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This cross-sectional diagnostic study evaluated multiple chairside adjuncts—conventional oral examination, VELscope autofluorescence, OralCDx brush cytology, and 1% toluidine blue—using latent class analysis to estimate unbiased diagnostic performance without universal verification. Incisional biopsy for ≥2 positive tests enabled histopathology comparison and showed differences in sensitivity, specificity, and inter-test agreement, supporting a two-tier sequential strategy.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/optimizing-oral-cancer-screening-latent-class-analysis-of-chairside-adjuncts-in-a-high-risk-dental-cohort/407990/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/optimizing-oral-cancer-screening-latent-class-analysis-of-chairside-adjuncts-in-a-high-risk-dental-cohort/407990.png","ImageObject",300,407,{"name":92,"@type":93},"Franzy","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-28",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What was the study aim for oral cancer screening?","Question",{"text":112,"@type":113},"To optimize oral cancer screening by estimating the diagnostic performance of multiple chairside tests in a high-risk dental cohort using latent class analysis.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which chairside adjuncts were evaluated in the study?",{"text":117,"@type":113},"Conventional oral examination, VELscope autofluorescence, OralCDx brush cytology, and 1% toluidine blue staining were tested under standardized conditions.",{"name":119,"@type":110,"acceptedAnswer":120},"How did latent class analysis influence the diagnostic performance estimates?",{"text":121,"@type":113},"LCA modeled true disease status without requiring universal verification, producing more robust and less biased diagnostic estimates compared with traditional reference approaches that rely on histopathology.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},407990,1790792611,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},2336478945519,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Review began 11/17/2025  \nReview ended 11/25/2025  \nPublished 11/30/2025  \n© Copyright 2025  \nGade et al. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0. , which permits unrestricted use , distribution , and reproduction in any medium , provided the original author and source are credited.  \nDOI: 10.7759/cureus.98157  \nOpen Access Original Article  \nOptimizing Oral Cancer Screening: Latent Class Analysis of Chairside Adjuncts in a High-Risk Dental Cohort  \nLalitkumar P. Gade 1, Sahrish Tariq 2, Shreya Bhukal 3, Radhika Thakkar 4, Grishmi Niswade 5 , Shreya Chatterjee 6, Rahul VC Tiwari 7, Seema Gupta 8, Manish Sharma 9  \n1. Department of Oral Pathology, Sau Mathurabai Bhausaheb Thorat Dental College and Hospital, Sangamner, IND 2. Department of Public Health Dentistry, Swami Devi Dyal Dental College and Hospital, Panchkula, IND 3. Department of Cardiology, All India Institute of Medical Sciences, New Delhi, IND 4. Eastman Institute for Oral Health, University of Rochester School of Medicine and Dentistry, Rochester, USA 5. Department of Periodontology, Swargiya Dadasaheb Kalmegh Smruti Dental College and Hospital, Nagpur, IND 6. Department of Laboratory Medicine, Rajendra Institute of Medical Sciences, Ranchi, IND 7. Department of Dental Research Cell, Dr. D. Y. Patil Dental College and Hospital, Dr.  \nD. Y. Patil Vidyapeeth (Deemed to be University), Pune, IND 8. Department of Orthodontics, Kothiwal Dental College and Research Centre, Moradabad, IND 9. Department of Oral Pathology, Jawahar Medical Foundation 's Annasaheb Chudaman Patil Dental College, Dhule, IND  \nCorresponding author: Shreya Bhukal, [shreyabhukal4@gmail.com](shreyabhukal4@gmail.com)  \nAbstract  \nIntroduction: Oral cancer remains a major public health challenge in high-burden regions, and late diagnosis contributes to poor survival. Conventional oral examination (COE) may be limited by subjectivity and low specificity, prompting the evaluation of adjuncts, such as toluidine blue (TB) staining, autofluorescence imaging, and oral brush cytology. This study applied latent class analysis (LCA) to estimate the unbiased diagnostic performance of multiple chairside tests in a single cohort.  \nMaterials and methods: A cross-sectional diagnostic study was conducted on 100 adults (aged 18-70 years) with visible oral lesions. Sequential testing included COE, VELscope autofluorescence (LED Dental Inc., White Rock, British Columbia, Canada), OralCDx brush cytology (CDx Diagnostics, Suffern, NY, USA), and 1% TB staining, which were performed under standardized conditions by calibrated examiners (kappa > 0.80) . Incisional biopsy was performed for lesions that were positive in ≥2 tests. LCA modeled the true disease status without universal verification; traditional metrics used histopathology as a reference.  \nResults: Histopathology confirmed dysplasia or malignancy in 43 patients (43%) . COE showed high sensitivity (83 . 7%), but low specificity (54 .4%) . TB staining yielded a sensitivity of 69 .8% and specificity of 86.0%, and autofluorescence showed a sensitivity of 60 .5% and specificity of 89 .5% . Brush cytology achieved a balanced accuracy (sensitivity 83. 7%; specificity 80. 7%), with the strongest correlation with histopathology (r = 0 .64) . LCA identified two latent classes, brush cytology and TB, demonstrating superior class discrimination. The inter-test agreement was highest between COE and TB (r = 0 .61) .  \nConclusions: No single test was found to be optimal. Brush cytology offered the best standalone accuracy, whereas COE and autofluorescence served as sensitive initial screens. A two-tier sequential strategy comprising COE/autofluorescence followed by brush cytology maximizes case detection and reduces false positives. The LCA provides robust and unbiased estimates for real-world screening. Integration into routine dental practice with structured training can improve early detection of ora","cbCairIKYnH689Ex","https://ap.wps.com/l/cbCairIKYnH689Ex","pdf",812891,"English","# Introduction\n# Materials and Methods\n# Results\n# Conclusions","[{\"question\":\"What was the study aim for oral cancer screening?\",\"answer\":\"To optimize oral cancer screening by estimating the diagnostic performance of multiple chairside tests in a high-risk dental cohort using latent class analysis.\"},{\"question\":\"Which chairside adjuncts were evaluated in the study?\",\"answer\":\"Conventional oral examination, VELscope autofluorescence, OralCDx brush cytology, and 1% toluidine blue staining were tested under standardized conditions.\"},{\"question\":\"How did latent class analysis influence the diagnostic performance estimates?\",\"answer\":\"LCA modeled true disease status without requiring universal verification, producing more robust and less biased diagnostic estimates compared with traditional reference approaches that rely on histopathology.\"}]","Optimizing Oral Cancer Screening - Latent Class Analysis of Chairside Adjuncts in a High-Risk Dental Cohort | PDF",1790577536,25]