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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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Detalles Bibliográficos
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
Descripción
Sumario: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.