  Utilizing natural history data as external control plays an important role in
the clinical development of rare diseases, since placebo groups in double-blind
randomization trials may not be available due to ethical reasons and low
disease prevalence. This article proposed an innovative approach for utilizing
natural history data to support rare disease clinical development by
constructing reference centile charts. Due to the deterioration nature of
certain rare diseases, the distributions of clinical endpoints can be
age-dependent and have an absorbing state of zero, which can result in censored
natural history data. Existing methods of reference centile charts can not be
directly used in the censored natural history data. Therefore, we propose a new
calibrated zero-inflated kernel quantile (ZIKQ) estimation to construct
reference centile charts from censored natural history data. Using the
application to Duchenne Muscular Dystrophy drug development, we demonstrate
that the reference centile charts using the ZIKQ method can be implemented to
evaluate treatment efficacy and facilitate a more targeted patient enrollment
in rare disease clinical development.
