Addition of p53 IHC significantly improves the histological assessment of BO biopsies, even within a group of dedicated GI pathologists. It decreases the proportion of IND diagnoses, and increases interobserver agreement and diagnostic accuracy. This justifies the use of accessory p53 IHC within our upcoming national digital review panel for BO biopsy cases.
<b>Background and study aims:</b> There is a risk for lymph node metastases (LNM) after endoscopic resection of early esophageal adenocarcinoma (EAC). The aim of this study was to develop and internally validate a prediction model that estimates the individual metastases risk in patients with pT1b EAC.
<b>Patients and methods:</b> This is a nationwide, retrospective, multicenter cohort study. Patients with pT1b EAC and treated with endoscopic resection and/or surgery between 1989 and 2016 were included. Primary endpoint was the presence of LNM in surgical resection specimen or the detection of metastases during follow-up. All resection specimens were histologically reassessed by specialized gastrointestinal pathologists. Subdistribution hazard regression analysis was used to develop a prediction model. The discriminative ability of this model was assessed using the c-statistic.
<b>Results:</b> 248 patients with pT1b EAC were included. Metastases were seen in 78 patients, and the 5-year cumulative incidence was 30.9% (95% CI 25.1%-36.8%). The risk for metastases increased with submucosal invasion depth (subdistribution hazard ratio [SHR] 1.08, 95% CI 1.02-1.14, for every increase of 500 μm), for tumors with lymphovascular invasion (SHR 2.95, 95% CI 1.95-4.45) and for larger tumors (SHR 1.23, 95% CI 1.10-1.37, for every increase of 10 mm). The model demonstrated a good discriminative ability (c-statistic 0.81, 95% CI 0.75-0.86).
<b>Conclusions:</b> One third of patients with pT1b EAC experienced metastases within 5 years. The probability for developing post resection metastases can be estimated with a personalized predicted risk score incorporating tumor invasion depth, tumor size and lymphovascular invasion. This model needs to be externally validated before implementation into clinical practice.
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