The potential value of sibling controls compared with population controls for association studies of lifestyle-related risk factors: an example from the Breast Cancer Family Registry

Milne RL, John EM, Knight JA, Dite GS, Southey MC, Giles GG, Apicella C, West DW, Andrulis IL, Whittemore AS, Hopper JL (2011) The potential value of sibling controls compared with population controls for association studies of lifestyle-related risk factors: an example from the Breast Cancer Family Registry. Int J Epidemiol 40:1342-1354

BACKGROUND: A previous Australian population-based breast cancer case-control study found indirect evidence that control participation, although high, was not random. We hypothesized that unaffected sisters may provide a more appropriate comparison group than unrelated population controls. METHODS: Three population-based case-control-family studies of breast cancer in women of white European origin were carried out by the Australian, Ontario and Northern California sites of the Breast Cancer Family Registry. We compared risk factors between 3643 cases, 2444 of their unaffected sisters and 2877 population controls and conducted separate case-control analyses based on population and sister controls using unconditional multivariable logistic regression. RESULTS: Compared with sister controls, population controls were more highly educated, had an earlier age at menarche, fewer births, their first birth at a later age and their last birth more recently. The established breast cancer associations detected using sister controls, but not detected using population controls, were decreasing risk with each of later age at menarche, more births, younger age at first birth and greater time since last birth. CONCLUSIONS: Since participation of population controls might be unintentionally related to some risk factors, we hypothesize that sister controls could provide more valid relative risk estimates and be recruited at lower cost. Given declining study participation by population controls, this contention is highly relevant to epidemiologic research.