Efficacy of Autofluorescence visualization devices in early detection of malignant transformation in Oral Potentially Malignant Disorders (OPMDs): A Systematic Review and Meta-Analysis

Efficacy of Autofluorescence visualization devices in early detection of malignant transformation in Oral Potentially Malignant Disorders (OPMDs): A Systematic Review and Meta-Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Efficacy of Autofluorescence visualization devices in early detection of malignant transformation in Oral Potentially Malignant Disorders (OPMDs): A Systematic Review and Meta-Analysis Ashish Bodhade, Adetola Emmanuel Babalola, Alka Dive, Rosana A. Morelatto, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8471378/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Autofluorescence visualisation devices have emerged as promising non-invasive adjuncts to conventional oral examinations to identify subtle tissue changes indicative of dysplasia or malignancy. However, their true diagnostic efficacy in detecting malignant transformation in Oral potentially malignant disorders remains debated. Methods: A search was conducted in PubMed, Scopus, and Web of Science using terms like "oral potentially malignant disorders", "autofluorescence" and "diagnostic accuracy". Diagnostic studies evaluating autofluorescence devices for early detection of OPMDs, with histopathology as the reference standard, were included. Meta-analysis was performed using a random-effects model to estimate pooled sensitivity, specificity, and diagnostic odds ratio (DOR), with heterogeneity assessed by the I² statistic. Results: Nine diagnostic accuracy studies comprising 1,262 patients were included. The pooled sensitivity of autofluorescence devices was 55.6% (95% CI: 34.6%–74.8%) and pooled specificity was 47.7% (95% CI: 29.2%–66.8%). The diagnostic odds ratio (DOR) was 1.77 (95% CI: 1.04–3.47), with substantial heterogeneity across studies (I² = 78.9%), reflecting inconsistency in diagnostic performance due to differences in lesion types, device models, examiner expertise, and patient demographic. Conclusion: Autofluorescence visualisation devices offer modest diagnostic value and should be considered as adjuncts, not replacements to conventional oral examinations and histopathological evaluation. Dentistry Oncology Autofluorescence Oral Potentially Malignant Disorders Malignant Transformation Early Detection Visualization Devices Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Oral cancer has been found to be a significant global health burden and has been characterised by high morbidity and mortality rates, especially in cases of late presentation or diagnosis at advanced stages. 1 , 2 González-Moles et al. (2022) opined that despite advancements in treatment modalities, there is no improvement in the 5-year survival rate for oral cancer, highlighting the urgent need for early detection strategies. 3 A group of seemingly harmless lesions like oral leukoplakia, erythroplakia, oral submucous fibrosis, and lichen planus have been found to sometimes undergo malignant transformations. 4 These lesions are collectively called oral potentially malignant disorders (OPMDs). It is therefore important to carry out regular surveillance and timely intervention for OPMDs in a bid to improve patient outcomes and reduce the devastating impact of oral malignancies, particularly oral squamous cell carcinoma (OSCC). 4 , 5 Kumari et al. (2022) suggest that the change of OPMDs into cancer is a complicated process that happens when harmful changes build up in a cell’s genes. These changes cause the cells to grow out of control and spread into nearby tissues. 6 , 7 These transformations can be subtle and challenging to identify during conventional oral examinations. The routine diagnostic approaches are heavily reliant on visual inspection and palpation of the lesion. 8 In addition, incisional biopsy and histopathological examination, the gold standard, are done to confirm the diagnosis. 9 , 10 Studies like Rao et al. (2020) noted that this approach is invasive and requires specialised surgical skill. In the same vein, Biggar (2009) argued that there could be a mistake in the collection of the tissue for histologic examination, potentially leading to missed diagnosis or delayed intervention in early-stage lesions. 8 , 11 , 12 To address these limitations, Xu et al. (2022) reported that some diagnostic tools have been developed to enhance early detection of malignant transformation in OPMDs, especially with minimal invasion; among these tools are autofluorescence visualisation devices. 13 , 14 These devices have been found to operate on the principle of tissue autofluorescence, where healthy tissues within the oral mucosa emit light at specific wavelengths when excited by a light source. 15 However, in tissues that are undergoing or have undergone malignant transformation, there is a reduction in autofluorescence. The tissues appear as a dark area. 15 , 16 These dark areas can then guide the clinicians on possible malignant transformation and further investigation with a biopsy. Mascitti et al. (2018) stated that autofluorescence visualisation devices like VELscope and Identafi have gained wide popularity in clinical practice and research. 17 , 18 They offer the advantage of being non-invasive and relatively easy to use; however, their true efficacy in the early detection of malignant transformation in OPMDs remains a subject of ongoing investigation and debate. 19 Existing studies have reported varying sensitivities and specificities; this has led to inconsistencies in recommendations for their routine clinical application. Therefore, a synthesis of the existing evidence is needed to ascertain the true diagnostic accuracy and clinical utility of autofluorescence visualisation devices in identifying malignant transformation within OPMDs. This study aims to evaluate the current body of literature by focusing on studies that assess the diagnostic performance of autofluorescence visualisation devices against histopathological diagnosis as the gold standard. It looks to provide a robust and evidence-based answer to the question of whether autofluorescence visualisation devices can significantly improve the early detection of malignant transformation in OPMDs. Thereby informing clinical guidelines and enhancing patient care in the fight against oral cancer. 2. Methods 2.1 Study Design This study was reported as per PRISMA 2020 checklist for diagnostic test accuracy (DTA) studies. The review was registered in PROSPERO (CRD42025648118) (Supplementary file.1). The objective was to evaluate the diagnostic performance of autofluorescence visualization devices in detecting oral cancer in OPMDs. 2.2 Research question How accurate are autofluorescence visualization devices in detecting OSCC in patients with OPMDs compared to histopathological examination? Population (P) Patients with oral potentially malignant disorders (leukoplakia, erythroplakia, OSMF, etc.) Index test Autofluorescence technique Reference test Histopathology Outcome (O) Sensitivity, specificity, diagnostic odds ratio for detection of OSCC 2.3 Search Strategy The search was carried out in the PubMed, Scopus, and Web of Science, covering literature published up to 29 Feb 2025. The search strategy (Appendix-1,Table.1) was curated using combinations of Medical Subject Headings (MeSH), free-text terms, and synonyms which included "oral potentially malignant disorders", "OPMD", "autofluorescence", "VELscope", "diagnostic accuracy", "oral cancer", "early detection", "sensitivity", "specificity". 2.4 Eligibility Criteria Inclusion criteria were diagnostic studies evaluating autofluorescence devices (e.g., VELscope) for early detection of OPMDs with histopathology as the reference standard, Studies reporting sensitivity and specificity, or providing sufficient data to construct a 2×2 contingency table (TP, FP, FN, TN). Exclusion criteria included Case reports, reviews, editorials, animal studies, or in vitro studies, studies not using histopathological confirmation, and studies using other adjunctive diagnostic aids without autofluorescence. 2.5 Screening and Selection The records were exported in Rayyan software [20]. The duplicates were removed. The remaining records were initially screened by reading title, abstract, and keywords. After removing the non-relevant records, full-text of records were retrieved and assessed for eligibility based on eligibility criteria. In case of any discrepancy, a third reviewer was contacted and discrepancies were resolved with discussion. Final included records taken for data extraction. 2.6 Data Extraction Two reviewers independently screened titles, abstracts, and full texts. Data extracted included: Author, year, country, sample size, autofluorescence test or technique including device used, Reference standard (Clinical oral examination or histopathology), True positives (TP), false positives (FP), false negatives (FN), true negatives (TN), Reported sensitivity, specificity, and area under the curve (AUC), if available. Further, required data was extrapolated in studies where there is limited data, using the available information in text in articles. Discrepancies were resolved through discussion or by consulting a third reviewer. 2.7 Risk of Bias Assessment The quality and risk of bias of the included DTA studies were evaluated independently by two reviewers using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool. The domains assessed included: 1. Patient selection, 2. Index test (autofluorescence), 3. Reference standard (histopathology), 4. Flow and timing. Each domain was rated as “low,” “high,” or “unclear” risk of bias. Four of the studies were rated as having a low risk of bias while 5 of the included studies achieved an uncertain overall risk of bias. 2.8 Summary Measures and Statistical Analysis Meta-analysis was performed using the random-effects model due to anticipated clinical and methodological heterogeneity. Sensitivity, Specificity, Diagnostic Odds Ratio (DOR), Positive and Negative Likelihood Ratios (PLR, NLR) were estimated. Logit transformation was applied to sensitivity and specificity to stabilize variance. Standard errors were computed for each estimate based on reconstructed 2×2 tables using reported sensitivity, specificity, and sample sizes. Heterogeneity was assessed using the I² statistic, and sources of heterogeneity were explored descriptively or via subgroup analysis if data permitted. All analysis were performed using the metafor and mada packages in R-Studio. 3. Results 3.1 Search results A literature search was conducted in Scopus (n = 25), PubMed (n = 12), and Web of Science (n = 13), yielding a total of 50 diagnostic test accuracy (DTA) studies (Figure.1). After removing 21 duplicate DTAs, 29 DTAs selected for screening. During the screening phase, 24 DTA studies were excluded after reading titles, abstracts, and keywords. The remaining 5 DTA studies were sought for full-text retrieval. After full-text assessment, all 5 records met eligibility criteria and were included in the review. In addition, 11 DTA studies were identified through citation and manual search. Of these, 4 studies were eligible for full-text review, and 7 studies were excluded due to lack of relevant data. All 4 eligible studies were included in the final synthesis. In total, 9 DTA studies were included in the systematic review and meta-analysis for qualitative and quantitative synthesis. 3.2 Characteristics of studies Following a thorough literature search and review, individual study characteristics (author, year of publication, study design, sample size, population, location, gender, habit history, follow-up duration, index test details, primary findings, and study limitations) of the included studies were extracted ( Supplementary file 2). A total of nine studies met our predefined criteria, including two clinical trials (CTs) 21 , 22 , one pilot cohort study 23 , one prospective observational study 24 two retrospective studies 25 , 26 , and three cross-sectional studies 27 – 29 . The total patient population ranged from 32 in the prospective observational study 4 to 517 in the cohort study 23 , totalling 1,262 participants. Autofluorescence interventions ranged from four months to forty-four months. Studies were performed in individuals aged 17 years or older. Only a few studies conducted a follow-up period that ranged from 12 months to 5 years. Three of these studies were conducted in Italy 22 , 24 , 26 , two in China 23 , 25 , two in India 28 , 29 , one in Germany 21 , and one in Iran 27 . Appendix-1- Table 2 further provides meta-analytic details extracted from the included studies. 3.3 Clinical Presentations Lajolo et al. classified lesions based on clinical presentations, including lichenoid, erythroplakia (red patches), leukoplakia (white patches), erythroleukoplakia (red and white patches), and verrucous leukoplakia. 26 Amirchaghmaghi et al. conducted a cross-sectional study, categorizing clinical presentations as positive or negative conventional oral cavity examinations (COE+/COE-). 27 COE + lesions were those with exophytic (mass-forming polypoid or verruciform and papillary lesions), endophytic (crater-like and destructive ulcers), leukoplakia-like features, erythroplakia-like features, and erythroleukoplakia-like features. In addition to being categorized as COE+, lesions must also exhibit dysplasia signs, such as stiffness and induration on palpation, surface roughness, non-healing ulceration, and a progressive course of growth. 27 All the studies in this review had predefined inclusion criteria combining all or some of the criteria above with important background data such as history of alcohol/tobacco smoking/areca nut chewing and surgical/radiotherapeutic interventions. 23,29 3.4. Quality Assessment Among the nine studies assessed (Supplementary file 3), three (Li et al., Hanken et al., Wang et al.) had low risk across all domains. 21 , 23 , 25 The remaining studies exhibited varying degrees of bias, most commonly in patient selection and reference standard domains. Notably, two studies (Moro et al., Moro A et al.) 22,24 showed high risk in patient selection, and Lajolo et al. had high bias in flow/timing. 26 Overall, while a subset of studies maintained methodological rigor, several presented with unclear or high-risk elements that may influence pooled estimates and should be interpreted with caution. 3.5 Diagnostic Approaches and Findings The explored studies included the different market available fluorescence products such as ViziLite (Visual Light enhanced diagnostic test) 28 , GOCCLES (Glasses for Oral Cancer Curing Light) 22 , 24 , 26 and VELscope (Visually Enhanced Lesion scope) 21 , 3 , 5 , 7 , 9 thus ensuring unique perspectives on outcomes of autofluorescence techniques across various clinical settings. All the diagnostic interventional studies combined autofluorescence interventions with conventional oral examinations (COE) or white light 21 , 29 , and histopathological biopsy results as standard reference points. 21 – 29 In a cross-sectional comparative study involving 150 patients, Jain et al. evaluated the diagnostic performance of VELscope autofluorescence versus conventional white light examination in detecting oral lesions. The VELscope demonstrated a significantly higher diagnostic accuracy of 95% (95% CI: 90%–98%), compared to 75.7% (95% CI: 67.8%–82.6%) achieved with white light examination. Similarly, Hanken et al also showed higher sensitivity, 97.9% (CI: 94%-100%) in the VELscope group compared to the conventional white light group with 75.9% (65%-87%). 21 Li et al also utilized VELscope in an extensive prospective cohort study. They achieved a 15%-47% positive predictive value (PPV) in detecting malignant transformation via autofluorescence in oral lichenoid lesions over five years [23]. Additionally, there was a nine-time (9x) risk of malignant transformation with a loss of autofluorescence (LAF) compared with retention of autofluorescence (RAF) (HR 9.18, CI: 1.22–68.79). 23 Lajolo et al, in a retrospective analysis of 24 patients with oral potentially malignant disorders, reported that GOCCLES was better (75%-100% accuracy) at identifying dysplastic areas in red/erythroplakic lesions as compared to proliferative verrucous lesions (0% accuracy). 26 Moro et al (2015) reported similar findings after using GOCCLES attached to different curing light sources (LED, Elipar, Optilux) in a non-randomized multicenter clinical trial of 61 patients. 22 It was reported that the specificity of GOCCLES in detecting low-risk lesions is higher than in detecting high-risk lesions. Additionally, the three different light sources showed no significant differences (p-value 0.488). 2 Wang et al (2022), using VELscope for a retrospective analysis of 59 potentially malignant disorders, also reported a higher specificity (82.1%) for low-risk lesions compared to (50.0%) for high-risk lesions. 25 3.6 Diagnostic efficacy of Autoflourences in detecting the malignancy or malignant transformation in OPMDs. The sensitivity meta-analysis reveals the variation across included studies in detecting OSCC, with a wide prediction interval (7.8%–94.9%). The pooled sensitivity is 55.6% (95% CI: 34.6% − 74.8%) (Figure.2), indicating that the autofluorescence technique accurately diagnosed slightly more than 50% of OSCC cases in OPMD. Furthermore, the high heterogeneity (I² = 78.9%) suggests substantial differences in the sensitivity estimates between studies, indicating that the diagnostic performance of autofluorescence may be inconsistent and unreliable. Similarly, the specificity meta-analysis also shows variation in correctly diagnosing OPMDs without OSCC. The pooled specificity is 47.7% (95% CI: 29.2%–66.8%) with a wide prediction interval (7.9%–90.6%), suggesting that the autofluorescence correctly rules out OSCC in only 50% (Figure.3). The diagnostic odds ratio (DOR) analysis yielded a value of 1.77 (95% CI: 1.04–3.47), indicating low diagnostic effectiveness of autofluorescence (Figure.4). While the autofluorescence technique shows limited ability to detect OSCC in OPMD, its poor specificity and low DOR suggest that it is not reliable as a standalone diagnostic tool. 4. Discussion This systematic review provides a synthesis of autofluorescence visualization devices in the early detection of malignant transformation in oral premalignant and malignant lesions. Several histopathological changes (hallmarks) have been described in the literature for an oral lesion to become malignant. These changes, such as, the acquisition of sustained proliferative signalling, evasion of growth suppressor cells, resistance to cell death, replicative immortality (immortalization), induction of angiogenesis, activation of tissue invasion and metastasis, deregulation of cellular energy metabolism, evasion of immune destruction are difficult/impossible to accurately detect with conventional oral examinations through the naked eye. 30 – 32 Over the past few decades, different biotechnological companies have developed devices (diagnostic tools) that claim to detect the histological changes that occur during carcinogenesis. 33 – 38 When these changes occur, they appear as a LOF or as a dark view during the autofluorescence examination. 36 , 38 Multiple studies have investigated the diagnostic value of using these diagnostic devices to assist in adjunctive diagnosis of oral cancers from OPMDs. 33 – 35 , 37 , 39 Despite the technological promise of autofluorescence-based adjunctive diagnostics, our findings suggest that their overall clinical reliability is limited. From our pooled meta-analysis, the overall sensitivity of autofluorescence devices was estimated at 55.6% (95% CI: 34.6%–74.8%), indicating that almost half of truly malignant or dysplastic lesions could be missed using these tools alone. Similarly, the pooled specificity was 47.7% (95% CI: 29.2%–66.8%), suggesting a mid ability to identify those without the disease, which may lead to unnecessary biopsies, anxiety, and overtreatment. The diagnostic odds ratio (DOR) of 1.77 (95% CI: 1.04–3.47) underscores the modest discriminative power of these tools when compared to the gold standard of histopathology. Additionally, variations in lesion types (e.g., erythroplakia, leukoplakia, verrucous leukoplakia), examiner expertise, device type, light source, and patient demographics (e.g., habits such as tobacco or areca nut chewing) likely contributed to the high heterogeneity (I² = 78.9%) observed across studies. This underlines the need for standardized protocols in clinical assessment and interpretation of autofluorescence findings. These results align with the current consensus in the literature that autofluorescence tools should not be used in isolation but rather serve as adjuncts to conventional oral examination (COE). 34 – 36 , 38 – 40 For instance, the study by Jain et al. highlighted that while autofluorescence showed improved diagnostic accuracy over white light examination (95% vs. 75.7%) 29 , the broad variation in sensitivity and specificity among included studies, as evidenced by the wide prediction intervals, suggests that diagnostic performance is highly context-dependent. The inaccuracies associated with using autofluorescence are described in the literature for lesions with hyperkeratosis or proliferative growths, which can result from additional cellular layers (e.g., keratin). 26 , 41 These additional cellular layers can cause an increase in fluorescence that may conceal dysplastic and/or neoplastic areas, leading to a masked or umbrella effect. 42 , 43 While advancements and alternative autofluorescence tools have emerged to address these shortcomings, diagnostic energy sources must ideally operate within a specific wavelength range (400–460 nm) to ensure optimal interaction with oral tissues. 44 While some studies have utilized devices with higher wavelength filters (up to 525nm) 44 , 45 , deviations from this range risk inducing oxidative stress and potential cellular damage, underscoring the need for both spectral precision and biological safety in the development of next-generation diagnostic adjuncts. 25 , 45 , 46 Despite the methodological quality of this systematic review and meta-analysis, it is not without limitations. There is considerable heterogeneity among the studies due to differences in study designs, sample sizes, autofluorescence devices, and variations in population groups, which may limit the generalizability of the findings. Additionally, we did not account for the subjective nature of autofluorescence interpretation, which may lead to operator-dependent variabilities. 5. Conclusion Autofluorescence tools offer a non-invasive and rapid adjunct to conventional oral examination, however, our systematic review reports a modest pooled sensitivity (55.6%) and specificity (47.7%), alongside a minimal diagnostic odds ratio (1.77), indicating that they cannot be relied upon as standalone diagnostic modalities.. Significant heterogeneity across studies stemming from variability in device types, lesion characteristics, examiner expertise, and patient habits further diminishes their clinical consistency and generalizability. Despite these limitations, autofluorescence may still play a supportive role in the screening process, particularly in guiding biopsy site selection and raising clinical suspicion in ambiguous cases. However, its use must be integrated with conventional oral examination and confirmed by histopathological assessment to ensure diagnostic accuracy and optimal patient outcomes. We call for further research on developing standardized protocols. Additionally, there is a need to enhance current autofluorescent models, by improving their ability to distinguish proliferative non-cancerous lesions from oral cancers. Until such advancements are achieved, clinicians are advised to exercise caution in interpreting autofluorescence findings and to avoid substituting it for gold-standard diagnostic approaches. Abbreviations OPMDs: Oral Potentially Malignant Disorders QUADAS-2: Quality Assessment of Diagnostic Accuracy Studies-2 DOR: Diagnostic Odds Ratio PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses CTs: Clinical Trials VELscope: Visually Enhanced Lesion scope ViziLite: Visual Light enhanced diagnostic test) GOCCLES: Glasses for Oral Cancer Curing Light LAF: Loss of AutoFluorescence RAF: Retention of AutoFluorescence OR: Odds Ratio TP: True Positive FP: False Positive FN: False Negative TN: True Negative PPV: Positive Predictive Value COE: Conventional Oral Examination AUC: Area Under the Curve PLR: Positive Likelihood Ratio NLR: Negative Likelihood Ratio DTA: Diagnostic Test Accuracy Declarations Acknowledgments Not Applicable Declaration of conflicting interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 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Photodiagnosis Photodyn Ther. 2022;38:102764. doi:10.1016/j.pdpdt.2022.102764 Perdiou A, Dumitrescu R, Jumanca D, et al. Leveraging autofluorescence for tumor detection, diagnosis, and accurate excision with surgical margin assessment in tumor excision. Dent J (Basel). 2025;13(1):10. doi:10.3390/dj13010010 Cioban CV, Petrutiu SA, Condor DC, Uriciuc WA. The use of autofluorescence for screening and early detection of oral potentially malignant disorders: a narrative review. Rom J Stomatol. 2022;68:153-159. doi:10.37897/RJS.2022.2.6 Yang EC, Tan MT, Schwarz RA, Richards-Kortum RR, Gillenwater AM, Vigneswaran N. Noninvasive diagnostic adjuncts for the evaluation of potentially premalignant oral epithelial lesions: current limitations and future directions. Oral Surg Oral Med Oral Pathol Oral Radiol. 2018;125:670-681. doi:10.1016/j.oooo.2018.02.012 Sharma D, Rimal J, Maharjan IK, et al. Evaluation of oral potentially malignant disorders with autofluorescence, reflectance spectroscopy, and vital staining and their correlation with histopathology: hospital-based prospective study. Oral Oncol. 2021;118:105312. doi:10.1016/j.oraloncology.2021.105312 Shin D, Vigneswaran N, Gillenwater A, Richards-Kortum R. Advances in fluorescence imaging techniques to detect oral cancer and its precursors. Future Oncol. 2010;6:1143-1154. doi:10.2217/fon.10.76 Balasubramaniam AM, Sriraman R, Sindhuja P, et al. Autofluorescence-based diagnostic techniques for oral cancer. J Pharm Bioallied Sci. 2015;7(suppl 2):S374-S377. doi:10.4103/0975-7406.163605 Huang TT, Chen KC, Wong TY, et al. Two-channel autofluorescence analysis for oral cancer. J Biomed Opt. 2018;24(6):065002. doi:10.1117/1.JBO.24.6.065002 Wang X, Ding Q, Groleau RR, et al. Fluorescent probes for disease diagnosis. Chem Rev. 2024;124:7106-7164. doi:10.1021/acs.chemrev.3c00327 Additional Declarations The authors declare no competing interests. Supplementary Files Appendix1.docx Appendix-1 Legends · Table 1-Search strategy for each database searched · Table 2- Meta-analysis of data extracted from included studies Supplementaryfile1.docx Supplementary file 1: PRISMA checklist Supplementaryfile2.docx Supplementary file 2: Characteristics of included studies Supplementaryfile3.docx Supplementary file 3: QUADAS-2 assessment of included studies Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8471378","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":566777927,"identity":"0637c595-0493-43a9-9ef9-3801ffc499fd","order_by":0,"name":"Ashish Bodhade","email":"","orcid":"","institution":"Department of Oral and Maxillofacial Pathology, Ranjeet Deshmukh Dental College and Research Centre, Nagpur, India","correspondingAuthor":false,"prefix":"","firstName":"Ashish","middleName":"","lastName":"Bodhade","suffix":""},{"id":566777928,"identity":"a9c4fd75-2e15-48f6-9ffd-dbc78bfc9a7b","order_by":1,"name":"Adetola Emmanuel Babalola","email":"","orcid":"","institution":"Kornberg Schools of Dentistry, Temple University, Philadelphia, USA.","correspondingAuthor":false,"prefix":"","firstName":"Adetola","middleName":"Emmanuel","lastName":"Babalola","suffix":""},{"id":566778084,"identity":"05c26204-d19d-484c-9eaa-70de45ccf675","order_by":2,"name":"Alka Dive","email":"","orcid":"","institution":"Department of Oral and Maxillofacial Pathology, Ranjeet Deshmukh Dental College and Research Centre, Nagpur, India","correspondingAuthor":false,"prefix":"","firstName":"Alka","middleName":"","lastName":"Dive","suffix":""},{"id":566783322,"identity":"531f4fb3-eda3-473b-8b18-d98f0e0e2f0a","order_by":3,"name":"Rosana A. Morelatto","email":"","orcid":"","institution":"Department of Oral Pathology, Faculty of Dentistry, National University of Córdoba, Argentina","correspondingAuthor":false,"prefix":"","firstName":"Rosana","middleName":"A.","lastName":"Morelatto","suffix":""},{"id":566783323,"identity":"782a6830-75f3-466f-a6a1-02cef628fda7","order_by":4,"name":"Graciela Robledo","email":"","orcid":"","institution":"[email protected]","correspondingAuthor":false,"prefix":"","firstName":"Graciela","middleName":"","lastName":"Robledo","suffix":""},{"id":566784406,"identity":"bc3214a4-4821-4195-832b-03406690f895","order_by":5,"name":"Paola Belardinelli","email":"","orcid":"","institution":"Department of Oral Pathology, Faculty of Dentistry, National University of Córdoba, Argentina","correspondingAuthor":false,"prefix":"","firstName":"Paola","middleName":"","lastName":"Belardinelli","suffix":""},{"id":566784407,"identity":"052a693f-a38d-4fe0-80c3-31fe59bf2386","order_by":6,"name":"Nicolás 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Dentistry, University of Ibadan, Ibadan, Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"Adeyanju","lastName":"Somoye","suffix":""},{"id":566799729,"identity":"dacd4780-8716-4b4a-a8ba-3c49bdb14e31","order_by":12,"name":"Monal Yuwanati","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYLCCBxU2PPbHG4AsAwsitSScSZNhOHMApEWCSC2JbYdtGG4kgJhEaNFt7z34IbEtjYdx5vOrG34USDDwt3cn4NViduZcskTCORseZumcsps9QIdJnDm7Ab+WGzkGEgllaTxs0jlpN3iAWgwkcglqMf6RwHaYh0fyTNrNP0RqMZNIaDvMIyHBfuw2cbacOWNmAQxkHgOeHLbbMgYSPIT9crzH+MaHCht7A/bjz26++WMjx9/ei18LEuAxAJPEKgcB9gekqB4Fo2AUjIIRBACDK0hjeWqxyAAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Oral and Maxillofacial Pathology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, 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09:22:08","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":127151,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/5cd122766883294a6e150817.html"},{"id":99594931,"identity":"13964b5f-5c87-44e7-bfed-52e8e6fde4c0","added_by":"auto","created_at":"2026-01-06 09:22:08","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":163677,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of databases searched, screened, selected and included in qualitative and quantitative analysis in systematic review\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/f460adc200e5f0c9b57af88b.jpg"},{"id":99594929,"identity":"9d4008dc-abf5-48d2-b451-54be84be4b08","added_by":"auto","created_at":"2026-01-06 09:22:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81549,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing pooled sensitivity estimates of included studies with 95% confidence intervals for Autofluorescence visualization device in detecting malignant transformation in patients with OPMDs, using a random-effects model (I² = 78.9%, p \u0026lt; 0.0001)\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/53bc7d2fe67975ef7beede44.jpg"},{"id":99594936,"identity":"64ac2a26-4f35-4ac2-9514-5f8fccb23aa0","added_by":"auto","created_at":"2026-01-06 09:22:08","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":79819,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing pooled specificity estimates of included studies with 95% confidence intervals for Autofluorescence visualization device in detecting malignant transformation in patients with OPMDs, using a random-effects model (I² = 81%, p \u0026lt; 0.0001)\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/4adbd272562f98ab985f12da.jpg"},{"id":99792958,"identity":"b03808c5-af8c-4c06-9406-6e73ead68aa1","added_by":"auto","created_at":"2026-01-08 13:30:44","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84156,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing pooled diagnostic odds ratios (OR) with 95% confidence intervals for multiple studies comparing experimental and control groups, using a random effects model. The analysis indicates substantial heterogeneity (I² = 81.3%, p = 0.0081)\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/cb3186b5efc35679893a77f3.jpg"},{"id":99804192,"identity":"394d7d48-bb23-4a0b-b19a-9be30258e32f","added_by":"auto","created_at":"2026-01-08 14:12:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1249409,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/dd87994a-aa66-43af-95bf-aa5083fe26b8.pdf"},{"id":99594925,"identity":"d7850e0f-6f01-4f4a-a27d-c13dd4344993","added_by":"auto","created_at":"2026-01-06 09:22:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17248,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eAppendix-1 Legends\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e· Table 1-Search strategy for each database searched\u003c/p\u003e\n\u003cp\u003e· \u0026nbsp;Table 2- Meta-analysis of data extracted from included studies\u003c/p\u003e","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/2c14cb8decd9a4f54500c0e8.docx"},{"id":99594927,"identity":"aa057a8c-5afa-46c3-b029-6a083c8d7efc","added_by":"auto","created_at":"2026-01-06 09:22:08","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19616,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary file 1\u003c/strong\u003e: PRISMA checklist\u003c/p\u003e","description":"","filename":"Supplementaryfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/8f78acfacde199f8c005a28f.docx"},{"id":99793755,"identity":"40272906-57ff-4bb9-b172-0260abd24b95","added_by":"auto","created_at":"2026-01-08 13:32:18","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":17415,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary file 2:\u003c/strong\u003e Characteristics of included studies\u003c/p\u003e","description":"","filename":"Supplementaryfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/858fd7e02d20af671316539f.docx"},{"id":99793021,"identity":"41fe6f7f-3c40-49c8-b7b2-9eb5401922dc","added_by":"auto","created_at":"2026-01-08 13:30:52","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":14246,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary file 3:\u003c/strong\u003e QUADAS-2 assessment of included studies\u003c/p\u003e","description":"","filename":"Supplementaryfile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8471378/v1/013f9d6dd6f5044894fabaa1.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eEfficacy of Autofluorescence visualization devices in early detection of malignant transformation in Oral Potentially Malignant Disorders (OPMDs): A Systematic Review and Meta-Analysis\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOral cancer has been found to be a significant global health burden and has been characterised by high morbidity and mortality rates, especially in cases of late presentation or diagnosis at advanced stages.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Gonz\u0026aacute;lez-Moles et al. (2022) opined that despite advancements in treatment modalities, there is no improvement in the 5-year survival rate for oral cancer, highlighting the urgent need for early detection strategies.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e A group of seemingly harmless lesions like oral leukoplakia, erythroplakia, oral submucous fibrosis, and lichen planus have been found to sometimes undergo malignant transformations.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e These lesions are collectively called oral potentially malignant disorders (OPMDs). It is therefore important to carry out regular surveillance and timely intervention for OPMDs in a bid to improve patient outcomes and reduce the devastating impact of oral malignancies, particularly oral squamous cell carcinoma (OSCC).\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eKumari et al. (2022) suggest that the change of OPMDs into cancer is a complicated process that happens when harmful changes build up in a cell\u0026rsquo;s genes. These changes cause the cells to grow out of control and spread into nearby tissues.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e These transformations can be subtle and challenging to identify during conventional oral examinations. The routine diagnostic approaches are heavily reliant on visual inspection and palpation of the lesion.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In addition, incisional biopsy and histopathological examination, the gold standard, are done to confirm the diagnosis.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Studies like Rao et al. (2020) noted that this approach is invasive and requires specialised surgical skill. In the same vein, Biggar (2009) argued that there could be a mistake in the collection of the tissue for histologic examination, potentially leading to missed diagnosis or delayed intervention in early-stage lesions.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTo address these limitations, Xu et al. (2022) reported that some diagnostic tools have been developed to enhance early detection of malignant transformation in OPMDs, especially with minimal invasion; among these tools are autofluorescence visualisation devices.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e These devices have been found to operate on the principle of tissue autofluorescence, where healthy tissues within the oral mucosa emit light at specific wavelengths when excited by a light source.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e However, in tissues that are undergoing or have undergone malignant transformation, there is a reduction in autofluorescence. The tissues appear as a dark area.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e These dark areas can then guide the clinicians on possible malignant transformation and further investigation with a biopsy.\u003c/p\u003e \u003cp\u003eMascitti et al. (2018) stated that autofluorescence visualisation devices like VELscope and Identafi have gained wide popularity in clinical practice and research.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e They offer the advantage of being non-invasive and relatively easy to use; however, their true efficacy in the early detection of malignant transformation in OPMDs remains a subject of ongoing investigation and debate.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Existing studies have reported varying sensitivities and specificities; this has led to inconsistencies in recommendations for their routine clinical application. Therefore, a synthesis of the existing evidence is needed to ascertain the true diagnostic accuracy and clinical utility of autofluorescence visualisation devices in identifying malignant transformation within OPMDs.\u003c/p\u003e \u003cp\u003eThis study aims to evaluate the current body of literature by focusing on studies that assess the diagnostic performance of autofluorescence visualisation devices against histopathological diagnosis as the gold standard. It looks to provide a robust and evidence-based answer to the question of whether autofluorescence visualisation devices can significantly improve the early detection of malignant transformation in OPMDs. Thereby informing clinical guidelines and enhancing patient care in the fight against oral cancer.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design\u003c/h2\u003e \u003cp\u003eThis study was reported as per PRISMA 2020 checklist for diagnostic test accuracy (DTA) studies. The review was registered in PROSPERO (CRD42025648118) (Supplementary file.1). The objective was to evaluate the diagnostic performance of autofluorescence visualization devices in detecting oral cancer in OPMDs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Research question\u003c/h2\u003e \u003cp\u003eHow accurate are autofluorescence visualization devices in detecting OSCC in patients with OPMDs compared to histopathological examination?\u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePopulation (P)\u003c/strong\u003e \u003cp\u003ePatients with oral potentially malignant disorders (leukoplakia, erythroplakia, OSMF, etc.)\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIndex test\u003c/strong\u003e \u003cp\u003eAutofluorescence technique\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eReference test\u003c/strong\u003e \u003cp\u003eHistopathology\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eOutcome (O)\u003c/strong\u003e \u003cp\u003eSensitivity, specificity, diagnostic odds ratio for detection of OSCC\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Search Strategy\u003c/h2\u003e \u003cp\u003eThe search was carried out in the PubMed, Scopus, and Web of Science, covering literature published up to 29 Feb 2025. The search strategy (Appendix-1,Table.1) was curated using combinations of Medical Subject Headings (MeSH), free-text terms, and synonyms which included \"oral potentially malignant disorders\", \"OPMD\", \"autofluorescence\", \"VELscope\", \"diagnostic accuracy\", \"oral cancer\", \"early detection\", \"sensitivity\", \"specificity\".\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Eligibility Criteria\u003c/h2\u003e \u003cp\u003eInclusion criteria were diagnostic studies evaluating autofluorescence devices (e.g., VELscope) for early detection of OPMDs with histopathology as the reference standard, Studies reporting sensitivity and specificity, or providing sufficient data to construct a 2\u0026times;2 contingency table (TP, FP, FN, TN). Exclusion criteria included Case reports, reviews, editorials, animal studies, or in vitro studies, studies not using histopathological confirmation, and studies using other adjunctive diagnostic aids without autofluorescence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Screening and Selection\u003c/h2\u003e \u003cp\u003eThe records were exported in Rayyan software [20]. The duplicates were removed. The remaining records were initially screened by reading title, abstract, and keywords. After removing the non-relevant records, full-text of records were retrieved and assessed for eligibility based on eligibility criteria. In case of any discrepancy, a third reviewer was contacted and discrepancies were resolved with discussion. Final included records taken for data extraction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data Extraction\u003c/h2\u003e \u003cp\u003eTwo reviewers independently screened titles, abstracts, and full texts. Data extracted included: Author, year, country, sample size, autofluorescence test or technique including device used, Reference standard (Clinical oral examination or histopathology), True positives (TP), false positives (FP), false negatives (FN), true negatives (TN), Reported sensitivity, specificity, and area under the curve (AUC), if available. Further, required data was extrapolated in studies where there is limited data, using the available information in text in articles. Discrepancies were resolved through discussion or by consulting a third reviewer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Risk of Bias Assessment\u003c/h2\u003e \u003cp\u003e The quality and risk of bias of the included DTA studies were evaluated independently by two reviewers using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool. The domains assessed included: 1. Patient selection, 2. Index test (autofluorescence), 3. Reference standard (histopathology), 4. Flow and timing. Each domain was rated as \u0026ldquo;low,\u0026rdquo; \u0026ldquo;high,\u0026rdquo; or \u0026ldquo;unclear\u0026rdquo; risk of bias. Four of the studies were rated as having a low risk of bias while 5 of the included studies achieved an uncertain overall risk of bias.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Summary Measures and Statistical Analysis\u003c/h2\u003e \u003cp\u003eMeta-analysis was performed using the random-effects model due to anticipated clinical and methodological heterogeneity. Sensitivity, Specificity, Diagnostic Odds Ratio (DOR), Positive and Negative Likelihood Ratios (PLR, NLR) were estimated. Logit transformation was applied to sensitivity and specificity to stabilize variance. Standard errors were computed for each estimate based on reconstructed 2\u0026times;2 tables using reported sensitivity, specificity, and sample sizes. Heterogeneity was assessed using the I\u0026sup2; statistic, and sources of heterogeneity were explored descriptively or via subgroup analysis if data permitted. All analysis were performed using the metafor and mada packages in R-Studio.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Search results\u003c/h2\u003e \u003cp\u003eA literature search was conducted in Scopus (n\u0026thinsp;=\u0026thinsp;25), PubMed (n\u0026thinsp;=\u0026thinsp;12), and Web of Science (n\u0026thinsp;=\u0026thinsp;13), yielding a total of 50 diagnostic test accuracy (DTA) studies (Figure.1). After removing 21 duplicate DTAs, 29 DTAs selected for screening. During the screening phase, 24 DTA studies were excluded after reading titles, abstracts, and keywords. The remaining 5 DTA studies were sought for full-text retrieval. After full-text assessment, all 5 records met eligibility criteria and were included in the review. In addition, 11 DTA studies were identified through citation and manual search. Of these, 4 studies were eligible for full-text review, and 7 studies were excluded due to lack of relevant data. All 4 eligible studies were included in the final synthesis. In total, 9 DTA studies were included in the systematic review and meta-analysis for qualitative and quantitative synthesis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Characteristics of studies\u003c/h2\u003e \u003cp\u003eFollowing a thorough literature search and review, individual study characteristics (author, year of publication, study design, sample size, population, location, gender, habit history, follow-up duration, index test details, primary findings, and study limitations) of the included studies were extracted \u003cb\u003e(\u003c/b\u003eSupplementary file 2). A total of nine studies met our predefined criteria, including two clinical trials (CTs) \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, one pilot cohort study\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, one prospective observational study\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e two retrospective studies\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, and three cross-sectional studies\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The total patient population ranged from 32 in the prospective observational study \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e to 517 in the cohort study \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, totalling 1,262 participants. Autofluorescence interventions ranged from four months to forty-four months. Studies were performed in individuals aged 17 years or older. Only a few studies conducted a follow-up period that ranged from 12 months to 5 years. Three of these studies were conducted in Italy\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, two in China\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, two in India\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, one in Germany\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and one in Iran\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Appendix-1- Table\u0026nbsp;2 further provides meta-analytic details extracted from the included studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Clinical Presentations\u003c/h2\u003e \u003cp\u003eLajolo et al. classified lesions based on clinical presentations, including lichenoid, erythroplakia (red patches), leukoplakia (white patches), erythroleukoplakia (red and white patches), and verrucous leukoplakia.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Amirchaghmaghi et al. conducted a cross-sectional study, categorizing clinical presentations as positive or negative conventional oral cavity examinations (COE+/COE-).\u003csup\u003e27\u003c/sup\u003e COE\u0026thinsp;+\u0026thinsp;lesions were those with exophytic (mass-forming polypoid or verruciform and papillary lesions), endophytic (crater-like and destructive ulcers), leukoplakia-like features, erythroplakia-like features, and erythroleukoplakia-like features. In addition to being categorized as COE+, lesions must also exhibit dysplasia signs, such as stiffness and induration on palpation, surface roughness, non-healing ulceration, and a progressive course of growth.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e All the studies in this review had predefined inclusion criteria combining all or some of the criteria above with important background data such as history of alcohol/tobacco smoking/areca nut chewing and surgical/radiotherapeutic interventions. \u003csup\u003e23,29\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Quality Assessment\u003c/h2\u003e \u003cp\u003eAmong the nine studies assessed (Supplementary file 3), three (Li et al., Hanken et al., Wang et al.) had low risk across all domains.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e The remaining studies exhibited varying degrees of bias, most commonly in patient selection and reference standard domains. Notably, two studies (Moro et al., Moro A et al.)\u003csup\u003e22,24\u003c/sup\u003e showed high risk in patient selection, and Lajolo et al. had high bias in flow/timing.\u003csup\u003e26\u003c/sup\u003e Overall, while a subset of studies maintained methodological rigor, several presented with unclear or high-risk elements that may influence pooled estimates and should be interpreted with caution.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Diagnostic Approaches and Findings\u003c/h2\u003e \u003cp\u003eThe explored studies included the different market available fluorescence products such as ViziLite (Visual Light enhanced diagnostic test)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, GOCCLES (Glasses for Oral Cancer Curing Light)\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and VELscope (Visually Enhanced Lesion scope)\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e thus ensuring unique perspectives on outcomes of autofluorescence techniques across various clinical settings. All the diagnostic interventional studies combined autofluorescence interventions with conventional oral examinations (COE) or white light \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, and histopathological biopsy results as standard reference points.\u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn a cross-sectional comparative study involving 150 patients, Jain et al. evaluated the diagnostic performance of VELscope autofluorescence versus conventional white light examination in detecting oral lesions. The VELscope demonstrated a significantly higher diagnostic accuracy of 95% (95% CI: 90%\u0026ndash;98%), compared to 75.7% (95% CI: 67.8%\u0026ndash;82.6%) achieved with white light examination. Similarly, Hanken et al also showed higher sensitivity, 97.9% (CI: 94%-100%) in the VELscope group compared to the conventional white light group with 75.9% (65%-87%).\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLi et al also utilized VELscope in an extensive prospective cohort study. They achieved a 15%-47% positive predictive value (PPV) in detecting malignant transformation via autofluorescence in oral lichenoid lesions over five years [23]. Additionally, there was a nine-time (9x) risk of malignant transformation with a loss of autofluorescence (LAF) compared with retention of autofluorescence (RAF) (HR 9.18, CI: 1.22\u0026ndash;68.79).\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Lajolo et al, in a retrospective analysis of 24 patients with oral potentially malignant disorders, reported that GOCCLES was better (75%-100% accuracy) at identifying dysplastic areas in red/erythroplakic lesions as compared to proliferative verrucous lesions (0% accuracy).\u003csup\u003e26\u003c/sup\u003e Moro et al (2015) reported similar findings after using GOCCLES attached to different curing light sources (LED, Elipar, Optilux) in a non-randomized multicenter clinical trial of 61 patients.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e It was reported that the specificity of GOCCLES in detecting low-risk lesions is higher than in detecting high-risk lesions. Additionally, the three different light sources showed no significant differences (p-value 0.488).\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Wang et al (2022), using VELscope for a retrospective analysis of 59 potentially malignant disorders, also reported a higher specificity (82.1%) for low-risk lesions compared to (50.0%) for high-risk lesions.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Diagnostic efficacy of Autoflourences in detecting the malignancy or malignant transformation in OPMDs.\u003c/h2\u003e \u003cp\u003eThe sensitivity meta-analysis reveals the variation across included studies in detecting OSCC, with a wide prediction interval (7.8%\u0026ndash;94.9%). The pooled sensitivity is 55.6% (95% CI: 34.6% \u0026minus;\u0026thinsp;74.8%) (Figure.2), indicating that the autofluorescence technique accurately diagnosed slightly more than 50% of OSCC cases in OPMD. Furthermore, the high heterogeneity (I\u0026sup2; = 78.9%) suggests substantial differences in the sensitivity estimates between studies, indicating that the diagnostic performance of autofluorescence may be inconsistent and unreliable. Similarly, the specificity meta-analysis also shows variation in correctly diagnosing OPMDs without OSCC. The pooled specificity is 47.7% (95% CI: 29.2%\u0026ndash;66.8%) with a wide prediction interval (7.9%\u0026ndash;90.6%), suggesting that the autofluorescence correctly rules out OSCC in only 50% (Figure.3). The diagnostic odds ratio (DOR) analysis yielded a value of 1.77 (95% CI: 1.04\u0026ndash;3.47), indicating low diagnostic effectiveness of autofluorescence (Figure.4). While the autofluorescence technique shows limited ability to detect OSCC in OPMD, its poor specificity and low DOR suggest that it is not reliable as a standalone diagnostic tool.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e This systematic review provides a synthesis of autofluorescence visualization devices in the early detection of malignant transformation in oral premalignant and malignant lesions. Several histopathological changes (hallmarks) have been described in the literature for an oral lesion to become malignant. These changes, such as, the acquisition of sustained proliferative signalling, evasion of growth suppressor cells, resistance to cell death, replicative immortality (immortalization), induction of angiogenesis, activation of tissue invasion and metastasis, deregulation of cellular energy metabolism, evasion of immune destruction are difficult/impossible to accurately detect with conventional oral examinations through the naked eye.\u003csup\u003e\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOver the past few decades, different biotechnological companies have developed devices (diagnostic tools) that claim to detect the histological changes that occur during carcinogenesis.\u003csup\u003e\u003cspan additionalcitationids=\"CR34 CR35 CR36 CR37\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e When these changes occur, they appear as a LOF or as a dark view during the autofluorescence examination.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e Multiple studies have investigated the diagnostic value of using these diagnostic devices to assist in adjunctive diagnosis of oral cancers from OPMDs.\u003csup\u003e\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Despite the technological promise of autofluorescence-based adjunctive diagnostics, our findings suggest that their overall clinical reliability is limited.\u003c/p\u003e \u003cp\u003eFrom our pooled meta-analysis, the overall sensitivity of autofluorescence devices was estimated at 55.6% (95% CI: 34.6%\u0026ndash;74.8%), indicating that almost half of truly malignant or dysplastic lesions could be missed using these tools alone. Similarly, the pooled specificity was 47.7% (95% CI: 29.2%\u0026ndash;66.8%), suggesting a mid ability to identify those without the disease, which may lead to unnecessary biopsies, anxiety, and overtreatment. The diagnostic odds ratio (DOR) of 1.77 (95% CI: 1.04\u0026ndash;3.47) underscores the modest discriminative power of these tools when compared to the gold standard of histopathology. Additionally, variations in lesion types (e.g., erythroplakia, leukoplakia, verrucous leukoplakia), examiner expertise, device type, light source, and patient demographics (e.g., habits such as tobacco or areca nut chewing) likely contributed to the high heterogeneity (I\u0026sup2; = 78.9%) observed across studies. This underlines the need for standardized protocols in clinical assessment and interpretation of autofluorescence findings.\u003c/p\u003e \u003cp\u003eThese results align with the current consensus in the literature that autofluorescence tools should not be used in isolation but rather serve as adjuncts to conventional oral examination (COE).\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e For instance, the study by Jain et al. highlighted that while autofluorescence showed improved diagnostic accuracy over white light examination (95% vs. 75.7%)\u003csup\u003e29\u003c/sup\u003e, the broad variation in sensitivity and specificity among included studies, as evidenced by the wide prediction intervals, suggests that diagnostic performance is highly context-dependent.\u003c/p\u003e \u003cp\u003eThe inaccuracies associated with using autofluorescence are described in the literature for lesions with hyperkeratosis or proliferative growths, which can result from additional cellular layers (e.g., keratin).\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e These additional cellular layers can cause an increase in fluorescence that may conceal dysplastic and/or neoplastic areas, leading to a masked or umbrella effect.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e While advancements and alternative autofluorescence tools have emerged to address these shortcomings, diagnostic energy sources must ideally operate within a specific wavelength range (400\u0026ndash;460 nm) to ensure optimal interaction with oral tissues.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e While some studies have utilized devices with higher wavelength filters (up to 525nm)\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, deviations from this range risk inducing oxidative stress and potential cellular damage, underscoring the need for both spectral precision and biological safety in the development of next-generation diagnostic adjuncts.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite the methodological quality of this systematic review and meta-analysis, it is not without limitations. There is considerable heterogeneity among the studies due to differences in study designs, sample sizes, autofluorescence devices, and variations in population groups, which may limit the generalizability of the findings. Additionally, we did not account for the subjective nature of autofluorescence interpretation, which may lead to operator-dependent variabilities.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eAutofluorescence tools offer a non-invasive and rapid adjunct to conventional oral examination, however, our systematic review reports a modest pooled sensitivity (55.6%) and specificity (47.7%), alongside a minimal diagnostic odds ratio (1.77), indicating that they cannot be relied upon as standalone diagnostic modalities.. Significant heterogeneity across studies stemming from variability in device types, lesion characteristics, examiner expertise, and patient habits further diminishes their clinical consistency and generalizability. Despite these limitations, autofluorescence may still play a supportive role in the screening process, particularly in guiding biopsy site selection and raising clinical suspicion in ambiguous cases. However, its use must be integrated with conventional oral examination and confirmed by histopathological assessment to ensure diagnostic accuracy and optimal patient outcomes.\u003c/p\u003e \u003cp\u003eWe call for further research on developing standardized protocols. Additionally, there is a need to enhance current autofluorescent models, by improving their ability to distinguish proliferative non-cancerous lesions from oral cancers. Until such advancements are achieved, clinicians are advised to exercise caution in interpreting autofluorescence findings and to avoid substituting it for gold-standard diagnostic approaches.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul\u003e\n \u003cli\u003eOPMDs: Oral Potentially Malignant Disorders\u003c/li\u003e\n \u003cli\u003eQUADAS-2: Quality Assessment of Diagnostic Accuracy Studies-2\u003c/li\u003e\n \u003cli\u003eDOR: Diagnostic Odds Ratio\u003c/li\u003e\n \u003cli\u003ePRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses\u003c/li\u003e\n \u003cli\u003eCTs: Clinical Trials\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eVELscope: Visually Enhanced Lesion scope\u003c/li\u003e\n \u003cli\u003eViziLite: Visual Light enhanced diagnostic test)\u003c/li\u003e\n \u003cli\u003eGOCCLES: Glasses for Oral Cancer Curing Light\u003c/li\u003e\n \u003cli\u003eLAF: Loss of AutoFluorescence\u003c/li\u003e\n \u003cli\u003eRAF: Retention of AutoFluorescence\u003c/li\u003e\n \u003cli\u003eOR: Odds Ratio\u003c/li\u003e\n \u003cli\u003eTP: True Positive\u003c/li\u003e\n \u003cli\u003eFP: False Positive\u003c/li\u003e\n \u003cli\u003eFN: False Negative\u003c/li\u003e\n \u003cli\u003eTN: True Negative\u003c/li\u003e\n \u003cli\u003ePPV: Positive Predictive Value\u003c/li\u003e\n \u003cli\u003eCOE: Conventional Oral Examination\u003c/li\u003e\n \u003cli\u003eAUC: Area Under the Curve\u003c/li\u003e\n \u003cli\u003ePLR: Positive Likelihood Ratio\u003c/li\u003e\n \u003cli\u003eNLR: Negative Likelihood Ratio\u003c/li\u003e\n \u003cli\u003eDTA: Diagnostic Test Accuracy\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of conflicting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors did not receive any funding for this work\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and informed consent statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbati S, Bramati C, Bondi S, Lissoni A, Trimarchi M. 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J Biomed Opt. 2018;24(6):065002. doi:10.1117/1.JBO.24.6.065002\u003c/li\u003e\n \u003cli\u003eWang X, Ding Q, Groleau RR, et al. Fluorescent probes for disease diagnosis. Chem Rev. 2024;124:7106-7164. doi:10.1021/acs.chemrev.3c00327\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Department of Oral and Maxillofacial Pathology, Ranjeet Deshmukh Dental College and Research Centre, Nagpur, India","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Autofluorescence, Oral Potentially Malignant Disorders, Malignant Transformation, Early Detection, Visualization Devices","lastPublishedDoi":"10.21203/rs.3.rs-8471378/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8471378/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Autofluorescence visualisation devices have emerged as promising non-invasive adjuncts to conventional oral examinations to identify subtle tissue changes indicative of dysplasia or malignancy. However, their true diagnostic efficacy in detecting malignant transformation in Oral potentially malignant disorders remains debated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A search was conducted in PubMed, Scopus, and Web of Science using terms like \"oral potentially malignant disorders\", \"autofluorescence\" and \"diagnostic accuracy\". Diagnostic studies evaluating autofluorescence devices for early detection of OPMDs, with histopathology as the reference standard, were included. Meta-analysis was performed using a random-effects model to estimate pooled sensitivity, specificity, and diagnostic odds ratio (DOR), with heterogeneity assessed by the I² statistic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eNine diagnostic accuracy studies comprising 1,262 patients were included. The pooled sensitivity of autofluorescence devices was 55.6% (95% CI: 34.6%–74.8%) and pooled specificity was 47.7% (95% CI: 29.2%–66.8%). The diagnostic odds ratio (DOR) was 1.77 (95% CI: 1.04–3.47), with substantial heterogeneity across studies (I² = 78.9%), reflecting inconsistency in diagnostic performance due to differences in lesion types, device models, examiner expertise, and patient demographic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eAutofluorescence visualisation devices offer modest diagnostic value and should be considered as adjuncts, not replacements to conventional oral examinations and histopathological evaluation.\u003c/p\u003e","manuscriptTitle":"Efficacy of Autofluorescence visualization devices in early detection of malignant transformation in Oral Potentially Malignant Disorders (OPMDs): A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-06 09:22:03","doi":"10.21203/rs.3.rs-8471378/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f6c4ffeb-3941-44cf-a231-0dd6fd9c7133","owner":[],"postedDate":"January 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60653733,"name":"Dentistry"},{"id":60653734,"name":"Oncology"}],"tags":[],"updatedAt":"2026-01-06T09:22:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-06 09:22:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8471378","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8471378","identity":"rs-8471378","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}