Produção Nacional
Revisado por pares
Risk Prediction Model of 90-Day Mortality After Esophagectomy for Cancer
2021; American Medical Association; Volume: 156; Issue: 9 Linguagem: Inglês
10.1001/jamasurg.2021.2376
ISSN2168-6262
AutoresXavier Benoît D’Journo, David Boulate, Alex Fourdrain, Anderson Loundou, Mark I. van Berge Henegouwen, Suzanne S. Gisbertz, J. Robert O’Neill, Arnulf H. Hoelscher, Guillaume Piessen, Jan van Lanschot, Bas P. L. Wijnhoven, Blair A. Jobe, Andrew Davies, Paul M. Schneider, Manuel Pera, Magnus Nilsson, Philippe Nafteux, Yuko Kitagawa, Christopher R. Morse, Wayne L. Hofstetter, Daniela Molena, Jimmy Bok Yan So, Arul Immanuel, Simon L. Parsons, Michael Hareskov Larsen, James P. Dolan, Stephanie G. Wood, Nick Maynard, B. Mark Smithers, Susana Puig, Simon Law, Yhi Wong, Andrew Kennedy, Kangning Wang, John V. Reynolds, C.S. Pramesh, Mark K. Ferguson, Gail Darling, Wölfgang Schröder, Marc Bludau, Timothy J. Underwood, Richard van Hillegersberg, Andrew C. Chang, Ivan Cecconello, Ulysses Ribeiro, Giovanni de Manzoni, Riccardo Rosati, MadhanKumar Kuppusamy, P. Thomas, Donald E. Low, Geoffrey Brioude, Delphine Trousse, Egle Jezerskyte, Wietse J. Eshuis, Richard Hardwick, Peter Safranek, John M. Bennett, Andrew Hindmarsh, Vijay Sujedran, Martin Hemmerich, Margerite Messier, Sebastien Degissors, Frederiek Nuytens, C. Mariette, Sjoerd M. Lagarde, Ali H. Zaidi, Janine Zylstra, James Gossage, Cara Baker, Mark Kelly, Simone Schillinger, Marta Gimeno, Fredrik Klevebro, Masaru Hayami, Antoon Lerut, Johnny Moons, Hirofumi Kawakubo, Satoru Matsuda, Yuki Hirata, Julie M. Garrity, Huawei Tang, Manjit S. Bains, Joseph Dycoco, Kristen Busalacchi, Rebecca Carr, David R. Jones, Asim Shabbir, Michael J. Griffin, Helen Jaretzke, Neil T. Welch, Ravinder Vohra, James Catton, J. Saunders, Fadi Yanni, Daniela Zanotti, Pritam Singh, Larsen Nicolaj, Marcus Stilling, Charlie Borzy, Kayla Siemens, John M. Findlay, Stephen Ash, Iain Thomson, Andrew P. Barbour, Janine Thomas, John Whiting, Jeannette Kwok, Raymond Kennedy, Qiang Fang, Yongtao Han, Penh Lin, Wenguang Xiao, Sinéad King, Ravinder Narayanasamy, Apurva Ashok, Amy Durkin-Celauro, Catherine Staub, Emma Small, Christiane J. Bruns, James Byrne, Jamie Kelly, Fergus Noble, Donna Sharland, Rachel Fraser, Rob F. Walker, Saqib Rahman, Ben Grace, Jelle P. Ruurda, Sylvia Van der Host, Arjen van der Veen, Gino M. Kuiper, Judy Miller, Shari Barnett, Rubens AA Sallum, Jacopo Weindelmayer, Carlo Alberto De Pasqual, Paolo Parisse, Andrea Cossu, Francesco Puccetti, Simonetta Massaron, Bonnie Marston,
Tópico(s)Gastric Cancer Management and Outcomes
ResumoImportance 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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