Risk Model Could Offer Personalized Prostate Cancer Risk Estimates

Researchers have developed a new prostate cancer risk model that has high discrimination and good calibration for the prediction of incident prostate cancers.

“Prostate cancer exhibits marked familial aggregation and has one of the highest heritabilities of any common cancer,” study researchers wrote in Journal of Clinical Oncology. “This is explained in part by rare pathogenic variants (PVs) in BRCA2, HOXB13, and possibly BRCA1, which are associated with moderate-to-high prostate cancer risks, together with several hundred commoner variants conferring lower risks, identified through genome-wide association studies.”

The model was developed using data from 16,633 prostate cancer families from the United Kingdom from 1993 to 2017 from the UK Genetic Prostate Cancer Study. The most economical model included effects of PVs from BRCA2, HOXB13, and BRCA1 and a polygenic score on the basis of 268 common low-risk variants.

Average population risk was 16% by age 85. The model-predicted risk was 54% for BRCA2, 29% for HOXB1 G84E, and 17% for BRCA1. On the basis of familial history alone, men with a relative diagnosed by age 50 had a risk of 42% when the father was affected and 43% when a brother was affected.

The model was externally validated in 170,850 unaffected men recruited from 2006 to 2010 to the UK Biobank prospective cohort study. The researchers acknowledged that the prostate cancer risks in these participants “were higher than corresponding year- and age-specific population incidences,” which could be explained by a higher observed socioeconomic status and the fact that PSA testing varies by socioeconomic status.

In the validation cohort, the model discriminated well between unaffected men and men with incident prostate cancers diagnosed within 5 years (C-index, 0.790; 95% CI, 0.783-0.797) and 10 years (C-index, 0.772; 95% CI, 0.768-0.777).

The majority (86.3%) of prostate cancers diagnosed within 10 years were captured among the half of men with the highest predicted risks, demonstrating that the model “might facilitate the identification of men who could benefit from screening and other early detection interventions.”

“The model will be beneficial for counselling of men in cancer family clinics, and can form the basis for future research evaluating risk-stratified population screening approaches,” the researchers concluded.