The impact of delayed diagnosis on the outcomes of oral cancer patients: a retrospective cohort study

Thomas, A; Manchella, Sankar; Koo, Kendrick; Tiong, Albert; Nastri, A.; Wiesenfeld, D.

doi:10.1016/j.ijom.2020.08.010

Cited by 18 publications

(29 citation statements)

References 25 publications

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“…OSCC is mostly diagnosed at late stages, as also evidenced by our study, in which only 15% of patients were diagnosed with early-stage cancer (stage I), revealing that early diagnosis remains a challenge [49]. It is noteworthy that early diagnosis implies greater possibilities of successful treatment, less mutilation of the patient concerning the treatments carried out, decreased mortality rate, and reduced costs [50][51][52].…”

Section: Discussionsupporting

confidence: 53%

Identification of Possible Salivary Metabolic Biomarkers and Altered Metabolic Pathways in South American Patients Diagnosed with Oral Squamous Cell Carcinoma

et al. 2021

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Oral squamous cell carcinoma (OSCC) represents 90% of oral malignant neoplasms. The search for specific biomarkers for OSCC is a very active field of research contributing to establishing early diagnostic methods and unraveling underlying pathogenic mechanisms. In this work we investigated the salivary metabolites and the metabolic pathways of OSCC aiming find possible biomarkers. Salivary metabolites samples from 27 OSCC patients and 41 control individuals were compared through a gas chromatography coupled to a mass spectrometer (GC-MS) technique. Our results allowed identification of pathways of the malate-aspartate shuttle, the beta-alanine metabolism, and the Warburg effect. The possible salivary biomarkers were identified using the area under receiver-operating curve (AUC) criterion. Twenty-four metabolites were identified with AUC > 0.8. Using the threshold of AUC = 0.9 we find malic acid, maltose, protocatechuic acid, lactose, 2-ketoadipic, and catechol metabolites expressed. We notice that this is the first report of salivary metabolome in South American oral cancer patients, to the best of our knowledge. Our findings regarding these metabolic changes are important in discovering salivary biomarkers of OSCC patients. However, additional work needs to be performed considering larger populations to validate our results.

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Section: Discussionsupporting

confidence: 53%

Identification of Possible Salivary Metabolic Biomarkers and Altered Metabolic Pathways in South American Patients Diagnosed with Oral Squamous Cell Carcinoma

et al. 2021

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“…Early diagnosis of oral cancer is essential to minimize cancer related morbidity and mortality (Schutte et al, 2020;Thomas et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Early detection of oral SCC can reduce cancer‐specific mortality and morbidity (Schutte et al., 2020; Thomas et al., 2020). However, despite significant improvement in the understanding of molecular mechanisms underlying the pathogenesis of oral SCC and the malignant transformation of OPMD, the majority of oral cancers remain diagnosed at late stage (Califano et al., 1996; Karunakaran & Muniyan, 2020; Thomas et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

A novel lightweight deep convolutional neural network for early detection of oral cancer

et al. 2021

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Objectives To develop a lightweight deep convolutional neural network (CNN) for binary classification of oral lesions into benign and malignant or potentially malignant using standard real‐time clinical images. Methods A small deep CNN, that uses a pretrained EfficientNet‐B0 as a lightweight transfer learning model, was proposed. A data set of 716 clinical images was used to train and test the proposed model. Accuracy, specificity, sensitivity, receiver operating characteristics (ROC) and area under curve (AUC) were used to evaluate performance. Bootstrapping with 120 repetitions was used to calculate arithmetic means and 95% confidence intervals (CIs). Results The proposed CNN model achieved an accuracy of 85.0% (95% CI: 81.0%–90.0%), a specificity of 84.5% (95% CI: 78.9%–91.5%), a sensitivity of 86.7% (95% CI: 80.4%–93.3%) and an AUC of 0.928 (95% CI: 0.88–0.96). Conclusions Deep CNNs can be an effective method to build low‐budget embedded vision devices with limited computation power and memory capacity for diagnosis of oral cancer. Artificial intelligence (AI) can improve the quality and reach of oral cancer screening and early detection.

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“…6 Diagnosis of oral cancer at an early stage offers the best chance for improved survival, decreased morbidity, and treatment cost. 7 The oral cavity is easily accessible for visual inspection to detect potentially malignant lesions and early cancer lesions. 8 Though oral cavity cancers meet many of the criteria that justify screening, [9][10][11][12] it is not yet fully adopted as a public health approach and remains controversial.…”

Section: Introductionmentioning

confidence: 99%

“…Diagnosis is often delayed in marginalized, rural, at‐risk populations with poor access to primary health care, low health literacy, and problematic adherence to follow up 6 . Diagnosis of oral cancer at an early stage offers the best chance for improved survival, decreased morbidity, and treatment cost 7 . The oral cavity is easily accessible for visual inspection to detect potentially malignant lesions and early cancer lesions 8…”

Section: Introductionmentioning

confidence: 99%

Cost‐effectiveness of oral cancer screening approaches by visual examination: Systematic review

et al. 2021

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The present study is the first systematic review of papers that have performed a full economic evaluation on oral cancer screening strategies using visual oral examination. The review questions were (1) Is screening a cost-effective strategy in oral cancer? (2) What is the most cost-effective strategy among the different screening approaches in oral cancer? The main outcome measure was the incremental cost-effectiveness ratio. The study identifies and reviews seven full economic evaluations. The included studies scored 75%-100% on the methodological appraisal. Majority of the studies reports that oral cancer screening is a cost-effective strategy, especially in an opportunistic setting and high-risk subset of patients. The results were sensitive to cost and effectiveness parameters. Oral cancer screening, though found cost-effective, the uncertainty around these parameters necessitates additional studies that include better estimates in the modeling assessments. The heterogeneity in studies limited comparison and generalization.

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The impact of delayed diagnosis on the outcomes of oral cancer patients: a retrospective cohort study

Cited by 18 publications

References 25 publications

Identification of Possible Salivary Metabolic Biomarkers and Altered Metabolic Pathways in South American Patients Diagnosed with Oral Squamous Cell Carcinoma

Identification of Possible Salivary Metabolic Biomarkers and Altered Metabolic Pathways in South American Patients Diagnosed with Oral Squamous Cell Carcinoma

A novel lightweight deep convolutional neural network for early detection of oral cancer

Cost‐effectiveness of oral cancer screening approaches by visual examination: Systematic review

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