Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer

Yifei Ma,1 Ping Lu,2 Xinjun Liang,2 Shaozhong Wei1 1Department of Gastrointestinal Oncology Surgery, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 2Department of Abd...

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Autores principales: Ma Y, Lu P, Liang X, Wei S
Formato: article
Lenguaje:EN
Publicado: Dove Medical Press 2021
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Acceso en línea:https://doaj.org/article/f7cbc9bc62344cd38df1b08176745ba6
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id oai:doaj.org-article:f7cbc9bc62344cd38df1b08176745ba6
record_format dspace
institution DOAJ
collection DOAJ
language EN
topic colorectal cancer
prognosis
time-dependent receiver operating characteristic curve
nomogram
inflammatory indices
biochemical indices
Pathology
RB1-214
Therapeutics. Pharmacology
RM1-950
spellingShingle colorectal cancer
prognosis
time-dependent receiver operating characteristic curve
nomogram
inflammatory indices
biochemical indices
Pathology
RB1-214
Therapeutics. Pharmacology
RM1-950
Ma Y
Lu P
Liang X
Wei S
Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer
description Yifei Ma,1 Ping Lu,2 Xinjun Liang,2 Shaozhong Wei1 1Department of Gastrointestinal Oncology Surgery, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 2Department of Abdominal Oncology, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of ChinaCorrespondence: Xinjun LiangDepartment of Abdominal Oncology, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, 116 Zhuodaoquan South Road, Wuhan, Hubei, 430079, People’s Republic of ChinaTel/Fax +86-27-87671663Email doctorlxj@163.comShaozhong WeiDepartment of Gastrointestinal Oncology Surgery, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, 116 Zhuodaoquan South Road, Wuhan, Hubei, 430079, People’s Republic of ChinaTel/Fax +86-27-87671663Email weishaozhong@163.comBackground: Recent studies have found that clinicopathological indices, such as inflammatory and biochemical indices, play a significant role in the prognosis of colorectal cancer (CRC) patients. However, few studies have focused on the effect of dynamic changes in these indicators. In our study, we studied the influence of dynamic changes in inflammatory and biochemical indices on patient outcomes during the perioperative period.Methods: We enrolled 551 patients from Hubei Cancer Hospital who had undergone radical resection of CRC and collected the results of laboratory examinations performed within 1 week before surgery and at the first admission after surgery. The whole population was randomly divided into the training (386) and testing (185) cohorts. We used postoperative inflammatory and biochemical indices/preoperative inflammatory and biochemical indices (ΔX) to reflect the dynamic changes. Chi-square tests, Kaplan–Meier survival analyses, and univariate and multivariate Cox regression analyses were used to evaluate the prognosis. The prediction accuracies of models for overall survival (OS) and disease-free survival (DFS) were estimated through Harrell’s concordance index (the C-index) and Brier scores. Nomograms of the prognostic models were plotted for evaluations of individualized outcomes.Results: The median follow-up time of the 551 patients was 35.6 (range: 1.1– 73.8) months. Ultimately, the prognostic models based on age, sex, TNM stage, pathological conditions, inflammatory and biochemical indices, CEA, and CA199 were found to have exceptional performance for OS and DFS. The C-index of the nomogram for OS was 0.806 (95% CI, 0.75– 0.86) in the training cohort and 0.921 (95% CI, 0.87– 0.96) in the testing cohort. The C-index of the nomogram for DFS was 0.781 (95% CI, 0.74– 0.82) in the training cohort and 0.835 (95% CI, 0.78– 0.88) in the testing cohort.Conclusion: We successfully established a novel model based on inflammatory and biochemical indices to guide clinical decision-making for CRC.Keywords: colorectal cancer, prognosis, time-dependent receiver operating characteristic curve, nomogram, inflammatory indices, biochemical indices
format article
author Ma Y
Lu P
Liang X
Wei S
author_facet Ma Y
Lu P
Liang X
Wei S
author_sort Ma Y
title Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer
title_short Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer
title_full Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer
title_fullStr Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer
title_full_unstemmed Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer
title_sort models based on dynamic clinicopathological indices for predicting prognosis during the perioperative period for patients with colorectal cancer
publisher Dove Medical Press
publishDate 2021
url https://doaj.org/article/f7cbc9bc62344cd38df1b08176745ba6
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spelling oai:doaj.org-article:f7cbc9bc62344cd38df1b08176745ba62021-12-02T16:41:09ZModels Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer1178-7031https://doaj.org/article/f7cbc9bc62344cd38df1b08176745ba62021-04-01T00:00:00Zhttps://www.dovepress.com/models-based-on-dynamic-clinicopathological-indices-for-predicting-pro-peer-reviewed-fulltext-article-JIRhttps://doaj.org/toc/1178-7031Yifei Ma,1 Ping Lu,2 Xinjun Liang,2 Shaozhong Wei1 1Department of Gastrointestinal Oncology Surgery, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 2Department of Abdominal Oncology, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of ChinaCorrespondence: Xinjun LiangDepartment of Abdominal Oncology, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, 116 Zhuodaoquan South Road, Wuhan, Hubei, 430079, People’s Republic of ChinaTel/Fax +86-27-87671663Email doctorlxj@163.comShaozhong WeiDepartment of Gastrointestinal Oncology Surgery, Hubei Cancer Hospital, The Seventh Clinical School Affiliated of Tongji Medical College, Huazhong University of Science and Technology, 116 Zhuodaoquan South Road, Wuhan, Hubei, 430079, People’s Republic of ChinaTel/Fax +86-27-87671663Email weishaozhong@163.comBackground: Recent studies have found that clinicopathological indices, such as inflammatory and biochemical indices, play a significant role in the prognosis of colorectal cancer (CRC) patients. However, few studies have focused on the effect of dynamic changes in these indicators. In our study, we studied the influence of dynamic changes in inflammatory and biochemical indices on patient outcomes during the perioperative period.Methods: We enrolled 551 patients from Hubei Cancer Hospital who had undergone radical resection of CRC and collected the results of laboratory examinations performed within 1 week before surgery and at the first admission after surgery. The whole population was randomly divided into the training (386) and testing (185) cohorts. We used postoperative inflammatory and biochemical indices/preoperative inflammatory and biochemical indices (ΔX) to reflect the dynamic changes. Chi-square tests, Kaplan–Meier survival analyses, and univariate and multivariate Cox regression analyses were used to evaluate the prognosis. The prediction accuracies of models for overall survival (OS) and disease-free survival (DFS) were estimated through Harrell’s concordance index (the C-index) and Brier scores. Nomograms of the prognostic models were plotted for evaluations of individualized outcomes.Results: The median follow-up time of the 551 patients was 35.6 (range: 1.1– 73.8) months. Ultimately, the prognostic models based on age, sex, TNM stage, pathological conditions, inflammatory and biochemical indices, CEA, and CA199 were found to have exceptional performance for OS and DFS. The C-index of the nomogram for OS was 0.806 (95% CI, 0.75– 0.86) in the training cohort and 0.921 (95% CI, 0.87– 0.96) in the testing cohort. The C-index of the nomogram for DFS was 0.781 (95% CI, 0.74– 0.82) in the training cohort and 0.835 (95% CI, 0.78– 0.88) in the testing cohort.Conclusion: We successfully established a novel model based on inflammatory and biochemical indices to guide clinical decision-making for CRC.Keywords: colorectal cancer, prognosis, time-dependent receiver operating characteristic curve, nomogram, inflammatory indices, biochemical indicesMa YLu PLiang XWei SDove Medical Pressarticlecolorectal cancerprognosistime-dependent receiver operating characteristic curvenomograminflammatory indicesbiochemical indicesPathologyRB1-214Therapeutics. PharmacologyRM1-950ENJournal of Inflammation Research, Vol Volume 14, Pp 1591-1601 (2021)