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

TitleA new way to estimate disease prevalence from random partial-mouth samples.
Publication TypeJournal Article
Year of Publication2017
AuthorsPreisser JS, Marks SJ, Sanders AE, Akinkugbe AA
Secondary AuthorsBeck JD
JournalJ Clin Periodontol
Volume44
Issue3
Pagination283-289
Date Published2017 03
ISSN1600-051X
KeywordsAged, Chronic Periodontitis, Female, Humans, Male, Middle Aged, Mouth, Prevalence, Specimen Handling
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 having disease is the same across all sites; and (ii) the correlation of disease status is the same for all pairs of sites within the mouth.

RESULTS: Using oral examination data from 6793 participants in the Arteriolosclerosis Risk in Communities study, the new formula yields CP prevalence estimates that are much closer than standard partial mouth estimates to full mouth estimates.

CONCLUSIONS: Resampling of the cohort shows that the proposed estimators give good precision and accuracy for as few as six tooth sites sampled per individual.

DOI10.1111/jcpe.12656
Alternate JournalJ Clin Periodontol
PubMed ID27883200
PubMed Central IDPMC5328941
Grant ListHHSN268201100012C / HL / NHLBI NIH HHS / United States
HHSN268201100009I / HL / NHLBI NIH HHS / United States
R01 DE011551 / DE / NIDCR NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
HHSN268201100005G / HL / NHLBI NIH HHS / United States
HHSN268201100008I / HL / NHLBI NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
HHSN268201100011I / HL / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
HHSN268201100005I / HL / NHLBI NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
HHSN268201100007I / HL / NHLBI NIH HHS / United States