Esophageal Neoplasms Research Articles

Esophageal Squamous Cell Carcinoma in Cats

Background: Esophageal neoplasms are rarely reported in cats. The frequency rate is less than 0.5% and those neoplasms are usually malignant. Esophageal squamous cell carcinoma (SCC) is an idiopathic epithelial neoplasm, invasive and metastatic that can induce partial or complete obstruction of the esophageal lumen. There is no breed or sex predisposition, and it is more common in cats over 8-years-old. Esophageal SCC is more frequent in the middle third of the esophagus. The prognosis is poor, as the cats are usually diagnosed at an advanced stage. This report aims to describe clinical, endoscopic, radiographic, and pathological features of two cases of esophageal squamous cell carcinoma in cats.Cases: A 11-year-old neutered male cat presenting regurgitation, weight loss, anorexia and dyspnea was referred to veterinary internal medicine care. Simple and contrast-enhanced radiographic images of the cervical and thoracic regions showed an alveolar pattern in the cranial lung lobes and signs of esophageal lumen irregularity and dilatation in the mediastinum topography. The upper digestive endoscopy showed a dilated esophageal lumen, and an irregular mass was observed in the thoracic esophagus involving the entire esophageal circumference. Biopsy fragments were collected, and the histopathological result was compatible with squamous cell carcinoma. The second case was a 10-year-old neutered male cat presenting hyporexia, regurgitation, dyspnea, tachypnea, and abnormal breath sounds. The ultrasound of the chest showed 3 amorphous hypoechogenic and heterogeneous areas in the right and left hemithorax between parietal and visceral pleura. The cytological examination was compatible with a malignant epithelial tumor. The patient died 3 months after the onset of clinical signs. At gross exam, it was observed a friable, irregular, and ulcerated mass of 5.0 x 3.0 cm in the middle third of the esophagus. Metastatic foci in the lungs and liver were also observed. The histopathological diagnosis was esophageal squamous cell carcinoma, with metastases to liver and lungs. Microscopically, in both cases, were seen aproliferation of polyhedral epithelial cells in the mucosa, arranged in nests or trabeculae with central keratinization. These cells presented oval to rounded nuclei, loose chromatin, prominent nucleolus, and abundant eosinophilic cytoplasm, with marked anisocytosis and anisokaryosis, supported by a thin fibrovascular stroma. In the second cat the neoplastic cells infiltrated the esophageal submucosa, including lymphatic vessels and muscle layer. Lung and liver metastases from theSCC had a cellular pattern similar to the primary neoplasm.Discussion: Esophageal squamous cell carcinoma is extremely rare in cats. The SCC begins in the squamous layer of the mucosa and can infiltrate the muscular layer or protrude into the esophageal lumen, leading to clinical signs, as seen in these 2 cats. The differential diagnoses for esophageal SCC include foreign bodies, esophageal strictures, and infiltrative or compressive non-esophageal tumors. Although uncommon, esophageal tumors should be considered when evaluatingelderly cats with regurgitation and weight loss. The diagnosis of esophageal SCC was confirmed by histopathological findings collected endoscopically or during necropsy. As noted in both cases, the prognosis of SCC is generally unfavorable, usually due to the difficulty in treatment and diagnosis in a late stage of the disease.Keywords: feline, esophagus, neoplasms, metastasis, cancer.

THE PROGNOSIS OF THE DIFFERENT ESOPHAGEAL NEUROENDOCRINE CARCINOMA SUBTYPES: A POPULATION-BASED STUDY.

Neuroendocrine neoplasms are extremely rare and account for 0.4% to 2% of all malignant esophageal neoplasms. The burden of the neuroendocrine histological type on the patients' prognosis and survival is poorly debated. This study aimed to compare the survival rates of primary neuroendocrine neoplasms compared with adenocarcinoma and squamous cell carcinoma of the esophagus. This is a retrospective cohort from the Surveillance, Epidemiology, and End Results Program database. Overall survival and cancer-specific survival were evaluated with Kaplan-Meier curves and logrank tests. Proportional Cox regression models were used to evaluate variables related to overall survival. After eligibility criteria, 66,528 patients were selected. The mean follow-up was 22.6 months (SD 35.6). Adenocarcinoma was predominant (62%), followed by squamous cell carcinoma (36%). Large cell carcinoma, small cell carcinoma, and mixed adenoneuroendocrine carcinoma each account for less than 1% each. On the long-term overall survival analysis, esophageal adenocarcinoma showed a better prognosis than all the other histologic types (P-value for logrank test <0.001). With adenocarcinoma as a reference, HR was 1.32 for large cell carcinoma (95%CI 1.2 to 1.45) and 1.37 for small cell carcinoma (95%CI 1.23 to 1.53). The HR was 1.22 for squamous cell carcinoma (95%CI: 1.2 to 1.24); and 1.3 for adenoneuroendocrine carcinoma (95%CI 1.01 to 1.66). For multivariate Cox regression analysis, besides age and stage, the neuroendocrine subtypes large cell carcinoma and small cell carcinoma were considered independent prognostic variables. In the esophagus, large cell carcinoma and small cell carcinoma show poorer long-term survival rates than squamous cell carcinoma and adenocarcinoma.

Prediction of potential miRNA-disease associations based on stacked autoencoder.

In recent years, increasing biological experiments and scientific studies have demonstrated that microRNA (miRNA) plays an important role in the development of human complex diseases. Therefore, discovering miRNA-disease associations can contribute to accurate diagnosis and effective treatment of diseases. Identifying miRNA-disease associations through computational methods based on biological data has been proven to be low-cost and high-efficiency. In this study, we proposed a computational model named Stacked Autoencoder for potential MiRNA-Disease Association prediction (SAEMDA). In SAEMDA, all the miRNA-disease samples were used to pretrain a Stacked Autoencoder (SAE) in an unsupervised manner. Then, the positive samples and the same number of selected negative samples were utilized to fine-tune SAE in a supervised manner after adding an output layer with softmax classifier to the SAE. SAEMDA can make full use of the feature information of all unlabeled miRNA-disease pairs. Therefore, SAEMDA is suitable for our dataset containing small labeled samples and large unlabeled samples. As a result, SAEMDA achieved AUCs of 0.9210 and 0.8343 in global and local leave-one-out cross validation. Besides, SAEMDA obtained an average AUC and standard deviation of 0.9102 ± /-0.0029 in 100 times of 5-fold cross validation. These results were better than those of previous models. Moreover, we carried out three case studies to further demonstrate the predictive accuracy of SAEMDA. As a result, 82% (breast neoplasms), 100% (lung neoplasms) and 90% (esophageal neoplasms) of the top 50 predicted miRNAs were verified by databases. Thus, SAEMDA could be a useful and reliable model to predict potential miRNA-disease associations.

Wide-tunnel endoscopic submucosal dissection with clip-and-line traction for large circumferential esophageal neoplasm.

Wide-tunnel endoscopic submucosal dissection with clip-and-line traction for large circumferential esophageal neoplasm.

MiRNA-disease association prediction based on meta-paths.

Since miRNAs can participate in the posttranscriptional regulation of gene expression, they may provide ideas for the development of new drugs or become new biomarkers for drug targets or disease diagnosis. In this work, we propose an miRNA-disease association prediction method based on meta-paths (MDPBMP). First, an miRNA-disease-gene heterogeneous information network was constructed, and seven symmetrical meta-paths were defined according to different semantics. After constructing the initial feature vector for the node, the vector information carried by all nodes on the meta-path instance is extracted and aggregated to update the feature vector of the starting node. Then, the vector information obtained by the nodes on different meta-paths is aggregated. Finally, miRNA and disease embedding feature vectors are used to calculate their associated scores. Compared with the other methods, MDPBMP obtained the highest AUC value of 0.9214. Among the top 50 predicted miRNAs for lung neoplasms, esophageal neoplasms, colon neoplasms and breast neoplasms, 49, 48, 49 and 50 have been verified. Furthermore, for breast neoplasms, we deleted all the known associations between breast neoplasms and miRNAs from the training set. These results also show that for new diseases without known related miRNA information, our model can predict their potential miRNAs. Code and data are available at https://github.com/LiangYu-Xidian/MDPBMP.

The Role of Esophageal Stenting in the Management of Anastomotic Leaks after Esophageal and Esophago-Gastric Cancer Resections. Literature Review.

Introduction: Anastomotic fistulas after surgery for esophageal cancer, remain a challenge for both the surgeon and the gastroenterologist. The aim of the study is to highlight the role of esophageal stenting in the management of leaks after esophagectomy for malignancies. Materials and Methods: We reviewed the available literature on the endoscopic treatment of esophageal anastomotic leaks, especially articles on endoscopic stenting in the management of this complication. Pubmed and ClinicalKey databases were searched using keywords such as esophageal anastomotic leaks, fully covered self-expanding metal stents, esophageal neoplasm. The relevant literature has been reviewed and included in the article. Results and Conclusions: The insertion of self-expanding stents in the fistulas of the esophageal anastomosis, represents an efficient method of treatment both for the closure of the fistula and in the control of sepsis. The morbidity and mortality associated with this method of treatment may be significant.

High-grade esophageal neuroendocrine neoplasm with waxing and waning disease course and differential response to chemotherapy: Dual tracer positron emission tomography-computed tomography (18F-flurodeoxyglucose and 68Ga-DOTATATE) features and disease monitoring with functional molecular imaging

Esophageal neuroendocrine neoplasms (NENs) are uncommon type of esophageal malignancies. We describe the clinical course and molecular imaging features of the relatively rare esophageal malignancy (an aggressive poorly differentiated NEN) that was widely metastatic at the initial presentation. The patient underwent multiple cycles of chemotherapeutic regimens, employing cisplatin-etoposide and nanopaclitaxel-carboplatin and later on rechallenge with cisplatin-etoposide. There was observation of fluctuating disease course and differential characteristics of tumor lesions in terms of treatment response and recurrences with multiple cycles of chemotherapy. In view of the histopathology of high Mib-1 labeling index and dual tracer positron emission tomography-computed tomography (PET-CT) (flurodeoxyglucose [FDG] and 68Ga-DOTATATE) features, the patient was not a suitable candidate for 177Lu-DOTATATE PRRT and FDG PET-CT was the preferred imaging modality for both treatment response assessment and disease monitoring in this patient. The varying response among metastatic lesions in the same individual (with one lesion showing partial response and the other one demonstrating disease progression) was an additional noteworthy feature of the case.

Risk factors of postoperative stricture after endoscopic submucosal dissection for superficial esophageal neoplasms: A meta-analysis.

Background:As larger-sized superficial esophageal neoplasms became candidates for endoscopic submucosal dissection (ESD), post-ESD esophageal stricture has inevitably developed into a significant complication during long-term follow-up.Method:The PubMed, Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, Web of Science, as well as China National Knowledge Infrastructure, the Wanfang Database, and the Chinese Biomedical Literature Database, were searched to identify all the appropriate studies published from January 2000 through October 2019. For risk factor assessment between postoperative stricture and control groups, pooled odds ratios (OR) and weighted mean differences (WMD) estimation was done. All meta-analytical procedures were conducted by using Stata version 15.1 software.Results:The results showed that 11 studies with 2248 patients (284 structure cases and 1964 controls) were eligible for this meta-analysis. Statistical results indicated 6 substantial risk factors: lesion characteristics involving the upper third of the esophagus (OR 1.51, [1.02–2.25]), macroscopic type of IIa/IIc (OR 2.76, [1.55–4.92]), tumor depth of invasion above m1 (OR 7.47, [3.31–16.86]), and m2 (OR 12.67, [4.00–40.10]), longitudinal length (WMD 13.75 mm, [7.76–19.74]), circumferential diameter (WMD 10.87 mm, [8.13–13.60]), and circumferential range >3/4 (OR 38.17, [9.94–146.52]). Each additional 10% of the circumferential range increased the risk of stricture by 149% (OR 9282.46, [978.14–88089.35]).Conclusions:Six risk factors were assessed to have a key role in the elevated risk levels of post-ESD esophageal stricture. The results can help doctors identify patients with increased risk and thus can guide management of the adequate period of surveillance after ESD and take available approaches of stricture prevention.

Prevalence and risk factors of upper gastrointestinal cancers missed during endoscopy: a nationwide registry-based study.

A significant proportion of upper gastrointestinal cancers (UGICs) remain undetected during esophagogastroduodenoscopy (EGD). We investigated the characteristics and risk factors of UGICs missed during endoscopy. In this nationwide registry-based study, we analyzed two large Polish datasets (National Health Fund and National Cancer Registry) to identify individuals who underwent EGD and were subsequently diagnosed with UGIC. Cancers diagnosed < 6 months after EGD were defined as "prevalent" and those within ≥ 6- < 36 months as "missed." We compared the characteristics of missed and prevalent cancers, and analyzed the risk factors for missed UGICs in a multivariable regression model. We included 4 105 399 patients (mean age 56.0 years [SD 17.4]; 57.5 % female) who underwent 5 877 674 EGDs in 2012-2018. Within this cohort, 33 241 UGICs were diagnosed, of which 1993 (6.0 %) were missed. Within esophageal neoplasms, adenocarcinomas were more frequently missed than squamous cell cancers (6.1 % vs. 4.2 %), with a relative risk of 1.4 (95 % confidence interval [CI] 1.1-1.8, P = 0.01). Most gastric cancers were adenocarcinomas, of which 5.7 % were classified as missed. Overall, a higher proportion of missed UGICs than prevalent cancers presented at an advanced stage (42.2 % vs. 36.2 %, P < 0.001). Risk factors for missed UGICs included initial EGD performed within primary (vs. secondary) care (odds ratio [OR] 1.3, 95 %CI 1.2-1.5), female sex (OR 1.3, 95 %CI 1.2-1.4), and higher comorbidity (Charlson comorbidity index ≥ 5 vs. 0; OR 6.0, 95 %CI 4.7-7.5). Among UGICs, esophageal adenocarcinomas were missed most frequently. Missed cancers occur more frequently within the primary care sector and are found more often in women and individuals with multiple comorbidities.

RFLMDA: A Novel Reinforcement Learning-Based Computational Model for Human MicroRNA-Disease Association Prediction.

Numerous studies have confirmed that microRNAs play a crucial role in the research of complex human diseases. Identifying the relationship between miRNAs and diseases is important for improving the treatment of complex diseases. However, traditional biological experiments are not without restrictions. It is an urgent necessity for computational simulation to predict unknown miRNA-disease associations. In this work, we combine Q-learning algorithm of reinforcement learning to propose a RFLMDA model, three submodels CMF, NRLMF, and LapRLS are fused via Q-learning algorithm to obtain the optimal weight . The performance of RFLMDA was evaluated through five-fold cross-validation and local validation. As a result, the optimal weight is obtained as S (0.1735, 0.2913, 0.5352), and the AUC is 0.9416. By comparing the experiments with other methods, it is proved that RFLMDA model has better performance. For better validate the predictive performance of RFLMDA, we use eight diseases for local verification and carry out case study on three common human diseases. Consequently, all the top 50 miRNAs related to Colorectal Neoplasms and Breast Neoplasms have been confirmed. Among the top 50 miRNAs related to Colon Neoplasms, Gastric Neoplasms, Pancreatic Neoplasms, Kidney Neoplasms, Esophageal Neoplasms, and Lymphoma, we confirm 47, 41, 49, 46, 46 and 48 miRNAs respectively.

Hot Tea Drinking and the Risk of Esophageal Cancer: A Systematic Review and Meta-Analysis

This study aimed to explore the association between hot tea drinking and the risk of esophageal cancer. PubMed, Web of Science, Embase, Scopus and Cochrane library were searched for relevant studies from inception to October 29, 2020 by using (Tea OR “Green Tea” OR “Black Tea”) AND (“Esophageal Neoplasms” OR “Esophageal Cancer” OR “Esophagus Cancer”) as key words. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literatures. The meta-analysis was performed using the Revman 5.3 and Stata 13.0 software. The subgroup analyses were conducted on publication year, population regions, tea type, tea temperature, and type of esophageal cancer, and the publication bias was calculated using the funnel plot and Begg’s regression. A total of 12 case-control studies with 5253 cases and 8273 controls were included. The meta-analysis displayed that hot tea drinking was significantly associated with the risk of esophageal cancer (pooled odds ratio, 2.04; 95% CI, 1.78–2.31). However, the research evidence is still limited, therefore, it needs further discussion.

State of the Russian Oncology Service: esophageal cancer. Population-based study at the federal district level. Part I. Morbidity and mortality rates, accuracy index, annual mortality

Malignant neoplasms (MNO) of esophagus is the localization with a high mortality rate. Years of searching for effective treatment in Russia have resulted in modest success. The median survival rate of patients is expressed in months, 70% of patients die in the first year of dispensary registration, the levels of one-year mortality rates for men and women practically do not differ.&#x0D; The esophageal cancer (EC) morbidity and mortality rates have slightly decreased in 20002018 in Russia and has declined only among the male population of the Northwestern Federal District.&#x0D; To study the trends in the morbidity and mortality rates in the population of Russia and the Northwestern Federal District of the Russian Federation. Qualitative analytical indicators, such as the accuracy index and the year-to-year mortality patterns in esophageal cancer patients, will be further considered.&#x0D; The highest standardized EC morbidity rates of the population were found in Zimbabwe (Harare, Africans) 15.5 0/0000, Japan (Miyage) 14.3 0/0000 and the Arkhangelsk region of Russia 12.8 0/0000. In 2000-2019 the level of standardized morbidity rates of the Russian population with EC has decreased from 3.44 to 3.19 0/0000 or 7.3% (both sexes), mortality rates from 3.32 to 2.66 0/0000, or 19.9%. A decrease in the morbidity and mortality rates from EC occurred in the Northwestern Federal District of the Russian Federation, only among the male population.&#x0D; Annual EC mortality rate mainly occurs according to the classical model. The highest level is determined in the first year of follow-up (72-74%); by the end of the decade, only 4.1% of patients remain from those initially recorded.&#x0D; The accuracy index has decreased in Russia and in the Northwestern Federal District of the Russian Federation, respectively, to 0.84 and 0.86 (both sexes) but has remained above the critical mark of 0.7 for localizations with a high mortality rate.

Novel genomic alteration in superficial esophageal squamous cell neoplasms in non-smoker non-drinker females

Alcohol consumption and smoking pose a significant risk for esophageal squamous cell neoplasia (ESCN) development in males; however, ESCN is often diagnosed in non-drinking and non-smoking females. The mechanisms underlying these differences remain elusive, and understanding them can potentially identify novel pathways involved in ESCN development. We performed short-read sequencing to identify somatic variants on a cancer panel targeting 409 genes using DNA extracted from the superficial squamous cell carcinoma (ESCC) tissues and adjacent non-neoplastic epithelium (NE), and immunohistochemical staining of the protein encoded by the target gene. All male patients (n = 117) were drinkers or smokers, whereas 45% of the female patients (n = 33) were not. Somatic variants were compared among three age-matched groups: 13 female ESCC patients with smoking and drinking habits (known-risk group, F-KR), 13 female ESCC patients without these habits (unknown-risk group, F-UR), and 27 males with ESCC and smoking and drinking habits (M-KR). In the NE, the frequencies of CDKN2A variants were significantly higher in F-UR than in F-KR and M-KR. In both ESCC and NE, p14ARF was significantly overexpressed in F-UR than in the other groups. In conclusion, CDKN2A might be important in ESCC development, independent of known risk factors.

Biased Random Walk With Restart on Multilayer Heterogeneous Networks for MiRNA-Disease Association Prediction.

Numerous experiments have proved that microRNAs (miRNAs) could be used as diagnostic biomarkers for many complex diseases. Thus, it is conceivable that predicting the unobserved associations between miRNAs and diseases is extremely significant for the medical field. Here, based on heterogeneous networks built on the information of known miRNA–disease associations, miRNA function similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases, we developed a computing model of biased random walk with restart on multilayer heterogeneous networks for miRNA–disease association prediction (BRWRMHMDA) through enforcing degree-based biased random walk with restart (BRWR). Assessment results reflected that an AUC of 0.8310 was gained in local leave-one-out cross-validation (LOOCV), which proved the calculation algorithm’s good performance. Besides, we carried out BRWRMHMDA to prioritize candidate miRNAs for esophageal neoplasms based on HMDD v2.0. We further prioritize candidate miRNAs for breast neoplasms based on HMDD v1.0. The local LOOCV results and performance analysis of the case study all showed that the proposed model has good and stable performance.

Identification of miRNA-disease associations via multiple information integration with Bayesian ranking.

In recent years, increasing microRNA (miRNA)-disease associations were identified through traditionally biological experiments. These associations contribute to revealing molecular mechanism of diseases and preventing and curing diseases. To improve the efficiency of miRNA-disease association discovery, some calculation methods were developed as auxiliary tools for researchers. In the current study, we raised a novel model named Bayesian Ranking for MiRNA-Disease Association prediction (BRMDA) by improving Bayesian Personalized Ranking from three aspects: (i) taking advantage of similarity of diseases and miRNAs; (ii) incorporating miRNA bias for miRNAs associated with different number of diseases; and (iii) implementing neighborhood-based approach for new miRNAs and diseases. For each investigated disease, BRMDA used the set of triples (i.e. disease, labeled miRNA, unlabeled miRNA) that reflected association preference of the disease to miRNAs as training set, which made full use of unknown samples rather than simply considering them as negative samples. To investigate the predictive performance of BRMDA, we employed leave-one-out cross-validation and obtained Area Under the Curve of 0.8697, which outperformed many classical methods. Besides, we further implemented three distinct classes of case studies for three common Neoplasms. As a result, there are 44 (Colon Neoplasms), 49 (Esophageal Neoplasms) and 49 (Lung Neoplasms) among the top 50 predicted miRNAs validated through experiments. In short, BRMDA would be a trustable tool for inferring valuable associations.

Current Status of Image-Enhanced Endoscopy for Early Identification of Esophageal Neoplasms.

Advanced esophageal cancer is known to have a poor prognosis. The early detection of esophageal neoplasms, including esophageal dysplasia and early esophageal cancer, is highly important for the accurate treatment of the disease. However, esophageal dysplasia and early esophageal cancer are usually subtle and can be easily missed. In addition to the early detection, proper pretreatment evaluation of the depth of invasion of esophageal cancer is very important for curative treatment. The progression of non-invasive diagnosis via image-enhanced endoscopy techniques has been shown to aid the early detection and estimate the depth of invasion of early esophageal cancer and, as a result, may provide additional opportunities for curative treatment. Here, we review the advancement of image-enhanced endoscopy-related technologies and their role in the early identification of esophageal neoplasms.

Multicenter prospective in vivo study of an endocytoscope system (ECS) for superficial esophageal cancer

BackgroundEndocytoscope systems (ECS) can visualize cellular nuclei of the mucosa of the gastrointestinal tract and are predicted to provide real-time microscopic diagnosis. However, their practical diagnostic performance remains unclear. Therefore, we conducted a multicenter prospective study to evaluate the visualization of superficial esophageal neoplasm in vivo using an ECS, and its diagnostic capability.MethodsThe study target was histologically confirmed squamous cell carcinoma (SCC) and high-grade intraepithelial neoplasia (HGIN). An integrated ECS was used to obtain ECS images. In each patient, three ECS images of cancerous and corresponding noncancerous regions were selected for evaluation. A pathological review board of five certified pathologists made the final diagnosis of the images. The primary endpoint was the sensitivity of ECS diagnosis by pathologists.ResultsECS images of 68 patients were assessed: 42 lesions were mucosal SCC, 13 were submucosal SCC, and 13 were HGIN. The rate of assessable images was 96% (95% CI 87.6–99.1). The sensitivity of ECS diagnosis by pathologists was 88% (95% CI 77.2–94.5).ConclusionsECS can provide high-quality images of cancerous lesions and a high diagnostic accuracy by pathologists, and could be useful for real-time endoscopic histological diagnosis of SCC and HGIN.Trial registrationThe UMIN Clinical Trials Registry Identification Number: 000004218

Image-enhanced endoscopy for detection of second primary esophageal neoplasms in patients with hypopharyngeal cancer: Prevalence, risk factors, and characteristics.

Esophageal second primary neoplasms (ESPNs) are common in hypopharyngeal squamous cell carcinoma (HPSCC) patients and are associated with poor prognoses. The effectiveness of image-enhanced endoscopy (IEE) has not been well established. We reviewed the patients between April 2016 and April 2018 with HPSCC receiving ESPNs screening via white-light imaging, narrow-band imaging, and Lugol chromoendoscopy. Of 99 eligible patients, ESPNs prevalence was 31%. Of the 69 patients assigned to the follow-up group, 23 with positive findings showed significantly increased previous histories of second primary malignancies in the upper aerodigestive tract. Among them, patients without symptoms at the time of IEE screening showed less advanced T stages and higher percentages of receiving minimal invasive therapy. The present study represented the clinical utility of routine IEE screening in HPSCC patients and proposed routine surveillance may help identify and properly manage early-stage ESPN.

Eosinophilic esophagitis, Barrett's esophagus and esophageal neoplasms in the pediatric patient: a narrative review.

There are several esophageal disorders that can occur in the pediatric population. Eosinophilic esophagitis (EoE) is an eosinophil predominant inflammatory disease of the esophagus that was first characterized in the early 1900's. EoE is the most common pediatric esophageal inflammatory condition after gastroesophageal reflux disease (GERD). Longstanding GERD is a known risk factor for the development of Barrett's esophagus (BE) in both children and adults. BE is associated with the development of dysplasia and, if left undiagnosed, may progress to the development of esophageal adenocarcinoma (EAC). EAC and esophageal squamous cell carcinoma (ESCC) comprise the majority of childhood esophageal malignant neoplasms. The prevalence of EoE continues to rise within the pediatric population. On the other hand, both BE and esophageal neoplasms remain extremely rare in children. The relationship between a chronic inflammatory condition like EoE to BE and/or esophageal neoplasms remains unclear. The current research of these disease entities is prioritized to further understanding the disease pathogenesis and disease progression, exploring new diagnostic modalities, and developing novel treatments or less invasive therapeutic options. The focus of the following narrative review is to provide a summary of the current clinical practices, future research and their implications on these various esophageal disorders.

Diagnostic Performance of Artificial Intelligence-Based Models for the Detection of Early Esophageal Cancers in Barret's Esophagus: A Meta-Analysis of Patient-Based Studies.

IntroductionBarret’s esophagus (BE) is a precursor of adenocarcinoma of the esophagus. The detection of high-grade dysplasia and adenocarcinoma at an early stage can improve survival but is very challenging. Artificial intelligence (AI)-based models have been claimed to improve diagnostic accuracy. The aim of the current study was to carry out a meta-analysis of papers reporting the results of artificial intelligence-based models used in real-time white light endoscopy of patients with BE to detect early esophageal adenocarcinoma (EEAC).MethodsThis meta-analysis was registered with the International Prospective Register of Systematic Reviews (PROSPERO; Reg No. CRD42021246148) and its conduction and reporting followed the Preferred Reporting Items for Systematic Review and Meta-Analysis of Diagnostic Test Accuracy (PRISMA-DTA) statement guidelines. All peer-reviewed and preprint original articles that reported the sensitivity and specificity of AI-based models on white light endoscopic imaging as an index test against the standard criterion of histologically proven early oesophageal cancer on the background of Barret's esophagus reported as per-patient analysis were considered for inclusion. There was no restriction on type and year of publication, however, articles published in the English language were searched. The search engines used included Medline, PubMed, EMBASE, EMCARE, AMED, BNI, and HMIC. The search strategy included the following keywords for all search engines: ("Esophageal Cancer" OR "Esophageal Neoplasms" OR " Oesophageal Cancer" OR "Oesophageal Neoplasms” OR "Barrett's Esophagus" OR "Barrett's Oesophagus") And ("Artificial Intelligence" OR "Deep Learning" OR "Machine Learning" OR "Convolutional Network"). This search was conducted on November 30, 2020. Duplicate studies were excluded. Studies that reported more than one dataset per patient for the diagnostic accuracy of the AI-based model were included twice. Quantitative and qualitative data, including first author, year of publication, true positives (TP), false negatives (FN), false positives (FP), true negatives (TN), the threshold of the index test, and country where the study was conducted, were extracted using a data extraction sheet. The Quality Appraisal for Diverse Studies 2 (QUADS-2) tool was used to assess the quality of each study. Data were analyzed using MetaDTA, interactive online software for meta-analysis of diagnostic studies. The diagnostic performance of the meta-analysis was assessed by a summary receiver operating characteristics (sROC) plot. A meta-analysis tree was constructed using MetaDTA software to determine the effect of cumulative sensitivity and specificity on surveillance of patients with BE in terms of miss rate and overdiagnosis.ResultsThe literature search revealed 171 relevant records. After removing duplicates, 117 records were screened. Full-text articles of 28 studies were assessed for eligibility. Only three studies reporting four datasets met the inclusion criteria. The summary sensitivity and specificity of AI-based models were 0.90 (95% CI, 0.83- 0.944) and 0.86 (95% CI, 0.781-0.91), respectively. The area under the curve for all the available evidence was 0.88.ConclusionCollective evidence for the routine usage of AI-based models in the detection of EEAC is encouraging but is limited by the low number of studies. Further prospective studies reporting the patient-based diagnostic accuracy of such models are required.