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Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy
BACKGROUND: Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complet...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673964/ https://www.ncbi.nlm.nih.gov/pubmed/33268952 http://dx.doi.org/10.3748/wjg.v26.i42.6638 |
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author | Wei, Fang-Ze Mei, Shi-Wen Chen, Jia-Nan Wang, Zhi-Jie Shen, Hai-Yu Li, Juan Zhao, Fu-Qiang Liu, Zheng Liu, Qian |
author_facet | Wei, Fang-Ze Mei, Shi-Wen Chen, Jia-Nan Wang, Zhi-Jie Shen, Hai-Yu Li, Juan Zhao, Fu-Qiang Liu, Zheng Liu, Qian |
author_sort | Wei, Fang-Ze |
collection | PubMed |
description | BACKGROUND: Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complete pathological response, and most patients require surgical resection and adjuvant therapy. Therefore, identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance. AIM: To establish effective prognostic nomograms and risk score prediction models to predict overall survival (OS) and disease-free survival (DFS) for LARC treated with NT. METHODS: Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017. The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors, which were validated by the Cox regression method. Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves, and that of the two nomograms was conducted by calculating the concordance index (C-index) and calibration curves. The results were validated in a cohort of 65 patients from 2015 to 2017. RESULTS: Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model: Vascular_tumors_bolt, cancer nodules, yN, body mass index, matchmouth distance from the edge, nerve aggression and postoperative carcinoembryonic antigen. The nomogram showed good predictive value for OS, with a C-index of 0.91 (95%CI: 0.85, 0.97) and good calibration. In the validation cohort, the C-index was 0.69 (95%CI: 0.53, 0.84). The risk factor prediction model showed good predictive value. The areas under the curve for 3- and 5-year survival were 0.811 and 0.782. The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77 (95%CI: 0.69, 0.85). In the validation cohort, the C-index was 0.71 (95%CI: 0.61, 0.81). The prediction model for DFS also had good predictive value, with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754. CONCLUSION: We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT. |
format | Online Article Text |
id | pubmed-7673964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-76739642020-12-01 Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy Wei, Fang-Ze Mei, Shi-Wen Chen, Jia-Nan Wang, Zhi-Jie Shen, Hai-Yu Li, Juan Zhao, Fu-Qiang Liu, Zheng Liu, Qian World J Gastroenterol Retrospective Cohort Study BACKGROUND: Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complete pathological response, and most patients require surgical resection and adjuvant therapy. Therefore, identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance. AIM: To establish effective prognostic nomograms and risk score prediction models to predict overall survival (OS) and disease-free survival (DFS) for LARC treated with NT. METHODS: Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017. The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors, which were validated by the Cox regression method. Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves, and that of the two nomograms was conducted by calculating the concordance index (C-index) and calibration curves. The results were validated in a cohort of 65 patients from 2015 to 2017. RESULTS: Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model: Vascular_tumors_bolt, cancer nodules, yN, body mass index, matchmouth distance from the edge, nerve aggression and postoperative carcinoembryonic antigen. The nomogram showed good predictive value for OS, with a C-index of 0.91 (95%CI: 0.85, 0.97) and good calibration. In the validation cohort, the C-index was 0.69 (95%CI: 0.53, 0.84). The risk factor prediction model showed good predictive value. The areas under the curve for 3- and 5-year survival were 0.811 and 0.782. The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77 (95%CI: 0.69, 0.85). In the validation cohort, the C-index was 0.71 (95%CI: 0.61, 0.81). The prediction model for DFS also had good predictive value, with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754. CONCLUSION: We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT. Baishideng Publishing Group Inc 2020-11-14 2020-11-14 /pmc/articles/PMC7673964/ /pubmed/33268952 http://dx.doi.org/10.3748/wjg.v26.i42.6638 Text en ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. |
spellingShingle | Retrospective Cohort Study Wei, Fang-Ze Mei, Shi-Wen Chen, Jia-Nan Wang, Zhi-Jie Shen, Hai-Yu Li, Juan Zhao, Fu-Qiang Liu, Zheng Liu, Qian Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy |
title | Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy |
title_full | Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy |
title_fullStr | Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy |
title_full_unstemmed | Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy |
title_short | Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy |
title_sort | nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy |
topic | Retrospective Cohort Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673964/ https://www.ncbi.nlm.nih.gov/pubmed/33268952 http://dx.doi.org/10.3748/wjg.v26.i42.6638 |
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