Sanderson, J. orcid.org/0000-0003-3326-9842, Thompson, S.G., White, I.R. et al. (2 more authors) (2013) Derivation and assessment of risk prediction models using case-cohort data. BMC Medical Research Methodology, 13. 113. ISSN 1471-2288
Abstract
Background Case-cohort studies are increasingly used to quantify the association of novel factors with disease risk. Conventional measures of predictive ability need modification for this design. We show how Harrell’s C-index, Royston’s D, and the category-based and continuous versions of the net reclassification index (NRI) can be adapted. Methods We simulated full cohort and case-cohort data, with sampling fractions ranging from 1% to 90%, using covariates from a cohort study of coronary heart disease, and two incidence rates. We then compared the accuracy and precision of the proposed risk prediction metrics. Results The C-index and D must be weighted in order to obtain unbiased results. The NRI does not need modification, provided that the relevant non-subcohort cases are excluded from the calculation. The empirical standard errors across simulations were consistent with analytical standard errors for the C-index and D but not for the NRI. Good relative efficiency of the prediction metrics was observed in our examples, provided the sampling fraction was above 40% for the C-index, 60% for D, or 30% for the NRI. Stata code is made available. Conclusions Case-cohort designs can be used to provide unbiased estimates of the C-index, D measure and NRI.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2013 Sanderson et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Case-cohort; Risk prediction; Discrimination; Reclassification; Cardiovascular disease |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Apr 2016 10:21 |
Last Modified: | 14 Apr 2016 10:21 |
Published Version: | http://dx.doi.org/10.1186/1471-2288-13-113 |
Status: | Published |
Publisher: | BioMed Central |
Refereed: | Yes |
Identification Number: | 10.1186/1471-2288-13-113 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:98513 |