Evidence mapPaperPMID 42345901Full record

ReviewBiosensors2026

Extraoral Detection of Biomarkers and Pathogens in Saliva: Comprehensive, Panoramic Review.

Aigerim Dyussupova, Aisha Ilyas, Aigerim Boranova, Yegor Shevchenko, Xeniya Terzapulo, Ansar Seitkali, Abduzhappar Gaipov, Olena Filchakova, Rostislav Bukasov

Abstract readReview
In one paragraph

Review in Biosensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Aigerim DyussupovaDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.ORCID 0000-0002-7326-6569
Aisha IlyasDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.ORCID 0000-0002-7870-9947
Aigerim BoranovaDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.
Yegor ShevchenkoDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.ORCID 0000-0003-3498-1364
Xeniya TerzapuloDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.ORCID 0009-0002-4490-2551
Ansar SeitkaliDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.ORCID 0009-0002-1170-5113
Abduzhappar GaipovDepartment of Medicine, School of Medicine, Nazarbayev University, 010000 Astana, Kazakhstan.ORCID 0000-0002-9844-8772
Olena FilchakovaDepartment of Biology, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.
Rostislav BukasovDepartment of Chemistry, School of Sciences and Humanities, Nazarbayev University, 010000 Astana, Kazakhstan.ORCID 0000-0002-7060-1632

Funding

Nazarbayev University Nazarbayev University Collaborative Research Program, 2024-2026, funding reference 211123CPR1603
6 · The paper itself

Abstract

Human saliva is a heterogeneous bodily fluid with a complex composition, which contains antibodies, proteins, and viruses, making it applicable in clinical diagnosis. There are several advantages of the analysis of saliva samples over other biofluids, including a non-invasive and simple collection procedure for extraoral detection. Biomarker or pathogen detection in saliva can be performed with various methods: mass spectrometry, PCR, ELISA, electrochemical, and optical methods such as fluorescence, SPR, and SERS. The early detection of cancer and other disease biomarkers, as well as infectious agents, can be crucial for effective treatment and minimization of mortality from those diseases. The following paper reviews extraoral detection techniques to identify the most sensitive methods for diagnosing early and asymptomatic patients. The LODs collected and tabulated from 149 analytical papers, alongside the sensitivity, specificity, and sometimes the area under the curve (AUC) tabulated from 118 clinical studies, have all become parameters for the comparative quantitative analysis. Based on the limited but substantial number of analytical studies on the detection of cortisol in saliva (29), the electrochemical platforms demonstrated the highest sensitivity, with a geometric mean LOD of 11 pM. Within these methods, voltametric ones showed the best performance with 6 pM geometric mean LOD. Electrochemical techniques are then followed by immunoassay- and mass spectrometry-based platforms, with corresponding geometric average LOD values of 39.1 and 171 pM, respectively. However, clinical outcomes are at least as meaningful as LOD values. In terms of clinical analysis, ELISA and direct-SERS outperformed other methods, achieving balanced accuracy of approximately 87% and AUC values of 0.96 for direct SERS and 0.86 for ELISA. MS and PCR followed closely, with balanced accuracies around 84%. While the direct SERS is not yet widespread in clinical applications, its potential can be forged if the standardization issue is addressed.

Indexed as

BiomarkersBiosensing TechniquesSalivaElectrochemical TechniquesHumansBiomarkersaccuracybacteriacancer biomarkerscortisollimit of detection (LOD)salivasensitivityspecificityviruses

Identifiers

PMID42345901
PMCPMC13297210

What Socratic holds

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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 Socratic graph.