Abstract
Purpose Reducing colorectal cancer (CRC) incidence and mortality through early detection would improve efficacy if targeted. A CRC risk-prediction model incorporating personal, family, genetic and environmental risk factors could enhance prediction.
Methods We developed risk-prediction models using population-based CRC cases (N=4,445) and controls (N=3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). A familial risk profile (FRP) was calculated to summarize individuals’ risk based on their CRC family history, family structure, germline mutation probability in major susceptibility genes, and a polygenic component. Using logistic regression, we developed risk models including individuals’ FRP or a binary CRC family-history (FH), and risk factors collected at recruitment. Model validation used follow-up data for population-(N=12,052) and clinic-based (N=5,584) relatives with no cancer history at recruitment, assessing calibration (E/O) and discrimination (AUC).
Results The E/O (95% confidence interval [CI]) for FRP models for population-based relatives were 1.04 (0.74-1.45) and 0.86 (0.64-1.20) for men and women, and for clinic-based relatives 1.15 (0.87-1.58) and 1.04 (0.76-1.45). The age-adjusted AUC (95% CI) for FRP models in population-based relatives were 0.69 (0.60-0.78) and 0.70 (0.62-0.77), and for clinic-based relatives 0.77 (0.69-0.84) and 0.68 (0.60-0.76). The incremental values of AUC (95% CI) for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) and 0.10 (0.04-0.16), and for clinic-based relatives 0.11 (0.05-0.17) and 0.11 (0.06-0.17).
Conclusion The FRP-based model and FH-based model calibrate well in both settings. The FRP-based model provided better risk-prediction and discrimination than the FH-based model. A detailed family history may be useful for targeted risk-based screening and clinical management.
Footnotes
↵* Joint last author
Presented at AACR special conference “Improving Cancer Risk Prediction for Prevention and Early Detection” 2016, “Does a comprehensive family history of colorectal cancer improve risk prediction?”
Funding: This work was supported by (R01 CA170122) from the National Cancer Institute, National Institutes of Health (NIH) and through cooperative agreements with the following Colon Cancer Family Registry (CCFR) centers: Australasian Colorectal Cancer Family Registry (U01/U24 CA097735), Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (U01/U24 CA074800), Ontario Familial Colorectal Cancer Registry (U01/U24 CA074783), Seattle Colorectal Cancer Family Registry (U01/U24 CA074794), and USC Consortium Colorectal Cancer Family Registry (U01/U24 CA074799).
Seattle CCFR research was also supported by the Cancer Surveillance System of the Fred Hutchinson Cancer Research Center, which was funded by Control Nos. N01-CN-67009 and N01-PC-35142 and Contract No. HHSN2612013000121 from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute. Additional support included grants from the National Institutes of Health UM1/U01 CA167551, K05 CA152715 (to PAN) and R01 GM085047 (to YZ), and through the Centre for Research Excellence grant APP1042021 and Program Grant APP1074383 from the National Health and Medical Research Council (NHMRC), Australia. MAJ is a NHMRC Senior Research Fellow. AKW is a NHMRC Early Career Fellow. JLH is a NHMRC Senior Principal Research Fellow.
Notes: The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; and the decision to submit the manuscript for publication.
The authors have no conflicts of interest to disclose.