Methods for testing familial aggregation of diseases in population-based samples: application to Hodgkin lymphoma in Swedish registry data.

Abstract

We use data on lymphoma in families of Hodgkin lymphoma (HL) cases from the Swedish Family Cancer Database (Hemminki et al. 2001) to illustrate survival methods for detecting familial aggregation in first degree relatives of case probands compared to first degree relatives of control probands, from registries that permit sampling of all cases. Because more than one case may occur in a given family, the first degree relatives of case probands are not necessarily independent, and we present procedures that allow for such dependence. A bootstrap procedure also accommodates matching of case and control probands by resampling the matching clusters, defined as the combined set of all first degree relatives of the matched case and control probands. Regarding families as independent sampling units leads to inferences based on "sandwich variance estimators" and accounts for dependencies from having more than one proband in a family, but not for matching. We compare these methods in analysis of familial aggregation of HL and also present simulations to compare survival analyses with analyses of binary outcome data.