Evidence map›Paper›PMID 33530491›Full record

ReviewInternational journal of molecular sciences2021

Fourier Transform Infrared Spectroscopy in Oral Cancer Diagnosis.

Rong Wang, Yong Wang

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

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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

2 authors.

Rong WangSchool of Dentistry, University of Missouri-Kansas City, Kansas City, MO 64108, USA.
Yong WangSchool of Dentistry, University of Missouri-Kansas City, Kansas City, MO 64108, USA.ORCID 0000-0002-2862-5075

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oral cancer is one of the most common cancers worldwide. Despite easy access to the oral cavity and significant advances in treatment, the morbidity and mortality rates for oral cancer patients are still very high, mainly due to late-stage diagnosis when treatment is less successful. Oral cancer has also been found to be the most expensive cancer to treat in the United States. Early diagnosis of oral cancer can significantly improve patient survival rate and reduce medical costs. There is an urgent unmet need for an accurate and sensitive molecular-based diagnostic tool for early oral cancer detection. Fourier transform infrared spectroscopy has gained increasing attention in cancer research due to its ability to elucidate qualitative and quantitative information of biochemical content and molecular-level structural changes in complex biological systems. The diagnosis of a disease is based on biochemical changes underlying the disease pathology rather than morphological changes of the tissue. It is a versatile method that can work with tissues, cells, or body fluids. In this review article, we aim to summarize the studies of infrared spectroscopy in oral cancer research and detection. It provides early evidence to support the potential application of infrared spectroscopy as a diagnostic tool for oral potentially malignant and malignant lesions. The challenges and opportunities in clinical translation are also discussed.

Indexed as

Biomarkers, TumorSpectroscopy, Fourier Transform InfraredAnimalsDisease SusceptibilityEarly Detection of CancerHistocytochemistryHumansMouth NeoplasmsNeoplasm GradingNeoplasm StagingSignal TransductionSpectrum AnalysisTumor MicroenvironmentBiomarkers, TumorFourier transform infrared spectroscopyFTIRinfrared imagingmachine learningmultivariate analysisoral cancer diagnosisoral dysplasiaoral squamous cell carcinomaspectral biomarkersspectral cytopathology

Identifiers

PMID33530491
PMCPMC7865696

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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.