Comparable long-term outcomes after endoscopic therapy and gastrectomy of early adenocarcinoma of esophagogastric junction: a population-based study

Comparable long-term survival outcomes after endoscopic and gastrectomy treatment of pT1acN0M0 gastric adenocarcinoma in patients who met the expanded criteria

BACKGROUND

Whether the Western pT1acN0M0 gastric cancer (GC) patients who met the Japanese expanded criteria could be the candidates for endoscopic treatment (ET) remains unclear because of unknown long-term survival outcomes.

METHODS

A retrospective cohort study using data from the Surveillance, Epidemiology, and End Results (SEER) program was performed. The survival differences between pT1acN0M0 gastric adenocarcinoma patients who received ET or gastrectomy treatment (GT) were evaluated using multivariate survival analysis.

RESULTS

A total of 314 pT1acN0M0 gastric adenocarcinoma patients who met the expanded criteria were included, 46 patients received ET and 268 patients received GT. pT1acN0M0 gastric adenocarcinoma patients met the expanded criteria underwent ET experienced a similar hazard of cancer-specific death compared with those underwent GT both in the multivariate Cox survival analysis (adjusted hazard ratio [HR]; 1.18, 95% confidence interval [CI] 0.40-3.49; P = 0.766) and the multivariate competing risk model (subdistribution HR [SHR], 1.12, 95% CI 0.38-3.29; P = 0.845). The result that pT1acN0M0 gastric adenocarcinoma patients met the expanded criteria underwent ET experienced comparable survival outcomes to those who underwent GT did not change even compared with those who underwent GT with > 15 lymph nodes examined (adjusted HR, 1.55, 95% CI 0.44-5.49; P = 0.499; SHR, 1.47, 95% CI 0.44-4.88; P = 0.532).

CONCLUSIONS

The ET can be considered in Western pT1acN0M0 gastric adenocarcinoma patients who met the Japanese expanded criteria. However, a prospective study should be warranted.

The development and validation of automated machine learning models for predicting lymph node metastasis in Siewert type II T1 adenocarcinoma of the esophagogastric junction

Background

Lymph node metastasis (LNM) is considered an essential prognosis factor for adenocarcinoma of the esophagogastric junction (AEG), which also affects the treatment strategies of AEG. We aimed to evaluate automated machine learning (AutoML) algorithms for predicting LNM in Siewert type II T1 AEG.

Methods

A total of 878 patients with Siewert type II T1 AEG were selected from the Surveillance, Epidemiology, and End Results (SEER) database to develop the LNM predictive models. The patients from two hospitals in Suzhou were collected as the test set. We applied five machine learning algorithms to develop the LNM prediction models. The performance of predictive models was assessed using various metrics including accuracy, sensitivity, specificity, the area under the curve (AUC), and receiver operating characteristic (ROC) curve.

Results

Patients with LNM exhibited a higher proportion of male individuals, a poor degree of differentiation, and submucosal infiltration, with statistical differences. The deep learning (DL) model demonstrated relatively good accuracy (0.713) and sensitivity (0.868) among the five models. Moreover, the DL model achieved the highest AUC (0.781) and sensitivity (1.000) in the test set.

Conclusion

The DL model showed good predictive performance among five AutoML models, indicating the advantage of AutoML in modeling LNM prediction in patients with Siewert type II T1 AEG.