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

John S. Preisser, Sarah J. Marks, Anne E. Sanders, Aderonke A. Akinkugbe, James D. Beck

Research output: Contribution to journalArticle

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.

LanguageEnglish (US)
Pages283-289
Number of pages7
JournalJournal of clinical periodontology
Volume44
Issue number3
DOIs
StatePublished - Mar 1 2017

Fingerprint

Mouth
Chronic Periodontitis
Arteriolosclerosis
Oral Diagnosis
Tooth
Population

Keywords

  • clinical attachment level
  • epidemiology
  • partial-recording protocol
  • periodontitis
  • pocket depth

ASJC Scopus subject areas

  • Periodontics

Cite this

A new way to estimate disease prevalence from random partial-mouth samples. / Preisser, John S.; Marks, Sarah J.; Sanders, Anne E.; Akinkugbe, Aderonke A.; Beck, James D.

In: Journal of clinical periodontology, Vol. 44, No. 3, 01.03.2017, p. 283-289.

Research output: Contribution to journalArticle

Preisser, John S. ; Marks, Sarah J. ; Sanders, Anne E. ; Akinkugbe, Aderonke A. ; Beck, James D./ A new way to estimate disease prevalence from random partial-mouth samples. In: Journal of clinical periodontology. 2017 ; Vol. 44, No. 3. pp. 283-289
@article{9dfdb180763d47fa99df7632de2bef18,
title = "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 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.",
keywords = "clinical attachment level, epidemiology, partial-recording protocol, periodontitis, pocket depth",
author = "Preisser, {John S.} and Marks, {Sarah J.} and Sanders, {Anne E.} and Akinkugbe, {Aderonke A.} and Beck, {James D.}",
year = "2017",
month = "3",
day = "1",
doi = "10.1111/jcpe.12656",
language = "English (US)",
volume = "44",
pages = "283--289",
journal = "Journal of Clinical Periodontology",
issn = "0303-6979",
publisher = "Blackwell Munksgaard",
number = "3",

}

TY - JOUR

T1 - A new way to estimate disease prevalence from random partial-mouth samples

AU - Preisser,John S.

AU - Marks,Sarah J.

AU - Sanders,Anne E.

AU - Akinkugbe,Aderonke A.

AU - Beck,James D.

PY - 2017/3/1

Y1 - 2017/3/1

N2 - 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.

AB - 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.

KW - clinical attachment level

KW - epidemiology

KW - partial-recording protocol

KW - periodontitis

KW - pocket depth

UR - http://www.scopus.com/inward/record.url?scp=85007417141&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85007417141&partnerID=8YFLogxK

U2 - 10.1111/jcpe.12656

DO - 10.1111/jcpe.12656

M3 - Article

VL - 44

SP - 283

EP - 289

JO - Journal of Clinical Periodontology

T2 - Journal of Clinical Periodontology

JF - Journal of Clinical Periodontology

SN - 0303-6979

IS - 3

ER -