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Procedures of data merging in precision cancer medicine: the PRIME-ROSE project
Henk Van der Pol1, Tina Kringelbach2, Maria Martin Agudo3
1Department of Medical Oncology, Leiden University Medical Centre, Leiden, The Netherlands; Mathematical Institute, Leiden University, Leiden, The Netherlands.
Background And Purpose:
As more interventional clinical trials in Precision Cancer Medicine (PCM) are introduced, molecular descriptions of tumours have led to multiple subtypes, even within common tumour types. Therefore, the main limitation of these trials is the small number of eligible patients to assess the clinical benefit. The PRIME-ROSE project addresses this limitation by pooling data from multiple European Drug Rediscovery Protocol (DRUP)-like clinical trials, such that slowly accruing cohorts are accelerated. To achieve this task, a well-documented commonly approved procedure for data merging needs to be established. Patient/material and methods: Data sharing is achievable when there is an organisation that includes people from different disciplines who can navigate institutional and country-specific information and governance requirements. Furthermore, alignment of all the study procedures are needed before data are shared. Next, the process of merging data requires harmonisation and standardisation. Implementation of the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) facilitates future data aggregation.
Results:
By aggregating data from European DRUP-like clinical trials, cohorts are completed that were unable to do so in stand-alone studies. Since initiation, the PRIME-ROSE project monitors over 300 cohorts across more than 20 treatments encompassing over 1,000 patients. At least 20 cohorts have progressed after interim analysis.
Interpretation:
Data sharing across European trials is feasible and enhances the advancements of PCM studies. The methodologies developed in the PRIME-ROSE project provide a foundation for future data integration efforts in PCM clinical trials, underscoring the viability of conducting robust trials in a global context.
Insights
Pooling data from European Precision Cancer Medicine (PCM) trials accelerates patient cohort completion. The PRIME-ROSE project demonstrates feasible data sharing for robust clinical trial advancements.
Area of Science:
- Oncology
- Clinical Trials
- Data Science
Background:
- Precision Cancer Medicine (PCM) trials face patient accrual challenges due to tumor heterogeneity.
- Small patient cohorts limit the assessment of clinical benefit in individual studies.
Purpose of the Study:
- To address patient accrual limitations in PCM trials by pooling data from multiple European studies.
- To establish a framework for data sharing and aggregation in PCM research.
Main Methods:
- The PRIME-ROSE project facilitates data merging by aligning study procedures and harmonizing data.
- Utilizing the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) for data standardization and aggregation.
- Establishing a multidisciplinary organization to navigate institutional and country-specific data governance requirements.
Main Results:
- Aggregated data from European Drug Rediscovery Protocol (DRUP)-like trials enabled cohort completion.
- The PRIME-ROSE project monitors over 300 cohorts across more than 20 treatments, involving over 1,000 patients.
- Over 20 cohorts have progressed following interim analysis.
Conclusions:
- Data sharing across European trials is feasible and significantly advances PCM studies.
- The PRIME-ROSE project's methodologies provide a foundation for future data integration in PCM clinical trials.
- This approach supports the viability of conducting robust PCM trials in a global context.
