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Hagens ERC, Cui N, van Dieren S, Eshuis WJ, Laméris W, van Berge Henegouwen MI, Gisbertz SS. Preoperative Risk Stratification in Esophageal Cancer Surgery: Comparing Risk Models with the Clinical Judgment of the Surgeon. Ann Surg Oncol 2023; 30:5159-5169. [PMID: 37120485 PMCID: PMC10319689 DOI: 10.1245/s10434-023-13473-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 03/21/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND Numerous prediction models estimating the risk of complications after esophagectomy exist but are rarely used in practice. The aim of this study was to compare the clinical judgment of surgeons using these prediction models. METHODS Patients with resectable esophageal cancer who underwent an esophagectomy were included in this prospective study. Prediction models for postoperative complications after esophagectomy were selected by a systematic literature search. Clinical judgment was given by three surgeons, indicating their estimated risk for postoperative complications in percentage categories. The best performing prediction model was compared with the judgment of the surgeons, using the net reclassification improvement (NRI), category-free NRI (cfNRI), and integrated discrimination improvement (IDI) indexes. RESULTS Overall, 159 patients were included between March 2019 and July 2021, of whom 88 patients (55%) developed a complication. The best performing prediction model showed an area under the receiver operating characteristic curve (AUC) of 0.56. The three surgeons had an AUC of 0.53, 0.55, and 0.59, respectively, and all surgeons showed negative percentages of cfNRIevents and IDIevents, and positive percentages of cfNRInonevents and IDIevents. This indicates that in the group of patients with postoperative complications, the prediction model performed better, whereas in the group of patients without postoperative complications, the surgeons performed better. NRIoverall was 18% for one surgeon, while the remainder of the NRIoverall, cfNRIoverall and IDIoverall scores showed small differences between surgeons and the prediction models. CONCLUSION Prediction models tend to overestimate the risk of any complication, whereas surgeons tend to underestimate this risk. Overall, surgeons' estimations differ between surgeons and vary between similar to slightly better than the prediction models.
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Affiliation(s)
- Eliza R C Hagens
- Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center, Amsterdam, The Netherlands
| | - Nanke Cui
- Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center, Amsterdam, The Netherlands
| | - Susan van Dieren
- Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center, Amsterdam, The Netherlands
| | - Wietse J Eshuis
- Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center, Amsterdam, The Netherlands
| | - Wytze Laméris
- Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center, Amsterdam, The Netherlands
| | - Mark I van Berge Henegouwen
- Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center, Amsterdam, The Netherlands
| | - Suzanne S Gisbertz
- Department of Surgery, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center, Amsterdam, The Netherlands.
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Grantham JP, Hii A, Shenfine J. Preoperative risk modelling for oesophagectomy: A systematic review. World J Gastrointest Surg 2023; 15:450-470. [PMID: 37032794 PMCID: PMC10080602 DOI: 10.4240/wjgs.v15.i3.450] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/09/2023] [Accepted: 02/23/2023] [Indexed: 03/27/2023] Open
Abstract
BACKGROUND Oesophageal cancer is a frequently observed and lethal malignancy worldwide. Surgical resection remains a realistic option for curative intent in the early stages of the disease. However, the decision to undertake oesophagectomy is significant as it exposes the patient to a substantial risk of morbidity and mortality. Therefore, appropriate patient selection, counselling and resource allocation is important. Many tools have been developed to aid surgeons in appropriate decision-making.
AIM To examine all multivariate risk models that use preoperative and intraoperative information and establish which have the most clinical utility.
METHODS A systematic review of the MEDLINE, EMBASE and Cochrane databases was conducted from 2000-2020. The search terms applied were ((Oesophagectomy) AND (Risk OR predict OR model OR score) AND (Outcomes OR complications OR morbidity OR mortality OR length of stay OR anastomotic leak)). The applied inclusion criteria were articles assessing multivariate based tools using exclusively preoperatively available data to predict perioperative patient outcomes following oesophagectomy. The exclusion criteria were publications that described models requiring intra-operative or post-operative data and articles appraising only univariate predictors such as American Society of Anesthesiologists score, cardiopulmonary fitness or pre-operative sarcopenia. Articles that exclusively assessed distant outcomes such as long-term survival were excluded as were publications using cohorts mixed with other surgical procedures. The articles generated from each search were collated, processed and then reported in accordance with PRISMA guidelines. All risk models were appraised for clinical credibility, methodological quality, performance, validation, and clinical effectiveness.
RESULTS The initial search of composite databases yielded 8715 articles which reduced to 5827 following the deduplication process. After title and abstract screening, 197 potentially relevant texts were retrieved for detailed review. Twenty-seven published studies were ultimately included which examined twenty-one multivariate risk models utilising exclusively preoperative data. Most models examined were clinically credible and were constructed with sound methodological quality, but model performance was often insufficient to prognosticate patient outcomes. Three risk models were identified as being promising in predicting perioperative mortality, including the National Quality Improvement Project surgical risk calculator, revised STS score and the Takeuchi model. Two studies predicted perioperative major morbidity, including the predicting postoperative complications score and prognostic nutritional index-multivariate models. Many of these models require external validation and demonstration of clinical effectiveness.
CONCLUSION Whilst there are several promising models in predicting perioperative oesophagectomy outcomes, more research is needed to confirm their validity and demonstrate improved clinical outcomes with the adoption of these models.
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Affiliation(s)
- James Paul Grantham
- Department of General Surgery, Modbury Hospital, Adelaide 5092, South Australia, Australia
| | - Amanda Hii
- Department of General Surgery, Modbury Hospital, Modbury 5092, South Australia, Australia
| | - Jonathan Shenfine
- General Surgical Unit, Jersey General Hospital, Saint Helier JE1 3QS, Jersey, United Kingdom
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Fumagalli Romario U, de Pascale S, Colombo S, Attanasio A, Sabbatini A, Sandrin F. Esophagectomy-prevention of complications-tips and tricks for the preoperative, intraoperative and postoperative stage. Updates Surg 2023; 75:343-355. [PMID: 35851675 DOI: 10.1007/s13304-022-01332-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 07/06/2022] [Indexed: 01/24/2023]
Abstract
Esophagectomy still remains the mainstay of treatment for localized esophageal cancer. Many progresses have been made in the technique of esophagectomy in the last decades but the overall morbidity for this operation remains formidable. Postoperative complication and mortality rate after esophagectomy are significant; anastomotic leak has an incidence of 11,4%. The occurrence of a complication is a significant negative prognostic factor for long term survival and is also linked to longer postoperative stay, a lower quality of life, increased hospital costs. Preventing the occurrence of postoperative morbidity and reducing associated postoperative mortality rate is a major goal for surgeons experienced in resective esophageal surgery. Many details of pre, intra and postoperative care for patients undergoing esophagectomy need to be shared among the professionals taking care of these patients (oncologists, dieticians, physiotherapists, surgeons, nurses, anesthesiologists, gastroenterologists) in order to improve the short and long term clinical results.
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Gray KD, Nobel TB, Hsu M, Tan KS, Chudgar N, Yan S, Rusch VW, Jones DR, Rocco G, Molena D, Isbell JM. Improved Preoperative Risk Assessment Tools Are Needed to Guide Informed Decision Making before Esophagectomy. Ann Surg 2023; 277:116-120. [PMID: 33351463 PMCID: PMC8211904 DOI: 10.1097/sla.0000000000004715] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE We sought to evaluate the performance of 2 commonly used prediction models for postoperative morbidity in patients undergoing open and minimally invasive esophagectomy. SUMMARY BACKGROUND DATA Patients undergoing esophagectomy have a high risk of postoperative complications. Accurate risk assessment in this cohort is important for informed decision-making. METHODS We identified patients who underwent esophagectomy between January 2016 and June 2018 from our prospectively maintained database. Predicted morbidity was calculated using the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator (SRC) and a 5-factor National Surgical Quality Improvement Programderived frailty index. Performance was evaluated using concordance index (C-index) and calibration curves. RESULTS In total, 240 consecutive patients were included for analysis. Most patients (85%) underwent Ivor Lewis esophagectomy. The observed overall complication rate was 39%; the observed serious complication rate was 33%.The SRC did not identify risk of complications in the entire cohort (C-index, 0.553), patients undergoing open esophagectomy (C-index, 0.569), or patients undergoing minimally invasive esophagectomy (C-index, 0.542); calibration curves showed general underestimation. Discrimination of the SRC was lowest for reoperation (C-index, 0.533) and highest for discharge to a facility other than home (C-index, 0.728). Similarly, the frailty index had C-index of 0.513 for discriminating any complication, 0.523 for serious complication, and 0.559 for readmission. CONCLUSIONS SRC and frailty index did not adequately predict complications after esophagectomy. Procedure-specific risk-assessment tools are needed to guide shared patient-physician decision-making in this high-risk population.
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Affiliation(s)
- Katherine D. Gray
- Department of Surgery, New York Presbyterian Hospital–Weill Cornell Medicine, New York, NY
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Tamar B. Nobel
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Meier Hsu
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Kay See Tan
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Neel Chudgar
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Shi Yan
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Valerie W. Rusch
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - David R. Jones
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Gaetano Rocco
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Daniela Molena
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - James M. Isbell
- Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
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Schröder W, Gisbertz SS, Voeten DM, Gutschow CA, Fuchs HF, van Berge Henegouwen MI. Surgical Therapy of Esophageal Adenocarcinoma-Current Standards and Future Perspectives. Cancers (Basel) 2021; 13:5834. [PMID: 34830988 PMCID: PMC8616112 DOI: 10.3390/cancers13225834] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 11/15/2021] [Accepted: 11/18/2021] [Indexed: 12/18/2022] Open
Abstract
Transthoracic esophagectomy is currently the predominant curative treatment option for resectable esophageal adenocarcinoma. The majority of carcinomas present as locally advanced tumors requiring multimodal strategies with either neoadjuvant chemoradiotherapy or perioperative chemotherapy alone. Minimally invasive, including robotic, techniques are increasingly applied with a broad spectrum of technical variations existing for the oncological resection as well as gastric reconstruction. At the present, intrathoracic esophagogastrostomy is the preferred technique of reconstruction (Ivor Lewis esophagectomy). With standardized surgical procedures, a complete resection of the primary tumor can be achieved in almost 95% of patients. Even in expert centers, postoperative morbidity remains high, with an overall complication rate of 50-60%, whereas 30- and 90-day mortality are reported to be <2% and <6%, respectively. Due to the complexity of transthoracic esophagetomy and its associated morbidity, esophageal surgery is recommended to be performed in specialized centers with an appropriate caseload yet to be defined. In order to reduce postoperative morbidity, the selection of patients, preoperative rehabilitation and postoperative fast-track concepts are feasible strategies of perioperative management. Future directives aim to further centralize esophageal services, to individualize surgical treatment for high-risk patients and to implement intraoperative imaging modalities modifying the oncological extent of resection and facilitating surgical reconstruction.
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Affiliation(s)
- Wolfgang Schröder
- Department of General, Visceral, Cancer and Transplantation Surgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany;
| | - Suzanne S. Gisbertz
- Cancer Center Amsterdam, Department of Surgery, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.S.G.); (D.M.V.); (M.I.v.B.H.)
| | - Daan M. Voeten
- Cancer Center Amsterdam, Department of Surgery, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.S.G.); (D.M.V.); (M.I.v.B.H.)
| | - Christian A. Gutschow
- Department of General and Transplantation Surgery, University Hospital Zurich, 8091 Zurich, Switzerland;
| | - Hans F. Fuchs
- Department of General, Visceral, Cancer and Transplantation Surgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany;
| | - Mark I. van Berge Henegouwen
- Cancer Center Amsterdam, Department of Surgery, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (S.S.G.); (D.M.V.); (M.I.v.B.H.)
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D'Journo XB, Boulate D, Fourdrain A, Loundou A, van Berge Henegouwen MI, Gisbertz SS, O'Neill JR, Hoelscher A, Piessen G, van Lanschot J, Wijnhoven B, Jobe B, Davies A, Schneider PM, Pera M, Nilsson M, Nafteux P, Kitagawa Y, Morse CR, Hofstetter W, Molena D, So JBY, Immanuel A, Parsons SL, Larsen MH, Dolan JP, Wood SG, Maynard N, Smithers M, Puig S, Law S, Wong I, Kennedy A, KangNing W, Reynolds JV, Pramesh CS, Ferguson M, Darling G, Schröder W, Bludau M, Underwood T, van Hillegersberg R, Chang A, Cecconello I, Ribeiro U, de Manzoni G, Rosati R, Kuppusamy M, Thomas PA, Low DE. Risk Prediction Model of 90-Day Mortality After Esophagectomy for Cancer. JAMA Surg 2021; 156:836-845. [PMID: 34160587 PMCID: PMC8223144 DOI: 10.1001/jamasurg.2021.2376] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 03/13/2021] [Indexed: 02/06/2023]
Abstract
Importance Ninety-day mortality rates after esophagectomy are an indicator of the quality of surgical oncologic management. Accurate risk prediction based on large data sets may aid patients and surgeons in making informed decisions. Objective To develop and validate a risk prediction model of death within 90 days after esophagectomy for cancer using the International Esodata Study Group (IESG) database, the largest existing prospective, multicenter cohort reporting standardized postoperative outcomes. Design, Setting, and Participants In this diagnostic/prognostic study, we performed a retrospective analysis of patients from 39 institutions in 19 countries between January 1, 2015, and December 31, 2019. Patients with esophageal cancer were randomly assigned to development and validation cohorts. A scoring system that predicted death within 90 days based on logistic regression β coefficients was conducted. A final prognostic score was determined and categorized into homogeneous risk groups that predicted death within 90 days. Calibration and discrimination tests were assessed between cohorts. Exposures Esophageal resection for cancer of the esophagus and gastroesophageal junction. Main Outcomes and Measures All-cause postoperative 90-day mortality. Results A total of 8403 patients (mean [SD] age, 63.6 [9.0] years; 6641 [79.0%] male) were included. The 30-day mortality rate was 2.0% (n = 164), and the 90-day mortality rate was 4.2% (n = 353). Development (n = 4172) and validation (n = 4231) cohorts were randomly assigned. The multiple logistic regression model identified 10 weighted point variables factored into the prognostic score: age, sex, body mass index, performance status, myocardial infarction, connective tissue disease, peripheral vascular disease, liver disease, neoadjuvant treatment, and hospital volume. The prognostic scores were categorized into 5 risk groups: very low risk (score, ≥1; 90-day mortality, 1.8%), low risk (score, 0; 90-day mortality, 3.0%), medium risk (score, -1 to -2; 90-day mortality, 5.8%), high risk (score, -3 to -4: 90-day mortality, 8.9%), and very high risk (score, ≤-5; 90-day mortality, 18.2%). The model was supported by nonsignificance in the Hosmer-Lemeshow test. The discrimination (area under the receiver operating characteristic curve) was 0.68 (95% CI, 0.64-0.72) in the development cohort and 0.64 (95% CI, 0.60-0.69) in the validation cohort. Conclusions and Relevance In this study, on the basis of preoperative variables, the IESG risk prediction model allowed stratification of an individual patient's risk of death within 90 days after esophagectomy. These data suggest that this model can help in the decision-making process when esophageal cancer surgery is being considered and in informed consent.
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Affiliation(s)
- Xavier Benoit D'Journo
- Department of Thoracic Surgery, Aix-Marseille University, North Hospital, Marseille, France
| | - David Boulate
- Department of Thoracic Surgery, Aix-Marseille University, North Hospital, Marseille, France
| | - Alex Fourdrain
- Department of Thoracic Surgery, Aix-Marseille University, North Hospital, Marseille, France
| | - Anderson Loundou
- Department of Thoracic Surgery, Aix-Marseille University, North Hospital, Marseille, France
| | - Mark I van Berge Henegouwen
- Department of Gastrointestinal Surgery, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Suzanne S Gisbertz
- Department of Gastrointestinal Surgery, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - J Robert O'Neill
- Department of Oesophago-Gastric Cancer Surgery, Cambridge Oesophago-Gastric Centre, Addenbrookes Hospital, Cambridge, United Kingdom
| | - Arnulf Hoelscher
- Center for Esophageal Diseases, Elisabeth Hospital Essen, University Medicine Essen, Essen, Germany
| | - Guillaume Piessen
- Department of Digestive and Oncological Surgery, Claude Huriez University Hospital, Lille, France
| | - Jan van Lanschot
- Department of Digestive Surgery, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Bas Wijnhoven
- Department of Digestive Surgery, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Blair Jobe
- Esophageal and Lung Institute, Allegheny Health Network, Pittsburgh, Pennsylvania
| | - Andrew Davies
- Department of Digestive Surgery, Guy's & St Thomas' National Health Service Foundation Trust, London, United Kingdom
| | - Paul M Schneider
- Department of Digestive and Oncological Surgery, Hirslanden Medical Center, Zurich, Switzerland
| | - Manuel Pera
- Department of Digestive Surgery, Hospital Universitario del Mar, Barcelona, Spain
| | - Magnus Nilsson
- Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Philippe Nafteux
- Department of Digestive Surgery, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Yuko Kitagawa
- Department of Thoracic Surgery, Keio University, Tokyo, Japan
| | | | - Wayne Hofstetter
- Department of Thoracic Surgery, MD Anderson Cancer Center, Houston, Texas
| | - Daniela Molena
- Department of Thoracic and Cardiovascular Surgery, Memorial Sloan Kettering Cancer Center, New York City, New York
| | - Jimmy Bok-Yan So
- Department of Thoracic Surgery, National University Hospital, Singapore, Singapore
| | - Arul Immanuel
- Department of Surgery, Northern Oesophagogastric Cancer Unit, Royal Victoria Infirmary, Newcastle upon Tyne, United Kingdom
| | - Simon L Parsons
- Department of Upper Gastrointestinal Surgery, Nottingham University Hospitals National Health Service Trust, Nottingham, United Kingdom
| | | | - James P Dolan
- Digestive Health Center, Oregon Health and Science University, Portland
| | - Stephanie G Wood
- Digestive Health Center, Oregon Health and Science University, Portland
| | - Nick Maynard
- Oesophagogastric Cancer Multidisciplinary Team, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | - Mark Smithers
- Department of Surgery, Princess Alexandra Hospital, University of Queensland, Brisbane, Australia
| | - Sonia Puig
- Department of Gastrointestinal Surgery, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham Foundation Trust, Birmingham, United Kingdom
| | - Simon Law
- Department of Gastrointestinal Surgery, Queen Mary Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Ian Wong
- Department of Gastrointestinal Surgery, Queen Mary Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Andrew Kennedy
- Department of Gastrointestinal Surgery, Royal Victoria Hospital, Belfast, Northern Ireland
| | - Wang KangNing
- Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Chengdu, China
| | - John V Reynolds
- Department of Surgery, St James's Hospital Trinity College, Dublin, Ireland
| | - C S Pramesh
- Department of Surgical Oncology, Tata Memorial Centre, Mumbai, India
| | - Mark Ferguson
- Department of Thoracic Surgery, The University of Chicago Medicine, Chicago, Illinois
| | - Gail Darling
- Department of Thoracic Surgery, Toronto General Hospital, Toronto, Ontario, Canada
| | - Wolfgang Schröder
- Department of Digestive Surgery, University Hospital of Cologne, Cologne, Germany
| | - Marc Bludau
- Department of Digestive Surgery, University Hospital of Cologne, Cologne, Germany
| | - Tim Underwood
- Department of Gastrointestinal Surgery, University Hospital Southampton National Health Service Foundation Trust, Southampton, United Kingdom
| | | | - Andrew Chang
- Department of Thoracic Surgery, University of Michigan Health System, Ann Arbor
| | - Ivan Cecconello
- Department of Digestive Surgery, University of Sao Paulo School of Medicine, Sao Paulo, Brazil
| | - Ulysses Ribeiro
- Department of Digestive Surgery, University of Sao Paulo School of Medicine, Sao Paulo, Brazil
| | - Giovanni de Manzoni
- Department of Upper Gastrointestinal Surgery, University of Verona, Verona, Italy
| | - Riccardo Rosati
- Department of Upper Gastrointestinal Surgery, Vita-Salute San Raffaele University, Milan, Italy
| | | | | | - Donald E Low
- Department of Thoracic Surgery, Virginia Mason Medical Center, Seattle, Washington
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Affiliation(s)
- M Dahan
- CNP de chirurgie thoracique et cardio-vasculaire, 56, boulevard Vincent-Auriol, 75013 Paris, France.
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8
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Morbidity After Esophagectomy With Three-Field Lymph Node Dissection in Patients With Esophageal Cancer: Looking for the Best Predictive Model. Int Surg 2020. [DOI: 10.9738/intsurg-d-18-00012.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Purpose
Esophagectomy with three-field lymphadenectomy (3FLD) is a potentially curative treatment option for resectable esophageal cancer (EC), which is associated with significant morbidity. Risk scores are useful for patient assessment; this study compares 7 different scores and indexes to find the best model for predicting morbidity in patients undergoing 3FLD.
Methods
Six years of data from January 2010 to January 2016 were reviewed, patients with EC who underwent 3FLD were retrospectively scored using 4 predictive scores and 3 predictive index models. Postoperative morbidity was assessed according to the extended Clavien-Dindo classification. The outcomes were the presence and severity of morbidity. Validation was performed by calculating the area under the ROC curve and by the assessment of collinearity among the variables independently associated with morbidity in the overall model to determine the best predictive model.
Results
We included 230 patients were included in the final analysis. Complications after 3FLD occurred in 168 patients (73%; minor complications, n = 96 [41%]; major complications, n=72 [31%]). The AUC values (<0.7) indicated that all scores and indexes had poor discrimination power in predicting the presence and severity of morbidity. Overall, the Steyerberg score was associated with the lowest risk of misestimation in predicting morbidity (P = 0.0330).
Conclusion
No score or index could predict the presence or severity of morbidity after 3FLD with good discrimination power. Age (>68 years) was the most critical factor affecting morbidity. The Steyerberg score model, based on the addition and subtraction of risk values was the best model for predicting morbidity after 3FLD.
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9
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Rinieri P, Ouattara M, Brioude G, Loundou A, de Lesquen H, Trousse D, Doddoli C, Thomas PA, D'Journo XB. Long-term outcome of open versus hybrid minimally invasive Ivor Lewis oesophagectomy: a propensity score matched study†. Eur J Cardiothorac Surg 2019; 51:223-229. [PMID: 28186271 DOI: 10.1093/ejcts/ezw273] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Revised: 06/28/2016] [Accepted: 07/05/2016] [Indexed: 12/16/2022] Open
Affiliation(s)
- Philippe Rinieri
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Moussa Ouattara
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Geoffrey Brioude
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Anderson Loundou
- Department of Biostatistics, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Henri de Lesquen
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Delphine Trousse
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Christophe Doddoli
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Pascal Alexandre Thomas
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
| | - Xavier Benoit D'Journo
- Department of Thoracic Surgery and Diseases of the Esophagus, North Hospital, Aix-Marseille University, Chemin des Bourrely, Marseille, France
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van den Boorn HG, Engelhardt EG, van Kleef J, Sprangers MAG, van Oijen MGH, Abu-Hanna A, Zwinderman AH, Coupé VMH, van Laarhoven HWM. Prediction models for patients with esophageal or gastric cancer: A systematic review and meta-analysis. PLoS One 2018; 13:e0192310. [PMID: 29420636 PMCID: PMC5805284 DOI: 10.1371/journal.pone.0192310] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 01/22/2018] [Indexed: 02/06/2023] Open
Abstract
Background Clinical prediction models are increasingly used to predict outcomes such as survival in cancer patients. The aim of this study was threefold. First, to perform a systematic review to identify available clinical prediction models for patients with esophageal and/or gastric cancer. Second, to evaluate sources of bias in the included studies. Third, to investigate the predictive performance of the prediction models using meta-analysis. Methods MEDLINE, EMBASE, PsycINFO, CINAHL, and The Cochrane Library were searched for publications from the year 2000 onwards. Studies describing models predicting survival, adverse events and/or health-related quality of life (HRQoL) for esophageal or gastric cancer patients were included. Potential sources of bias were assessed and a meta-analysis, pooled per prediction model, was performed on the discriminative abilities (c-indices). Results A total of 61 studies were included (45 development and 16 validation studies), describing 47 prediction models. Most models predicted survival after a curative resection. Nearly 75% of the studies exhibited bias in at least 3 areas and model calibration was rarely reported. The meta-analysis showed that the averaged c-index of the models is fair (0.75) and ranges from 0.65 to 0.85. Conclusion Most available prediction models only focus on survival after a curative resection, which is only relevant to a limited patient population. Few models predicted adverse events after resection, and none focused on patient’s HRQoL, despite its relevance. Generally, the quality of reporting is poor and external model validation is limited. We conclude that there is a need for prediction models that better meet patients’ information needs, and provide information on both the benefits and harms of the various treatment options in terms of survival, adverse events and HRQoL.
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Affiliation(s)
- H. G. van den Boorn
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- * E-mail:
| | - E. G. Engelhardt
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - J. van Kleef
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - M. A. G. Sprangers
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - M. G. H. van Oijen
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - A. Abu-Hanna
- Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - A. H. Zwinderman
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - V. M. H. Coupé
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - H. W. M. van Laarhoven
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
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Mora A, Nakajima Y, Okada T, Tokairin Y, Kawada K, Kawano T. Comparative Study of Predictive Mortality Scores in Esophagectomy with Three-Field Lymph Node Dissection in Patients with Esophageal Cancer. Dig Surg 2018; 36:67-75. [PMID: 29393197 DOI: 10.1159/000486551] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Accepted: 12/30/2017] [Indexed: 12/26/2022]
Abstract
BACKGROUND/AIM Esophagectomy is still the best therapeutic option for curing resectable esophageal cancer (EC). Radical surgical resection with three-field lymphadenectomy (3FLD) is a potentially curative treatment option. We compared the predictive accuracy of 5 different scores in patients with EC who underwent 3FLD. METHODS Five years' worth of medical records in a single institution were analyzed (January 2010 to January 2015) from 311 patients who underwent esophagectomy for EC. We selected 191 in whom 3FLD was performed. Mortality was calculated based on 5 predictive scores. Outcomes measures were intraoperative mortality, 30-day mortality, and 1- and 2-year mortality after surgery. RESULTS Intraoperative mortality and 30-day mortality after surgery was 0%; 1 and 2-year mortality were 19.8 and 31.4%, respectively. The area under the curve showed poor discriminatory power for all 5 scores (<0.7). In one-way analysis of variance, for 1 year mortality, Portsmouth-Physiological and Operative Severity Score for mortality (P-Possum) was significant (p = 0.0424); in a multivariable analysis for 2-year mortality, P-Possum (p < 0.0001) remained significant. CONCLUSION There is no accurate prognosis score for esophagectomy in patients who undergo high-risk procedures like 3FLD. New scores are needed to predict the mortality after 3FLD with good discriminatory power. Independent factors affect survival and may function as the baseline for obtaining a new accurate mortality score.
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Xing XZ, Wang HJ, Qu SN, Huang CL, Zhang H, Wang H, Yang QH, Gao Y. The value of esophagectomy surgical apgar score (eSAS) in predicting the risk of major morbidity after open esophagectomy. J Thorac Dis 2016; 8:1780-7. [PMID: 27499969 DOI: 10.21037/jtd.2016.06.28] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Recently, surgical apgar score (SAS) has been reported to be strongly associated with major morbidity after major abdominal surgery. The aim of this study was to assess the value of esophagectomy SAS (eSAS) in predicting the risk of major morbidity after open esophagectomy in a high volume cancer center. METHODS The data of all patients who admitted to intensive care unit (ICU) after open esophagectomy at Cancer Hospital of Chinese Academy of Medical Sciences & Peking Union Medical College from September 2008 through August 2010 was retrospectively collected and reviewed. Preoperative and perioperative variables were recorded and compared. The eSAS was calculated as the sum of the points of EBL, lowest MAP and lowest HR for each patient. Patients were divided into high-risk (below the cutoff) and low-risk (above the cutoff) eSAS groups according to the cutoff score with optimal accuracy of eSAS for major morbidity. Univariable and multivariable regression analysis were used to define risk factors of the occurrence of major morbidity. RESULTS Of 189 patients, 110 patients developed major morbidities (58.2%) and 30-day operative mortality was 5.8% (11/189). There were 156 high risk patients (eSAS ≤7) and 33 low risk (eSAS >7) patients. Univariable analysis demonstrated that forced expiratory volume in one second of predicted (FEV1%) ≤78% (44% vs. 61%, P=0.024), McKeown approach (22.7% vs. 7.6%, P=0.011), duration of operation longer than 230 minutes, intraoperative estimated blood loss (347±263 vs. 500±510 mL, P=0.015) and eSAS ≤7 (62.2% vs. 90.0%, P=0.001) were predictive of major morbidity. Multivariable analysis demonstrated that FEV1% ≤78% (OR, 2.493; 95% CI, 1.279-4.858, P=0.007) and eSAS ≤7 (OR, 2.810; 95% CI, 1.105-7.144; P=0.030) were independent predictors of major morbidity after esophagectomy. Compared with patients who had eSAS >7, patients who had eSAS ≤7 had longer hospital length of stay (25.39±14.36 vs. 32.22±22.66 days, P=0.030). However, there were no significant differences in ICU length of stay, duration of mechanical ventilation, ICU death, 30-day death rate and in-hospital death rate between high risk and low risk patients. CONCLUSIONS The eSAS score is predictive of major morbidity, and lower eSAS is associated with longer hospital length of stay in esophageal cancer patients after open esophagectomy.
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Affiliation(s)
- Xue-Zhong Xing
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Hai-Jun Wang
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Shi-Ning Qu
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Chu-Lin Huang
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Hao Zhang
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Hao Wang
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Quan-Hui Yang
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yong Gao
- Department of Intensive Care Unit, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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