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A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer

BACKGROUND: The pathological T3N0M0 (pT3N0M0) rectal cancer is the earliest stage and has the best prognosis in the locally advanced rectal cancer, but the optimal treatment remains controversial. A reliable prognostic model is needed to discriminate the high-risk patients from the low-risk patients...

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Autores principales: Liu, Shuang, Yang, Shanfei, Yu, Haina, Luo, Huilong, Chen, Gong, Gao, Yuanhong, Sun, Rui, Xiao, Weiwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441689/
https://www.ncbi.nlm.nih.gov/pubmed/36072948
http://dx.doi.org/10.3389/fmed.2022.977652
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author Liu, Shuang
Yang, Shanfei
Yu, Haina
Luo, Huilong
Chen, Gong
Gao, Yuanhong
Sun, Rui
Xiao, Weiwei
author_facet Liu, Shuang
Yang, Shanfei
Yu, Haina
Luo, Huilong
Chen, Gong
Gao, Yuanhong
Sun, Rui
Xiao, Weiwei
author_sort Liu, Shuang
collection PubMed
description BACKGROUND: The pathological T3N0M0 (pT3N0M0) rectal cancer is the earliest stage and has the best prognosis in the locally advanced rectal cancer, but the optimal treatment remains controversial. A reliable prognostic model is needed to discriminate the high-risk patients from the low-risk patients, and optimize adjuvant chemotherapy (ACT) treatment decisions by predicting the likelihood of ACT benefit for the target population. PATIENTS AND METHODS: We gathered and analyzed 276 patients in Sun Yat-sen University Cancer Center from March 2005 to December 2011. All patients underwent total mesorectal excision (TME), without preoperative therapy, and were pathologically proven pT3N0M0 rectal cancer with negative circumferential resection margin (CRM). LASSO regression model was used for variable selection and risk factor prediction. Multivariable cox regression was used to develop the predicting model. Optimum cut-off values were determined using X-Tile plot analysis. The 10-fold cross-validation was adopted to validate the model. The performance of the nomogram was evaluated with its calibration, discrimination and clinical usefulness. RESULTS: A total of 188 patients (68.1%) had ACT and no patients had adjuvant radiotherapy. Age, monocyte percentage, carbohydrate antigen 19–9, lymph node dissection numbers and perineural invasion (PNI) were identified as significantly associated variables that could be combined for an accurate prediction risk of Cancer Specific Survival (CSS) for pT3N0M0 patients. The model adjusted for CSS showed good discrimination with a C-index of 0.723 (95% CI: 0.652–0.794). The calibration curves showed that the nomogram adjusted for CSS was able to predict 3-, 5-, and 10-year CSS accurately. The corresponding predicted probability was used to stratify high and low-risk patients (10-year CSS: 69.1% vs. 90.8%, HR = 3.815, 95%CI: 2.102–6.924, P < 0.0001). ACT improved overall survival (OS) in the low-risk patients (10-year OS: 91.9% vs. 83.3%, HR = 0.338, 95% CI: 0.135–0.848, P < 0.0001), while it did not exhibit a significant benefit in the high-risk patients. CONCLUSION: The present study showed that age, monocyte percentage, carbohydrate antigen 19–9, lymph node dissection numbers and PNI were independent prognostic factors for pT3N0M0 rectal cancer patients. A nomogram based on these prognostic factors effectively predicts CSS in patients, which can be conveniently used in clinical practice. ACT may improve overall survival in the low-risk patients. But the benefit of ACT was not seen in the high-risk patients.
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spelling pubmed-94416892022-09-06 A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer Liu, Shuang Yang, Shanfei Yu, Haina Luo, Huilong Chen, Gong Gao, Yuanhong Sun, Rui Xiao, Weiwei Front Med (Lausanne) Medicine BACKGROUND: The pathological T3N0M0 (pT3N0M0) rectal cancer is the earliest stage and has the best prognosis in the locally advanced rectal cancer, but the optimal treatment remains controversial. A reliable prognostic model is needed to discriminate the high-risk patients from the low-risk patients, and optimize adjuvant chemotherapy (ACT) treatment decisions by predicting the likelihood of ACT benefit for the target population. PATIENTS AND METHODS: We gathered and analyzed 276 patients in Sun Yat-sen University Cancer Center from March 2005 to December 2011. All patients underwent total mesorectal excision (TME), without preoperative therapy, and were pathologically proven pT3N0M0 rectal cancer with negative circumferential resection margin (CRM). LASSO regression model was used for variable selection and risk factor prediction. Multivariable cox regression was used to develop the predicting model. Optimum cut-off values were determined using X-Tile plot analysis. The 10-fold cross-validation was adopted to validate the model. The performance of the nomogram was evaluated with its calibration, discrimination and clinical usefulness. RESULTS: A total of 188 patients (68.1%) had ACT and no patients had adjuvant radiotherapy. Age, monocyte percentage, carbohydrate antigen 19–9, lymph node dissection numbers and perineural invasion (PNI) were identified as significantly associated variables that could be combined for an accurate prediction risk of Cancer Specific Survival (CSS) for pT3N0M0 patients. The model adjusted for CSS showed good discrimination with a C-index of 0.723 (95% CI: 0.652–0.794). The calibration curves showed that the nomogram adjusted for CSS was able to predict 3-, 5-, and 10-year CSS accurately. The corresponding predicted probability was used to stratify high and low-risk patients (10-year CSS: 69.1% vs. 90.8%, HR = 3.815, 95%CI: 2.102–6.924, P < 0.0001). ACT improved overall survival (OS) in the low-risk patients (10-year OS: 91.9% vs. 83.3%, HR = 0.338, 95% CI: 0.135–0.848, P < 0.0001), while it did not exhibit a significant benefit in the high-risk patients. CONCLUSION: The present study showed that age, monocyte percentage, carbohydrate antigen 19–9, lymph node dissection numbers and PNI were independent prognostic factors for pT3N0M0 rectal cancer patients. A nomogram based on these prognostic factors effectively predicts CSS in patients, which can be conveniently used in clinical practice. ACT may improve overall survival in the low-risk patients. But the benefit of ACT was not seen in the high-risk patients. Frontiers Media S.A. 2022-08-22 /pmc/articles/PMC9441689/ /pubmed/36072948 http://dx.doi.org/10.3389/fmed.2022.977652 Text en Copyright © 2022 Liu, Yang, Yu, Luo, Chen, Gao, Sun and Xiao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Liu, Shuang
Yang, Shanfei
Yu, Haina
Luo, Huilong
Chen, Gong
Gao, Yuanhong
Sun, Rui
Xiao, Weiwei
A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer
title A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer
title_full A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer
title_fullStr A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer
title_full_unstemmed A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer
title_short A nomogram for predicting 10-year cancer specific survival in patients with pathological T3N0M0 rectal cancer
title_sort nomogram for predicting 10-year cancer specific survival in patients with pathological t3n0m0 rectal cancer
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441689/
https://www.ncbi.nlm.nih.gov/pubmed/36072948
http://dx.doi.org/10.3389/fmed.2022.977652
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