Evidence map›Paper›PMID 33356775›Full record

ArticleJournal of dental research2021

Oral Microbiota Composition Predicts Early Childhood Caries Onset.

A Grier, J A Myers, T G O'Connor, R G Quivey, S R Gill, D T Kopycka-Kedzierawski

Open access · greenAbstract read
In one paragraph

Article in Journal of dental research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
7.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 2 syntheses or guidelines pooled it, 113 citations in OpenAlex.

  1. Pooled it
  2. Meta-Analysis Using NGS Data: TheFrontiers in oral health · 2021
    Pooled it
  3. Article
  4. Review
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  10. [Comparative analysis of microbial communities in different oral ecological niches of preschool children].Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2026
    Article
  11. Review
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  15. Multicohort external validation ofFrontiers in cellular and infection microbiology · 2026
    Article
  16. Draft genome sequences of sixMicrobiology resource announcements · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

A GrierGenomics Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
J A MyersGenomics Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
T G O'ConnorDepartment of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
R G QuiveyDepartment of Microbiology and Immunology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
S R GillGenomics Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
D T Kopycka-KedzierawskiCenter for Oral Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.ORCID 0000-0003-0798-6805
University of Rochester · US

Funding

Oxidative Stress Responses in Oral StreptococciR01DE013683 · NIDCR · UNIVERSITY OF ROCHESTER · PI QUIVEY, ROBERT G · 2000 to 2019
$6.2M
Integrating Oral Biology and Behavioral and Social Mechanisms for ECC OnsetR01DE024985 · NIDCR · UNIVERSITY OF ROCHESTER · PI KOPYCKA-KEDZIERAWSKI, DOROTA T. · 2015 to 2019
$3.5M
NIDCR NIH HHS R01 DE013683NIDCR NIH HHS R01 DE024985
6 · The paper itself

Abstract

As the most common chronic disease in preschool children in the United States, early childhood caries (ECC) has a profound impact on a child's quality of life, represents a tremendous human and economic burden to society, and disproportionately affects those living in poverty. Caries risk assessment (CRA) is a critical component of ECC management, yet the accuracy, consistency, reproducibility, and longitudinal validation of the available risk assessment techniques are lacking. Molecular and microbial biomarkers represent a potential source for accurate and reliable dental caries risk and onset. Next-generation nucleotide-sequencing technology has made it feasible to profile the composition of the oral microbiota. In the present study, 16S ribosomal RNA (rRNA) gene sequencing was applied to saliva samples that were collected at 6-mo intervals for 24 mo from a subset of 56 initially caries-free children from an ongoing cohort of 189 children, aged 1 to 3 y, over the 2-y study period; 36 children developed ECC and 20 remained caries free. Analyses from machine learning models of microbiota composition, across the study period, distinguished between affected and nonaffected groups at the time of their initial study visits with an area under the receiver operating characteristic curve (AUC) of 0.71 and discriminated ECC-converted from healthy controls at the visit immediately preceding ECC diagnosis with an AUC of 0.89, as assessed by nested cross-validation.

Indexed as

Dental CariesMicrobiotaChild, PreschoolDental Caries SusceptibilityHumansMicrococcaceaeQuality of LifeReproducibility of ResultsRNA, Ribosomal, 16SVeillonellaRNA, Ribosomal, 16S16S rRNAbiomarkersdental cariesmachine learningreceiver operating characteristic curverisk assessment

Identifiers

PMID33356775
PMCPMC8142088
OpenAlexW3117347091

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.