Risk Prediction Model of 90-Day Mortality after Esophagectomy for Cancer

Xavier Benoit D'Journo, David Boulate, Alex Fourdrain, Anderson Loundou, Mark I. Van Berge Henegouwen, Suzanne S. Gisbertz, J. Robert O'Neill, Arnulf Hoelscher, Guillaume Piessen, Jan Van Lanschot, Bas Wijnhoven, Blair Jobe, Andrew Davies, Paul M. Schneider, Manuel Pera, Magnus Nilsson, Philippe Nafteux, Yuko Kitagawa, Christopher R. Morse, Wayne HofstetterDaniela Molena, Jimmy Bok Yan So, Arul Immanuel, Simon L. Parsons, Michael Hareskov Larsen, James P. Dolan, Stephanie G. Wood, Nick Maynard, Mark Smithers, Sonia Puig, Simon Law, Ian Wong, Andrew Kennedy, Wang Kangning, John V. Reynolds, C. S. Pramesh, Mark Ferguson, Gail Darling, Wolfgang Schröder, Marc Bludau, Tim Underwood, Richard Van Hillegersberg, Andrew Chang, Ivan Cecconello, Ulysses Ribeiro, Giovanni De Manzoni, Riccardo Rosati, Madhankumar Kuppusamy, Pascal Alexandre Thomas, Donald E. Low

Research output: Contribution to journalArticleAcademicpeer-review

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 ß 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.

Original languageEnglish
Pages (from-to)836-845
Number of pages10
JournalJAMA Surgery
Volume156
Issue number9
DOIs
Publication statusPublished - Sept 2021

Bibliographical note

Funding Information:
Author Contributions: Dr D’Journo had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: D’Journo, Boulate, Fourdrain, Gisbertz, Pera, Nilsson, Nafteux, Kitagawa, Molena, Chang, Cecconello, Rosati, Low. Acquisition, analysis, or interpretation of data: D’Journo, Fourdrain, Loundou, van Berge Henegouwen, Gisbertz, O’Neill, Hoelscher, Piessen, van Lanschot, Wijnhoven, Jobe, Davies, Schneider, Nilsson, Nafteux, Kitagawa, Morse, Hofstetter, So, Immanuel, Parsons, Larsen, Dolan, Wood, Maynard, Smithers, Puig, Law, Wong, Kennedy, KangNing, Reynolds, Pramesh, Ferguson, Darling, Schröder, Bludau, Underwood, van Hillegersberg, Chang, Ribeiro, de Manzoni, Rosati, Kuppusamy, Thomas, Low. Drafting of the manuscript: D’Journo, Fourdrain, Loundou, Jobe, Pera, Immanuel, KangNing, Reynolds, Low. Critical revision of the manuscript for important intellectual content: D’Journo, Boulate, Fourdrain, van Berge Henegouwen, Gisbertz, O’Neill, Hoelscher, Piessen, van Lanschot, Wijnhoven, Davies, Schneider, Pera, Nilsson, Nafteux, Kitagawa, Morse, Hofstetter, Molena, So, Parsons, Larsen, Dolan, Wood, Maynard, Smithers, Puig, Law, Wong, Kennedy, Reynolds, Pramesh, Ferguson, Darling, Schröder, Bludau, Underwood, van Hillegersberg, Chang, Cecconello, Ribeiro, de Manzoni, Rosati, Kuppusamy, Thomas, Low. Statistical analysis: D’Journo, Loundou, Wong. Obtained funding: D’Journo. Administrative, technical, or material support: D’Journo, Gisbertz, Piessen, Jobe, Davies, Nilsson, Kitagawa, Morse, Hofstetter, Dolan, Smithers, Law, Wong, Reynolds, Ferguson, Darling, Schröder, Underwood,vanHillegersberg,Chang,Kuppusamy,Low. Supervision: D’Journo, Fourdrain, Hoelscher, van Lanschot, Wijnhoven, Nafteux, Molena, Immanuel, Law, Reynolds, Pramesh, Cecconello, Ribeiro, Rosati, Thomas, Low. Conflict of Interest Disclosures: Dr D’Journo reported receiving grants from the Marseille Research Thoracic Oncology Foundation during the conduct of the study. Dr van Berge Henegouwen reported receiving grants from Olympus and Stryker and personal fees from Medtronic, Mylan, Alesi Surgical, and Johnson & Johnson outside the submitted work. Dr Piessen reported receiving nonfinancial support from Medtronic and personal fees from BMS, Amgen, Roche, Stryker, Nestle, and MSD outside the submitted work. Dr Kitagawa reported receiving grants from Chugai Pharmaceutical Co Ltd, Taiho Pharmaceutical Co Ltd, Yakult Honsha Co Ltd, Asahi Kasei Pharma Corporation, Otsuka Pharmaceutical Co Ltd, and Nippon Covidien Inc outside the submitted work. Dr Molena reported receiving travel reimbursement from Intuitive, Johnson & Johnson, Urogen, Boston Scientific, and AstraZeneca outside the submitted work. Dr Thomas reported receiving personal fees from Ethicon and AstraZeneca outside the submitted work. No other disclosures were reported. Funding/Support: This study was supported by the Marseille Research Thoracic Oncology Foundation. Role of the Funder/Sponsor: The funder played a role in the collection, management, analysis, and interpretation of the data.

Publisher Copyright:
© 2021 American Medical Association. All rights reserved.

Fingerprint

Dive into the research topics of 'Risk Prediction Model of 90-Day Mortality after Esophagectomy for Cancer'. Together they form a unique fingerprint.

Cite this