ArticleOral oncology2016
'Cytology-on-a-chip' based sensors for monitoring of potentially malignant oral lesions.
Article in Oral oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
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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.
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.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- CD44-SNA1 integrated cytopathology for delineation of high grade dysplastic and neoplastic oral lesions.PloS one · 2023Pooled it
- Diagnostic tests for oral cancer and potentially malignant disorders in patients presenting with clinically evident lesions.The Cochrane database of systematic reviews · 2021Pooled it
- Deep learning single-cell analysis for cytologic evaluation of oral potentially malignant disorders.Scientific reports · 2026Article
- Dissecting oral premalignant carcinogenesis: spatial omics mechanisms and nanomedicine-driven therapeutic innovation.Molecular cancer · 2026Review
- Emerging roles of microfluidics in oral cancer research and clinical translation.Materials today. Bio · 2026Review
- Application of artificial intelligence in oral potentially malignant disorders: current opinions and future barriers.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Review
- A cytomics-on-a-chip platform and diagnostic model stratifies risk for oral lichenoid conditions.Oral surgery, oral medicine, oral pathology and oral radiology · 2024Article
- A brief review of cytology in dentistry.British dental journal · 2024Review
- Smart Diagnostics: Combining Artificial Intelligence and In Vitro Diagnostics.Sensors (Basel, Switzerland) · 2022Article
- Podoplanin Expression Independently and Jointly with Oral Epithelial Dysplasia Grade Acts as a Potential Biomarker of Malignant Transformation in Oral Leukoplakia.Biomolecules · 2022Article
- Nuclear F-actin Cytology in Oral Epithelial Dysplasia and Oral Squamous Cell Carcinoma.Journal of dental research · 2021Article
- Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19.Lab on a chip · 2020Article
- Clinical Decision Support Tool and Rapid Point-of-Care Platform for Determining Disease Severity in Patients with COVID-19.medRxiv : the preprint server for health sciences · 2020Article
- Point-of-care oral cytology tool for the screening and assessment of potentially malignant oral lesions.Cancer cytopathology · 2020Article
- Point-of-care characterization and risk-based management of oral lesions in primary dental clinics: A simulation model.PloS one · 2020Article
- Development of a cytology-based multivariate analytical risk index for oral cancer.Oral oncology · 2019Article
- Sensors that Learn: The Evolution from Taste Fingerprints to Patterns of Early Disease Detection.Micromachines · 2019Review
- Risk Stratification of Oral Potentially Malignant Disorders in Fanconi Anemia Patients Using Autofluorescence Imaging and Cytology-On-A Chip Assay.Translational oncology · 2018Article
- Biomarkers of chronic inflammation in disease development and prevention: challenges and opportunities.Nature immunology · 2017Article
Corrections and comments
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Authors and funding
33 authors.
Funding
Abstract
unlabelledDespite significant advances in surgical procedures and treatment, long-term prognosis for patients with oral cancer remains poor, with survival rates among the lowest of major cancers. Better methods are desperately needed to identify potential malignancies early when treatments are more effective.
objectiveTo develop robust classification models from cytology-on-a-chip measurements that mirror diagnostic performance of gold standard approach involving tissue biopsy. MATERIALS AND
methodsMeasurements were recorded from 714 prospectively recruited patients with suspicious lesions across 6 diagnostic categories (each confirmed by tissue biopsy -histopathology) using a powerful new 'cytology-on-a-chip' approach capable of executing high content analysis at a single cell level. Over 200 cellular features related to biomarker expression, nuclear parameters and cellular morphology were recorded per cell. By cataloging an average of 2000 cells per patient, these efforts resulted in nearly 13 million indexed objects.
resultsBinary "low-risk"/"high-risk" models yielded AUC values of 0.88 and 0.84 for training and validation models, respectively, with an accompanying difference in sensitivity+specificity of 6.2%. In terms of accuracy, this model accurately predicted the correct diagnosis approximately 70% of the time, compared to the 69% initial agreement rate of the pool of expert pathologists. Key parameters identified in these models included cell circularity, Ki67 and EGFR expression, nuclear-cytoplasmic ratio, nuclear area, and cell area.
conclusionsThis chip-based approach yields objective data that can be leveraged for diagnosis and management of patients with PMOL as well as uncovering new molecular-level insights behind cytological differences across the OED spectrum.
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Registered trials
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