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Risk prediction model of 90-day mortality after esophagectomy for Cancer

Risk prediction model of 90-day mortality after esophagectomy for Cancer
Risk prediction model of 90-day mortality after esophagectomy for Cancer

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.

2168-6254
836-845
D'Journo, Xavier Benoit
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Boulate, David
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Fourdrain, Alex
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van Berge Henegouwen, Mark I
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Gisbertz, Suzanne S
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International Esodata Study Group (2021) Risk prediction model of 90-day mortality after esophagectomy for Cancer. JAMA Surgery, 156 (9), 836-845. (doi:10.1001/jamasurg.2021.2376).

Record type: Article

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.

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e-pub ahead of print date: 23 June 2021
Published date: 23 June 2021
Additional Information: 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.

Identifiers

Local EPrints ID: 450530
URI: http://eprints.soton.ac.uk/id/eprint/450530
ISSN: 2168-6254
PURE UUID: 3c5a6969-69ab-4d84-afcd-c1225122875e
ORCID for Tim Underwood: ORCID iD orcid.org/0000-0001-9455-2188

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Date deposited: 03 Aug 2021 16:30
Last modified: 17 Mar 2024 02:58

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Contributors

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

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