The Long-Term Outcomes of Surgery Versus Endoscopic Treatment in Patients With Siewert Type II T1M0N0 Adenocarcinoma of the Esophagogastric Junction

Chen, Han; Yu, Xin; Yang, Ruoyun; Li, Shuo; Zhang, Guoxin; Si, Xiaoyan; Zhou, Xiaoying

doi:10.1177/10732748221143389

Cited by 4 publications

(6 citation statements)

References 33 publications

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“…Chen et al ( 38 ) found that the procedure speed of ESD for early AEG is slower than that for early gastric carcinoma, possibly due to AEG extending beyond the cardia, including the angle of His. However, endoscopic treatment (including ESD) remains an effective alternative to surgery for the treatment of early AEG based on comparable long-term outcomes ( 18 , 20 ). With the advancements in endoscopic treatment, early AEG can be effectively resected by EMR/ESD with fewer complications, better preservation of gastric function, a shorter duration of hospital stay, and a lower cost compared with traditional gastrectomy or esophagectomy ( 16 , 17 ).…”

Section: Discussionmentioning

confidence: 99%

“…Chen et al (38) found that the procedure speed of ESD for early AEG is slower than that for early gastric carcinoma, possibly due to AEG extending beyond the cardia, including the angle of His. However, endoscopic treatment (including ESD) remains an effective alternative to surgery for the treatment of early AEG based on comparable longterm outcomes (18,20). With the advancements in endoscopic For the differentiation variable, well-differentiated is defined as 1, moderately differentiated is defined as 2, and poorly differentiated or undifferentiated is defined as 3.…”

Section: Discussionmentioning

confidence: 99%

“…Endoscopic treatment is gaining acceptance because it is more tolerable, especially in elderly patients. Chen et al (20) revealed that endoscopic treatment may be considered in patients aged 65 years or those with submucosal (T1b stage) cancer of the AEG. It has been widely accepted that LNM is an important prognostic factor for patients with Siewert type II AEG.…”

Section: Discussionmentioning

confidence: 99%

“…However, with gastrointestinal endoscopy screening, patients with digestive tract cancer are diagnosed at an early stage, making it possible to treat early AEG without lymphatic and organ metastasis by endoscopy. The endoscopic resection of superficial AEG, such as endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD), is considered safe and effective (16)(17)(18)(19)(20)(21). Endoscopic resection techniques are increasingly being employed for early AEG, leading to a reduction in the morbidity and mortality associated with gastrectomy or esophagectomy and an improvement in the quality of life (16).…”

Section: Introductionmentioning

confidence: 99%

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

Lu,

Liu,

Yin

et al. 2024

Front. Med.

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BackgroundLymph 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.MethodsA 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.ResultsPatients 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.ConclusionThe 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.

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Section: Discussionmentioning

confidence: 99%

“…Chen et al (38) found that the procedure speed of ESD for early AEG is slower than that for early gastric carcinoma, possibly due to AEG extending beyond the cardia, including the angle of His. However, endoscopic treatment (including ESD) remains an effective alternative to surgery for the treatment of early AEG based on comparable longterm outcomes (18,20). With the advancements in endoscopic For the differentiation variable, well-differentiated is defined as 1, moderately differentiated is defined as 2, and poorly differentiated or undifferentiated is defined as 3.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Lu,

Liu,

Yin

et al. 2024

Front. Med.

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“…In the literature, there are several comparative studies of the results of endoscopic resections and those of MIS. Chen et al [ 13 ], performed a propensity study to evaluate the survival of patients treated by the two types of approaches and found that no significant difference was observed in the 5-year cumulative incidence of cancer-specific death between the cohorts and that the type of treatment was not a prognostic factor [hazard ratio (HR) = 1.51, 95% confidence interval (95%CI): 0.81-2.81, P = 0.20) in multivariate Cox analysis. Similar results were reported by other authors: Overall survival (OS) rates at 5 years were not statistically significantly different (93.9% vs 97.3%)[ 14 ], in another study (93.3 vs 92.9%; P = 0.282)[ 15 ], concluding that endoscopic submucosal dissection (ESD) may be an effective alternative to surgery, for the treatment of early GOJ cancer.…”

Section: Indications and Types Of Mis For Goj Adenocarcinomamentioning

confidence: 99%

Minimally invasive surgery for gastro-oesophageal junction adenocarcinoma: Current evidence and future perspectives

Bîrlă,

Hoara,

Achim

et al. 2023

World J Gastrointest Oncol

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Minimally invasive surgery is increasingly indicated in the management of malignant disease. Although oesophagectomy is a difficult operation, with a long learning curve, there is actually a shift towards the laparoscopic/thoracoscopic/ robotic approach, due to the advantages of visualization, surgeon comfort (robotic surgery) and the possibility of the whole team to see the operation as well as and the operating surgeon. Although currently there are still many controversial topics, about the surgical treatment of patients with gastro-oesophageal junction (GOJ) adenocarcinoma, such as the type of open or minimally invasive surgical approach, the type of oesophago-gastric resection, the type of lymph node dissection and others, the minimally invasive approach has proven to be a way to reduce postoperative complications of resection, especially by decreasing pulmonary complications. The implementation of new technologies allowed the widening of the range of indications for this type of surgical approach. The short-term and long-term results, as well as the benefits for the patient - reduced surgical trauma, quick and easy recovery - offer this type of surgical treatment the premises for future development. This article reviews the updates and perspectives on the minimally invasive approach for GOJ adenocarcinoma.

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Construction and validation of nomograms to predict overall survival and cancer-specific survival in patients with gastroesophageal junction cancer of no distant metastasis

Zhang,

Qiang,

Shi

et al. 2023

Preprint

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Background Gastroesophageal junction (GEJ) cancer is a distinctive type because of its site of incidence, our study aimed to explore the factors affecting the overall survival (OS) and cancer-specific survival (CSS) in patients with GEJ cancer of no distant metastasis and to construct nomogram model to predict the prognosis. Methods Patients with GEJ cancer of no distant metastases were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomized into two cohorts in a 7:3 ratio. Univariate and multivariate Cox regression analyses were performed to determine the OS and CSS risk factors, and nomograms were constructed utilizing these factors. The C-index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to validate the reliability of the model. Results 3,831 GEJ cancer patients without distant metastases were enrolled in the study; 2,686 of these patients were in the training cohort and 1,145 were in the validation cohort. In the training cohort, the result of the multivariate Cox proportional hazards regression model demonstrated that age, histological grading, T-stage, N-stage, and primary site surgery were independent factors for OS. As for CSS, in addition to the appeal factors, the number of tumors was also an independent influencing factor, The C-index of OS and CSS predicted by nomogram models were 0.681 (95% CI: 0.668–0.694) and 0.707 (95% CI: 0.693–0.721). Based on the result of calibration curve and ROC, the nomogram model was able to predict the prognosis of GEJ cancer without distant metastases with accuracy. Up to a certain point, DCA showed a good net advantage of the model in predicting patient survival over a wide range. Conclusion The nomogram prediction model had been validated to have good predictive and clinical application value, which can accurately predict survival rates and inform individualized treatment decisions in patients with GEJ cancer without distant metastases.

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The Long-Term Outcomes of Surgery Versus Endoscopic Treatment in Patients With Siewert Type II T1M0N0 Adenocarcinoma of the Esophagogastric Junction

Cited by 4 publications

References 33 publications

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

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

Minimally invasive surgery for gastro-oesophageal junction adenocarcinoma: Current evidence and future perspectives

Construction and validation of nomograms to predict overall survival and cancer-specific survival in patients with gastroesophageal junction cancer of no distant metastasis

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