A new way to estimate disease prevalence from random partial-mouth samples.

ABSTRACT:

Aim

Standard partial-mouth estimators of chronic periodontitis (CP) that define an individual's disease status solely in terms of selected sites underestimate prevalence. This study proposes an improved prevalence estimator based on randomly sampled sites and evaluates its accuracy in a well-characterized population cohort.

Methods

Importantly, this method does not require determination of disease status at the individual level. Instead, it uses a statistical distributional approach to derive a prevalence formula from randomly selected periodontal sites. The approach applies the conditional linear family of distributions for correlated binary data (i.e. the presence or absence of disease at sites within a mouth) with two simple working assumptions: (i) the probability of hav

SUBMITTER: Preisser JS 

PROVIDER: S-EPMC5328941 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature