Impact of Complications After Pancreatoduodenectomy on Mortality, Organ Failure, Hospital Stay, and Readmission Analysis of a Nationwide Audit:Analysis of a Nationwide Audit

OBJECTIVE: To quantify the impact of individual complications on mortality, organ failure, hospital stay, and readmission after pancreatoduodenectomy. SUMMARY OF BACKGROUND DATA: An initial complication may provoke a sequence of adverse events potentially leading to mortality after pancreatoduodenectomy. This study was conducted to aid prioritization of quality improvement initiatives. METHODS: Data from consecutive patients undergoing pancreatoduodenectomy (2014-2017) were extracted from the Dutch Pancreatic Cancer Audit. Population attributable fractions (PAF) were calculated for the association of each complication (ie, postoperative pancreatic fistula, postpancreatectomy hemorrhage, bile leakage, delayed gastric emptying, wound infection, and pneumonia) with each unfavorable outcome [ie, in-hospital mortality, organ failure, prolonged hospital stay (>75th percentile), and unplanned readmission), whereas adjusting for confounders and other complications. The PAF represents the proportion of an outcome that could be prevented if a complication would be eliminated completely. RESULTS: Overall, 2620 patients were analyzed. In-hospital mortality occurred in 95 patients (3.6%), organ failure in 198 patients (7.6%), and readmission in 427 patients (16.2%). Postoperative pancreatic fistula and postpancreatectomy hemorrhage had the greatest independent impact on mortality [PAF 25.7% (95% CI 13.4-37.9) and 32.8% (21.9-43.8), respectively] and organ failure [PAF 21.8% (95% CI 12.9-30.6) and 22.1% (15.0-29.1), respectively]. Delayed gastric emptying had the greatest independent impact on prolonged hospital stay [PAF 27.6% (95% CI 23.5-31.8)]. The impact of individual complications on unplanned readmission was smaller than 11%. CONCLUSION: Interventions focusing on postoperative pancreatic fistula and postpancreatectomy hemorrhage may have the greatest impact on in-hospital mortality and organ failure. To prevent prolonged hospital stay, initiatives should in addition focus on delayed gastric emptying

Perioperative management of esophageal cancer

At present, the incidence of esophageal carcinoma continues to rise and will form an increasingly large health burden in the years ahead. Action is needed to curb this "quiet epidemic". Despite remarkable progress in available treatment strategies during the last decade, some patients that opt for curative therapy remain unresponsive to treatment. One of the primary reasons why not all patients respond to – or some suffer from – the currently available treatment regimens can be attributed to high inter-patient variability in response to such treatment. Therefore, the key to successful improvement of healthcare outcomes is to take this inter-patient variability into consideration to design a successful treatment plan for individual patients. As such, the aim of this thesis was to contribute to this improvement by optimizing patient selection and improve the use of existing therapies for patients with esophageal cancer. To achieve this aim this thesis points towards the use of specific diagnostic tools, novel predictors and models for individual treatment efficacy and risk estimation, and remaining gaps in esophageal cancer research. Some findings have already changed – or provide a basis for changes in – the perioperative management of these patients

Perioperative management of esophageal cancer

At present, the incidence of esophageal carcinoma continues to rise and will form an increasingly large health burden in the years ahead. Action is needed to curb this "quiet epidemic". Despite remarkable progress in available treatment strategies during the last decade, some patients that opt for curative therapy remain unresponsive to treatment. One of the primary reasons why not all patients respond to – or some suffer from – the currently available treatment regimens can be attributed to high inter-patient variability in response to such treatment. Therefore, the key to successful improvement of healthcare outcomes is to take this inter-patient variability into consideration to design a successful treatment plan for individual patients. As such, the aim of this thesis was to contribute to this improvement by optimizing patient selection and improve the use of existing therapies for patients with esophageal cancer. To achieve this aim this thesis points towards the use of specific diagnostic tools, novel predictors and models for individual treatment efficacy and risk estimation, and remaining gaps in esophageal cancer research. Some findings have already changed – or provide a basis for changes in – the perioperative management of these patients

ASO Author Reflections : Predicting Early Recurrence After Trimodality Therapy for Esophageal Adenocarcinoma

ASO Author Reflections is a brief invited commentary on the article “Preoperative Nomogram to Risk Stratify Patients for the Benefit of Trimodality Therapy in Esophageal Adenocarcinoma”, Ann Surg Oncol. 2018;25:1598–1607

The emerging field of radiomics in esophageal cancer : Current evidence and future potential

'Radiomics' is the name given to the emerging field of extracting additional information from standard medical images using advanced feature analysis. This innovative form of quantitative image analysis appears to have future potential for clinical practice in patients with esophageal cancer by providing an additional layer of information to the standard imaging assessment. There is a growing body of evidence suggesting that radiomics may provide incremental value for staging, predicting treatment response, and predicting survival in esophageal cancer, for which the current work-up has substantial limitations. This review outlines the available evidence and future potential for the application of radiomics in the management of patients with esophageal cancer. In addition, an overview of the current evidence on the importance of reproducibility of image features and the substantial influence of varying smoothing scales, quantization levels, and segmentation methods is provided

Learning Curve for Robot-Assisted Minimally Invasive Thoracoscopic Esophagectomy : Results From 312 Cases

Background: Thoracic laparoscopic robot-assisted minimally invasive esophagectomy (RAMIE) was developed in 2003. RAMIE was shown to be safe and oncologically effective. The aim of this study was to assess the learning curve and the proctoring program for a newly introduced surgeon (surgeon 2). Methods: The “learning curve” was defined as the number of operations that must be performed by a surgeon to achieve a steady level of performance. Measures of proficiency to describe the learning curve of the proctor and the newly introduced surgeon 2 included operating time, blood loss, and conversion rates and were analyzed using the cumulative sum method. Results of the newly introduced surgeon were compared with the proctor in the same period of time. Results: The proctor performed 232 of 312 procedures (74%) and surgeon 2 performed 80 of 312 procedures (26%). The proctor reached proficiency after 70 procedures in 55 months. The structured proctoring program for surgeon 2 started with 20 procedures as assisting table surgeon, followed by 5 observational and 15 supervised cases. Surgeon 2 performed at the same level as the proctor concerning operating time, blood loss, conversion rates, radicality, and complications. For surgeon 2, the learning phase of thoracic laparoscopic RAMIE was completed within 24 cases (15 supervised and 9 independent cases) in 13 months; a reduction of 66% in the number of operations and a reduction of 76% in time, compared with the proctor. Conclusions: The learning phase of thoracic laparoscopic RAMIE consisted of 70 procedures in 55 months. A structured proctoring for RAMIE substantially reduced the number of procedures and time required to achieve proficiency