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To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients

Context: Appropriate selection of aging patient who fit for cancer surgery is an art-of-state. Objectives: This study aimed to identify predictive factors pertinent to 3-month postoperative mortality in geriatric cancer patients. Methods: A total of 8,425 patients over 70 years old with solid cancer...

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Autores principales: Chou, Wen-Chi, Liu, Keng-Hao, Lu, Chang-Hsien, Hung, Yu-Shin, Chen, Miao-Fen, Cheng, Yu-Fan, Wang, Cheng-Hsu, Lin, Yung-Chang, Yeh, Ta-Sen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4679376/
https://www.ncbi.nlm.nih.gov/pubmed/26722355
http://dx.doi.org/10.7150/jca.13126
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author Chou, Wen-Chi
Liu, Keng-Hao
Lu, Chang-Hsien
Hung, Yu-Shin
Chen, Miao-Fen
Cheng, Yu-Fan
Wang, Cheng-Hsu
Lin, Yung-Chang
Yeh, Ta-Sen
author_facet Chou, Wen-Chi
Liu, Keng-Hao
Lu, Chang-Hsien
Hung, Yu-Shin
Chen, Miao-Fen
Cheng, Yu-Fan
Wang, Cheng-Hsu
Lin, Yung-Chang
Yeh, Ta-Sen
author_sort Chou, Wen-Chi
collection PubMed
description Context: Appropriate selection of aging patient who fit for cancer surgery is an art-of-state. Objectives: This study aimed to identify predictive factors pertinent to 3-month postoperative mortality in geriatric cancer patients. Methods: A total of 8,425 patients over 70 years old with solid cancer received radical surgery between 2007 and 2012 at four affiliated hospitals of the Chang Gung Memorial Hospital were included. The clinical variables of patients who died within 3 months post-surgery were analyzed retrospectively. Recursive partitioning analysis (RPA) was performed by randomly selecting 50% of the patients (testing set) to identify specific groups of patients with the lowest and highest probability of 3-month postoperative mortality. The remaining 50% were used as validation set of the model. Results: Patients' gender, Eastern Cooperative Oncology Group performance (ECOG scale), Charlson comorbidity index (CCI), American Society of Anesthesiologist physical status, age, tumor staging, and mode of admission were independent variables that predicted 3-month postoperative mortality. The RPA model identified patients with an ECOG scale of 0-2, localized tumor stage, and a CCI of 0-2 as having the lowest probability of 3-month postoperative mortality (1.1% and 1.3% in the testing set and validation set, respectively). Conversely, an ECOG scale of 3-4 and a CCI >2 were associated with the highest probability of 3-month postoperative mortality (55.2% and 47.8% in the testing set and validation set, respectively). Conclusion: We identified ECOG scale and CCI score were the two most influencing factors that determined 3-month postoperative mortality in geriatric cancer patients.
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spelling pubmed-46793762016-01-01 To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients Chou, Wen-Chi Liu, Keng-Hao Lu, Chang-Hsien Hung, Yu-Shin Chen, Miao-Fen Cheng, Yu-Fan Wang, Cheng-Hsu Lin, Yung-Chang Yeh, Ta-Sen J Cancer Research Paper Context: Appropriate selection of aging patient who fit for cancer surgery is an art-of-state. Objectives: This study aimed to identify predictive factors pertinent to 3-month postoperative mortality in geriatric cancer patients. Methods: A total of 8,425 patients over 70 years old with solid cancer received radical surgery between 2007 and 2012 at four affiliated hospitals of the Chang Gung Memorial Hospital were included. The clinical variables of patients who died within 3 months post-surgery were analyzed retrospectively. Recursive partitioning analysis (RPA) was performed by randomly selecting 50% of the patients (testing set) to identify specific groups of patients with the lowest and highest probability of 3-month postoperative mortality. The remaining 50% were used as validation set of the model. Results: Patients' gender, Eastern Cooperative Oncology Group performance (ECOG scale), Charlson comorbidity index (CCI), American Society of Anesthesiologist physical status, age, tumor staging, and mode of admission were independent variables that predicted 3-month postoperative mortality. The RPA model identified patients with an ECOG scale of 0-2, localized tumor stage, and a CCI of 0-2 as having the lowest probability of 3-month postoperative mortality (1.1% and 1.3% in the testing set and validation set, respectively). Conversely, an ECOG scale of 3-4 and a CCI >2 were associated with the highest probability of 3-month postoperative mortality (55.2% and 47.8% in the testing set and validation set, respectively). Conclusion: We identified ECOG scale and CCI score were the two most influencing factors that determined 3-month postoperative mortality in geriatric cancer patients. Ivyspring International Publisher 2016-01-01 /pmc/articles/PMC4679376/ /pubmed/26722355 http://dx.doi.org/10.7150/jca.13126 Text en © Ivyspring International Publisher. Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited. See http://ivyspring.com/terms for terms and conditions.
spellingShingle Research Paper
Chou, Wen-Chi
Liu, Keng-Hao
Lu, Chang-Hsien
Hung, Yu-Shin
Chen, Miao-Fen
Cheng, Yu-Fan
Wang, Cheng-Hsu
Lin, Yung-Chang
Yeh, Ta-Sen
To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients
title To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients
title_full To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients
title_fullStr To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients
title_full_unstemmed To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients
title_short To Operate or Not: Prediction of 3-Month Postoperative Mortality in Geriatric Cancer Patients
title_sort to operate or not: prediction of 3-month postoperative mortality in geriatric cancer patients
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4679376/
https://www.ncbi.nlm.nih.gov/pubmed/26722355
http://dx.doi.org/10.7150/jca.13126
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