  Many countries have established population-based biobanks, which are being
used increasingly in epidemiolgical and clinical research. These biobanks offer
opportunities for large-scale studies addressing questions beyond the scope of
traditional clinical trials or cohort studies. However, using biobank data
poses new challenges. Typically, biobank data is collected from a study cohort
recruited over a defined calendar period, with subjects entering the study at
various ages falling between $c_L$ and $c_U$. This work focuses on biobank data
with individuals reporting disease-onset age upon recruitment, termed prevalent
data, along with individuals initially recruited as healthy, and their disease
onset observed during the follow-up period. We propose a novel cumulative
incidence function (CIF) estimator that efficiently incorporates prevalent
cases, in contrast to existing methods, providing two advantages: (1) increased
efficiency, and (2) CIF estimation for ages before the lower limit, $c_L$.
