Evidence map›Paper›PMID 26258476›Full record

ArticlePloS one2015

Correlations of salivary biomarkers with clinical assessments in patients with cystic fibrosis.

Shuai Nie, Huaibin Zhang, Kathryn M Mayer, Frank G Oppenheim, Frédéric F Little, Jonathan Greenberg, Ahmet Z Uluer, David R Walt

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
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  6. Review
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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

8 authors at 3 institutions in 1 country.

Shuai NieDepartment of Chemistry, Tufts University, Medford, Massachusetts, United States of America.
Huaibin ZhangDepartment of Chemistry, Tufts University, Medford, Massachusetts, United States of America.
Kathryn M MayerDepartment of Chemistry, Tufts University, Medford, Massachusetts, United States of America.
Frank G OppenheimGoldman School of Dental Medicine, Boston University, Boston, Massachusetts, United States of America.
Frédéric F LittleSchool of Medicine, Boston University, Boston, Massachusetts, United States of America.
Jonathan GreenbergDivision of Respiratory Diseases, Boston Children's Hospital and Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
Ahmet Z UluerDivision of Respiratory Diseases, Boston Children's Hospital and Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
David R WaltDepartment of Chemistry, Tufts University, Medford, Massachusetts, United States of America.
Tufts University · USBoston University · USHarvard University · US

Funding

Microsensor Arrays for Saliva DiagnosticsU01DE017788 · NIDCR · TUFTS UNIVERSITY MEDFORD · PI WALT, DAVID R. · 2006 to 2010
$8.2M
NIDCR NIH HHS U01 DE017788PHS HHS 08UDE017788
6 · The paper itself

Abstract

rationaleMonitoring clinical disease status in cystic fibrosis frequently requires invasive collection of clinical samples. Due to its noninvasive collection process and direct anatomic relationship with the lower airway, saliva shows great potential as a biological fluid for cystic fibrosis monitoring.

objectivesTo measure the levels of multiple protein markers in human saliva supernatants and investigate the possibility of utilizing them to provide a more quantitative measure of disease state for use in research and monitoring of patients with cystic fibrosis clinically.

methodsWhole saliva samples were collected and processed from cystic fibrosis patients at two distinct time points (2010 and 2013) and measured by two separate platforms. In this cross sectional study, a convenience sample of 71 participants were recruited with samples measured by multiplexed fluorescence microarray (fiber microarray) and another 117 participant samples were measured by an automated, point-of-care, analyzer (SDReader) using a microsphere-based array via fluorescence sandwich immunoassay. For comparison, saliva from 56 and 50 healthy subjects were collected, respectively. The levels of six target proteins were quantified. Various demographic and clinical data, including spirometry, medical history, and clinicians' assessments were also collected from patients with cystic fibrosis on the day of saliva collection. MEASUREMENTS AND MAIN

resultsSimilar trends were observed with both platforms and compared with healthy subjects, cystic fibrosis patients had significantly elevated levels of VEGF, IP-10, IL-8, and EGF as well as lower levels of MMP-9 (P ≤ 0.005) using fiber microarray and significantly elevated levels of IP-10, IL-8 with lower levels of MMP-9 and IL-1β (P ≤ 0.02) using the SDReader. The levels of the six proteins correlated with each other significantly, and in some cases, biomarker levels could be used to differentiate between subgroups of patients with different clinical presentations. For example, IP-10 levels significantly correlated with FEV1 and disease severity (as evaluated by clinicians) with both platforms (P < 0.05).

conclusionsSignificant variations of the levels of six proteins in saliva supernatants, and the correlations of these levels with clinical assessments, demonstrated the potential of saliva for cystic fibrosis research and monitoring.

Indexed as

AdolescentAdultAgedBiomarkersChemokine CXCL10ChildCross-Sectional StudiesCystic FibrosisEpidermal Growth FactorFemaleHumansImmunoassayInterleukin-8Longitudinal StudiesMaleMatrix Metalloproteinase 9BiomarkersChemokine CXCL10CXCL10 protein, humanEpidermal Growth FactorInterleukin-8Matrix Metalloproteinase 9Vascular Endothelial Growth Factor AVEGFA protein, human

Identifiers

PMID26258476
PMCPMC4530931
OpenAlexW1807602519

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Registered trials

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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.