Non-invasive visual tools for diagnosis of oral cancer and dysplasia: A systematic review

Giovannacci, Ilaria; Vescovi, Paolo; Manfredi, Maddalena; Meleti, Marco

doi:10.4317/medoral.20996

Cited by 35 publications

(19 citation statements)

References 39 publications

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“…The negative predictive values for the COE vary from 0% for the second study group (OC) to high 83,33% for the first group (PL), similar to other research in which the screening was carried out by community agents 33,34 and higher in comparison to that found by Ikeda et al 35 using dentists as screeners.…”

Section: Figure 2 Roc Curve -Sensitivity and Specificity Of Coe In Psupporting

confidence: 84%

Assessment of clinical examination validity in oral cancer risk patients

Nikolovski¹,

Monevska²,

Поповска³

et al. 2020

Balkan J Dent Med

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SummaryBackground/Aim: Oral cancer is one of the ten most common cancers in the world, recently positioned as a sixth one, unfortunately with poor prognosis after treatment because of the late diagnostics in advanced stages of the disease. Aim of this study was to present the basic criteria in assessment the accuracy/efficacy, specificity and sensitivity, the positive and negative predicted values of the conventional oral examination (COE) as the easiest and most acceptable procedure in detection of the early changes of the suspicious oral tissue changes compared to the diagnostic gold standard – tissue biopsy in two different groups of examinees.Material and Methods: Sixty patients divided into two study groups (one with potentially malignant oral lesions and a second consisted of clinically suspicious oral cancer lesions) were examined with COE and subjected to histopathological confirmation - tissue biopsy. All examined patients underwent the diagnostic protocol by the American Joint Commission on Cancer, selected under certain inclusion and exclusion criteria.Results: Sensitivity of COE in the group of examinees with oral potentially malignant lesions is 83.33%, its specificity is 20.83%, the positive predictive value is 20.83% and the negative predictive value is 83.33%. The accuracy of the COE method is 33.33%. The sensitivity, in the group of patients with oral cancer is 96.43%, specificity is 0%, the positive predictive value is 93.10% and the negative predictive value is 0%. The accuracy of this method is 90%.Conclusions: The accuracy reaches a value over 90% for the group with lesions with highly suspected malignant potential – oral cancer, and sets the thesis that COE as screening method for oral cancer or premalignant tissue changes is more valuable for the patients with advanced oral epithelial changes, but is recommended to be combined with some other type of screening procedure in order to gain relevant results applicable in the everyday clinical practice.

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Section: Figure 2 Roc Curve -Sensitivity and Specificity Of Coe In Psupporting

confidence: 84%

Assessment of clinical examination validity in oral cancer risk patients

Nikolovski¹,

Monevska²,

Поповска³

et al. 2020

Balkan J Dent Med

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“…Among the ProInflammatory Activities promoting carcinogenesis, we identified several species of pathobionts from Porphyromonas , Treponema , Fusobacterium , and Streptococcus genera and their raffinose, stachyose, and melibiose transporters, as previously reported [ Alanazi 2018 ;Conrads 2014 ]. This theme also captured two Porphyromonas species and one microbial KO shown to produce proinflammatory mediators [ Utispan 2018 ;Goncalves 2016 ] and eight KOs that are involved in biofilm formation and virulence Matilla 2018 ]. Protein Fermentation and polyamine metabolism is known to be associated with tumorigenesis by mediating oxidative damage to the host cells [ Goodwin 2011 ], we report protein fermentation and ammonia-producing KOs as predictors of OC [ Palmer 2009 ; Moreno-Sanchez 2020 ; ).…”

Section: Discussionsupporting

confidence: 55%

“…Several adjunct diagnostic tools are available to aid providers in identification and diagnosis of OCs [ Charanya 2016 ], such as brush cytology [ Abdulhameed 2018 ; CDx Diagnostics 2020 ], toluidine blue staining [ Pallagatti 2013 ], and light-based visual detection systems [ Nagi 2016 ]. The use of these tools varies among providers, and currently, none of the available tools has been studied sufficiently to prove that their use improves the sensitivity and specificity of the current standard of care physical exam [ Lingen 2008 ;Giovannacci 2016 ]. The work presented in this paper addresses these issues in the standard of care.…”

Section: Discussionmentioning

confidence: 99%

The salivary metatranscriptome as an accurate diagnostic indicator of oral cancer

Banavar¹,

Ogundijo

Toma

et al. 2020

Preprint

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Despite advances in cancer treatment, the five-year mortality rate for oral cancers (OC) is 40%, mainly due to the lack of early diagnostics. To advance early diagnostics for high-risk and average-risk populations, we developed and evaluated machine-learning (ML) classifiers using metatranscriptomic data from saliva samples (n=433) collected from oral premalignant disorders (OPMD), OC patients (n=71) and normal controls (n=171). Our diagnostic classifiers yielded a receiver operating characteristics (ROC) area under the curve (AUC) up to 0.9, sensitivity up to 83% (92.3% for stage 1 cancer) and specificity up to 97.9%. Our metatranscriptomic signature incorporates both taxonomic and functional microbiome features, and reveals a number of previously known and novel taxa and functional pathways associated with OC. For the first time, we demonstrate the potential clinical utility of an AI/ML model for diagnosing OC early, opening a new era of non-invasive diagnostics, enabling early intervention and improved patient outcomes.

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“…Currently, no method allowing for screening, early detection, or monitoring of OSCC in high‐risk groups is commercially available 8 . In the past few decades, several noninvasive diagnostic tools have been proposed, including toluidine blue staining, autofluorescence, chemiluminescence, exfoliative cytology, and optical diagnostic method, such as Raman spectroscopy, elastic scattering, diffuse reflectance, narrow‐band imaging, and fluorescence visualization 9,10 . However, these methods have several limitations, and there is no evidence indicating that their use could reduce cancer mortality 11 .…”

Section: Introductionmentioning

confidence: 99%

Clinical validation of 13‐gene DNA methylation analysis in oral brushing samples for detection of oral carcinoma: Italian multicenter study

et al. 2021

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Background The aim of this Italian multicenter study was to evaluate the diagnostic performance of a minimally invasive method for the detection of oral squamous cell carcinoma (OSCC) based on 13‐gene DNA methylation analysis in oral brushing samples. Methods Oral brushing specimens were collected in 11 oral medicine centers across Italy. Twenty brushing specimens were collected by each center, 10 from patients with OSCC, and 10 from healthy volunteers. DNA methylation analysis was performed in blindness, and each sample was determined as positive or negative based on a predefined cutoff value. Results DNA amplification failed in 4 of 220 (1.8%) samples. Of the specimens derived from patients with OSCC, 93.6% (103/110) were detected as positive, and 84.9% (90/106) of the samples from healthy volunteers were negative. Conclusion These data confirmed the diagnostic performance of our novel procedure in a large cohort of brushing specimens collected from 11 different centers and analyzed in blindness.

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Non-invasive visual tools for diagnosis of oral cancer and dysplasia: A systematic review

Cited by 35 publications

References 39 publications

Assessment of clinical examination validity in oral cancer risk patients

Assessment of clinical examination validity in oral cancer risk patients

The salivary metatranscriptome as an accurate diagnostic indicator of oral cancer

Clinical validation of 13‐gene DNA methylation analysis in oral brushing samples for detection of oral carcinoma: Italian multicenter study

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