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Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

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Updated: May 8, 2026

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
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A comprehensive European Colorectal Cancer Cohort dataset.

Petr Holub1,2, Outi Törnwall3, Eva Garcia Alvarez4

  • 1BBMRI-ERIC, Neue Stiftingtalstrasse 2/B/6, 8010, Graz, Austria. petr.holub@bbmri-eric.eu.

Scientific Data
|March 13, 2026
PubMed
Summary
This summary is machine-generated.

A large European colorectal cancer (CRC) cohort was created using data from 26 biobanks. This resource supports biomarker research for early detection, prognosis, and treatment of CRC.

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Area of Science:

  • Oncology
  • Biobanking
  • Data Science

Background:

  • Colorectal cancer (CRC) is a significant global health concern, driving the need for robust research infrastructure.
  • The Biobanking and Biomolecular Resources European Research Infrastructure (BBMRI-ERIC) initiated a multi-national CRC cohort to consolidate patient data.
  • Existing biobanks hold valuable clinical and molecular data crucial for advancing CRC research.

Purpose of the Study:

  • To establish a comprehensive, European-wide colorectal cancer cohort with curated clinical data.
  • To facilitate research into biomarkers for early detection, prognosis, and treatment of CRC.
  • To integrate advanced data types, including histopathology slides and whole genome sequencing, for novel research applications.

Main Methods:

  • A retrospective, multi-center study design was employed, collecting data from 26 biobanks across 12 countries.
  • A standardized phenotypical/clinical data model was defined for data collection and curation.
  • Individual-level data from 10,780 CRC patients were aggregated into a central data deposition service.

Main Results:

  • A large-scale colorectal cancer cohort (CRC-Cohort) with 10,780 patients has been successfully established.
  • Structured and curated clinical data are available, supporting diverse research avenues.
  • The cohort infrastructure was extended with histopathology slides and whole genome sequencing data, enabling AI and EHDS use cases.

Conclusions:

  • The BBMRI-ERIC CRC-Cohort represents a valuable, large-scale resource for advancing colorectal cancer research.
  • The implementation of FAIR and FAIR-Health principles ensures data accessibility and reusability.
  • This initiative provides a foundation for future research in precision medicine and digital pathology for CRC.