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The ABC model of prostate cancer: A conceptual framework for the design and interpretation of prognostic studies.
Pettersson, Andreas; Gerke, Travis; Fall, Katja; Pawitan, Yudi; Holmberg, Lars; Giovannucci, Edward L; Kantoff, Philip W; Adami, Hans-Olov; Rider, Jennifer R; Mucci, Lorelei A.
Afiliação
  • Pettersson A; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Gerke T; Clinical Epidemiology Unit, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden.
  • Fall K; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Pawitan Y; Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center, Tampa, Florida.
  • Holmberg L; Clinical Epidemiology and Biostatistics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
  • Giovannucci EL; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
  • Kantoff PW; Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.
  • Adami HO; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Rider JR; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Mucci LA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Cancer ; 123(9): 1490-1496, 2017 05 01.
Article em En | MEDLINE | ID: mdl-28152172
ABSTRACT
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. Cancer 2017;1231490-1496. © 2017 American Cancer Society.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Prostatectomia / Neoplasias da Próstata / Conduta Expectante Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans / Male Idioma: En Revista: Cancer Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Prostatectomia / Neoplasias da Próstata / Conduta Expectante Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans / Male Idioma: En Revista: Cancer Ano de publicação: 2017 Tipo de documento: Article