title: Multiple imputation was a valid approach to estimate absolute risk from a prediction model based on case-cohort data.
abstract: OBJECTIVE
  To compare weighting methods for Cox regression and multiple imputation (MI) in a case-cohort study in the context of risk prediction modeling.
  
  
  METHODS
  Based on the European Prospective Investigation into Cancer and Nutrition Potsdam study, we estimated risk scores to predict incident type-2 diabetes using full cohort data and case-cohort data assuming missing information on waist circumference outside the case-cohort (∼90%). Varying weighting approaches and MI were compared with regard to the calculation of relative risks, absolute risks, and predictive abilities including C-index, the net reclassification improvement, and calibration.
  
  
  RESULTS
  The full cohort comprised 21,845 participants, and the case-cohort comprised 2,703 participants. Relative risks were similar across all methods and compatible with full cohort estimates. Absolute risk estimates showed stronger disagreement mainly for Prentice and Self & Prentice weighting. Barlow and Langholz & Jiao weighting methods and MI were in good agreement with full cohort analysis. Predictive abilities were closest to full cohort estimates for MI or for Barlow and Langholz & Jiao weighting.
  
  
  CONCLUSIONS
  MI seems to be a valid method for deriving or extending a risk prediction model from case-cohort data and might be superior for absolute risk calculation when compared to weighted approaches.
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, Neuherberg 85764, Germany.
authors.forename: Kristin
authors.initials: K
authors.lastname: Mühlenbruch
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, Neuherberg 85764, Germany.
authors.forename: Olga
authors.initials: O
authors.lastname: Kuxhaus
authors.affiliation: Research Group Cardiovascular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Postfach 65 21 33, Berlin 13316, Germany.
authors.forename: Romina
authors.initials: R
authors.lastname: di Giuseppe
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany.
authors.forename: Heiner
authors.initials: H
authors.lastname: Boeing
authors.affiliation: Research Group Cardiovascular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Postfach 65 21 33, Berlin 13316, Germany; Department of Food Safety, Federal Institute of Risk Assessment, Max-Dohrn-Str. 8-10, Berlin 10589, Germany.
authors.forename: Cornelia
authors.initials: C
authors.lastname: Weikert
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, Neuherberg 85764, Germany. Electronic address: mschulze@dife.de.
authors.forename: Matthias B
authors.initials: MB
authors.lastname: Schulze
mesh_terms: D000328:Adult; D000368:Aged; D015331:Cohort Studies; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology*; D005260:Female; D005858:Germany / Q000453:epidemiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D016016:Proportional Hazards Models; D011446:Prospective Studies; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D055105:Waist Circumference
keywords: Case–cohort studies; Diabetes mellitus; Model extension; Multiple imputation; Risk prediction; Type 2