Evidence map›Paper›PMID 35315584›Full record

SynthesisCancer medicine2022

Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta-analysis.

Maryam Koopaie, Sajad Kolahdooz, Mahnaz Fatahzadeh, Soheila Manifar

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
5.3field-weighted citation impact, top 3% 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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 46 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 2 countries.

Maryam KoopaieTehran University of Medical Sciences, Tehran, Iran.ORCID 0000-0002-9999-1443
Sajad KolahdoozUSERN, Tehran University of Medical Sciences, Tehran, Iran.
Mahnaz FatahzadehDepartment of Diagnostic Sciences, Rutgers School of Dental Medicine, Newark, New Jersey, USA.
Soheila ManifarTehran University of Medical Sciences, Tehran, Iran.
Motamed Cancer Institute · IRRutgers, The State University of New Jersey · USTehran University of Medical Sciences · IRUniversal Scientific Education and Research Network · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSalivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

methodsWe conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

resultsOur systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.

conclusionSaliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

Indexed as

Breast NeoplasmsAdultBiomarkersFemaleHumansMiddle AgedOdds RatioROC CurveSensitivity and SpecificityBiomarkersbiomarkerbreast cancerdiagnosismeta-analysissaliva

Identifiers

PMID35315584
PMCPMC9249990
OpenAlexW4220942290

What OpenQuestion holds

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LicenceCC BY
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.