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Approved research

Development and validation of risk prediction model for prostate cancer

Principal Investigator: Professor Kenneth Muir
Approved Research ID: 5339
Approval date: September 1st 2014

Lay summary

Prostate cancer is more suitable to risk based surveillance as the PSA test alone is not optimal for assessing the likelihood of having prostate cancer or distinguishing aggressive cancers from indolent ones. Therefore the evidence for PSA based population screening or surveillance is not supported. Risk based prostate cancer detection in the community offers potential significant improvements in performance over the current PSA threshold based approach. This proposal therefore aims to build a risk calculator for prostate cancer by utilising data on lifestyle/environmental factors, biomarkers and genetic markers. This research fits with the UK Biobank purpose in that it is in public interest. We will build one or more optimised risk prediction models fit for predicting risk in both familial and sporadic cases (including biomarkers,genetic markers, lifestyle/environmental factors collected within the male cohort). Familial cases are defined as prostate cancer cases with first degree relatives affected with prostate cancer. We will also explore whether breast, ovarian and ?any cancer? in first degree relatives also add to the prediction models. Both cohort and nested case control methods will be used. We will build a risk calculator for prostate cancer by utilising data on lifestyle/environmental factors, biomarkers (not samples) and genetic markers (not samples). We will require data from the whole male cohort including full genotyping data (not samples) and biomarker data (not samples) once available. We would like to receive the baseline and cancer registry dataset so we can work on prediction models that include the nonĀ­genetic markers, and in due course the genotyping data (not samples)and biomarker data (not samples) once they become available.