pubmed.ncbi.nlm.nih.gov

On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data - PubMed

  • ️Sat Jan 01 2011

. 2011 May 10;30(10):1105-17.

doi: 10.1002/sim.4154. Epub 2011 Jan 13.

Affiliations

On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data

Hajime Uno et al. Stat Med. 2011.

Abstract

For modern evidence-based medicine, a well thought-out risk scoring system for predicting the occurrence of a clinical event plays an important role in selecting prevention and treatment strategies. Such an index system is often established based on the subject's 'baseline' genetic or clinical markers via a working parametric or semi-parametric model. To evaluate the adequacy of such a system, C-statistics are routinely used in the medical literature to quantify the capacity of the estimated risk score in discriminating among subjects with different event times. The C-statistic provides a global assessment of a fitted survival model for the continuous event time rather than focussing on the prediction of bit-year survival for a fixed time. When the event time is possibly censored, however, the population parameters corresponding to the commonly used C-statistics may depend on the study-specific censoring distribution. In this article, we present a simple C-statistic without this shortcoming. The new procedure consistently estimates a conventional concordance measure which is free of censoring. We provide a large sample approximation to the distribution of this estimator for making inferences about the concordance measure. Results from numerical studies suggest that the new procedure performs well in finite sample.

Copyright © 2011 John Wiley & Sons, Ltd.

PubMed Disclaimer

Figures

Figure 1
Figure 1

Estimates for survival functions for CV events and censoring variables with Framingham study data.

Figure 2
Figure 2

Estimates for survival functions for death and censoring variables with breast cancer data.

Similar articles

Cited by

References

    1. Anderson KM, Odell PM, Wilson PW, Kannel WB. Cardiovascular risk profiles. American Heart Journal. 1991;121:293–8. - PubMed
    1. D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain MR, Massaro JM, Kannel WB. General cardiovascular risk profile for use in primary care: The Framingham Heart Study. Circulation. 2008;117(6):743–53. doi: 10.1161/CIRCULATIONAHA.107.699579. - DOI - PubMed
    1. Shariat SF, Karakiewicz PI, Roehrborn CG, Kattan MW. An updated catalog of prostate cancer predictive tools. Cancer. 2008;113(11):3075–99. doi: 10.1002/cncr.23908. - DOI - PubMed
    1. Parikh NI, Pencina MJ, Wang TJ, Benjamin EJ, Lanier KJ, Levy D, D’Agostino RB, Sr, Kannel WB, Vasan RS. A risk score for predicting near-term incidence of hypertension: the Framingham Heart Study. Annals of Internal Medicine. 2008;148(2):102–10. - PubMed
    1. Bamber D. The area above the ordinal dominance graph and the area below the receiver operating characteristic graph. Journal of Mathematical Psychology. 1975;12:387–415.

Publication types

MeSH terms

LinkOut - more resources