Does the Prentice criterion validate surrogate endpoints?

Stat Med. 2004 May 30;23(10):1571-8. doi: 10.1002/sim.1780.


Randomized Phase II or Phase III clinical trials that are powered based on clinical endpoints, such as survival time, may be prohibitively expensive, in terms of both the time required for their completion and the number of patients required. As such, surrogate endpoints, such as objective tumour response or markers including prostate specific antigen or CA-125, have gained widespread popularity in clinical trials. If an improvement in a surrogate endpoint does not itself confer patient benefit, then consideration must be given to the extent to which improvement in a surrogate endpoint implies improvement in the true clinical endpoint of interest. That this is not a trivial issue is demonstrated by the results of an NIH-sponsored trial of anti-arrhythmic drugs, in which the ability to correct an irregular heart beat not only did not correspond to a survival benefit but in fact led to excess mortality. One approach to the validation of surrogate endpoints involves ensuring that a valid between-group analysis of the surrogate endpoint constitutes also a valid analysis of the true clinical endpoint. The Prentice criterion is a set of conditions that essentially specify the conditional independence of the impact of treatment on the true endpoint, given the surrogate endpoint. It is shown that this criterion alone ensures that an observed effect of the treatment on the true endpoint implies a treatment effect also on the surrogate endpoint, but contrary to popular belief, it does not ensure the converse, specifically that the observation of a significant treatment effect on the surrogate endpoint can be used to infer a treatment effect on the true endpoint.

MeSH terms

  • Antineoplastic Agents / therapeutic use
  • Biomarkers*
  • Clinical Trials, Phase II as Topic / methods*
  • Clinical Trials, Phase III as Topic / methods*
  • Humans
  • Models, Statistical*
  • Neoplasms / drug therapy
  • Predictive Value of Tests
  • Treatment Outcome


  • Antineoplastic Agents
  • Biomarkers