Individual risk calculator to predict lymph node metastases in patients with submucosal (T1b) esophageal adenocarcinoma: a multicenter cohort study

Background Lymph node metastasis (LNM) is possible after endoscopic resection of early esophageal adenocarcinoma (EAC). This study aimed to develop and internally validate a prediction model that estimates the individual risk of metastases in patients with pT1b EAC. Methods A nationwide, retrospective, multicenter cohort study was conducted in patients with pT1b EAC treated with endoscopic resection and/or surgery between 1989 and 2016. The primary end point was presence of LNM in surgical resection specimens or detection of metastases during follow-up.All resection specimens were histologically reassessed by specialist gastrointestinal pathologists. Subdistribution hazard regression analysis was used to develop the prediction model. The discriminative ability of this model was assessed using the c-statistic. Results 248 patients with pT1b EAC were included. Metastases were seen in 78 patients, and the 5-year cumulative incidence was 30.9% (95% confidence interval [CI] 25.1%-36.8%). The risk of metastases increased with submucosal invasion depth (subdistribution hazard ratio [SHR] 1.08, 95%CI 1.02-1.14, for every increase of 500 mu m), 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 10mm). The model demonstrated good discriminative ability (c-statistic 0.81, 95%CI 0.75-0.86). Conclusions A third of patients with pT1b EAC experienced metastases within 5 years. The probability of developing post-resection metastases was estimated with a personalized predicted risk score incorporating tumor invasion depth, tumor size, and lymphovascular invasion. This model requires external validation before implementation into clinical practice.

Automated summary

This study focused on predicting the risk of lymph node metastasis in patients with pT1b EAC after endoscopic resection or surgery. Factors like submucosal invasion depth, tumor size, and lymphovascular invasion were found to be associated with an increased risk of metastases. The developed prediction model demonstrated good discriminative ability in estimating the probability of post-resection metastases.