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Introducing PIONEER: a project to harness big data in prostate cancer research

An Author Correction to this article was published on 25 June 2020

This article has been updated


Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. Launched by the Innovative Medicines Initiative 2 and part of the Big Data for Better Outcomes Programme (BD4BO), the overarching goal of PIONEER is to provide high-quality evidence on prostate cancer management by unlocking the potential of big data. The project has identified critical evidence gaps in prostate cancer care, via a detailed prioritization exercise including all key stakeholders. By standardizing and integrating existing high-quality and multidisciplinary data sources from patients with prostate cancer across different stages of the disease, the resulting big data will be assembled into a single innovative data platform for research. Based on a unique set of methodologies, PIONEER aims to advance the field of prostate cancer care with a particular focus on improving prostate-cancer-related outcomes, health system efficiency by streamlining patient management, and the quality of health and social care delivered to all men with prostate cancer and their families worldwide.

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Fig. 1: Organization of PIONEER and key stakeholders.
Fig. 2: Data collection in PIONEER.
Fig. 3: Overview of the PIONEER project and expected outcomes.

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PIONEER is funded through the IMI2 Joint Undertaking and is listed under grant agreement No. 777492. This joint undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.

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Authors and Affiliations




M.I.O. researched data for the article. M.I.O., M.J. Roobol and M.J. Ribal made substantial contributions to discussions of content. All authors contributed to writing the article and reviewed and edited the manuscript before submission.

Corresponding author

Correspondence to Muhammad Imran Omar.

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The authors declare no competing interests.

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Related links


Europa Uomo:

European Alliance for Personalized Medicine (EAPM):

European Association of Urology (EAU):

European Commission:

European Federation of Pharmaceutical Industry Associations (EFPIA):

Innovative Medicines Initiative 2 (IMI2):


Urological Cancer Charity (UCAN):

Supplementary information


Adaptive clinical trials

In adaptive clinical trials, the parameters of the trials could be modified during the course of the study, based upon the observations of participants.

Big data

Big data describes very-high-volume data that could be difficult to process using traditional methods, database and software techniques.


COMET’s objective is to encourage the development of evidence-based core outcome sets.

Delphi consensus-building process

Delphi consensus-building is a structured approach to decision-making.

European Medical Information Framework

(EMIF). A central metadata catalogue that is a unified platform to support a wide range of studies.

Europa Uomo

An organization supporting patients with prostate diseases in general and prostate cancer in particular.

European Alliance for Personalized Medicine

(EAPM). An alliance that brings together various stakeholders including health-care experts, health-care organizations and institutions, and patient advocates.

European Commission

One of the executive arms of the European Union. The role of the European Commission is to propose and enforce legislation, as well as implement policies and the European Union budget.

Federated data model

In a federated data model, the data are converted into a standard format within the environment of the data provider and made available for research upon request.

Health-technology assessment

A systematic process to assess both the intended and unintended effects of health technology, comparing the balance of benefits and harms.


An organization committed to developing standard sets of condition-specific outcomes.


A data observatory enabling data visualization from various angles.

Medical Adaptive Pathways to Patients

(MAPPs). Prospectively planned processes, starting with the early authorization of a medicine in a restricted patient population, followed by iterative phases of evidence gathering and adaptations of the marketing authorization to expand access to the medicine to broader patient populations.


An international network of researchers and observational health databases.

Observational Medical Outcomes Partnership (OMOP) Common Data Model

Allows systematic analysis of disparate observational databases.


The private or public entity that pays for health-care services. Examples include private insurance companies or a government-supported single public system (for example, the National Health Service in the UK).

Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines

A checklist of 27 items containing reporting standards in systematic reviews and meta-analysis.

R package

A software environment for statistical computing.

SAS open Platform

A data analytics platform.

SPARK infrastructure

A unified analytics engine for big data processing.


A knowledge management and big data analytics platform.


A urological cancer charity dedicated to providing support to patients and their families.

Williamson–Clarke taxonomy

Consists of 38 items and was developed to provide a robust scope to classify core outcome sets that are listed in the COMET database in a way that classifies what the outcome is at the conceptual level rather than how the outcomes are measured.

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Omar, M.I., Roobol, M.J., Ribal, M.J. et al. Introducing PIONEER: a project to harness big data in prostate cancer research. Nat Rev Urol 17, 351–362 (2020).

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