The healthy participant effect: insights and results from a population-based case–control study on breast cancer - Top-Institutions - MDSpire

The healthy participant effect: insights and results from a population-based case–control study on breast cancer

  • By

  • Kevin Maldonado-Cañón

  • Annika Möhl

  • Nadia Obi

  • Sabine Behrens

  • Fabian Flaßkamp

  • Petra Seibold

  • Jenny Chang-Claude

  • Heiko Becher

  • June 24, 2024

  • 0 min

Share

Top Institutions in Oncology

Brief introduction explaining scope and methodology.

  • #1

    Harvard T.H. Chan School of Public Health
    Harvard T.H. Chan School of Public Health

    Boston, MA

    Key Differentiators

    • Epidemiology
    • Cancer Prevention
    • Biostatistics

  • #2

    Fred Hutchinson Cancer Research Center
    Fred Hutchinson Cancer Research Center

    Seattle, WA

    Key Differentiators

    • Cancer Epidemiology
    • Population Health
    • Biostatistics

  • #3

    Johns Hopkins Bloomberg School of Public Health
    Johns Hopkins Bloomberg School of Public Health

    Baltimore, MD

    Key Differentiators

    • Epidemiology
    • Cancer Research
    • Public Health

  • #4

    University of California, San Francisco (UCSF) Helen Diller Family Comprehensive Cancer Center
    University of California, San Francisco (UCSF) Helen Diller Family Comprehensive Cancer Center

    San Francisco, CA

    Key Differentiators

    • Cancer Epidemiology
    • Biostatistics
    • Population Health

  • #5

    National Cancer Institute (NCI)
    National Cancer Institute (NCI)

    Bethesda, MD

    Key Differentiators

    • Cancer Epidemiology
    • Population Studies
    • Biostatistics

Original Source(s)

The healthy participant effect: insights and results from a population-based case–control study on breast cancer

  • by Kevin Maldonado-Cañón, Annika Möhl, Nadia Obi, Sabine Behrens, Fabian Flaßkamp, Petra Seibold, Jenny Chang-Claude, Heiko Becher

  • June 24, 2024

Related Content

Multi-parametric MRI habitat radiomics with interpretable machine learning for early prediction of axillary lymph node metastasis in triple-negative breast cancer

Lactylation-mediated remodelling of the breast cancer microenvironment: single-cell multidimensional analysis and prognostic model construction

Dana-Farber Research News 05.15.2026

This twice-monthly newsletter highlights recently published research where Dana-Farber faculty are listed as first or senior authors. The information is pulled from PubMed and this issue notes papers published from April 16 - 30.

  • by

  • May 15, 2026

  • 21 min