Literature DB >> 21871985

Comparison of different risk-adjustment models in assessing short-term surgical outcome after transthoracic esophagectomy in patients with esophageal cancer.

Dirk J Bosch1, Bastiaan B Pultrum, Gertrude H de Bock, Jurjen K Oosterhuis, Michael G G Rodgers, John T M Plukker.   

Abstract

BACKGROUND: Different risk-prediction models have been developed, but none is generally accepted in selecting patients for esophagectomy. This study evaluated 5 most frequently used risk-prediction models, including the American Society of Anesthesiologists, Portsmouth-modified Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (P-POSSUM), and the adjusted version for Oesophagogastric surgery (O-POSSUM), Charlson and the Age adjusted Charlson score to assess postoperative mortality after transthoracic esophagectomy.
METHODS: Data were obtained from 278 consecutive esophageal cancer patients between 1991 and 2007. Performance in predicting postoperative mortality (in-hospital and 90-day mortality) were analyzed regarding calibration (Hosmer and Lemeshow goodness-of-fit test) and discrimination (area under the receiver operator curve).
RESULTS: The Hosmer and Lemeshow goodness-of-fit test was applied to each model and showed a significant outcome for only the P-POSSUM score (P = .035). The receiver operator curve indicated discriminatory power for P-POSSUM (.766) and for O-POSSUM (.756), other models did not exceed the minimal surface of .7.
CONCLUSIONS: Postoperative mortality after esophagectomy was best predicted by O-POSSUM. However, it still overpredicted postoperative mortality.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21871985     DOI: 10.1016/j.amjsurg.2011.04.003

Source DB:  PubMed          Journal:  Am J Surg        ISSN: 0002-9610            Impact factor:   2.565


  4 in total

1.  Patient Selection for Oesophagectomy: Impact of Age and Comorbidities on Outcome.

Authors:  Gregory O'Grady; Ahmer M Hameed; Tony C Pang; Emma Johnston; Vincent T Lam; Arthur J Richardson; Michael J Hollands
Journal:  World J Surg       Date:  2015-08       Impact factor: 3.352

Review 2.  Individual risk modelling for esophagectomy: a systematic review.

Authors:  John M Findlay; Richard S Gillies; Bruno Sgromo; Robert E K Marshall; Mark R Middleton; Nicholas D Maynard
Journal:  J Gastrointest Surg       Date:  2014-04-24       Impact factor: 3.452

Review 3.  Prediction models for patients with esophageal or gastric cancer: A systematic review and meta-analysis.

Authors:  H G van den Boorn; E G Engelhardt; J van Kleef; M A G Sprangers; M G H van Oijen; A Abu-Hanna; A H Zwinderman; V M H Coupé; H W M van Laarhoven
Journal:  PLoS One       Date:  2018-02-08       Impact factor: 3.240

4.  Impact of Age and Comorbidity on Choice and Outcome of Two Different Treatment Options for Patients with Potentially Curable Esophageal Cancer.

Authors:  Z Faiz; M van Putten; R H A Verhoeven; J W van Sandick; G A P Nieuwenhuijzen; M J C van der Sangen; V E P P Lemmens; B P L Wijnhoven; J T M Plukker
Journal:  Ann Surg Oncol       Date:  2019-02-04       Impact factor: 5.344

  4 in total

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