Epidemiology of Postoperative Complications After Esophagectomy: Implications for Management

Efficacy evaluation and prognostic prediction of endoscopic ultrasound for neoadjuvant immunotherapy in esophageal cancer

BACKGROUND AND OBJECTIVES

Neoadjuvant immunotherapy combined with chemotherapy or chemoradiotherapy has emerged as a promising approach in the treatment of esophageal cancer. However, there is a lack of comprehensive understanding regarding the clinical factors that can predict patient response to this therapy. The aim of this study was to develop a predictive model for assessing the efficacy of neoadjuvant immunotherapy in patients undergoing surgical treatment.

METHODS

This study retrospectively enrolled 220 consecutive patients with preoperative immunotherapy combined chemotherapy or chemoradiotherapy. A logistic regression was used to evaluate the association between pathologic complete response (pCR) and endoscopic ultrasound parameters, constructing a predictive model for treatment response. Additional, overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method, and Cox regression analyses were introduced to explore the associations between EUS factors after neoadjuvant immunotherapy.

RESULTS

Logistic regression analysis identified that the significant predictors of pCR were treatment regimen, negative biopsy findings, RECIST assessment, endoscopic ultrasound responder, and downstaging in uN. A predictive model including above five variables was generated, and area under the curve was 0.840(95%CI 0.78-0.89), this nomogram was also adequately validated internally. In the cox regression analyses, EUS responder was found to be a significant predictor of overall survival with a hazard ratio (HR) of 0.38(95%CI 0.15-0.98), whereas only pCR status was a significant predictor of PFS (HR 0.80; 95%CI 0.01-0.60).

CONCLUSIONS

EUS responder can serve as a valuable predictor of the efficacy of adjuvant immunotherapy combined with chemotherapy or chemoradiotherapy, as well as of survival outcomes.

Automated machine learning model for predicting anastomotic strictures after esophageal cancer surgery: a retrospective cohort study

BACKGROUND

Anastomotic strictures (AS) frequently occurs in patients following esophageal cancer surgery, significantly affecting their long-term quality of life. This study aims to develop a machine learning model to predict high-risk AS, enabling early intervention and precise management.

METHODS

A total of 1549 patients underwent radical esophageal cancer surgery and were split into a training set (1084) and a validation set (465). Adaptive Synthetic Sampling (ADASYN) handled class imbalance, while Boruta and Least Absolute Shrinkage and Selection Operator (LASSO) with cross-validation refined key features. High-correlation features (r > 0.8) were assessed using variance inflation factors (VIFs) and clinical relevance. Machine learning models were trained and evaluated using area under curve (AUC), accuracy, sensitivity, specificity, calibration curves, and decision curve analysis (DCA). Shapley Additive exPlanations (SHAP) analysis improved model interpretability.

RESULTS

Seven critical variables were finalized, including anastomotic leakage (AL), neoadjuvant therapy (NCRT), suture method (SM), endoscopic assistance (EA), white blood cell count (WBC), albumin (Alb), and Suture site (SS). The Gradient Boosting Machine (GBM) model achieved the highest AUC, with 0.886 in the training set and 0.872 in the validation set. Shapley Additive Explanations (SHAP) analysis indicated that AL, SM, and NCRT were the most significant variables for model predictions.

CONCLUSION

The GBM machine learning model constructed in this study can effectively identify high-risk patients for AS following esophageal cancer surgery, offering strong support for earlier postoperative detection and precise clinical management.

Towards personalized care in minimally invasive esophageal surgery: An adverse events prediction model

This letter addressed the impactful study by Zhong et al, which introduced a risk prediction and stratification model for surgical adverse events following minimally invasive esophagectomy. By identifying key risk factors such as chronic obstructive pulmonary disease and hypoalbuminemia, the model demonstrated strong predictive accuracy and offered a pathway to personalized perioperative care. This correspondence highlighted the clinical significance, emphasizing its potential to optimize patient outcomes through tailored interventions. Further prospective validation and application across diverse settings are essential to realize its full potential in advancing esophageal surgery practices.

Perioperative Risk Factors for New-Onset Perioperative Atrial Fibrillation Following Minimally Invasive Esophagectomy: A Single-Center Retrospective Study

BACKGROUND

Atrial fibrillation (AF) is the most common cardiovascular complication following esophagectomy. The aim of this study was to identify the risk factors for new-onset perioperative (intraoperative and/or postoperative) AF in patients undergoing minimally invasive esophagectomy (MIE).

METHODS

This study used a single-center retrospective design and included 814 patients who were diagnosed with esophageal cancer and underwent McKeown MIE. The patients' characteristics and perioperative data were collected from the electronic medical records and analyzed.

RESULTS

New-onset perioperative AF occurred in 5.3% of the patients (43/814), with 4 patients developing intraoperative AF and 39 patients developing postoperative AF. Multivariate logistic regression analysis identified age (odds ratio [OR] 1.081 and p < 0.001), history of coronary heart disease (OR 4.269 and p < 0.001), and intraoperative blood loss (OR 1.004 and p = 0.008) as independent risk factors for perioperative AF following MIE. The area under the receiver operating characteristic curve for the multivariate logistic regression model was 0.735 (95% confidence interval 0.660-0.810). The incidences of postoperative pulmonary complications and anastomotic leakage were significantly higher in patients with perioperative AF than in those without perioperative AF (both p = 0.011). Patients with perioperative AF also had a longer hospital stay (15.0 vs. 13.0 days and p = 0.034).

CONCLUSIONS

Increasing age, history of coronary heart disease, and intraoperative blood loss were associated with new-onset perioperative AF following MIE. However, the impact of intraoperative blood loss on AF is likely to be of marginal clinical relevance. The observed AF fell below projected estimates, resulting in inadequate statistical power for the study outcomes.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (No. ChiCTR2300074003; date of registration, 27/07/2023).

Risk and management of adverse events in minimally invasive esophagectomy

Minimally invasive esophagectomy (MIE) has transformed esophageal surgery by reducing morbidity, accelerating recovery, and improving postoperative outcomes compared to traditional open esophagectomy. By utilizing techniques such as laparoscopic, thoracoscopic, and robotic-assisted approaches, MIE minimizes surgical trauma while maintaining oncological thoroughness. However, it also presents unique challenges, including risks of complications such as anastomotic leakage, pulmonary complications, and atrial fibrillation. Zhong et al developed and validated a risk stratification model for predicting surgical adverse events after MIE, enhancing preoperative assessment and patient management. This editorial further examines the advantages of MIE, its comparable oncological and long-term outcomes, as well as the incidence and contributing factors of postoperative complications. Emerging technologies, including machine learning models, intraoperative nerve monitoring, and robotic-assisted surgery, are highlighted as innovative solutions for risk prediction and prevention. Strategies such as enhanced recovery after surgery protocols and multidisciplinary collaboration are emphasized for their critical roles in minimizing complications and optimizing patient outcomes. By addressing these aspects, this editorial provides guidance to surgical teams in maximizing the benefits of MIE while effectively managing its associated risks.

Effects of Postoperative Complications on Overall Survival Following Esophagectomy: A Meta-Analysis Using the Restricted Mean Survival Time Analysis

OBJECTIVE

This study aims to conduct a comprehensive meta-analysis of the effects of postoperative complications (PCs) on survival following esophagectomy using the restricted mean survival time (RMST) analysis.

METHODS

A systematic literature search was performed in PubMed, Embase, Web of Science, Cochrane, and Medline, including articles published up to July 2024. Data were reconstructed from Kaplan-Meier curves, and the difference in RMST (RMSTD) and the RMST/restricted mean time loss (RMTL) ratios were calculated to examine the effects of PCs on overall survival.

RESULTS

A total of 12 articles, including 7925 patients, met the inclusion criteria. RMSTD estimates indicate that patients with overall PCs survived an average of 0.04 years shorter (RMSTD = -0.04, 95% CI: -0.06, -0.03) than those without PCs at the 1-year follow-up and 0.39 years shorter (RMSTD = -0.39, 95% CI: -0.55, -0.22) at the 5-year follow-up. Patients with anastomotic leaks survived an average of 0.34 years shorter (RMSTD = -0.34, 95% CI: -0.49, -0.19), and patients with pulmonary complications survived an average of 0.63 years shorter (RMSTD = -0.63, 95% CI: -0.81, -0.45) at the 5-year follow-up. Additionally, RMTL ratios were estimated to be 1.21 (95% CI: 1.12, 1.31) for overall PCs, 1.19 (95% CI: 1.11, 1.28) for anastomotic leaks, and 1.53 (95% CI: 1.36, 1.73) for pulmonary complications at the 5-year follow-up, respectively.

CONCLUSIONS

Our findings quantified the annual negative impact of PCs of esophageal cancer on overall patient survival following esophagectomy. Increased efforts are needed to enhance prevention, early screening, and timely treatment for complications, particularly for patients with pulmonary complications.

Prediction and stratification for the surgical adverse events after minimally invasive esophagectomy: A two-center retrospective study

BACKGROUND

Minimally invasive esophagectomy (MIE) is a widely accepted treatment for esophageal cancer, yet it is associated with a significant risk of surgical adverse events (SAEs), which can compromise patient recovery and long-term survival. Accurate preoperative identification of high-risk patients is critical for improving outcomes.

AIM

To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.

METHODS

This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024. Patients were separated into a train set (n = 549) and a validation set (n = 198). After screening by least absolute shrinkage and selection operator regression, multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs. A risk stratification model was constructed and validated to predict the probability of SAEs.

RESULTS

SAEs occurred in 10.2% of patients in train set and 13.6% in the validation set. Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery. The key independent risk factors identified included chronic obstructive pulmonary disease, a history of alcohol consumption, low forced expiratory volume in the first second, and low albumin levels. The stratification model has excellent prediction accuracy, with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.

CONCLUSION

The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE, facilitating targeted preoperative interventions and improving perioperative management.

Curative treatment for oligometastatic gastroesophageal cancer- results of a prospective multicenter study

PURPOSE

Oligometastatic gastroesophageal cancer is a clinical entity with no standard treatment recommendation. Treatment with curative intent has recently emerged as an option for selected patients in contrast to the traditional palliative treatment strategy. This prospective study aimed to assess the safety and efficacy of combined systemic and local treatment with curative intent for patients with oligometastatic gastroesophageal cancer.

METHODS

In a multicenter study, consecutive patients with gastroesophageal cancer and metastases in the liver and/or extra-regional lymph nodes were screened for inclusion. Eligible patients were offered curatively intended perioperative chemotherapy followed by surgical resection or liver ablation. Primary endpoints were treatment safety and feasibility. Secondary outcomes included postoperative mortality, treatment response, progression-free survival, and overall survival. Subgroup analyses were stratified based on oligometastatic location.

RESULTS

A total of 29 (82.9%) patients completed treatment with surgical resection (93.1%), liver ablation (3.4%), or definitive chemoradiotherapy (3.4%). Postoperative complications were found in 19 (73.1%) patients, whereas postoperative mortality was 0%. The most common complications included infection (34.6%) and respiratory complications (34.6%). Median overall survival was 20.9 months (interquartile range 11.2-42.6) from diagnosis and 17.0 months (interquartile range 6.4-35.9) from surgery in patients who were treated with neoadjuvant chemotherapy followed by surgery. Median progression-free survival was 5.8 months (interquartile range 3.1-11.3).

CONCLUSION

This study found curative treatment to be a relatively safe option, with an overall survival of 20.8 months and no postoperative mortality.

Effect of Neoadjuvant Therapy on Endoluminal Vacuum-Assisted Closure Therapy (EVAC) for Anastomotic Leakage After Oesophagectomy

BACKGROUND

Anastomotic leakage (AL) is a dreaded complication after oesophagectomy. Endoluminal vacuum-assisted closure therapy (EVAC) has been increasingly used as a first-line treatment for AL. We aimed to identify any potential adverse effects of a neoadjuvant therapy (chemotherapy (CT) or radiochemotherapy (RCT)) on EVAC.

METHODS

We performed a retrospective cohort study at our tertiary centre between 2013 and 2024. All patients who underwent EVAC for AL after oesophagectomy were included in this study. Parameters such as success rate, length of therapy, number of sponges needed, changes in treatment, and survival were analysed.

RESULTS

A total of 29 patients were included, 19 of whom received CT/RCT and 10 of whom received no neoadjuvant treatment (NT). There was no significant difference in patient survival (30-day survival rate CT/RCT n = 1 (5.3%) vs. NT n = 1 (10%), p = 0.632), success rate (CT/RCT n = 15 (78.9%) vs. NT n = 9 (90%), p = 0.454), and length of therapy (CT/RCT vs. NT 24.11 vs. 23.8, p = 0.681), the number of sponges required (CT/RCT vs. NT 6.26 vs. 6.6, p = 0.835), and the need for changing treatment (CT/RCT n = 5 (26.3%) vs. NT n = 1 (10%), p = 0.303).

CONCLUSIONS

NT did not affect the success rate or length of therapy. Thus, we found no significant influence of CT/RCT on EVAC for AL after oesophagectomy.

Management of Major Complications After Esophagectomy

Esophagectomy remains a procedure with one of the highest complication rates. Given the advances in medical and surgical management of patients and increased patient survival, the number of complications reported has increased. There are different grading systems for complications which vary based on severity or organ system, with the Esophageal Complications Consensus Group unifying them. Management involves conservative intervention and dietary modification to endoscopic interventions and surgical reintervention. Treatment is etiology specific but rehabilitation and patient optimization play a significant role in managing these complications by preventing them. Management is a step-up approach depending on the severity of symptoms.

Long-Term Impact of Severe Postoperative Complications after Esophagectomy for Cancer: Individual Patient Data Meta-Analysis

BACKGROUND

Severe postoperative complications (SPCs) may occur after curative esophagectomy for cancer and are associated with prolonged hospital stay, augmented costs, and increased in-hospital mortality. However, the effect of SPCs on survival after esophagectomy is uncertain.

AIM

To assess the impact of severe postoperative complications (SPCs) on long-term survival following curative esophagectomy for cancer, we conducted a systematic search of PubMed, MEDLINE, Scopus, and Web of Science databases up to December 2023. The included studies examined the relationship between SPCs and survival outcomes, defining SPCs as Clavien-Dindo grade > 3. The primary outcome measure was long-term overall survival (OS). We used restricted mean survival time difference (RMSTD) and 95% confidence intervals (CIs) to calculate pooled effect sizes. Additionally, we applied the GRADE methodology to evaluate the certainty of the evidence.

RESULTS

Ten studies (2181 patients) were included. SPCs were reported in 651 (29.8%) patients. The RMSTD overall survival analysis shows that at 60-month follow-up, patients experiencing SPCs lived for 8.6 months (95% Cis -12.5, -4.7; p < 0.001) less, on average, compared with no-SPC patients. No differences were found for 60-month follow-up disease-free survival (-4.6 months, 95% CIs -11.9, 1.9; p = 0.17) and cancer-specific survival (-6.8 months, 95% CIs -11.9, 1.7; p = 0.21). The GRADE certainty of this evidence ranged from low to very low.

CONCLUSIONS

This study suggests a statistically significant detrimental effect of SPCs on OS in patients undergoing curative esophagectomy for cancer. Also, a clinical trend toward reduced CSS and DFS was perceived.