Evidence map›Paper›PMID 35633529›Full record

SynthesisAsian Pacific journal of cancer prevention : APJCP2022

Diagnostic Accuracy of Salivary Biomarkers in Detecting Early Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis.

Amar Kumar Shaw, Vikram Garcha, Vittaldas Shetty, Vineet Vinay, Ketaki Bhor, Kadambari Ambildhok, Purnima Karande

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Asian Pacific journal of cancer prevention : APJCP, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 6 pooled it
6.5field-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

21 citing papers in PubMed, 6 syntheses or guidelines pooled it, 34 citations in OpenAlex.

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  10. Comparative diagnostic accuracy of ChatGPT models in salivary gland disease: a multimodal vignette-based evaluation.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
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  17. Oral Squamous Cell Carcinoma: Focus on Biomarkers for Screening.Journal of dentistry (Shiraz, Iran) · 2024
    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

7 authors at 2 institutions in 1 country.

Amar Kumar ShawDepartment of Public Health Dentistry, Sinhgad Dental College and Hospital, Pune 411041, Maharashtra, India.ORCID 0000-0002-7785-9644
Vikram GarchaDepartment of Public Health Dentistry, Sinhgad Dental College and Hospital, Pune 411041, Maharashtra, India.
Vittaldas ShettyDepartment of Public Health Dentistry, Sinhgad Dental College and Hospital, Pune 411041, Maharashtra, India.
Vineet VinayDepartment of Public Health Dentistry, Sinhgad Dental College and Hospital, Pune 411041, Maharashtra, India.ORCID 0000-0003-3847-4319
Ketaki BhorDepartment of Public Health Dentistry, D Y Patil (Deemed to be University) School of Dentistry, Nerul, Navi Mumbai-400706, Maharashtra, India.ORCID 0000-0003-3847-4319
Kadambari AmbildhokDepartment of Public Health Dentistry, Sinhgad Dental College and Hospital, Pune 411041, Maharashtra, India.
Purnima KarandeDepartment of Public Health Dentistry, Sinhgad Dental College and Hospital, Pune 411041, Maharashtra, India.
Sinhgad Dental College and Hospital · IND.Y. Patil University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiopsy is the gold standard for oral squamous cell carcinoma (OSCC) diagnosis. Salivary biomarkers provide promising complementary alternative diagnostic adjunct for its simple non- invasive collection and technique and to screen large population.

objectiveTo summarize and compare the existing evidence on diagnostic accuracy of salivary biomarkers with their estimation method in detecting early oral squamous cell carcinoma.

methodsThe review protocol is registered under PROSPERO(CRD42021225704). PubMed, Google Scholar, EBSCOhost were searched from 2000 to 2020 to identify the screening potential of eight salivary biomarkers: mRNA, miRNA, DUSP100, s100P, IL-8, IL-1B, TNF-a and MMP-9. True-positive, false-positive, true-negative, false-negative, sensitivity, specificity values were extracted or calculated if not present for each study. Quality of selected studies was evaluated based on QUADAS 2 tool. Meta-analysis was performed using a bivariate model parameter for the sensitivity and specificity and summary points, summary receiver operating curve (SROC), confidence region, and prediction region were calculated.

resultsEighteen studies were included for qualitative synthesis and out of that 13 for meta-analysis. Sensitivity and specificity were calculated with AUC. For mRNA it was 91% and 90% with 0.96 AUC, miRNA had 91% and 91% with 0.95 AUC for PCR. IL-1B had 46% and 60% with 0.61 AUC, S100p had 45% and 90% with 0.57 AUC for ELISA. IL-8 had 54% and 74% for ELISA and 89% and 90% for PCR with 0.79 AUC and DUSP1 had 32% and 87% for ELISA and 76% and 83% for PCR with 0.83 AUC respectively.

conclusionEarly detection of OSCC was best achieved by screening for salivary mRNA and miRNA estimated by PCR. Further investigation is required into salivary RNA as novel biomarkers and these salivary biomarkers may be potentially used for non-invasive diagnosis of early OSCC.

Indexed as

Mouth NeoplasmsSquamous Cell Carcinoma of Head and NeckBiomarkers, TumorHumansMicroRNAsRNA, MessengerSalivaBiomarkers, TumorMicroRNAsRNA, MessengeraccuracyDiagnosisoral cancerSalivasalivary biomarker

Identifiers

PMID35633529
PMCPMC9587865
OpenAlexW4281661169

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.