Current and future cancer staging after neoadjuvant treatment for solid tumors.

Until recently, cancer registries have only collected cancer clinical stage at diagnosis, before any therapy, and pathological stage after surgical resection, provided no treatment has been given before the surgery, but they have not collected stage data after neoadjuvant therapy (NAT). Because NAT is increasingly being used to treat a variety of tumors, it has become important to make the distinction between both the clinical and the pathological assessment without NAT and the assessment after NAT to avoid any misunderstanding of the significance of the clinical and pathological findings. It also is important that cancer registries collect data after NAT to assess response and effectiveness of this treatment approach on a population basis. The prefix y is used to denote stage after NAT. Currently, cancer registries of the American College of Surgeons' Commission on Cancer only partially collect y stage data, and data on the clinical response to NAT (yc or posttherapy clinical information) are not collected or recorded in a standardized fashion. In addition to NAT, nonoperative management after radiation and chemotherapy is being used with increasing frequency in rectal cancer and may be expanded to other treatment sites. Using examples from breast, rectal, and esophageal cancers, the pathological and imaging changes seen after NAT are reviewed to demonstrate appropriate staging.

The Ethics of Cancer Screening Based on Race and Ethnicity.

Racial and ethnic disparities in incidence and mortality are well documented for many types of cancer. As a result, there is understandable policy and clinical interest in race- and ethnicity-based clinical screening guidelines to address cancer health disparities. Despite the theoretical benefits, such proposals do not typically address associated ethical considerations. Using the examples of gastric cancer and esophageal adenocarcinoma, which have demonstrated disparities according to race and ethnicity, this article examines relevant ethical arguments in considering screening based on race and ethnicity.Race- and ethnicity-based clinical preventive care services have the potential to improve the balance of harms and benefits of screening. As a result, programs focused on high-risk racial or ethnic groups could offer a practical alternative to screening the general population, in which the screening yield may be too low to demonstrate sufficient effectiveness. However, designing screening according to socially based categorizations such as race or ethnicity is controversial and has the potential for intersectional stigma related to social identity or other structurally mediated environmental factors. Other ethical considerations include miscategorization, unintended negative effects on health disparities, disregard for underlying risk factors, and the psychological costs of being assigned higher risk.Given the ethical considerations, the practical application of race and ethnicity in cancer screening is most relevant in multicultural countries if and only if alternative proxies are not available. Even in those instances, policymakers and clinicians should carefully address the ethical considerations within the historical and cultural context of the intended population. Further research on alternative proxies, such as social determinants of health and culturally based characteristics, could provide more adequate factors for risk stratification.

Understanding the malignant potential of gastric metaplasia of the oesophagus and its relevance to Barrett's oesophagus surveillance: individual-level data analysis.

OBJECTIVE: Whether gastric metaplasia (GM) of the oesophagus should be considered as Barrett's oesophagus (BO) is controversial. Given concern intestinal metaplasia (IM) may be missed due to sampling, the UK guidelines include GM as a type of BO. Here, we investigated whether the risk of misdiagnosis and the malignant potential of GM warrant its place in the UK surveillance. DESIGN: We performed a thorough pathology and endoscopy review to follow clinical outcomes in a novel UK cohort of 244 patients, covering 1854 person years of follow-up. We complemented this with a comparative genomic analysis of 160 GM and IM specimens, focused on early molecular hallmarks of BO and oesophageal adenocarcinoma (OAC). RESULTS: We found that 58 of 77 short-segment (<3 cm) GM (SS-GM) cases (75%) continued to be observed as GM-only across a median of 4.4 years of follow-up. We observed that disease progression in GM-only cases and GM+IM cases (cases with reported GM on some occasions, IM on others) was significantly lower than in the IM-only cases (Kaplan-Meier, p=0.03). Genomic analysis revealed that the mutation burden in GM is significantly lower than in IM (p<0.01). Moreover, GM does not bear the mutational hallmarks of OAC, with an absence of associated signatures and driver gene mutations. Finally, we established that GM found adjacent to OAC is evolutionarily distant from cancer. CONCLUSION: SS-GM is a distinct entity from SS-IM and the malignant potential of GM is lower than IM. It is questionable whether SS-GM warrants inclusion in BO surveillance.

National Institute for Health and Care Excellence (NICE) guidance on monitoring and management of Barrett's oesophagus and stage I oesophageal adenocarcinoma.

Barrett's oesophagus is the only known precursor to oesophageal adenocarcinoma, a cancer with very poor prognosis. The main risk factors for Barrett's oesophagus are a history of gastro-oesophageal acid reflux symptoms and obesity. Men, smokers and those with a family history are also at increased risk. Progression from Barrett's oesophagus to cancer occurs via an intermediate stage, known as dysplasia. However, dysplasia and early cancer usually develop without any clinical signs, often in individuals whose symptoms are well controlled by acid suppressant medications; therefore, endoscopic surveillance is recommended to allow for early diagnosis and timely clinical intervention. Individuals with Barrett's oesophagus need to be fully informed about the implications of this diagnosis and the benefits and risks of monitoring strategies. Pharmacological treatments are recommended for control of symptoms, but not for chemoprevention. Dysplasia and stage 1 oesophageal adenocarcinoma have excellent prognoses, since they can be cured with endoscopic or surgical therapies. Endoscopic resection is the most accurate staging technique for early Barrett's-related oesophageal adenocarcinoma. Endoscopic ablation is effective and indicated to eradicate Barrett's oesophagus in patients with dysplasia. Future research should focus on improved accuracy for dysplasia detection via new technologies and providing more robust evidence to support pathways for follow-up and treatment.

METTL3 as a novel diagnosis and treatment biomarker and its association with glycolysis, cuproptosis and ceRNA in oesophageal carcinoma.

METTL3 has been shown to be involved in regulating a variety of biological processes. However, the relationship between METTL3 expression and glycolysis, cuproptosis-related genes and the ceRNA network in oesophageal carcinoma (ESCA) remains unclear. ESCA expression profiles from databases were obtained, and target genes were identified using differential analysis and visualization. Immunohistochemistry (IHC) staining assessed METTL3 expression differences. Functional enrichment analysis using GO, KEGG and GSEA was conducted on the co-expression profile of METTL3. Cell experiments were performed to assess the effect of METTL3 interference on tumour cells. Correlation and differential analyses were carried out to assess the relationship between METTL3 with glycolysis and cuproptosis. qRT-PCR was used to validate the effects of METTL3 interference on glycolysis-related genes. Online tools were utilized to screen and construct ceRNA networks based on the ceRNA theory. METTL3 expression was significantly higher in ESCA compared to the controls. The IHC results were consistent with the above results. Enrichment analysis revealed that METTL3 is involved in multiple pathways associated with tumour development. Significant correlations were observed between METTL3 and glycolysis-related genes and cuproptosis-related gene. Experiments confirmed that interfered with METTL3 significantly inhibited glucose uptake and lactate production in tumour cells, and affected the expression of glycolytic-related genes. Finally, two potential ceRNA networks were successfully predicted and constructed. Our study establishes the association between METTL3 overexpression and ESCA progression. Additionally, we propose potential links between METTL3 and glycolysis, cuproptosis and ceRNA, presenting a novel targeted therapy strategy for ESCA.

Early Diagnostic Markers for Esophageal Squamous Cell Carcinoma: Copy Number Alteration Gene Identification and cfDNA Detection.

The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis revealed widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer data sets. Subsequent validation of 5 candidate markers via ddPCR underscored the efficacy of combined predictive models encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1 in early ESCC screening, as evidenced by the area-under-the-curve values exceeding 0.92 (P < .0001) across various detection contexts. The findings highlighted the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.

Minimal residual disease profiling predicts pathological complete response in esophageal squamous cell carcinoma.

Accurate presurgical prediction of pathological complete response (pCR) can guide treatment decisions, potentially avoiding unnecessary surgeries and improving the quality of life for cancer patients. We developed a minimal residual disease (MRD) profiling approach with enhanced sensitivity and specificity for detecting minimal tumor DNA from cell-free DNA (cfDNA). The approach was validated in two independent esophageal squamous cell carcinoma (ESCC) cohorts. In a cohort undergoing neoadjuvant, surgical, and adjuvant therapy (NAT cohort), presurgical MRD status precisely predicted pCR. All MRD-negative cases (10/10) were confirmed as pCR by pathological evaluation on the resected tissues. In contrast, MRD-positive cases included all the 27 non-pCR cases and only one pCR case (10/10 vs 1/28, P < 0.0001, Fisher's exact test). In a definitive radiotherapy cohort (dRT cohort), post-dRT MRD status was closely correlated with patient prognosis. All MRD-negative patients (25/25) remained progression-free during the follow-up period, while 23 of the 26 MRD-positive patients experienced disease progression (25/25 vs 3/26, P < 0.0001, Fisher's exact test; progression-free survival, P < 0.0001, log-rank test). The MRD profiling approach effectively predicted the ESCC patients who would achieve pCR with surgery and those likely to remain progression-free without surgery. This suggests that the cancer cells in these MRD-negative patients have been effectively eliminated and they could be suitable candidates for a watch-and-wait strategy, potentially avoiding unnecessary surgery.

The United States experience with diagnosing and treating esophageal cancer during the SARS-CoV-2 pandemic: A retrospective cohort study.

The downstream effects on healthcare delivery during the initial wave of the COVID-19 pandemic remain unclear. The purpose of this study was to determine how the healthcare environment surrounding the pandemic affected the oncologic care of patients diagnosed with esophageal cancer. This was a retrospective cohort study evaluating patients in the National Cancer Database (2019-2020). Patients with esophageal cancer diagnoses were divided into pre-pandemic (2019) and pandemic (2020) groups. Patient demographics, cancer-related variables, and treatment modalities were compared. Among 26,231 esophageal cancer patients, 14,024 patients (53.5%) were in the pre-pandemic cohort and 12,207 (46.5%) were in the pandemic cohort. After controlling for demographics, patients diagnosed during the pandemic were more likely to have poorly differentiated tumors (odds ratio [OR] 1.24, 95% confidence interval [CI] 1.08-1.42), pathologic T3 disease compared to T1 (OR 1.25, 95% CI 1.02-1.53), positive lymph nodes on pathology (OR 1.36, 95% CI 1.14-1.64), and to be pathologic stage IV (OR 1.51, 95% CI 1.29-1.76). After controlling for oncologic characteristics, patients diagnosed during the pandemic were more likely to require at least two courses of systemic therapy (OR 1.78, 95% CI 1.48-2.14) and to be offered palliative care (OR 1.13, 95% CI 1.04-1.22). While these patients were offered curative therapy at lower rates, this became non-significant after risk-adjustment (p = .15). The pandemic healthcare environment was associated with significantly increased risk-adjusted rates of patients presenting with advanced esophageal cancer. While this led to significant differences in treatment, most of these differences became non-significant after controlling for oncologic factors.

Salivary metabolomic biomarkers for esophageal and gastric cancers by liquid chromatography-mass spectrometry.

Early detection of esophageal and gastric cancers is essential for patients' prognosis; however, optimal noninvasive screening tests are currently not available. Saliva is a biofluid that is readily available, allowing for frequent screening tests. Thus, we explored salivary diagnostic biomarkers for esophageal and gastric cancers using metabolomic analyses. Saliva samples were collected from patients with esophageal (n = 50) and gastric cancer (n = 63), and patients without cancer as controls (n = 20). Salivary metabolites were analyzed by liquid chromatography-mass spectrometry to identify salivary biomarkers. We also examined the metabolic profiles of gastric cancer tissues and compared them with the salivary biomarkers. The sensitivity of the diagnostic models based on salivary biomarkers was assessed by comparing it with that of serum tumor markers. Additionally, using postoperative saliva samples collected from patients with gastric cancer, we analyzed the changes in the biomarkers' concentrations before and after surgery. Cytosine was detected as a salivary biomarker for gastric cancer, and cytosine, 2-oxoglutarate, and arginine were detected as salivary biomarkers for esophageal cancer. Cytidine, a cytosine nucleotide, showed decreased concentrations in gastric cancer tissues. The sensitivity of the diagnostic models for esophageal and gastric cancers was 66.0% and 47.6%, respectively, while that of serum tumor markers was 40%. Salivary cytosine concentration increased significantly postoperatively relative to the preoperative value. In summary, we identified salivary biomarkers for esophageal and gastric cancers, which showed diagnostic sensitivity at least comparable to that of serum tumor markers. Salivary metabolomic tests could be promising screening tests for these types of cancer.

Genomic instability signals offer diagnostic possibility in early cancer detection.

Emerging evidence from the large numbers of cancer genomes analyzed in recent years indicates that chromosomal instability (CI), a well-established hallmark of cancer cells, is detectable in precancerous lesions. In this opinion, we discuss the association of this instability with tumor progression and cancer risk. We highlight the opportunity that early genomic instability presents for the diagnosis of esophageal adenocarcinoma (EAC) and its precancerous lesion, Barrett's esophagus (BE). With a growing body of evidence suggesting that only a small pool of cancer-related genes are involved in early tumor development, we argue that general genomic instability may hold greater diagnostic potential for early cancer detection as opposed to the identification of individual mutational biomarkers.

ESCCPred: a machine learning model for diagnostic prediction of early esophageal squamous cell carcinoma using autoantibody profiles.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically ideal biomarkers for early diagnosis. The objective of this study was to develop and validate a user-friendly diagnostic tool for early ESCC detection. METHODS: The study encompassed three phases: discovery, verification, and validation, comprising a total of 1309 individuals. Serum autoantibodies were profiled using the HuProtTM human proteome microarray, and autoantibody levels were measured using the enzyme-linked immunosorbent assay (ELISA). Twelve machine learning algorithms were employed to construct diagnostic models, and evaluated using the area under the receiver operating characteristic curve (AUC). The model application was facilitated through R Shiny, providing a graphical interface. RESULTS: Thirteen autoantibodies targeting TAAs (CAST, FAM131A, GABPA, HDAC1, HDGFL1, HSF1, ISM2, PTMS, RNF219, SMARCE1, SNAP25, SRPK2, and ZPR1) were identified in the discovery phase. Subsequent verification and validation phases identified five TAAbs (anti-CAST, anti-HDAC1, anti-HSF1, anti-PTMS, and anti-ZPR1) that exhibited significant differences between ESCC and control subjects (P < 0.05). The support vector machine (SVM) model demonstrated robust performance, with AUCs of 0.86 (95% CI: 0.82-0.89) in the training set and 0.83 (95% CI: 0.78-0.88) in the test set. For early-stage ESCC, the SVM model achieved AUCs of 0.83 (95% CI: 0.79-0.88) in the training set and 0.83 (95% CI: 0.77-0.90) in the test set. Notably, promising results were observed for high-grade intraepithelial neoplasia, with an AUC of 0.87 (95% CI: 0.77-0.98). The web-based implementation of the early ESCC diagnostic tool is publicly accessible at https://litdong.shinyapps.io/ESCCPred/ . CONCLUSION: This study provides a promising and easy-to-use diagnostic prediction model for early ESCC detection. It holds promise for improving early detection strategies and has potential implications for public health.

Prevalence and Predictors of Barrett's Esophagus After Negative Initial Endoscopy: Analysis From Two National Databases.

BACKGROUND & AIMS: Guidelines suggest a single screening esophagogastroduodenoscopy (EGD) in patients with multiple risk factors for Barrett's esophagus (BE). We aimed to determine BE prevalence and predictors on repeat EGD after a negative initial EGD, using 2 large national databases (GI Quality Improvement Consortium [GIQuIC] and TriNetX). METHODS: Patients who underwent at least 2 EGDs were included and those with BE or esophageal adenocarcinoma detected at initial EGD were excluded. Patient demographics and prevalence of BE on repeat EGD were collected. Multivariate logistic regression was performed to assess for independent risk factors for BE detected on the repeat EGD. RESULTS: In 214,318 and 153,445 patients undergoing at least 2 EGDs over a median follow-up of 28-35 months, the prevalence of BE on repeat EGD was 1.7% in GIQuIC and 3.4% in TriNetX, respectively (26%-45% of baseline BE prevalence). Most (89%) patients had nondysplastic BE. The prevalence of BE remained stable over time (from 1 to >5 years from negative initial EGD) but increased with increasing number of risk factors. BE prevalence in a high-risk population (gastroesophageal reflux disease plus ≥1 risk factor for BE) was 3%-4%. CONCLUSIONS: In this study of >350,000 patients, rates of BE on repeat EGD ranged from 1.7%-3.4%, and were higher in those with multiple risk factors. Most were likely missed at initial evaluation, underscoring the importance of a high-quality initial endoscopic examination. Although routine repeat endoscopic BE screening after a negative initial examination is not recommended, repeat screening may be considered in carefully selected patients with gastroesophageal reflux disease and ≥2 risk factors for BE, potentially using nonendoscopic tools.

Algorithm Training and Testing for a Nonendoscopic Barrett's Esophagus Detection Test in Prospective Multicenter Cohorts.

BACKGROUND & AIMS: Endoscopic Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC) detection is invasive and expensive. Nonendoscopic BE/EAC detection tools are guideline-endorsed alternatives. We previously described a 5-methylated DNA marker (MDM) panel assayed on encapsulated sponge cell collection device (CCD) specimens. We aimed to train a new algorithm using a 3-MDM panel and test its performance in an independent cohort. METHODS: Algorithm training and test samples were from 2 prospective multicenter cohorts. All BE cases had esophageal intestinal metaplasia (with or without dysplasia/EAC); control subjects had no endoscopic evidence of BE. The CCD procedure was followed by endoscopy. From CCD cell lysates, DNA was extracted, bisulfite treated, and MDMs were blindly assayed. The algorithm was set and locked using cross-validated logistic regression (training set) and its performance was assessed in an independent test set. RESULTS: Training (N = 352) and test (N = 125) set clinical characteristics were comparable. The final panel included 3 MDMs (NDRG4, VAV3, ZNF682). Overall sensitivity was 82% (95% CI, 68%-94%) at 90% (79%-98%) specificity and 88% (78%-94%) sensitivity at 84% (70%-93%) specificity in training and test sets, respectively. Sensitivity was 90% and 68% for all long- and short-segment BE, respectively. Sensitivity for BE with high-grade dysplasia and EAC was 100% in training and test sets. Overall sensitivity for nondysplastic BE was 82%. Areas under the receiver operating characteristic curves for BE detection were 0.92 and 0.94 in the training and test sets, respectively. CONCLUSIONS: A locked 3-MDM panel algorithm for BE/EAC detection using a nonendoscopic CCD demonstrated excellent sensitivity for high-risk BE cases in independent validation samples. (Clinical trials.gov: NCT02560623, NCT03060642.).

Salivary Extracellular MicroRNAs for Early Detection and Prognostication of Esophageal Cancer: A Clinical Study.

BACKGROUND & AIMS: Early detection of esophageal squamous cell carcinoma (ESCC) will facilitate curative treatment. We aimed to establish a microRNA (miRNA) signature derived from salivary extracellular vesicles and particles (EVPs) for early ESCC detection and prognostication. METHODS: Salivary EVP miRNA expression was profiled in a pilot cohort (n = 54) using microarray. Area under the receiver operator characteristic curve (AUROC) and least absolute shrinkage and selector operation regression analyses were used to prioritize miRNAs that discriminated patients with ESCC from controls. Using quantitative reverse transcription polymerase chain reaction, the candidates were measured in a discovery cohort (n = 72) and cell lines. The prediction models for the biomarkers were derived from a training cohort (n = 342) and validated in an internal cohort (n = 207) and an external cohort (n = 226). RESULTS: The microarray analysis identified 7 miRNAs for distinguishing patients with ESCC from control subjects. Because 1 was not always detectable in the discovery cohort and cell lines, the other 6 miRNAs formed a panel. A signature of this panel accurately identified patients with all-stage ESCC in the training cohort (AUROC = 0.968) and was successfully validated in 2 independent cohorts. Importantly, this signature could distinguish patients with early-stage (stage Ⅰ/Ⅱ) ESCC from control subjects in the training cohort (AUROC = 0.969, sensitivity = 92.00%, specificity = 89.17%) and internal (sensitivity = 90.32%, specificity = 91.04%) and external (sensitivity = 91.07%, specificity = 88.06%) validation cohorts. Moreover, a prognostic signature based on the panel was established and efficiently predicted the high-risk cases with poor progression-free survival and overall survival. CONCLUSIONS: The salivary EVP-based 6-miRNA signature can serve as noninvasive biomarkers for early detection and risk stratification of ESCC. Chinese Clinical Trial Registry, ChiCTR2000031507.

Barrett's Esophagus Risk Factors in Patients Without Gastroesophageal Reflux: A Large Population-Based Study.

Esophageal adenocarcinoma (EAC) is a lethal malignancy with an abysmal 5-year survival rate of <20%.1 Barrett's esophagus (BE) is the only known precursor to EAC.1,2 BE is characterized by intestinal metaplasia of the distal esophagus, typically arising in the setting of gastroesophageal reflux disease (GERD).1 Hence, chronic GERD symptoms are an essential criterion for BE screening in most gastroenterology guidelines, alongside other BE risk factors including age >50 years, male sex, White race, history of tobacco smoking, hiatal hernia (HH) diagnosis, obesity, and family history of BE/EAC in first-degree relatives.1,3 Dysplastic BE and early stage EAC are amenable to endoscopic eradication therapy, highlighting the importance of BE/EAC screening and surveillance.4.

Surveillance in Barrett's Esophagus: Challenges, Progress, and Possibilities.

Endoscopic surveillance of Barrett's esophagus, aiming to detect prevalent dysplasia and adenocarcinoma, followed by effective endoscopic treatment, is an integral part of the esophageal adenocarcinoma prevention paradigm. However, several limitations, such as the subtle appearance of dysplasia, sampling error (inherent in current surveillance protocols), and noncompliance with surveillance recommendations, lead to missed dysplasia and neoplasia, reducing the effectiveness of surveillance as currently practiced. Careful endoscopic assessment with high-resolution white-light endoscopy, dye-based or electronic chromoendoscopy, and comprehensive sampling of the BE mucosa, remains the cornerstone of endoscopic surveillance. Emerging innovations in this area span the gamut of more efficient sampling methods, advanced imaging tools, artificial intelligence, and molecular marker-powered approaches as adjuncts, to identify prevalent and predict incident dysplasia or adenocarcinoma. Development and implementation of validated quality indicators will allow additional advancement of this critical field. These approaches will hopefully enable efficient and effective cancer prevention and treatment.

Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records.

BACKGROUND & AIMS: Tools that can automatically predict incident esophageal adenocarcinoma (EAC) and gastric cardia adenocarcinoma (GCA) using electronic health records to guide screening decisions are needed. METHODS: The Veterans Health Administration (VHA) Corporate Data Warehouse was accessed to identify Veterans with 1 or more encounters between 2005 and 2018. Patients diagnosed with EAC (n = 8430) or GCA (n = 2965) were identified in the VHA Central Cancer Registry and compared with 10,256,887 controls. Predictors included demographic characteristics, prescriptions, laboratory results, and diagnoses between 1 and 5 years before the index date. The Kettles Esophageal and Cardia Adenocarcinoma predictioN (K-ECAN) tool was developed and internally validated using simple random sampling imputation and extreme gradient boosting, a machine learning method. Training was performed in 50% of the data, preliminary validation in 25% of the data, and final testing in 25% of the data. RESULTS: K-ECAN was well-calibrated and had better discrimination (area under the receiver operating characteristic curve [AuROC], 0.77) than previously validated models, such as the Nord-Trøndelag Health Study (AuROC, 0.68) and Kunzmann model (AuROC, 0.64), or published guidelines. Using only data from between 3 and 5 years before index diminished its accuracy slightly (AuROC, 0.75). Undersampling men to simulate a non-VHA population, AUCs of the Nord-Trøndelag Health Study and Kunzmann model improved, but K-ECAN was still the most accurate (AuROC, 0.85). Although gastroesophageal reflux disease was strongly associated with EAC, it contributed only a small proportion of gain in information for prediction. CONCLUSIONS: K-ECAN is a novel, internally validated tool predicting incident EAC and GCA using electronic health records data. Further work is needed to validate K-ECAN outside VHA and to assess how best to implement it within electronic health records.

Magnitude and Time-Trends of Post-Endoscopy Esophageal Adenocarcinoma and Post-Endoscopy Esophageal Neoplasia in a Population-Based Cohort Study: The Nordic Barrett's Esophagus Study.

BACKGROUND & AIMS: Post-endoscopy esophageal adenocarcinoma (PEEC) and post-endoscopy esophageal neoplasia (PEEN) undermine early cancer detection in Barrett's esophagus (BE). We aimed to assess the magnitude and conduct time-trend analysis of PEEC and PEEN among patients with newly diagnosed BE. METHODS: This population-based cohort study was conducted in Denmark, Finland, and Sweden between 2006 and 2020 and included 20,588 patients with newly diagnosed BE. PEEC and PEEN were defined as esophageal adenocarcinoma (EAC) or high-grade dysplasia (HGD)/EAC, respectively, diagnosed 30-365 days from BE diagnosis (index endoscopy). HGD/EAC diagnosed from 0-29 days and HGD/EAC diagnosed >365 days from BE diagnosis (incident HGD/EAC) were assessed. Patients were followed up until HGD/EAC, death, or end of study period. Incidence rates (IR) per 100,000 person-years with 95% confidence interval (95% CI) were calculated using Poisson regression. RESULTS: Among 293 patients diagnosed with EAC, 69 (23.5%) were categorized as PEEC, 43 (14.7%) as index EAC, and 181 (61.8%) as incident EAC. The IRs/100,000 person-years for PEEC and incident EAC were 392 (95% CI, 309-496), and 208 (95% CI, 180-241), respectively. Among 279 patients diagnosed with HGD/EAC (Sweden only), 17.2% were categorized as PEEN, 14.6% as index HGD/EAC, and 68.1% as incident HGD/EAC. IRs/100,000 person-years for PEEN, and incident HGD/EAC were 421 (95% CI, 317-558), and 285 (95% CI, 247-328), respectively. Sensitivity analyses that varied time interval for occurrence of PEEC/PEEN demonstrated similar results. A time-trend analysis for IRs demonstrated rising incidence rates of PEEC/PEEN. CONCLUSIONS: Almost a quarter of all EACs are detected within a year after an ostensibly negative upper endoscopy in patients with newly diagnosed BE. Interventions to improve detection may reduce PEEC/PEEN rates.

Comparison of Effective Imaging Modalities for Detecting Gastric Neoplasms: A Randomized 3-Arm Phase II Trial.

INTRODUCTION: The early detection of gastric neoplasms (GNs) leads to favorable treatment outcomes. The latest endoscopic system, EVIS X1, includes third-generation narrow-band imaging (3G-NBI), texture and color enhancement imaging (TXI), and high-definition white-light imaging (WLI). Therefore, this randomized phase II trial aimed to identify the most promising imaging modality for GN detection using 3G-NBI and TXI. METHODS: Patients with scheduled surveillance endoscopy after a history of esophageal cancer or GN or preoperative endoscopy for known esophageal cancer or GN were randomly assigned to the 3G-NBI, TXI, or WLI groups. Endoscopic observations were performed to detect new GN lesions, and all suspected lesions were biopsied. The primary endpoint was the GN detection rate during primary observation. Secondary endpoints were the rate of missed GNs, early gastric cancer detection rate, and positive predictive value for a GN diagnosis. The decision rule had a higher GN detection rate between 3G-NBI and TXI, outperforming WLI by >1.0%. RESULTS: Finally, 901 patients were enrolled and assigned to the 3G-NBI, TXI, and WLI groups (300, 300, and 301 patients, respectively). GN detection rates in the 3G-NBI, TXI, and WLI groups were 7.3, 5.0, and 5.6%, respectively. The rates of missed GNs were 1.0, 0.7, and 1.0%, the detection rates of early gastric cancer were 5.7, 4.0, and 5.6%, and the positive predictive values for the diagnosis of GN were 36.5, 21.3, and 36.8% in the 3G-NBI, TXI, and WLI groups, respectively. DISCUSSION: Compared with TXI and WLI, 3G-NBI is a more promising modality for GN detection.