Literature DB >> 34160587

Risk Prediction Model of 90-Day Mortality After Esophagectomy for Cancer.

Xavier Benoit D'Journo1, David Boulate1, Alex Fourdrain1, Anderson Loundou1, Mark I van Berge Henegouwen2, Suzanne S Gisbertz2, J Robert O'Neill3, Arnulf Hoelscher4, Guillaume Piessen5, Jan van Lanschot6, Bas Wijnhoven6, Blair Jobe7, Andrew Davies8, Paul M Schneider9, Manuel Pera10, Magnus Nilsson11, Philippe Nafteux12, Yuko Kitagawa13, Christopher R Morse14, Wayne Hofstetter15, Daniela Molena16, Jimmy Bok-Yan So17, Arul Immanuel18, Simon L Parsons19, Michael Hareskov Larsen20, James P Dolan21, Stephanie G Wood21, Nick Maynard22, Mark Smithers23, Sonia Puig24, Simon Law25, Ian Wong25, Andrew Kennedy26, Wang KangNing27, John V Reynolds28, C S Pramesh29, Mark Ferguson30, Gail Darling31, Wolfgang Schröder32, Marc Bludau32, Tim Underwood33, Richard van Hillegersberg34, Andrew Chang35, Ivan Cecconello36, Ulysses Ribeiro36, Giovanni de Manzoni37, Riccardo Rosati38, MadhanKumar Kuppusamy39, Pascal Alexandre Thomas1, Donald E Low39.   

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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Mesh:

Year:  2021        PMID: 34160587      PMCID: PMC8223144          DOI: 10.1001/jamasurg.2021.2376

Source DB:  PubMed          Journal:  JAMA Surg        ISSN: 2168-6254            Impact factor:   16.681


  4 in total

1.  Error in a Supplement.

Authors: 
Journal:  JAMA Surg       Date:  2021-09-01       Impact factor: 14.766

Review 2.  Esophagectomy-prevention of complications-tips and tricks for the preoperative, intraoperative and postoperative stage.

Authors:  Uberto Fumagalli Romario; Stefano de Pascale
Journal:  Updates Surg       Date:  2022-07-18

3.  Perioperative Outcomes of Minimally Invasive Esophagectomy After Neoadjuvant Immunotherapy for Patients With Locally Advanced Esophageal Squamous Cell Carcinoma.

Authors:  Jiahan Cheng; Minzhang Guo; Yushang Yang; Yilin Liu; Weipeng Hu; Qixin Shang; Chuan Li; Liang Xia; Yun Wang; Wenping Wang; Dong Tian; Yong Yuan; Yang Hu; Longqi Chen
Journal:  Front Immunol       Date:  2022-03-11       Impact factor: 7.561

4.  Mortality Prediction Model before Surgery for Acute Mesenteric Infarction: A Population-Based Study.

Authors:  Shang-Wei Lin; Chung-Yen Chen; Yu-Chieh Su; Kun-Ta Wu; Po-Chin Yu; Yung-Chieh Yen; Jian-Han Chen
Journal:  J Clin Med       Date:  2022-10-08       Impact factor: 4.964

  4 in total

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