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Quantification of the prentice criteria for surrogate endpoints
Authors:O'Quigley John  Flandre Philippe
Institution:INSERM, Institut Curie, 26 rue d'Ulm, 75005 Paris, France.
Abstract:In a recent discussion on the Prentice criteria for surrogate endpoints (1989) and the role of meta analyses in this context, Alonso et al. expand on a number of points. Among these is a suggestion to base a measure of the degree at which an endpoint meets the Prentice criteria on a likelihood reduction factor. Although new in this context, the suggestion has been studied elsewhere and the measure of Alonso et al., as presented, requires some modification if it is to be useful in general situations. As it stands it depends upon the censoring mechanism, even when independent of the failure mechanism. This is, however, easily fixed. The measure suggested by Alonso et al. can be seen to fit in with a well-established theory so that, once corrected for the presence of censoring, it can be employed with confidence. Of particular interest is the wide availability of a standard SAS program producing a coefficient which can be immediately transformed to provide an estimate of the population quantity behind the Alonso et al. proposal.
Keywords:Explained randomness  Information gain  Kaplan–Meier estimator  Kullback–Leibler distance  Predictive ability  Proportional hazards model  Residuals  Surrogate endpoint
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