title: Statistical controversies in clinical research: the importance of importance.
abstract: We define the notion of 'importance' of prognostic factors in studies of survival and suggest quantifying it by the Schemper-Henderson measure of explained variation. Conceptual differences to the standard approach for the statistical analysis of oncologic studies of survival are discussed and exemplified by means of a study of ovarian cancer. Explained variation permits to establish a ranking of the importance of factors, also if measured on different scales, or of different types (dichotomous, qualitative or continuous), and permits to compare groups of related factors. In practice, the importance of prognostic factors often is disappointingly low. From this, it follows that even strong and highly significant prognostic factors often do not translate into close determination of individual survival of patients.
authors.affiliation: Section for Clinical Biometrics, Center for Medical Statistics, Informatics, and Intelligent Systems.
authors.forename: A
authors.initials: A
authors.lastname: Gleiss
authors.affiliation: Molecular Oncology Group, Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria.
authors.forename: R
authors.initials: R
authors.lastname: Zeillinger
authors.affiliation: Department of Gynecology, Tumor Bank Ovarian Cancer (TOC), European Competence Center for Ovarian Cancer, Campus Virchow Klinikum, Charité-Universitätsmedizin Berlin, Berlin.
authors.forename: E I
authors.initials: EI
authors.lastname: Braicu
authors.affiliation: Department of Gynecology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
authors.forename: F
authors.initials: F
authors.lastname: Trillsch
authors.affiliation: Department of Gynecologic Oncology, Leuven Cancer Institute, University Hospitals Leuven, KU Leuven, Leuven, Belgium.
authors.forename: I
authors.initials: I
authors.lastname: Vergote
authors.affiliation: Section for Clinical Biometrics, Center for Medical Statistics, Informatics, and Intelligent Systems michael.schemper@meduniwien.ac.at.
authors.forename: M
authors.initials: M
authors.lastname: Schemper
mesh_terms: D035843:Biomedical Research / Q000706:statistics & numerical data*; D006801:Humans; D008495:Medical Oncology / Q000706:statistics & numerical data*; D015233:Models, Statistical; D009369:Neoplasms / Q000453:epidemiology; D009859:Oncology Nursing; D011379:Prognosis; D016019:Survival Analysis
keywords: explained variation; ovarian cancer diagnosis initiative (OVCAD); prognostic factors; regression models; survival outcomes