A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium.

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Cost-effectiveness of surveillance programs for families at high and moderate risk of hereditary non-polyposis colorectal cancer.

OBJECTIVES: Surveillance programs are recommended to both families at high risk (Amsterdam-positive families with known- and unknown mutation) and moderate risk (families not fulfilling all Amsterdam criteria) of colorectal cancer (CRC). Cost-effectiveness has so far only been estimated for the group at high risk. The aim of the present study is to determine cost-effectiveness of surveillance programs where families at both high and moderate risk of HNPCC participate. METHODS: A decision analytic model (Markov model) is developed to assess surveillance programs where families at high and moderate risk of HNPCC are offered surveillance from age 25 and age 45, respectively. The model includes costs for all families referred to genetic counseling, including genetic risk assessment, mutation analysis, and surveillance in relevant families with or without known mutation, plus the costs related to any surgical treatment. The risk of metachronous CRC is also modeled. RESULTS: Incremental costs per life year gained are estimated to be euro 980 when families at both high and moderate risk of HNPCC undergo surveillance (euro 508 for high risk and euro 1600 for moderate risk) and euro 1947 when the moderate risk group is evaluated genetically but not offered surveillance. Sensitivity analysis showed these findings to be robust, although cost-effectiveness can be improved in cases of more conservative referrals to genetic counseling. CONCLUSIONS: The result for high risk families confirms the findings in similar studies. Somewhat surprisingly, cost-effectiveness improves when surveillance of the moderate risk groups are included in the decision model.