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RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer

BACKGROUND: The clinical outcomes of patients with resected T(1-3)N(0–2)M(0) non-small cell lung cancer (NSCLC) with the same tumor-node-metastasis (TNM) stage are diverse. Although other prognostic factors and prognostic prediction tools have been reported in many published studies, a convenient, a...

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Autores principales: Zhang, Yunkui, Li, YaoChen, Zhang, Rongsheng, Zhang, Yujie, Ma, Haitao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708148/
https://www.ncbi.nlm.nih.gov/pubmed/31462928
http://dx.doi.org/10.1186/s13040-019-0205-0
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author Zhang, Yunkui
Li, YaoChen
Zhang, Rongsheng
Zhang, Yujie
Ma, Haitao
author_facet Zhang, Yunkui
Li, YaoChen
Zhang, Rongsheng
Zhang, Yujie
Ma, Haitao
author_sort Zhang, Yunkui
collection PubMed
description BACKGROUND: The clinical outcomes of patients with resected T(1-3)N(0–2)M(0) non-small cell lung cancer (NSCLC) with the same tumor-node-metastasis (TNM) stage are diverse. Although other prognostic factors and prognostic prediction tools have been reported in many published studies, a convenient, accurate and specific prognostic prediction software for clinicians has not been developed. The purpose of our research was to develop this type of software that can analyze subdivided T and N staging and additional factors to predict prognostic risk and the corresponding mean and median survival time and 1–5-year survival rates of patients with resected T(1-3)N(0–2)M(0) NSCLC. RESULTS: Using a Cox proportional hazard regression model, we determined the independent prognostic factors and obtained a prognostic index (PI) eq. PI = ∑(βixi). =0.379X(1)–0.403X(2)–0.267X(51)–0.167X(61)–0.298X(62) + 0.460X(71) + 0.617X(72)–0.344X(81)–0.105X(91)–0.243X(92) + 0.305X(101) + 0.508X(102) + 0.754X(103) + 0.143X(111) + 0.170X(112) + 0.434X(113)–0.327X(122)–0.247X(123) + 0.517X(133) + 0.340X(134) + 0.457X(143) + 0.419X(144) + 0.407X(145). Using the PI equation, we determined the PI value of every patient. According to the quantile of the PI value, patients were divided into three risk groups: low-, intermediate-, and high-risk groups with significantly different survival rates. Meanwhile, we obtained the mean and median survival times and 1–5-year survival rates of the three groups. We developed the RNSCLC-PRSP software which is freely available on the web at http://www.rnsclcpps.com with all major browsers supported to determine the prognostic risk and associated survival of patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer. CONCLUSIONS: After prognostic factor analysis, prognostic risk grouping and corresponding survival assessment, we developed a novel software program. It is practical and convenient for clinicians to evaluate the prognostic risk and corresponding survival of patients with resected T(1-3)N(0–2)M(0) NSCLC. Additionally, it has guiding significance for clinicians to make decisions about complementary treatment for patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13040-019-0205-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-67081482019-08-28 RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer Zhang, Yunkui Li, YaoChen Zhang, Rongsheng Zhang, Yujie Ma, Haitao BioData Min Software Article BACKGROUND: The clinical outcomes of patients with resected T(1-3)N(0–2)M(0) non-small cell lung cancer (NSCLC) with the same tumor-node-metastasis (TNM) stage are diverse. Although other prognostic factors and prognostic prediction tools have been reported in many published studies, a convenient, accurate and specific prognostic prediction software for clinicians has not been developed. The purpose of our research was to develop this type of software that can analyze subdivided T and N staging and additional factors to predict prognostic risk and the corresponding mean and median survival time and 1–5-year survival rates of patients with resected T(1-3)N(0–2)M(0) NSCLC. RESULTS: Using a Cox proportional hazard regression model, we determined the independent prognostic factors and obtained a prognostic index (PI) eq. PI = ∑(βixi). =0.379X(1)–0.403X(2)–0.267X(51)–0.167X(61)–0.298X(62) + 0.460X(71) + 0.617X(72)–0.344X(81)–0.105X(91)–0.243X(92) + 0.305X(101) + 0.508X(102) + 0.754X(103) + 0.143X(111) + 0.170X(112) + 0.434X(113)–0.327X(122)–0.247X(123) + 0.517X(133) + 0.340X(134) + 0.457X(143) + 0.419X(144) + 0.407X(145). Using the PI equation, we determined the PI value of every patient. According to the quantile of the PI value, patients were divided into three risk groups: low-, intermediate-, and high-risk groups with significantly different survival rates. Meanwhile, we obtained the mean and median survival times and 1–5-year survival rates of the three groups. We developed the RNSCLC-PRSP software which is freely available on the web at http://www.rnsclcpps.com with all major browsers supported to determine the prognostic risk and associated survival of patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer. CONCLUSIONS: After prognostic factor analysis, prognostic risk grouping and corresponding survival assessment, we developed a novel software program. It is practical and convenient for clinicians to evaluate the prognostic risk and corresponding survival of patients with resected T(1-3)N(0–2)M(0) NSCLC. Additionally, it has guiding significance for clinicians to make decisions about complementary treatment for patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13040-019-0205-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-23 /pmc/articles/PMC6708148/ /pubmed/31462928 http://dx.doi.org/10.1186/s13040-019-0205-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software Article
Zhang, Yunkui
Li, YaoChen
Zhang, Rongsheng
Zhang, Yujie
Ma, Haitao
RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer
title RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer
title_full RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer
title_fullStr RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer
title_full_unstemmed RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer
title_short RNSCLC-PRSP software to predict the prognostic risk and survival in patients with resected T(1-3)N(0–2) M(0) non-small cell lung cancer
title_sort rnsclc-prsp software to predict the prognostic risk and survival in patients with resected t(1-3)n(0–2) m(0) non-small cell lung cancer
topic Software Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708148/
https://www.ncbi.nlm.nih.gov/pubmed/31462928
http://dx.doi.org/10.1186/s13040-019-0205-0
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