Identification of genomic alteration and prognosis using pathomics-based artificial intelligence in oral leukoplakia and head and neck squamous cell carcinoma: A multicenter experimental study.

BACKGROUND: Loss of chromosome 9p is an important biomarker in the malignant transformation of oral leukoplakia (OLK) to head and neck squamous cell carcinoma (HNSCC), and is associated with the prognosis of HNSCC patients. However, various challenges have prevented 9p loss from being assessed in clinical practice. The objective of this study was to develop a pathomics-based artificial intelligence (AI) model for the rapid and cost-effective prediction of 9p loss (9PLP). MATERIALS AND METHODS: 333 OLK cases were retrospectively collected with hematoxylin and eosin (H&E)-stained whole slide images and genomic alteration data from multicenter cohorts to develop the genomic alteration prediction AI model. They were divided into a training dataset (n=217), a validation dataset (n=93), and an external testing dataset (n=23). The latest Transformer method and XGBoost algorithm were combined to develop the 9PLP model. The AI model was further applied and validated in two multicenter HNSCC datasets (n=42, n=365, respectively). Moreover, the combination of 9PLP with clinicopathological parameters was used to develop a nomogram model for assessing HNSCC patient prognosis. RESULTS: 9PLP could predict chromosome 9p loss rapidly and effectively using both OLK and HNSCC images, with the area under the curve achieving 0.890 and 0.825, respectively. Furthermore, the predictive model showed high accuracy in HNSCC patient prognosis assessment (the area under the curve was 0.739 for 1-year prediction, 0.705 for 3-year prediction, and 0.691 for 5-year prediction). CONCLUSION: To the best of our knowledge, this study developed the first genomic alteration prediction deep learning model in OLK and HNSCC. This novel AI model could predict 9p loss and assess patient prognosis by identifying pathomics features in H&E-stained images with good performance. In the future, the 9PLP model may potentially contribute to better clinical management of OLK and HNSCC.

Differences in the landscape of colonized microorganisms in different oral potentially malignant disorders and squamous cell carcinoma: a multi-group comparative study.

BACKGROUND: The role of microbes in diseases, especially cancer, has garnered significant attention. However, research on the oral microbiota in oral potentially malignant disorders (OPMDs) remains limited. Our study investigates microbial communities in OPMDs. MATERIALS AND METHODS: Oral biopsies from19 oral leukoplakia (OLK) patients, 19 proliferative verrucous leukoplakia (PVL) patients, 19 oral lichen planus (OLP) patients, and 19 oral lichenoid lesions (OLL) patients were obtained. 15 SCC specimens were also collected from PVL patients. Healthy individuals served as controls, and DNA was extracted from their paraffin-embedded tissues. 2bRAD-M sequencing generated taxonomic profiles. Alpha and beta diversity analyses, along with Linear Discriminant Analysis effect size analysis, were conducted. RESULTS: Our results showed the microbial richness and diversity were significantly different among groups, with PVL-SCC resembling controls, while OLK exhibited the highest richness. Each disease group displayed unique microbial compositions, with distinct dominant bacterial species. Noteworthy alterations during PVL-SCC progression included a decline in Fusobacterium periodonticum and an elevation in Prevotella oris. CONCLUSIONS: Different disease groups exhibited distinct dominant bacterial species and microbial compositions. These findings offer promise in elucidating the underlying mechanisms of this disease.

Mast Cell Infiltration and Subtype Promote Malignant Transformation of Oral Precancer and Progression of Oral Cancer.

The role of mast cell (MC), a common myeloid-derived immune cell, in the development of oral squamous cell carcinoma (OSCC) is unclear. The aim of this study was to investigate MC infiltration in oral precancer and oral cancer. The evaluation of immune cell infiltration and its association with prognosis in OSCC used RNA sequencing and multiple public datasets. Multiplex immunofluorescence was used to explore the infiltration of MC in the microenvironment of OSCC and oral precancer and the interaction with CD8+ cells. The role of MC in OSCC progression was verified by in vivo experiments. The resting MC infiltration was mainly present in oral precancer, whereas activated MC infiltration was significantly higher in OSCC. Activated MC was associated with malignant transformation of oral precancer and poor prognosis of OSCC. In vivo studies showed that MC promoted the growth of OSCC. The infiltration of activated MC was negatively correlated with the infiltration of CD8+ T cells. The subtype of MC containing tryptase without chymase (MCT) was significantly higher in OSCC compared with oral precancer and was associated with poor survival. Furthermore, spatial distance analysis revealed a greater distance between MCT and CD8+ cells, which was also linked to poor prognosis in OSCC. Cox regression analysis showed that MCT could be a potential diagnostic and prognostic biomarker. This study provides new insights into the role of MC in the immune microenvironment of OSCC. It might enhance the immunotherapeutic efficacy of OSCC by developing targeted therapies against MC. SIGNIFICANCE: In this study, we investigated the role of mast cells (MC) in oral precancer and oral cancer and demonstrated that MCs are involved in oral cancer progression and may serve as a potential diagnostic and prognostic marker. It might improve the immunotherapeutic efficacy through developing targeted therapies against MCs.

Candida albicans-myeloid cells-T lymphocytes axis in the tumor microenvironment of oral tumor-bearing mice.

Candida albicans (C. albicans) is associated with the development of oral cancer. Here, we report the altered tumor microenvironment in oral tumor-bearing mice caused by C. albicans infection. Single-cell RNA sequencing showed that C. albicans infection influenced the tumor microenvironment significantly. Specifically, C. albicans infection reduced the CD8+ T cells but increased the IL-17A+ CD4+ T cells and IL-17A+ γδ T cells in oral tumor. The neutralization of IL-17A or TCR γ/δ alleviated the tumor progression caused by C. albicans infection. Additionally, C. albicans infection promoted the infiltration of myeloid-derived suppressor cells (MDSCs) into tumor, especially polymorphonuclear (PMN)-MDSCs, which infiltration was reduced after the neutralization of CCL2. Thus, our findings reveal the myeloid cells-T lymphocytes axis in oral tumor microenvironment with C. albicans infection, which helps to understand the mechanisms for C. albicans promoting oral cancer from the perspective of immune microenvironment.

Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts.

Odontogenic keratocyst (OKC) is a common jaw cyst with a high recurrence rate. OKC combined with basal cell carcinoma as well as skeletal and other developmental abnormalities is thought to be associated with Gorlin syndrome. Moreover, OKC needs to be differentiated from orthokeratinized odontogenic cyst and other jaw cysts. Because of the different prognosis, differential diagnosis of several cysts can contribute to clinical management. We collected 519 cases, comprising a total of 2 157 hematoxylin and eosin-stained images, to develop digital pathology-based artificial intelligence (AI) models for the diagnosis and prognosis of OKC. The Inception_v3 neural network was utilized to train and test models developed from patch-level images. Finally, whole slide image-level AI models were developed by integrating deep learning-generated pathology features with several machine learning algorithms. The AI models showed great performance in the diagnosis (AUC = 0.935, 95% CI: 0.898-0.973) and prognosis (AUC = 0.840, 95%CI: 0.751-0.930) of OKC. The advantages of multiple slides model for integrating of histopathological information are demonstrated through a comparison with the single slide model. Furthermore, the study investigates the correlation between AI features generated by deep learning and pathological findings, highlighting the interpretative potential of AI models in the pathology. Here, we have developed the robust diagnostic and prognostic models for OKC. The AI model that is based on digital pathology shows promise potential for applications in odontogenic diseases of the jaw.

Genomic alterations in oral multiple primary cancers.

Oral squamous cell carcinoma (OSCC) is the predominant type of oral cancer, while some patients may develop oral multiple primary cancers (MPCs) with unclear etiology. This study aimed to investigate the clinicopathological characteristics and genomic alterations of oral MPCs. Clinicopathological data from patients with oral single primary carcinoma (SPC, n = 202) and oral MPCs (n = 34) were collected and compared. Copy number alteration (CNA) analysis was conducted to identify chromosomal-instability differences among oral MPCs, recurrent OSCC cases, and OSCC patients with lymph node metastasis. Whole-exome sequencing was employed to identify potential unique gene mutations in oral MPCs patients. Additionally, CNA and phylogenetic tree analyses were used to gain preliminary insights into the molecular characteristics of different primary tumors within individual patients. Our findings revealed that, in contrast to oral SPC, females predominated the oral MPCs (70.59%), while smoking and alcohol use were not frequent in MPCs. Moreover, long-term survival outcomes were poorer in oral MPCs. From a CNA perspective, no significant differences were observed between oral MPCs patients and those with recurrence and lymph node metastasis. In addition to commonly mutated genes such as CASP8, TP53 and MUC16, in oral MPCs we also detected relatively rare mutations, such as HS3ST6 and RFPL4A. Furthermore, this study also demonstrated that most MPCs patients exhibited similarities in certain genomic regions within individuals, and distinct differences of the similarity degree were observed between synchronous and metachronous oral MPCs.

Architectural and cytological features of epithelial dysplasia associated with transformation risk.

OBJECTIVES: This study explored associations between histological features of dysplasia and malignant transformation, as well as genomic copy number alterations. MATERIALS AND METHODS: Overall, 201 samples were collected from patients of oral leukoplakia. The associations of dysplastic features with malignant transformation and copy number alterations were investigated by Cox proportional hazards regression analysis and the Mann-Whitney U-test. RESULTS: Eight individual histological features, such as irregular epithelial stratification (p = 0.001), mitoses high in epithelium (p = 0.033), extension of changes along minor gland ducts (p < 0.001), etc., were associated with greater risk of malignant transformation. A model including histological features and age showed good performance for predicting malignant transformation (area under receiver operating characteristic curve: 0.806). Irregular epithelial stratification (p = 0.007), abnormal nuclear shape (p = 0.005), abnormal cell size (p = 0.004), etc. were associated with greater genomic instability. CONCLUSIONS: A Cox proportional hazards model using eight histological features and patient age reliably predicted the malignant potential of oral epithelial dysplasia. Identification of these histological features closely related to malignant transformation may aid the management of oral potentially malignant disorders and early detection of oral squamous cell carcinoma.

Head and neck carcinoma in children: A clinicopathological study of 42 cases.

Background/purpose: Cancer is an important part of the global burden of childhood diseases. Head and neck carcinoma in children is rare and related research is limited. This study aimed to investigate the clinicopathological features of childhood head and neck carcinoma. Materials and methods: Forty-two cases of childhood head and neck carcinoma treated in our institution were reviewed and analyzed. Results: Median age overall was 11 years. Twenty-three patients (54.8%) were male and 19 (45.2%) were female. Parotid gland location was most common (54.8%). Mucoepidermoid carcinoma and squamous cell carcinoma were the most common histological types (57.1% and 11.9%, respectively). Two patients had a history of bone marrow transplantation and two had a history of odontogenic keratocyst. The recurrence rate after treatment was 8.6%. Conclusion: Early diagnosis and treatment and close follow-up of childhood head and neck carcinoma are warranted to prevent recurrence and improve clinical outcome.

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Oral leukoplakia is a common precursor lesion of oral squamous cell carcinoma, which indicates a high potential of malignancy. The malignant transformation of oral leukoplakia seriously affects patient survival and quality of life; however, it is difficult to identify oral leukoplakia patients who will develop carcinoma because no biomarker exists to predict malignant transformation for effective clinical management. As a major problem in the field of head and neck pathologies, it is imperative to identify biomarkers of malignant transformation in oral leukoplakia. In this review, we discuss the potential biomarkers of malignant transformation reported in the literature and explore the translational probabilities from bench to bedside. Although no single biomarker has yet been applied in the clinical setting, profiling for genomic instability might be a promising adjunct.

Isolation of Cells with Morphological and Spatial Information from Oral Submucous Fibrosis Samples by Laser Capture Microdissection.

Oral submucous fibrosis (OSF) is a common type of potentially malignant disorder in the oral cavity. The atrophy of epithelium and fibrosis of the lamina propria and the submucosa are often found on histopathological slides. Epithelial dysplasia, epithelial atrophy, and senescent fibroblasts have been proposed to be associated with the malignant transformation of OSF. However, because of the heterogeneity of potentially malignant oral disorders and oral squamous cell carcinoma, it is difficult to identify the specific molecular mechanisms of malignant transformation in OSF. Here, we present a method to obtain a small number of epithelial or mesenchymal cells carrying morphological data and spatial information by laser capture microdissection on formalin-fixed paraffin-embedded tissue slides. Using a microscope, we can precisely capture microscale (~500 cells) dysplastic or atrophic epithelial tissue and fibrotic subepithelial tissue. The extracted cells can be evaluated by genome or transcriptome sequencing to acquire genomic and transcriptomic data with morphological and spatial information. This approach removes the heterogeneity of bulk OSF tissue sequencing and the interference caused by cells in non-lesioned areas, allowing for precise spatial-omics analysis of OSF tissue.

Molecular mechanisms underlying the epigallocatechin-3-gallate-mediated inhibition of oral squamous cell carcinogenesis.

OBJECTIVES: To reveal the mechanisms underlying the epigallocatechin-3-gallate (EGCG)-mediated inhibition of carcinogenesis and the related regulatory signaling pathways. DESIGN: The effect of EGCG on the proliferation of OSCC cells was examined. SuperPred, ChEMBL, Swiss TargetPrediction, DisGeNET, GeneCards, and National Center for Biotechnology Information databases were used to predict the EGCG target genes and oral leukoplakia (OL)-related, oral submucosal fibrosis (OSF)-related, and OSCC-related genes. The binding of EGCG to the target proteins was simulated using AutoDock and PyMOL. The Cancer Genome Atlas (TCGA) dataset was subjected to consensus clustering analysis to predict the downstream molecules associated with these targets, as well as their potential functions and pathways. RESULTS: EGCG significantly inhibited OSCC cell proliferation (p < 0.001). By comparing EGCG target genes with genes linked to oral potentially malignant disorder (OPMD) and OSCC, a total of eleven potential EGCG target genes were identified. Furthermore, EGCG has the capacity to bind to eleven proteins. Based on consensus clustering and enrichment analysis, it is suggested that EGCG may hinder the progression of cancer by altering the cell cycle and invasive properties in precancerous lesions of the oral cavity. Some possible strategies for modifying the cell cycle and invasive properties may include EGCG-mediated suppression of specific genes and proteins, which are associated with cancer development. CONCLUSIONS: This study investigated the molecular mechanisms and signaling pathways associated with the EGCG-induced suppression of OSCC. The identification of specific pharmacological targets of EGCG during carcinogenesis is crucial for the development of innovative combination therapies involving EGCG.

Development of a Pathomics-Based Model for the Prediction of Malignant Transformation in Oral Leukoplakia.

Accurate prognostic stratification of oral leukoplakia (OLK) with risk of malignant transformation into oral squamous cell carcinoma is crucial. We developed an objective and powerful pathomics-based model for the prediction of malignant transformation in OLK using hematoxylin and eosin (H&E)-stained images. In total, 759 H&E-stained images from multicenter cohorts were included. A training set (n = 489), validation set (n = 196), and testing set (n = 74) were used for model development. Four deep learning methods were used to train and validate the model constructed using H&E-stained images. Pathomics features generated through deep learning combined with machine learning algorithms were used to develop a pathomics-based model. Immunohistochemical staining of Ki67, p53, and PD-L1 was used to interpret the black box of the model. Pathomics-based models predicted the malignant transformation of OLK (validation set area under curve [AUC], 0.899; testing set AUC, 0.813) and significantly identified high-risk and low-risk populations. The prediction performance of malignant transformation from dysplasia grading (validation set AUC, 0.743) was lower than that of the pathomics-based model. The expressions of Ki67, p53, and PD-L1 were correlated with various pathomics features. The pathomics-based model accurately predicted the malignant transformation of OLK and may be useful for the objective and rapid assessment of the prognosis of patients with OLK.

The preliminary exploration of immune microenvironment in oral leukoplakia concomitant with oral submucosal fibrosis: A comparative immunohistochemical study.

BACKGROUND: Oral leukoplakia concomitant with oral submucous fibrosis is a high-risk oral potentially malignant disorder, but little is known about its immune microenvironment. METHODS: Thirty samples of oral leukoplakia concomitant with oral submucous fibrosis, 30 oral leukoplakia samples, and 30 oral submucous fibrosis samples were collected from two hospitals. Immunohistochemistry was performed to analyze expression of T cell biomarkers [CD3, CD4, CD8, and Forkhead box P3 (Foxp3)], a B cell biomarker (CD20), macrophage biomarkers (CD68 and CD163), an immune inhibitory receptor ligand (PD-L1), and Ki-67. RESULTS: The numbers of CD3+ (p < 0.001), CD4+ (p = 0.018), and CD8+ (p = 0.031) cells in oral leukoplakia concomitant with oral submucous fibrosis were less than those in oral leukoplakia. The number of CD4+ cells (p = 0.035) in oral leukoplakia concomitant with oral leukoplakia was higher than that in oral submucous fibrosis. More CD3+ (p < 0.001), CD4+ (p < 0.001), Foxp3+ (p = 0.019), and CD163+ (p = 0.029) cells were found in oral leukoplakia than in oral submucous fibrosis. CONCLUSION: Various levels of immune infiltration were observed among oral leukoplakia concomitant with oral submucous fibrosis, oral leukoplakia, and oral submucous fibrosis. Characterization of the immune microenvironment may contribute to personalized immunotherapy.

Bibliometric analysis of immunotherapy for head and neck squamous cell carcinoma.

Background/purpose: Head and neck squamous cell carcinoma (HNSCC) is a serious disease endangering the health of patients, and the application of immunotherapy in HNSCC is gradually emerging. However, there is no bibliometric analysis in this research field. This study aims to provide a comprehensive overview of the knowledge structure and research hotspots of immunotherapy for HNSCC. Materials and methods: Publications related to immunotherapy for HNSCC from 2002 to 2021 were searched in the Web of Science Core Collection database. The software VOSviewers, CiteSpace, and the R package 'bibliometrix' were used to perform this bibliometric analysis. Results: A total of 1297 publications were from 63 countries, led by the USA and China. The number of publications related to immunotherapy for HNSCC has increased rapidly from 2015. University of Pittsburgh and The University of Texas M.D. Anderson Cancer Center are the main research institutions. Oral Oncology is the most popular journal in this field, and the Journal of Clinical Oncology is the most highly co-cited journal. These publications were from 7569 authors, with Robert L. Ferris publishing the most papers and being the most frequently co-cited. Clinical trials related to nivolumab and pembrolizumab have attracted wide attention. 'Immune checkpoint inhibitors', 'human papillomavirus', 'programmed cell death-ligand 1', and 'programmed cell death protein 1' are the main keywords of emerging research hotspots. Conclusion: This study presents a comprehensive summary of the trends and development of immunotherapy for HNSCC, identifies the research frontier and hotspot direction, and could provide a valuable reference for researchers in this field.

Clinical and prognostic features of multiple primary cancers with oral squamous cell carcinoma.

OBJECTIVE: To characterize the epidemiological, clinical, and prognostic features of multiple primary cancers (MPC) following oral squamous cell carcinoma (OSCC). DESIGN: Data from the Surveillance, Epidemiology, and End Results Program database were analyzed to determine the standardized incidence ratio (SIR) of multiple subsequent sites, difference in clinical and prognostic features between MPC and single primary OSCC. RESULTS: The sites with the highest SIRs were the oral cavity (SIR = 69.48), other oral cavity and pharynx (SIR=55.46), pharynx (SIR=39.21), tonsils (SIR=33.52), trachea (SIR=33.24), esophagus (SIR=18.00), and larynx (SIR=13.12). The 5- and 10-year survival rates for single primary OSCC were 57.9% (95% CI: 56.7-59.2%) and 47.1% (95% CI: 45.7-48.6%), respectively, while those for MPC were 66.9% (95% CI: 64.6-69.4%) and 42.2% (95% CI: 39.5-45.2%), respectively. The mean age of MPC patients was significantly higher than that of single primary OSCC patients. MPC are more common in the gums and other sites of the oral cavity, and more likely to be detected in early TNM stage and pathological grade. Age, site, T-stage, and N-stage were significantly associated with prognosis of MPC. CONCLUSIONS: Significant differences in clinical and prognostic features were found between MPC and single primary OSCC. Considering MPC has a poor long-term prognosis, it is necessary to identify MPC and single primary OSCC early.

Screening for Biomarkers for Progression from Oral Leukoplakia to Oral Squamous Cell Carcinoma and Evaluation of Diagnostic Efficacy by Multiple Machine Learning Algorithms.

The aim of the study is to identify key genes during the progression from oral leukoplakia (OL) to oral squamous cell carcinoma (OSCC) and predict effective diagnoses. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were performed to identify seven genes associated with the progression from OL to OSCC. Twelve machine learning algorithms including k-nearest neighbor (KNN), neural network (NNet), and extreme gradient boosting (XGBoost) were used to construct multi-gene models, which revealed that each model had good diagnostic efficacy. The functional mechanism or the pathways associated with these genes were evaluated using enrichment analysis, subtype clustering, and immune infiltration analysis. The enrichment analysis revealed that the genes enriched were associated with the cell cycle, cell division, and intracellular energy metabolism. The immunoassay results revealed that the genes primarily affected the infiltration of proliferating T cells and macrophage polarization. Finally, a nomogram and Kaplan-Meier survival analysis were used to predict the prognostic efficacy of key genes in OSCC patients. The results showed that genes could predict the prognosis of the patients, and patients in the high-risk group had a poor prognosis. Our study identified that the seven key genes, including DHX9, BCL2L12, RAD51, MELK, CDC6, ANLN, and KIF4A, were associated with the progression from OL to OSCC. These genes had good diagnostic efficacy and could be used as potential biomarkers for the prognosis of OSCC patients.

Overestimated risk of transformation in oral lichen planus.

OBJECTIVES: Oral lichen planus (OLP) was classified as an oral potentially malignant disorder due to the association with oral squamous cell carcinoma (OSCC). However, the malignant potential of OLP has been controversial. Whether epithelial dysplasia should be differentiated from OLP and lichenoid dysplasia could be identified as a pathological entity has been the subject of debate. MATERIALS AND METHODS: We recruited a large retrospective cohort with 3568 patients, and 10 of them developed OSCC. These cases were reviewed retrospectively to investigate association between OLP and OSCC. RESULTS: In 10 cases of OSCC, three of them were primary cancers distinct from the site with OLP, two were malignant transformation of proliferative verrucous leukoplakia, and five were malignant transformation of oral leukoplakia. All OSCC is not transformed from OLP. Therefore, previous insights into OLP might have overestimated its transformation risk. There may be the reasons: I. did not distinguish OLP from epithelial dysplasia, II. neglect of oral leukoplakia with dysplasia developed in the course after OLP, III. misdiagnosis in the early stage of proliferative verrucous leukoplakia. CONCLUSION: The pathological and molecular biological features of OLP differed from those of oral leukoplakia and OSCC. Strict control of the diagnostic criteria for OLP and close surveillance during the course could contribute to correctly identify the origin of OSCC and avoid overestimating the risk of OLP transformation.

Clinicopathological factors associated with progression of oral submucous fibrosis: A population-based retrospective study.

Oral submucosal fibrosis was one of the oral potentially malignant disorders, which has become a global epidemic disease. This study aimed to investigate the clinicopathological features associated with the disease progression of oral submucosal fibrosis. We recruited 700 cases of oral submucosal fibrosis in the Department of oral pathology, Xiangya Stomatological Hospital, Central South University from July 1996 to July 2019, and analyzed the association among staging of oral submucosal fibrosis and age, sex, sites, duration of areca nut chewing. The age of the patients ranged from 14 to 63 years, with a median age of 32 years. The average age of oral submucosal fibrosis in the early stage (35.89 ± 9.97) was different from the average age in the middle stage (32.74 ± 8.83) and advanced stage (31.43 ± 7.57, P < 0.05). The risk of staging progression of oral submucosal fibrosis decreased with age (OR = 0.965, 95%CI: 0.945-0.986, P = 0.001).

Could the socket shield technique be better than conventional immediate implantation? A meta-analysis.

OBJECTIVES: The purpose of this study was to evaluate whether the clinical outcome of socket shield technique (SST) is superior to that of conventional immediate implantation (CII). MATERIALS AND METHOD: Five electronic databases (PubMed, Cochrane, Web of Science, CNKI, and Google Scholar) were searched to identify randomized controlled trials up to June 31, 2021. Five evaluation indexes were extracted, namely, buccal bone resorption at the horizontal and vertical levels (BBH and BBV), the soft tissue recession assessed by pink evaluation scores (PES), patient satisfaction (PS), ISQ, and the success rate of implantation (SRI), to compare the superiority between SST and CII operations. All data analyses were performed using Review Manager (version 5.4). RESULTS: Ten studies were included in this review. The sample included 388 implants, with 194 in the SST group and 194 in the CII group. Compared with the CII group, the SST group had a lower BBH and BBV (standardized mean difference (SMD), - 1.77; 95% CI, - 2.26 to - 1.28; P < 0.00001 and SMD, - 1.85; 95% CI, - 2.16 to 1.54; P < 0.00001), higher PES improvement (SMD, 2.27; 95% CI, 1.59 to 2.95; P < 0.00001), higher rate of PS (OR, 3.12; 95% CI, 1.08 to 9.04; P = 0.04), and slightly higher ISQ (SMD, 0.71; 95% CI, 0.28 to 1.15; P = 0.001). CONCLUSIONS: Compared with CII, SST could be a better option for esthetic area implantation, but evaluation of its long-term success is still needed. CLINICAL RELEVANCE: By comparing and analyzing the operations of immediate implant in esthetic zone, we could choose SST to effectively alleviate the absorption of bone tissue and improve the contouring of soft tissue after anterior teeth extraction, so as to achieve a more stable and superior clinical outcomes of implant in esthetic zone.

Development and validation of a nomogram prediction model for malignant transformation of oral potentially malignant disorders.

OBJECTIVE: Oral potentially malignant disorders have increased the risk of oral squamous cell carcinoma. This study developed a nomogram model to assess the risks of malignant transformation of oral potentially malignant disorders. MATERIALS AND METHODS: A retrospective analysis of patients diagnosed with oral potentially malignant disorders confirmed by pre-treatment biopsy was performed between 2010 and 2017 at the Peking University Hospital of Stomatology. The candidate risk factors for malignant transformation were screened from clinicopathological variables using Cox and stepwise regression analyses. The nomogram model was constructed based on the regression results and was validated through receiver operating characteristic curves and calibration curves. Decision curve analysis was used to estimate clinical usefulness. RESULTS: A total of 6964 cases of oral potentially malignant disorders were assessed. The malignant transformation rate of oral potentially malignant disorders was 2.00%. Risk factors (age, site, kind of oral potentially malignant disorder, existence of dysplasia and its grade, and other cancers) derived from the regression analyses were entered into the nomogram model. Time-dependent receiver operating characteristic curve, calibration curve, and decision curve analyses showed high levels of predictive value and clinical relevance, although not for all oral potentially malignant disorders. CONCLUSION: A specific dynamic nomogram could be adopted to predict the malignant transformation of oral potentially malignant disorders and implement interventions.