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Lung adenocarcinoma patient lifetime prognosis evaluation method, computer device and storage medium

A prognostic assessment and lung adenocarcinoma technology, applied in the field of biomedicine, can solve the problem that the TNM staging cannot accurately assess the patient's survival period, and achieve the effect of solving the inability to accurately assess the patient's survival period and improving the prediction effect.

Pending Publication Date: 2022-07-05
CENT SOUTH UNIV
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Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a method for assessing the prognosis of the survival period of patients with lung adenocarcinoma, a computer device and a storage medium, so as to solve the problem that the survival period of patients cannot be accurately assessed by TNM staging.

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  • Lung adenocarcinoma patient lifetime prognosis evaluation method, computer device and storage medium
  • Lung adenocarcinoma patient lifetime prognosis evaluation method, computer device and storage medium
  • Lung adenocarcinoma patient lifetime prognosis evaluation method, computer device and storage medium

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Embodiment Construction

[0046] The specific construction method of the joint survival prediction model in the embodiment of the present invention is as follows:

[0047] (1) Via the UCSC Xena website ( https: / / xenabrowser.net / ), the gene expression and clinical data of 517 lung adenocarcinoma patients were obtained from The Cancer Genome Atlas (TCGA) database, and the gene expression and clinical data were obtained from the GEO database ( http: / / www.ncbi.nlm.nih.gov / geo / ) to obtain the gene expression and clinical data of three cohorts of GSE30219, GSE31210 and GSE720924 lung adenocarcinoma patients, of which the TCGA cohort was used as the training set for endoplasmic reticulum stress score and prediction model construction, and the GEO cohort was used as the validation set for the prediction model. Externally validated, Table 1 shows the clinical characteristics of the four cohorts of patients.

[0048] Table 1 Clinicopathological characteristics of lung adenocarcinoma patients in TCGA coho...

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Abstract

The invention discloses a lung adenocarcinoma patient lifetime prognosis evaluation method, a computer device and a storage medium. A prognosis index is calculated by adopting the following formula: prognosis index = beta1 * TNM stage + beta2 * ERSS, wherein beta 1 and beta 2 are weight coefficients, and ERSS is an endoplasmic reticulum stress score. According to the method, correlation between endoplasmic reticulum stress related genes and prognosis of the lung adenocarcinoma patient is evaluated according to a machine learning method, endoplasmic reticulum stress scores are established, the survival prediction model is established in combination with the endoplasmic reticulum stress scores and TNM staging, and experiments show that the survival prediction model has a good prediction effect on the total lifetime, and the survival prediction model can be used for predicting the total lifetime of the lung adenocarcinoma patient. The problem that the lifetime of a patient cannot be accurately evaluated by independently applying TNM staging is solved.

Description

technical field [0001] The invention relates to the technical field of biomedicine, in particular to a method, computer device and storage medium for evaluating the prognosis of the survival period of patients with lung adenocarcinoma. Background technique [0002] Survival risk prediction is an extremely important part of the medical safety management system. According to the accumulated disease data, the method of risk prediction can be summarized and analyzed, which is beneficial to guide the individualized treatment of patients. [0003] In China, the morbidity and lethality of lung cancer ranks first among various malignant tumors, which brings huge health and economic burden to the Chinese people. [1] . According to histological types, lung cancer can be divided into small cell carcinoma, adenocarcinoma, squamous cell carcinoma, large cell carcinoma, etc. Among them, lung adenocarcinoma accounts for more than 40% of lung cancer and is the most numerous type of lung ca...

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Application Information

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IPC IPC(8): G16H50/20G16H50/30G16H50/80
CPCG16H50/20G16H50/30G16H50/80
Inventor 陶永光舒龙刘双
Owner CENT SOUTH UNIV
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