDSI approach (http://book.ohdsi.org). Please register your interest via this link and join us in this journey!
PIONEER (Prostate Cancer DIagnOsis and TreatmeNt Enhancement through the Power of Big Data in EuRope) is a European project focused on using big data to improve the clinical understanding and inform the diagnosis and treatment of prostate cancer, funded through IMI2 JU, and is listed under grant agreement No. 777492.
EHDEN (European Health Data & Evidence Network) is a European project focused on generating medical insights at scale from real-world clinical data, funded through IMI2 JU, and is listed under grant agreement No. 806968.
OHDSI (Observational Health Data Sciences and Informatics) is a multi-stakeholder, interdisciplinary open science collaborative aiming to bring out the value of health data through large-scale analytics. Earlier studyathons have resulted in publications in amongst others The Lancet Rheumatology, The Lancet Digital Health and Nature Communications.