Prognostic value of the extent of lymphadenectomy for esophageal cancer-specific survival among T1 patients

Extensive lymphadenectomy may improve survival in node negative oesophageal cancer

Lymph node metastases are a major prognostic factor in survival of patients with oesophageal cancer. The number of lymph nodes removed during oesophagectomy has been previously proven to be associated with improved survival. The aim of this study was to examine the effect of lymph node harvest on survival specifically in pathologically node negative (pN0) patients with oesophageal cancer. Data were extracted from a prospectively populated single-surgeon database of oesophageal resections for cancer. All consecutive patients with pN0 were included. Patient-specific risk adjusted analysis of overall and disease-free survival was performed to identify the number of lymph nodes associated with improved survival. Inclusion criteria were met by 137 patients (49 squamous cell carcinoma and 88 adenocarcinoma). Adjusted for cancer stage, tumour (histological type, degree of differentiation, lympho-vascular invasion, neo-adjuvant therapy) and patient related factors (age, sex), increased lymph node number was associated with significant improvement in overall (P = 0.045) and disease free (P = 0.030) survival. Lymph node count ≥ 17 was associated with improved overall and disease-free survival. In this cohort of patients with pathologically node-negative oesophageal cancer, lymph node count of 17 or above was associated with significantly improved survival.

Mapping of Lymph Node Metastasis and Efficacy Index in Thoracic Esophageal Squamous Cell Carcinoma: A Large-Scale Retrospective Analysis

BACKGROUND

Esophageal squamous cell carcinoma has a high mortality rate in China. The metastatic pattern in the lymph nodes and the value of their dissection on the overall survival of these patients remain controversial. The primary aim of this study was to provide a basis for accurate staging of esophageal cancer and to identify the relationship between esophageal cancer surgery, lymph node dissection, and overall survival rates.

METHODS

We utilized our hospital database to retrospectively review the data of 1727 patients with esophageal cancer who underwent R0 esophagectomy from January 2010 to December 2017. The lymph nodes were defined according to Japanese Classification of Esophageal Cancer, 11th Edition. The Efficacy Index (EI) was calculated by multiplying the frequency (%) of metastases to a zone and the 5-year survival rate (%) of patients with metastases to that zone, and then dividing by 100.

RESULTS

The EI was high in the supraclavicular and mediastinal zones in patients with upper esophageal tumors, and the EI of 101R was 17.39, which was the highest among the lymph node stations. In patients with middle esophageal tumors, the EI was highest in the mediastinal zone, followed by the celiac and supraclavicular zones. Furthermore, the EI was highest in the celiac zone, followed by the mediastinal zones in patients with lower esophageal tumors.

CONCLUSIONS

The EI of resected lymph nodes was found to vary between stations and was related to the primary location of the tumor.

Artificial intelligence-based computer-aided diagnosis system supports diagnosis of lymph node metastasis in esophageal squamous cell carcinoma: A multicenter study

Background

This study aimed to develop an artificial intelligence-based computer-aided diagnosis system (AI-CAD) emulating the diagnostic logic of radiologists for lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC) patients, which contributed to clinical treatment decision-making.

Methods

A total of 689 ESCC patients with PET/CT images were enrolled from three hospitals and divided into a training cohort and two external validation cohorts. 452 CT images from three publicly available datasets were also included for pretraining the model. Anatomic information from CT images was first obtained automatically using a U-Net-based multi-organ segmentation model, and metabolic information from PET images was subsequently extracted using a gradient-based approach. AI-CAD was developed in the training cohort and externally validated in two validation cohorts.

Results

The AI-CAD achieved an accuracy of 0.744 for predicting pathological LNM in the external cohort and a good agreement with a human expert in two external validation cohorts (kappa = 0.674 and 0.587, p < 0.001). With the aid of AI-CAD, the human expert's diagnostic performance for LNM was significantly improved (accuracy [95% confidence interval]: 0.712 [0.669-0.758] vs. 0.833 [0.797-0.865], specificity [95% confidence interval]: 0.697 [0.636-0.753] vs. 0.891 [0.851-0.928]; p < 0.001) among patients underwent lymphadenectomy in the external validation cohorts.

Conclusions

The AI-CAD could aid in preoperative diagnosis of LNM in ESCC patients and thereby support clinical treatment decision-making.

Development and validation of the novel subclassification of pN3 for patients with esophageal cancer

Background

Patients with stage pN3 esophageal cancer (EC) have a large number of metastatic lymph nodes (mLNs) and have poor prognosis. This study was to elucidate whether subclassification of pN3 according to the number of mLNs could improve the discrimination ability of EC patients.

Methods

This study retrospectively analyzed patients with pN3 EC from the Surveillance, Epidemiology, and End Results (SEER) database as a training cohort and SEER validation cohort. Patients with pN3 esophageal cancer from the Affiliated Cancer Hospital of Harbin Medical University were used as the validation cohort. The optimal cutoff value of mLNs was identified using the X-tile software, and group pN3 into pN3-I and pN3-II based on mLNs. Kaplan-Meier method and log-rank test were used to analyze the disease-specific survival (DSS). The Cox proportional hazards regression analysis was used to identify the independent prognostic factors.

Results

For the training cohort, patients with 7 to 9 mLNs were categorized as pN3-I, while those with more than 9 mLNs were categorized as pN3-II. There were 183 (53.8%) pN3-I and 157 (46.2%) pN3-II. The 5-year DSS rates of pN3-I and pN3-II in the training cohort were 11.7% and 5.2% (P=0.033), and the pN3 subclassification was an independent risk factor associated with patient prognosis. More RLNs may not improve patient prognosis, but the use of mLNs/RLNs is effective in predicting patient prognosis. Furthermore, the pN3 subclassification was well validated in the validation cohort.

Conclusion

Subclassification of pN3 can better distinguish survival differences in EC patients.

Contributing factors to lymph node recovery with esophagectomy by thoracic surgeons: an analysis of the Society of Thoracic Surgeons General Thoracic Surgery Database

Given the association between lymphadenectomy and survival after esophagectomy, and the ongoing development of effective adjuvant protocols for identified residual disease, we determined factors contributing to lymph node yield and effects on postoperative morbidity following esophagectomy by thoracic surgeons. Using the Society of Thoracic Surgeons General Thoracic Surgery Database, all patients who underwent esophagectomy for primary esophageal cancer with gastric conduit reconstruction from 2012 to 2016 were identified. Patient demographics, technical factors, and tumor characteristics associated with lymph node yield were determined using a multivariable multilevel mixed-effects regression model. Associations between lymph node yield and perioperative morbidity and mortality were similarly assessed. A total of 8480 patients were included. The median number of nodes harvested was 16 [Interquartile Range 11-22]. Factors associated with fewer nodes included female gender (b=-0.53, P=0.032), body mass index <18.5 (b=-1.46, P=0.012), prior cardiothoracic surgery (b=-0.73, P=0.015), intraoperative blood transfusion (b=-1.43, P<0.001), squamous cell histology (b=-0.86, P=0.006), and neoadjuvant treatment (b=-1.41, P<0.001). Operative approach significantly affected lymph node yield, with minimally invasive approaches demonstrating higher lymph node counts, and open transhiatal esophagectomy recovering the fewest nodes. Findings were independent of clinical center. There was no association of higher lymph node yield with 30-day mortality, with only slightly increased risk for chyle leak (odds ratio [OR] 1.02, P=0.012). In conclusion, several patient and tumor factors affect lymph node recovery with esophagectomy, independent of hospital center. Technical aspects, specifically minimally invasive approach, play a significant role in quantified lymph node yield. Higher operative lymph node yield was associated with minimal increased morbidity.

The minimum number of examined lymph nodes for accurate nodal staging and optimal survival of stage T1-2 esophageal squamous cell carcinoma: A retrospective multicenter cohort with SEER database validation

BACKGROUND

The extent of lymphadenectomy during esophagectomy remains controversial for patients with T1-2 ESCC. The aim of this study was to identify the minimum number of examined lymph node (ELN) for accurate nodal staging and overall survival (OS) of patients with T1-2 esophageal squamous cell carcinoma (ESCC).

MATERIALS AND METHODS

Patients with T1-2 ESCC from three institutes between January 2011 and December 2020 were retrospectively reviewed. The associations of ELN count with nodal migration and OS were evaluated using multivariable models, and visualized by using locally weighted scatterplot smoothing (LOWESS). Chow test was used to determine the structural breakpoints of ELN count. External validation in the SEER database was performed.

RESULTS

In total, 1537 patients were included. Increased ELNs was associated with an increased likelihood of having positive nodal disease and incremental OS. The minimum numbers of ELNs for accurate nodal staging and optimal survival were 14 and 18 with validation in the SEER database (n = 519), respectively. The prognostic prediction ability of N stage was improved in the group with ≥14 ELNs compared with those with fewer ELNs (iAUC, 0.70 (95%CI 0.66-0.74) versus 0.61(95%CI 0.57-0.65)). The higher prognostic value was found for patients with ≥18 ELNs than those with <18 ELNs (iAUC, 0.78 (95%CI 0.74-0.82) versus 0.73 (95%CI 0.7-0.77)).

CONCLUSION

The minimum numbers of ELNs for accurate nodal staging and optimal survival of stage T1-2 ESCC patients were 14 and 18, respectively.