In using second primary cancers for epidemiologic studies of cancer risk, the fundamental premise is that any risk factor that increases the risk of the cancer under study in people previously unaffected with the disease will also increase the risk of a second primary among cancer survivors. Our results support this hypothesis for genetic risk factors associated with breast cancer. This hypothesis assumes there is nothing unique or etiologically distinct about the occurrence of double malignancies (i.e. that they represent two independent occurrences of the disease), and two occurrences will typically occur in people at high risk. Given this presumption, we have explored the further hypothesis that the degree of elevation of risk for any risk factor is similar (on a multiplicative scale) in the setting of cancer survivors to what is observed in the general population. Our results suggest that on the relative scale (ie using relative risks as opposed to, say, risk differences) the risk elevation among cancer survivors is typically similar, although with possible attenuation in some cases. Of the 4 genes investigated, only one (BRCA1) had a summary relative risk in the second cancers design substantially smaller than the summary estimate from the case-control studies. In contrast, the 3 “enriched” studies of BRCA1 produced a summary odds ratio higher than expected (62). A modest attenuation of the relative risk is consistent with an investigation of known risk factors for melanoma in a similar setting.21
The possibility of such attenuation has implications for statistical power. Our calculations show that studies involving second primaries have major advantages in terms of statistical power if the relative risk can be considered to be constant. Attenuation of the relative risk can alter this balance of power, depending on the magnitude of the attenuation. However, studies that compare second primaries with population controls have power advantages even with attenuation, and across the spectrum of risk factor characteristics.
Our results provide only an imprecise investigation of these phenomena. Many of the individual studies in the literature are vague with respect to criteria for case and control selection. Just as with conventional case-control studies, the other two designs would ideally be constructed using population-based sampling of both cases and controls. Also, , these designs have practical merit only for selected cancer sites, i.e. those for which second primaries in the same organ type are common and clearly distinguishable from metastatic lesions. This includes cancers of the breast, lung, colon-rectum and skin, but excludes rare cancers and those for which much of the primary site is typically removed by surgery, e.g. prostate cancer. Also, multiple primaries are common for head and neck cancers, but reliable discrimination between multiple primaries and superficial metastases is complicated.
In what circumstances might the relative risk of any risk factor be different in cancer survivors than in the general population? One possibility (as just discussed) is diagnostic error whereby metastases are misdiagnosed as second primaries. There is a substantial literature of studies evaluating this issue, but the consensus for breast cancer is that most contralateral occurrences are indeed independent occurrences of the disease.22–24
Recent studies support this conclusion for melanoma, but suggest that mis-diagnoses may be common for multiple primary lung cancers.25–27
Another possibility is interaction with treatment. Common treatments for primary breast cancer include agents such as tamoxifen that reduce the incidence of the disease by 50%. If the sub-types of tumors that are prevented by treatment are associated with a genetic risk factor then the impact of this risk factor overall will be different in second primaries compared with first primaries. These influences could affect the relative risk, but they are unlikely to affect the detectability of any risk factor. Another possibility is simply that the relative effect of individual risk factors diminishes as the background risk increases. Indeed studies showing an approximately constant risk in BRCA1/2 carriers by age would seem to support this thesis, in that the “background” risk increases markedly with age.6
A final possibility is that the variant may be associated with case survival. If so, the odds ratio could be either attenuated or enhanced, depending on the direction of this association.
Many investigators studying genetic risk factors elect to “enrich” the case selection by restricting attention to cases with a family history of the disease. This approach is similarly designed to increase power by genetically enriching the case base. These studies are rarely population-based, and it is more difficult to make a precise estimate of the extent to which the power is likely to be enhanced. Interestingly, Antoniou and Easton28
have studied this issue using a polygenic model with a normally distributed polygenic component estimated from a large population-based study; they conclude that if one restricts case selection to breast cancer cases with an affected mother and sister, the study will deliver increased power of a similar order of magnitude to using cases with bilateral breast cancer. Of course, a consideration in the use of any “enriched” design (whether using cases with multiple primary or cases with a strong family history of cancer) is the added difficulty in identifying and recruiting these enriched cases. Our statistical power comparisons assume equivalent sample sizes but do not address the relative ease by which these can be obtained in practice.
The conventional case-control study has a long history in cancer epidemiology. The gold standard is the population-based design, whereby incident cases from a defined population are compared with controls randomly selected from the same population. However, this ideal is increasingly challenged by the difficulty in enrolling population controls with a high response rate.29
While it is suitable for relatively common risk factors, the design is problematic for important but rare risk factors (ie those that confer a high relative risk). An enriched design based on second primaries offers an attractive alternative in that it provides substantial power advantages across a broad spectrum of risk-factor prevalences and relative risks. However, like the conventional approach, it requires population controls with the attendant difficulties. An enriched design may be especially attractive for genome-wide association studies of candidate SNPs due to its power advantages for a broad spectrum of SNP prevalences. The second-cancers design, by its case-only nature, promises higher participation rates, especially when biologic samples are required (as for genetic analysis). This design has more statistical power than the conventional design for rare risk factors, although its advantages can be muted if there is risk attenuation. Its power is competitive with that of the enriched design for very rare, strong risk factors. This is likely to be an increasingly important area as knowledge of strong genetic risk factors emerges. Major genes such as BRCA1 and BRCA2 possess hundreds of individual variants, many extremely rare, and consequently individual studies require a high level of power to distinguish harmful rare variants from the harmless ones.30
In summary, our study provides strong empirical evidence that studies of second primary cancers are capable of detecting cancer risk factors, in many circumstances with greatly improved power. This underused resource could be employed to facilitate the on-going search for cancer risk factors.