Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors
Andrew Lee, Xin Yang, Jonathan P. Tyrer, Aleksandra Gentry‐Maharaj, Andy Ryan, Nasim Mavaddat, Alex Cunningham, Tim Carver, Stephanie Archer, Goska Leslie, Jatinder Kalsi, Faiza Gaba, Ranjit Manchanda, Simon A. Gayther, Susan J. Ramus, Fiona M Walter, Marc Tischkowitz, Ian Jacobs, Usha Menon, Douglas F. Easton, Paul D.P. Pharoah, Antonis C. Antoniou
Abstract
Background Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention. Methods We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in BRCA1 , BRCA2 , RAD51C , RAD51D and BRIP1 , a Polygenic Risk Score (PRS) of arbitrary size, the effects of RFs and explicit family history (FH) using a synthetic model approach. The PRS, PV and RFs were assumed to act multiplicatively. Results Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%–10.3%. Based on the combined risk distribution, 33% of RAD51D PV carriers are expected to have a lifetime EOC risk of less than 10%. RFs provided the widest distribution, followed by the PRS. In an independent partial model validation, absolute and relative 5-year risks were well calibrated in quintiles of predicted risk. Conclusion This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool ( www.canrisk.org ).