Objective <p>To develop SXRNSCLC-PRSP software which can predict the prognostic risk and survival of resected T<sub>1-3</sub>N<sub>0-2</sub>M<sub>0</sub> (according to the 9th AJCC/UICC TNM stage of lung cancer) non-small cell lung cancer (NSCLC) patients in Shanxi Province China more comprehensively, accurately and conveniently, and provide reference and help for clinicians tailoring patients’follow-up adjuvant therapy and care.</p> Methods <p>Patients with NSCLC whose tumor stage is T<sub>1-3</sub>N<sub>0-2</sub>M<sub>0</sub> underwent surgical treatment only were selected from the medical records of Shanxi Tumor Hospital. The clinicopathological features that may affect the prognosis of these patients’survival outcome and survival time were collected (there are no missing data), and then the survival data set was established. In the survival data set, 70% of the patients were randomly selected as the training set, and the rest were composed of the test set. A prognostic model of resected T<sub>1-3</sub>N<sub>0-2</sub>M<sub>0</sub> NSCLC patients in Shanxi Province China was constructed using the training set, and the model was validated using the test set. SXRNSCLC-PRSP software was developed to implement the model for prognostic risk and survival prediction in such patients. The software can be used free of charge by clinicians who log on to a specific website. After they register and log on to the software, they can select the corresponding clinicopathological characteristics of the patient and obtain the prognostic risk and survival prediction results of the patient.</p> Results <p>Using a Cox proportional hazard regression model, we determined the independent prognostic factors and obtained a prognostic index (PI) eq. PI = <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\sum {\beta_{i} x_{i} }\)</EquationSource> </InlineEquation> = -0.392X<sub>2</sub> + 0.927X<sub>71</sub> + 1.695X<sub>72</sub> + 0.537X<sub>111</sub> + 0.401X<sub>112</sub>-0.434X<sub>113</sub>. 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 restricted mean survival times and 1–5-year survival rates of the three groups. Based on the construction of prognostic risk and survival prediction model and the programming in JAVA language, we developed the SXRNSCLC-PRSP software to determine the prognostic risk and associated survival of patients with resected T<sub>1-3</sub>N<sub>0–2</sub>M<sub>0</sub> NSCLC in Shanxi Province China. At last, we have established a Risk Assessment System(RAS). In this system, clinicians can use the software. clinicians can input URL <a href="https://www.sxrnsclcpps.com">https://www.sxrnsclcpps.com</a> into one of browsers (latest versions of Chrome, Firefox, Safari, Microsoft Edge which have passed the compatibility test for the login function) to reach its login screen. By processing clinical parameter inputs, the software stratifies patient risk levels and generates Restricted Mean Survival Time (RMST) estimates and survival rate projections, providing clinical support for follow-up care planning, adjuvant therapy selection, and patient screening.</p> Conclusions <p>After prognostic factor analysis, prognostic risk grouping and corresponding survival assessment, we developed a novel software program and established the Risk Assessment System (RAS). It is practical and convenient for clinicians to evaluate the prognostic risk and corresponding survival of patients with resected T<sub>1-3</sub>N<sub>0–2</sub>M<sub>0</sub> NSCLC in Shanxi Province China. Additionally, it has guiding significance for clinicians to make decisions about complementary treatment for patients.</p>

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SXRNSCLC-PRSP software to predict prognostic risk and survival in patients with resected T1-3N0-2M0 non-small cell lung cancer in Shanxi Province China

  • Yunkui Zhang,
  • Xuesong Wu,
  • Bin Yang,
  • Rongsheng Zhang,
  • Bin Wang

摘要

Objective

To develop SXRNSCLC-PRSP software which can predict the prognostic risk and survival of resected T1-3N0-2M0 (according to the 9th AJCC/UICC TNM stage of lung cancer) non-small cell lung cancer (NSCLC) patients in Shanxi Province China more comprehensively, accurately and conveniently, and provide reference and help for clinicians tailoring patients’follow-up adjuvant therapy and care.

Methods

Patients with NSCLC whose tumor stage is T1-3N0-2M0 underwent surgical treatment only were selected from the medical records of Shanxi Tumor Hospital. The clinicopathological features that may affect the prognosis of these patients’survival outcome and survival time were collected (there are no missing data), and then the survival data set was established. In the survival data set, 70% of the patients were randomly selected as the training set, and the rest were composed of the test set. A prognostic model of resected T1-3N0-2M0 NSCLC patients in Shanxi Province China was constructed using the training set, and the model was validated using the test set. SXRNSCLC-PRSP software was developed to implement the model for prognostic risk and survival prediction in such patients. The software can be used free of charge by clinicians who log on to a specific website. After they register and log on to the software, they can select the corresponding clinicopathological characteristics of the patient and obtain the prognostic risk and survival prediction results of the patient.

Results

Using a Cox proportional hazard regression model, we determined the independent prognostic factors and obtained a prognostic index (PI) eq. PI =  \(\sum {\beta_{i} x_{i} }\)  = -0.392X2 + 0.927X71 + 1.695X72 + 0.537X111 + 0.401X112-0.434X113. 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 restricted mean survival times and 1–5-year survival rates of the three groups. Based on the construction of prognostic risk and survival prediction model and the programming in JAVA language, we developed the SXRNSCLC-PRSP software to determine the prognostic risk and associated survival of patients with resected T1-3N0–2M0 NSCLC in Shanxi Province China. At last, we have established a Risk Assessment System(RAS). In this system, clinicians can use the software. clinicians can input URL https://www.sxrnsclcpps.com into one of browsers (latest versions of Chrome, Firefox, Safari, Microsoft Edge which have passed the compatibility test for the login function) to reach its login screen. By processing clinical parameter inputs, the software stratifies patient risk levels and generates Restricted Mean Survival Time (RMST) estimates and survival rate projections, providing clinical support for follow-up care planning, adjuvant therapy selection, and patient screening.

Conclusions

After prognostic factor analysis, prognostic risk grouping and corresponding survival assessment, we developed a novel software program and established the Risk Assessment System (RAS). It is practical and convenient for clinicians to evaluate the prognostic risk and corresponding survival of patients with resected T1-3N0–2M0 NSCLC in Shanxi Province China. Additionally, it has guiding significance for clinicians to make decisions about complementary treatment for patients.