Clustering of Contiguous Age Groups

Examining trends in age-adjusted rates for all ages combined may mask important differences in trends for specific age groups. One way of selecting age groupings for age-specific analyses is to use knowledge of how specific cancers progress or differ by age, e.g. separating trends for female gynecologic cancers and female breast cancer into pre- and post-menopausal groups.  Absent a strong substantive reason to form specific age groupings, an alternative method is to use a statistical data-dependent algorithm to partition the age groups into clusters of contiguous age groupings for which cancer (or other disease) incidence or mortality rates follow the same trend, while at the same time separating clusters where the trends differ.  An algorithm for determining optimized clusters and to summarize cluster characteristics using joinpoint regression models is being added to the Joinpoint software using the methodology described in Kim et al., Stat Med, 2014.  The expected release date is January 2026.  Please check back for further updates on this release. 

Kim HJ, Luo J, Kim J, Chen HS, Feuer EJ. Clustering of trend data using joinpoint regression models. Stat Med 2014; 33: 4087-103.