Prediction system for jointly predicting gastric cancer prognosis based on patient age, nutritional index, tumor stage and tumor marker

A prediction system and nutritional index technology, applied in the field of prediction system, can solve the problems that the prediction accuracy and discrimination need to be further improved, and the survival rate of gastric cancer patients cannot be predicted, so as to achieve better prediction effect, best prediction effect, and construction method simple effect

Active Publication Date: 2021-11-16
WEST CHINA HOSPITAL SICHUAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this system is a scoring system established using the data training of patients with stage II-III gastric cancer who underwent radical surgery and received adjuvant chemotherapy, and cannot be widely applied to the survival of patients with stage I-IV (especially stage I, IV) gastric cancer. Moreover, the C-index of the system is 0.714 (95% CI: 0.680-0.749), and the prediction accuracy and discrimination need to be further improved

Method used

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  • Prediction system for jointly predicting gastric cancer prognosis based on patient age, nutritional index, tumor stage and tumor marker
  • Prediction system for jointly predicting gastric cancer prognosis based on patient age, nutritional index, tumor stage and tumor marker
  • Prediction system for jointly predicting gastric cancer prognosis based on patient age, nutritional index, tumor stage and tumor marker

Examples

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Effect test

Embodiment 1

[0091] Example 1: The method for constructing a nomogram for predicting the prognosis of gastric cancer based on multiple indicators of age, nutritional index CONUT, tumor stage and tumor markers in the present invention

[0092] 1. Input module

[0093] The age (Age), tumor TNM stage (stage), tumor markers AFP, CA153 and CA724, and nutritional index CONUT of 649 patients in the model training group were collected as indicators related to the prognosis of gastric cancer patients. Enter these indicators into the input module.

[0094] 2. Establishment of a prognosis prediction model for gastric cancer

[0095] Use the indicators in the input module to construct the cox regression model, and use the RMS calculation package to complete the nomogram visualization of the cox regression model, and use the calibration curve and decision curve calculation packages to complete the nomogram verification of the cox regression model, and get figure 1 collinear figure 1 .

[0096] The ...

Embodiment 2

[0121] Example 2: The method for constructing a nomogram for predicting the prognosis of gastric cancer based on multiple indicators of age, nutritional index NRI, tumor stage and tumor markers in the present invention

[0122] 1. Input module

[0123] The age, tumor TNM stage, tumor markers AFP, CA153 and CA724, and nutritional index NRI of 649 patients in the model training group were collected as indicators related to the prognosis of patients with gastric cancer. Enter these indicators into the input module.

[0124] 2. Establishment of a prognosis prediction model for gastric cancer

[0125] Use the indicators in the input module to construct the cox regression model, and use the RMS calculation package to complete the nomogram visualization of the cox regression model, and use the calibration curve and decision curve calculation packages to complete the nomogram verification of the cox regression model, and get figure 2 collinear figure 2 .

[0126] The nomogram co...

Embodiment 3

[0151] Example 3: The method for constructing a nomogram for predicting the prognosis of gastric cancer based on multiple indicators of age, nutritional index PNI, tumor stage and tumor markers in the present invention

[0152] 1. Input module

[0153] The age, tumor TNM stage, tumor markers AFP, CA153 and CA724, and nutritional index PNI of 649 patients in the model training group were collected as indicators related to the prognosis of gastric cancer patients. Enter these indicators into the input module.

[0154] 2. Establishment of a prognosis prediction model for gastric cancer

[0155] Use the indicators in the input module to construct the cox regression model, and use the RMS calculation package to complete the nomogram visualization of the cox regression model, and use the calibration curve and decision curve calculation packages to complete the nomogram verification of the cox regression model, and get image 3 collinear image 3 .

[0156] The nomogram contains ...

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Abstract

The invention provides a prediction system for combined prediction of gastric cancer prognosis based on patient age, nutrition index, tumor stage and tumor marker. The prediction system is constructed by taking patient age, tumor TNM stage, AFP, CA153, CA724 and nutrition index as prediction indexes, and the invention belongs to the field of prediction models. The prediction system can be used for accurately predicting the prognosis condition of a gastric cancer patient (especially a patient subjected to gastric cancer resection surgery in an I-IV stage) and accurately predicting the survival rate of the patient. The prediction system for predicting gastric cancer prognosis provided by the invention is simple in construction method and high in prediction accuracy and distinction degree, has important significance in clinically assisting in judging the prognosis condition and survival rate of gastric cancer patients, and is beneficial to individual precise treatment of clinical patients.

Description

technical field [0001] The invention belongs to the field of prediction models, and in particular relates to a prediction system for jointly predicting the prognosis of gastric cancer based on patient age, nutrition indicators, tumor stages and tumor markers. Background technique [0002] Gastric cancer is one of the most common malignant tumors at present. Although its incidence rate has declined in some countries in recent years, due to the growth of the total population in high-incidence areas of gastric cancer and the aging of the population, the global total incidence rate is declining. The absolute value of the number of new cases is still increasing. Currently, surgery is the primary method of treatment for gastric cancer. However, the long-term efficacy of gastric cancer patients who underwent surgery is not the same. Accurately predicting the prognosis of patients with gastric cancer is of great significance to guide the treatment of patients and improve the progn...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30
CPCG16H50/30Y02A90/10
Inventor 宋亚莉曾婷婷
Owner WEST CHINA HOSPITAL SICHUAN UNIV
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