Oxford Pooling Project: Prostate (endogenous hormones and nutritional biomarkers)
Principal Investigator
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
2010-0320
Initial CDAS Request Approval
Jan 31, 2011
Title
Oxford Pooling Project: Prostate (endogenous hormones and nutritional biomarkers)
Summary
The Endogenous Hormones and Prostate Cancer Collaborative Group (EHPCCG) was established in 2004, with the aim of collating the worldwide prospective data and to perform collaborative re-analyses on the relationship between circulating sex hormones, insulin-like growth factors (IGFs) and prostate cancer risk. The first results (based on almost 4,000 cases) were published in 2008 showing no association between circulating sex hormones and prostate cancer risk. An increased risk of prostate cancer was observed with increasing levels of IGF-I. Since then, 2000 more cases of cancer have become available worldwide. PLCO was not included in the earlier analyses but has since published on hormones and prostate cancer risk. EHPCCG has invited PLCO to participate in a new effort to update the information on sex hormones and IGFs in relation to prostate cancer and to include new data on nutritional biomarkers. The aim of this pooling project is to provide a unified analysis of the published worldwide prospective data to further our understanding of the relationships of endogenous hormones and nutritional biomarkers with risk of prostate cancer. To date, PLCO has published on the relationship between prostate cancer and hormones and nutritional biomarkers (including testosterone, IGF-I, SHBG, carotenoids, tocopherols, retinol, vitamin D and selenium). We request permission to participate in this collaborative effort and to share these published data with the EHPCCG.
Aims
Aims of pooling the data
The aims of pooling the data are to:
1. Use uniform methods to provide more precise estimates of the relative risks for each individual biomarker.
2. Investigate the relationship of time between blood collection and diagnosis with risk.
3. Identify which biomarker is most closely associated with risk by allowing the biomarkers to be mutually adjusted.
4. Examine the relationships between subject characteristics and biomarker concentrations in a cross-sectional manner.
5. Examine the relative risks in subgroups by stage and grade of the cancer and other factors, as appropriate.
Collaborators
Kevin Dodd (DCP, NCI)
Ann Hsing (DCEG)