BMC Cancer 2004, 4 http://www.biomedcentral.com/1471-2407/4/9 Reasons for eligible women not providing a blood sample were that they could not be located, refused, or were too ill. The distribution of demographic and known breast cancer risk factors such as education, age at menarche, age at first live birth, age at breast cancer diagnosis, and year of birth were similar for participants and non-partici- pants. Unsurprisingly, women over age 80 in 1999 were less likely to provide a blood sample (63% did not pro- vide a blood sample compared to 48% for those under age 80). Regarding employment characteristics, more women who began to work in the 1950s tended to donate a sam- ple (57%) compared to women who began work after 1970 (43%). Interestingly, women who reported a first degree relative with breast cancer were less inclined to donate a sample (44% vs. 53% of those with no family breast cancer history). However, for selection bias to have caused spurious associations, the differential participation would also need to be related to genotype, a generally improbable scenario. Another limitation was that the kin-cohort method is less powerful for common genotypes, such that discrimination in risk is reduced because the "at risk" allele assignment among relatives becomes less precise with increasing prevalence. Statistical power, in the presence of results, is important to report, but these calculations for the kin-cohort method are computationally difficult. Since the statistical power to detect a two-fold increased or decreased effect in a case- control study with 190 breast cancer cases and 2240 con- trols for the homozygous variant genotype or the com- bined homozygous variant and heterozygous genotypes (for polymorphisms with rare homozygous variant geno- type) ranges from 0.30 to 0.99 (assuming a = 0.05, two- sided test, and the SNP frequency varies between 0.01 to 0.25), we conclude the statistical power of our kin-cohort study was even less because the genotypes of the relatives were not known with certainty and multiple genotypes were evaluated. Breast cancers among first degree family members were not independently confirmed by medical records, however we considered that breast cancer was likely to be accurately reported in family members of breast cancer cases [43] and possibly even more so because the cases are trained to work in the medical field as radiologic technologists. It is not possible to adjust for breast cancer risk factors among family members, although all of the relatives, by definition, have a first- degree relative with breast cancer. Relative risk estimates from the kin-cohort analyses should not be affected, how- ever absolute risk estimates could be inflated above the true values. There were a large number of comparisons evaluated (n = 46), such that one or more relationships reported here could be due solely to chance. Of all the hypotheses tested in Table 3, only those corresponding to the two p-values < 0.001 (BRCA2 N372H heterozygous vs. homozygous common and APEX D148E heterozygous vs. homozygous common) can be rejected while controlling the family- wise error rate, i.e. the probability of a least one false positive at 0.05 [18] or while controlling the false discov- ery rate, i.e. the expected proportion of false positives among the positives at 0.05 [19]. It has to be noted that the hypotheses tested may not be independent. For exam- ple, SNPs in the same gene may be in linkage disequilib- rium with each other and the risk to age 50 and risk to age 70 are presumably not independent. In this situation, our correction for multiple comparisons is likely overly con- servative. However, the associations that we found signif- icant at 0.05, but not 0.001, are certainly suggestive and serve as a means of hypothesis generation. Even though the kin-cohort design allows for the evaluation of gene- gene interactions [17], we did not perform such an analy- sis because of its very low statistical power and because of a lack of strong prior biologic hypotheses about the joint effect of SNPs in the genes studied. The study and the kin-cohort method have several strengths and advantages. The strengths are that risks are determined by the breast cancer experience in relatives, who are included whether living or deceased, reducing concerns of selection bias from recruiting prevalent cases. The study uses information on risk from a group outside the parent study, essentially providing a rationale for later testing using other designs and increases confidence if similar associations are observed in the upcoming case- control study. In addition, the breast cancer risks among female relatives are independent of specific occupational exposures (in this study, medical radiation exposure from work as a radiologic technologist) that were the reason for the cohort assembly and follow-up. A very important fea- ture is that a control series is not required, such that this method could easily be implemented among hospital- based cases. Once the genotypes are known for the index case series, risks for other common cancer outcomes (such as prostate, lung, or colon cancer) can readily be com- puted using family cancer history information collected at the time of blood sampling. Thus, the kin-cohort study provides additional independent supplemental data to an existing (or in progress) case-control study [16]. In summary, differences in breast cancer risk were associ- ated with XRCC1 R194W, XRCC1 R399Q, BRIP1 P919S, APEX D148E and BRCA2 N372H, and were suggestive for several others. Although HH homozygotes for the BRCA2 N372H SNP had approximately 30% greater odds of breast cancer compared to NN homozygotes, as had been consistently observed in two previous studies of breast cancer [40,41], this association was weak, and we observed a significantly decreased risk among heterozy- gotes, a relationship that had not been suggested previ- ously. We express caution in the interpretation of the Page 10 of 12 (page number not for citation purposes)