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Nomogram for predicting overall survival in stage II‐III colorectal cancer

PURPOSE: The overall survival (OS) of patients diagnosed with stage II‐III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II‐III CRC and stratify patients with CRC into different risk groups. P...

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Autores principales: Liu, Jungang, Huang, Xiaoliang, Yang, Wenkang, Li, Chan, Li, Zhengtian, Zhang, Chuqiao, Chen, Shaomei, Wu, Guo, Xie, Weishun, Wei, Chunyin, Tian, Chao, Huang, Lingxu, Jeen, Franco, Mo, Xianwei, Tang, Weizhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7131840/
https://www.ncbi.nlm.nih.gov/pubmed/32027098
http://dx.doi.org/10.1002/cam4.2896
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author Liu, Jungang
Huang, Xiaoliang
Yang, Wenkang
Li, Chan
Li, Zhengtian
Zhang, Chuqiao
Chen, Shaomei
Wu, Guo
Xie, Weishun
Wei, Chunyin
Tian, Chao
Huang, Lingxu
Jeen, Franco
Mo, Xianwei
Tang, Weizhong
author_facet Liu, Jungang
Huang, Xiaoliang
Yang, Wenkang
Li, Chan
Li, Zhengtian
Zhang, Chuqiao
Chen, Shaomei
Wu, Guo
Xie, Weishun
Wei, Chunyin
Tian, Chao
Huang, Lingxu
Jeen, Franco
Mo, Xianwei
Tang, Weizhong
author_sort Liu, Jungang
collection PubMed
description PURPOSE: The overall survival (OS) of patients diagnosed with stage II‐III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II‐III CRC and stratify patients with CRC into different risk groups. PATIENTS AND METHODS: Based on data from 873 patients with CRC, we used univariate Cox regression analysis to select the significant prognostic features, which were subjected to the least absolute shrinkage and selection operator (LASSO) regression algorithm for feature selection. Cross‐validation was used to confirm suitable tuning parameters (λ) for LASSO logistic regression. Then, the nomogram was used to estimate 3‐ and 5‐year OS based on the multivariable Cox regression model. The survival curves of the two groups were produced using the Kaplan‐Meier method. Risk group stratification was performed to assess the predictive capacity of the nomogram. RESULTS: Preoperative mean platelet volume, preoperative platelet distribution width, monocytes, and postoperative adjuvant chemotherapy were identified as independent prognostic factors by LASSO regression and integrated for the construction of the nomogram. The nomogram provided good discrimination, with C‐indices of 0.67 and 0.69 for the training and validation sets, respectively. Calibration plots illustrated excellent agreement between the nomogram predictions and actual observations for 3‐ and 5‐year OS. Moreover, a significant difference in OS was shown between patients stratified into different risk groups (P < .001). CONCLUSION: We constructed and validated an original predictive nomogram for OS in patients with CRC after surgery, facilitating physicians to appraise the individual survival of postoperative patients accurately and identify high‐risk patients who need more aggressive treatment and follow‐up strategies.
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spelling pubmed-71318402020-04-06 Nomogram for predicting overall survival in stage II‐III colorectal cancer Liu, Jungang Huang, Xiaoliang Yang, Wenkang Li, Chan Li, Zhengtian Zhang, Chuqiao Chen, Shaomei Wu, Guo Xie, Weishun Wei, Chunyin Tian, Chao Huang, Lingxu Jeen, Franco Mo, Xianwei Tang, Weizhong Cancer Med Clinical Cancer Research PURPOSE: The overall survival (OS) of patients diagnosed with stage II‐III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II‐III CRC and stratify patients with CRC into different risk groups. PATIENTS AND METHODS: Based on data from 873 patients with CRC, we used univariate Cox regression analysis to select the significant prognostic features, which were subjected to the least absolute shrinkage and selection operator (LASSO) regression algorithm for feature selection. Cross‐validation was used to confirm suitable tuning parameters (λ) for LASSO logistic regression. Then, the nomogram was used to estimate 3‐ and 5‐year OS based on the multivariable Cox regression model. The survival curves of the two groups were produced using the Kaplan‐Meier method. Risk group stratification was performed to assess the predictive capacity of the nomogram. RESULTS: Preoperative mean platelet volume, preoperative platelet distribution width, monocytes, and postoperative adjuvant chemotherapy were identified as independent prognostic factors by LASSO regression and integrated for the construction of the nomogram. The nomogram provided good discrimination, with C‐indices of 0.67 and 0.69 for the training and validation sets, respectively. Calibration plots illustrated excellent agreement between the nomogram predictions and actual observations for 3‐ and 5‐year OS. Moreover, a significant difference in OS was shown between patients stratified into different risk groups (P < .001). CONCLUSION: We constructed and validated an original predictive nomogram for OS in patients with CRC after surgery, facilitating physicians to appraise the individual survival of postoperative patients accurately and identify high‐risk patients who need more aggressive treatment and follow‐up strategies. John Wiley and Sons Inc. 2020-02-06 /pmc/articles/PMC7131840/ /pubmed/32027098 http://dx.doi.org/10.1002/cam4.2896 Text en © 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Cancer Research
Liu, Jungang
Huang, Xiaoliang
Yang, Wenkang
Li, Chan
Li, Zhengtian
Zhang, Chuqiao
Chen, Shaomei
Wu, Guo
Xie, Weishun
Wei, Chunyin
Tian, Chao
Huang, Lingxu
Jeen, Franco
Mo, Xianwei
Tang, Weizhong
Nomogram for predicting overall survival in stage II‐III colorectal cancer
title Nomogram for predicting overall survival in stage II‐III colorectal cancer
title_full Nomogram for predicting overall survival in stage II‐III colorectal cancer
title_fullStr Nomogram for predicting overall survival in stage II‐III colorectal cancer
title_full_unstemmed Nomogram for predicting overall survival in stage II‐III colorectal cancer
title_short Nomogram for predicting overall survival in stage II‐III colorectal cancer
title_sort nomogram for predicting overall survival in stage ii‐iii colorectal cancer
topic Clinical Cancer Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7131840/
https://www.ncbi.nlm.nih.gov/pubmed/32027098
http://dx.doi.org/10.1002/cam4.2896
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