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The ABC model of prostate cancer: A conceptual framework for the design and interpretation of prognostic studies
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston Massachusetts, USA; Clinical Epidemiology Unit, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden.
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston MA, USA; Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center, Tampa FL, USA.
Örebro University, School of Medical Sciences. Örebro University Hospital. Department of Clinical Epidemiology and Biostatistics, Örebro University Hospital, Örebro, Sweden.ORCID iD: 0000-0002-3649-2639
Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
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2017 (English)In: Cancer, ISSN 0008-543X, E-ISSN 1097-0142, Vol. 123, no 9, 1490-1496 p.Article, review/survey (Refereed) Published
Abstract [en]

There has been limited success in identifying prognostic biomarkers in prostate cancer. A partial explanation may be that insufficient emphasis has been put on clearly defining what type of marker or patient category a biomarker study aims to identify and how different cohort characteristics affect the ability to identify such a marker. In this article, the authors put forth the ABC model of prostate cancer, which defines 3 groups of patients with localized disease that an investigator may seek to identify: patients who, within a given time frame, will not develop metastases even if untreated (category A), will not develop metastases because of radical treatment (category B), or will develop metastases despite radical treatment (category C). The authors demonstrate that follow-up time and prostate-specific antigen screening intensity influence the prevalence of patients in categories A, B, and C in a study cohort, and that prognostic markers must be tested in both treated and untreated cohorts to accurately distinguish the 3 groups. The authors suggest that more emphasis should be put on considering these factors when planning, conducting, and interpreting the results from prostate cancer biomarker studies, and propose the ABC model as a framework to aid in that process.

Place, publisher, year, edition, pages
Hoboken, USA: John Wiley & Sons, 2017. Vol. 123, no 9, 1490-1496 p.
Keyword [en]
Biomarkers, epidemiology, predictive markers, prognostic markers, prostate cancer, survival
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:oru:diva-55407DOI: 10.1002/cncr.30582ISI: 000399903900006PubMedID: 28152172Scopus ID: 2-s2.0-85018516008OAI: oai:DiVA.org:oru-55407DiVA: diva2:1080537
Available from: 2017-03-10 Created: 2017-03-10 Last updated: 2017-09-06Bibliographically approved

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