HER2 negative advanced gastric cancer patient first-line chemotherapy effect prediction model based on VEGFA (vascular endothelial growth factor A) and application thereof

A technology for advanced gastric cancer and predictive models, applied in the field of clinical medicine, can solve problems such as difficulty in popularization, and achieve the effect of guiding clinical judgment and stratification

Pending Publication Date: 2022-03-04
THE FIRST AFFILIATED HOSPITAL OF BENGBU MEDICAL COLLEGE
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] At present, the prediction models of gastric cancer are mainly diagnostic and prognostic models, most of which are based on retrospective studies, and some models based on gene expression are difficult to promote clinically

Method used

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  • HER2 negative advanced gastric cancer patient first-line chemotherapy effect prediction model based on VEGFA (vascular endothelial growth factor A) and application thereof
  • HER2 negative advanced gastric cancer patient first-line chemotherapy effect prediction model based on VEGFA (vascular endothelial growth factor A) and application thereof
  • HER2 negative advanced gastric cancer patient first-line chemotherapy effect prediction model based on VEGFA (vascular endothelial growth factor A) and application thereof

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Experimental program
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Effect test

Embodiment 1

[0033] In the present invention, the method for constructing a VEGFA-based first-line chemotherapy curative effect and prognosis model for predicting HER2-negative advanced gastric cancer patients comprises the following steps:

[0034] (1) Screening of the modeling population: A total of 111 untreated patients with postoperative recurrent or metastatic HER2-negative advanced gastric cancer who were treated in the First Affiliated Hospital of Bengbu Medical College from November 2017 to September 2021 were enrolled. The inclusion criteria are as follows: histologically confirmed HER2-negative patients; patients who have not received anti-tumor therapy for recurrent or metastatic gastric cancer; patients who are not suitable or unwilling to receive surgery or radiotherapy; patients with target lesions that can be evaluated for efficacy. The exclusion criteria were as follows: combined with other tumors or subtypes; patients with severe heart, liver, and kidney diseases; patients...

Embodiment 2

[0053] Figure 5 ROC curve of Figure 6 The calibration curves were used to verify the discrimination and calibration of the curative effect prediction model in the examples.

[0054] Based on the patient population data included in Example 1, the model in Example 1 was evaluated. The discrimination of the model is determined by the ROC curve ( Figure 5 ), the ordinate is the true positive rate (TPR), which is the number of patients who are really ineffective and the model also judges that the treatment is ineffective divided by the number of patients who are really ineffective. The abscissa is the false positive rate (False positive rate, FPR), which is the number of patients whose treatment is effective but the model predicts that the treatment is ineffective divided by the number of patients who are actually effective. The true positive rate of TPR is the detection rate of people who are ineffective in treatment, how many people are detected in the ineffective people; a...

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Abstract

The invention discloses a HER2 negative advanced gastric cancer patient first-line chemotherapy curative effect prediction model based on VEGFA and application thereof, the model comprises a line chart used for evaluating chemotherapy curative effect, scores corresponding to four indexes BMI, Diagnose Pattern, VEGFA and CA19-9 in the first row from the second row to the fifth row are added to obtain a total score of a sixth row of patients, and the total score of the sixth row of patients is calculated to obtain the first-line chemotherapy curative effect prediction model based on the HER2 negative advanced gastric cancer patient first-line chemotherapy curative effect prediction model based on the HER2 negative advanced gastric cancer patient first-line chemotherapy curative effect. And correspondingly projecting the total score of the patient in the sixth row to the seventh row to obtain the probability that the treatment of the patient is invalid. The curative effect prediction line diagram integrating serum VEGFA and common baseline characteristics is simple, clear, popular and easy to understand, and clinical doctors and patients can conveniently perform operation to predict the curative effect. Meanwhile, a satisfactory prediction result is displayed by a curative effect line diagram, clinical judgment and layering can be better guided, and certain help is provided for treatment of HER2 negative advanced gastric cancer patients in the future.

Description

technical field [0001] The invention belongs to the field of clinical medicine, and specifically relates to a VEGFA-based first-line chemotherapy curative effect prediction model for patients with HER2-negative advanced gastric cancer and its application. Background technique [0002] Gastric cancer (GC) is the fifth leading cancer and the fourth leading cause of cancer death in the world. Morbidity and mortality are higher in Asian countries. At present, for HER2-negative gastric cancer patients, despite the availability of immune checkpoint inhibitors, chemotherapy is still the cornerstone of systemic treatment for advanced patients. Due to the highly heterogeneous and malignant nature of gastric cancer, patient responses to chemotherapy vary from individual to individual. Therefore, it is very important to find new ways to predict the efficacy of chemotherapy in patients to make more appropriate treatment decisions and improve the survival rate of patients with advanced...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/50G01N33/68
CPCG16H50/50G01N33/74G01N33/68G01N2333/49G01N2333/4725G01N2800/7028G01N2800/52G01N2800/60G01N2800/54
Inventor 杨燕邵玉姚景昊李曼刘静周争光徐令婕饶维维
Owner THE FIRST AFFILIATED HOSPITAL OF BENGBU MEDICAL COLLEGE
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