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Published on: November 2, 2013
Time to biochemical failure and prostate-specific antigen doubling time as surrogates for prostate cancer-specific
James W Denham1, Allison Steigler, Chantelle Wilcox
1School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia.
Time to biochemical failure (TTBF) and prostate-specific antigen doubling time (PSADT) show promise as surrogate endpoints for prostate cancer mortality. These measures may significantly shorten follow-up duration in clinical trials for prostate cancer treatments.
Area of Science:
- Oncology
- Clinical Trials
- Biostatistics
Background:
- Established surrogate endpoints for prostate cancer-specific mortality after curative treatment are lacking.
- This study investigated time to biochemical failure (TTBF) and prostate-specific antigen doubling time (PSADT) as potential surrogate endpoints.
Purpose of the Study:
- To evaluate TTBF and PSADT as surrogate endpoints for prostate cancer-specific mortality.
- To assess their ability to predict trial outcomes and meet established criteria for surrogate endpoints.
Main Methods:
- Utilized PSA and survival data from the TROG 96.01 trial involving 802 men with locally advanced prostate cancer.
- Patients received radiation alone or with 3 or 6 months of short-term androgen deprivation (STAD).
- Assessed surrogate candidates based on Prentice criteria and prediction of trial findings.
Main Results:
- Six months of STAD significantly reduced prostate cancer-specific mortality, while 3 months did not.
- PSADT met Prentice criteria, predicting trial findings with proportion of treatment effect ratios between 0.36 and 0.56.
- TTBF demonstrated superior prediction of trial findings and met Prentice criteria at multiple cutpoints, with ratios between 0.45 and 0.64.
Conclusions:
- TTBF and PSADT can serve as valuable surrogate endpoints for prostate cancer-specific mortality.
- These surrogate endpoints have the potential to significantly reduce follow-up periods in clinical trials.
- Further validation through multi-trial meta-analyses is recommended before widespread clinical adoption.
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