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Cancer J. 2004 Nov-Dec;10(6):357-67.

Designing a randomized phase I/II prostate cancer chemoprevention trial using 1alpha-hydroxy-24-ethyl-cholecalciferol, an analogue of vitamin D3.

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Department of Radiation Oncology, School of Medicine, University of California at Davis, One Shields Avenue, Davis, California, USA.


Prostate cancer continues to be a significant source of morbidity and mortality among older men. One possible means of reducing its impact on overall health and vitality is via cancer chemoprevention, both in the population that is unaffected but at some risk and in those who have undergone some form of curative therapy after the onset of the disease. Chemoprevention holds significant promise, but large phase III clinical trials evaluating chemopreventive agents in prostate cancer can require vast numbers of enrollees and require the commitment of significant financial resources and time before any therapeutic benefit may become apparent. One technique to shorten the time required for chemoprevention clinical trials is to use surrogate endpoint biomarkers in place of the currently used actual endpoints of cancer incidence or survival. The validation of such surrogate endpoint biomarkers will require small, well-designed phase I and/or II trials to accumulate data on the modulation of the surrogate biomarkers and the endpoints of cancer incidence or survival by the chemopreventive agent. Careful statistical correlation and clinical validation of the data will then allow us to justify the use such surrogates in place of the actual endpoint in large, randomized trials, potentially shortening trial duration, improving financial efficiency, and accelerating approval of the chemopreventive agent. To that end, we first review the theoretical construct of cancer chemoprevention trials with particular reference to prostate cancer. We thereafter describe the design of a small, randomized, double-blinded, placebo-controlled phase I/II clinical trial of an analogue of vitamin D, vitamin D5, which we believe could serve as a model for data accumulation on surrogate biomarkers and correlation with other clinical endpoints.

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