Related Experiment Video
Updated: Apr 21, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Maastricht Delphi consensus on event definitions for classification of recurrence in breast cancer research
Martine Moossdorff1, Lori M van Roozendaal1, Luc J A Strobbe1
1Department of Surgery and GROW School for Oncology and Developmental Biology (MM, MLS), Department of Surgery and Radiology (LMvR), Department of Medical Oncology, GROW School for Oncology and Developmental Biology (VCGTH), and Department of Epidemiology and GROW School for Oncology and Developmental Biology (ACV), Maastricht University Medical Center, Maastricht, the Netherlands; Department of Surgery, Canisius-Wilhelmina Hospital, Nijmegen, the Netherlands (LJAS); Division of Medical Oncology, Luzerner Kantonsspital, Lucerne, Switzerland (SA); Edinburgh Cancer Research Centre, University of Edinburgh and NHS Lothian (DAC), Edinburgh Breast Unit (JMD), Western General Hospital, Edinburgh, UK; Cedars-Sinai Medical Center, Los Angeles, CA (AEG); Rutgers Cancer Institute of New Jersey, New Brunswick, NJ (BGH); Mater Centre Radiation Oncology Service, Princess Alexandra Hospital, Brisbane, Australia (BEH); Breast Cancer Medicine Service, Memorial Sloan Kettering Cancer Center and Professor of Medicine, Weill Cornell Medical College, New York, NY (CAH); University of Arkansas for Medical Sciences, Winthrop P. Rockefeller Cancer Institute, Little Rock, AR (VSK); Flinders Centre for Innovation in Cancer, Flinders University, Adelaide, Australia (BK); Interdisciplinary Breast Centre, Department of Gynaecology and Obstetrics, Klinikum Esslingen, Germany (TK); University of Miami Miller School of Medicine, Miami, FL (MEL); Radiation Oncology (BDS) and Department of Surgical Oncology, Division of Surgery (AL), University of Texas/MD Anderson Cancer Center, Houston, TX; Institut Jules Bordet, Université Libre de Bruxelles, Head of Medicine Department, Brussels, Belgium (MP); Surgery, University Medical Center, Leiden, the Netherlands (CJHvdV); Breast Service, Memorial Sloan-Kettering Cancer Center, Evelyn Lauder Breast Center, New York, NY(KJVZ); Antwerp University Hospital, Department of Medical Oncology, Edegem, Belgium (JBV); Department of Pathology, European Institute of
Background:
In breast cancer studies, many different endpoints are used. Definitions are often not provided or vary between studies. For instance, "local recurrence" may include different components in similar studies. This limits transparency and comparability of results. This project aimed to reach consensus on the definitions of local event, second primary breast cancer, regional and distant event for breast cancer studies.
Methods:
The RAND-UCLA Appropriateness method (modified Delphi method) was used. A Consensus Group of international breast cancer experts was formed, including representatives of all involved clinical disciplines. Consensus was reached in two rounds of online questionnaires and one meeting.
Results:
Twenty-four international breast cancer experts participated. Consensus was reached on 134 items in four categories. Local event is defined as any epithelial breast cancer or ductal carcinoma in situ (DCIS) in the ipsilateral breast, or skin and subcutaneous tissue on the ipsilateral thoracic wall. Second primary breast cancer is defined as epithelial breast cancer in the contralateral breast. Regional events are breast cancer in ipsilateral lymph nodes. A distant event is breast cancer in any other location. Therefore, this includes metastasis in contralateral lymph nodes and breast cancer involving the sternal bone. If feasible, tissue sampling of a first, solitary, lesion suspected for metastasis is highly recommended.
Conclusion:
This project resulted in consensus-based event definitions for classification of recurrence in breast cancer research. Future breast cancer research projects should adopt these definitions to increase transparency. This should facilitate comparison of results and conducting reviews as well as meta-analysis.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
