Method for severe intestinal aGVHD model based on aGVHD biomarker

A kind of intestinal and severe technology, applied in the fields of genomics, instrumentation, proteomics, etc., can solve the problem that the conclusion cannot be directly applied to the patient population

Pending Publication Date: 2021-06-11
北京博富瑞基因诊断技术有限公司
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The above studies show that the diagnosis (prediction) of intestinal aGVHD based on biomarker has good clinical application value, but due to the differences in patient groups, the conclusions drawn from Western patient groups cannot be directly applied to Chinese patient groups

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for severe intestinal aGVHD model based on aGVHD biomarker
  • Method for severe intestinal aGVHD model based on aGVHD biomarker
  • Method for severe intestinal aGVHD model based on aGVHD biomarker

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0025] see figure 1 , a method for severe intestinal aGVHD model based on aGVHD biomarker, including four steps of aGVHD biomarker index monitoring, data screening and grouping, single severe intestinal aGVHD model training, multi-model fusion, and prospective verification of severe intestinal aGVHD model performance :

[0026] S1. Monitoring of aGVHD biomarker indicators and data screening and grouping, dynamic monitoring of aGVHD biomarker indicators at important time points in multi-center patient groups (patients with severe intestinal aGVHD accounted for 13%), aGVHD biomarker indicators include sST2, REG3α, IL-6 , IL-8, and TNFR1, and were grouped according to whether intestinal aGVHD occurred within 100 days after HSCT. Among them, the aGVHD biomarker index monitored at the time point of the screening event occurred in the group with intestinal aGVHD, and the group without intestinal aGVHD was divided into groups. Screen the monitored aGVHD biomarker indicators in the s...

Embodiment 2

[0031] Using the method of a severe intestinal aGVHD model based on aGVHD biomarker in Example 1, dynamically monitor the aGVHD biomarker index at important time points of the multi-center patient population (severe intestinal aGVHD accounts for about 13%), and according to the method within 100 days after transplantation Whether intestinal aGVHD occurs or not is grouped for data screening, using one data per patient, the patients in the intestinal aGVHD occurrence group take the biomarker data at the occurrence of intestinal aGVHD, and the patients in the intestinal aGVHD non-occurrence group follow the same principle as the occurrence group biomarker data measurement time distribution Filter the data to form a model dataset.

[0032] The above model data set is randomly divided into a training set and a test set in proportion, and the patient's aGVHD biomarker index is correlated with whether severe intestinal aGVHD occurs clinically, and stacking and logistic regression tech...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method for a severe intestinal aGVHD model based on aGVHD biomarker, and belongs to the technical field of hematopoietic stem cell transplantation. The method comprises four steps: aGVHD biomarker index monitoring and data screening and grouping, single severe intestinal aGVHD model training, multi-model fusion, and severe intestinal aGVHD model performance foresight verification. According to the severe intestinal aGVHD model method based on the aGVHD biomarker, the severity of severe intestinal aGVHD of a patient is evaluated by establishing a machine learning model and adopting a multi-model fusion technology, the effect is better than that of a single intestinal aGVHD model, the severity of intestinal aGVHD of the patient is accurately divided, and guidance is provided for clinical decision making; and meanwhile, only an aGVHD biomarker index in serum needs to be detected, so that strong discomfort brought to patients by conventional intestinal aGVHD diagnosis methods such as endoscopy and intestinal mucosa biopsy is avoided, and the method is more suitable for Chinese patient groups.

Description

technical field [0001] The invention belongs to the technical field of hematopoietic stem cell transplantation, in particular to a method for a severe intestinal aGVHD model based on aGVHD biomarker. Background technique [0002] Acute Graft-versus-Host Disease (aGVHD) is the main source of fatal complications and mortality after allogeneic Hematopoietic Stem Cell Transplantation (allo-HSCT). aGVHD can affect multiple organs, primarily the skin, liver, and gastrointestinal tract. Among them, the incidence of intestinal aGVHD is high and severe, and severe intestinal aGVHD is often difficult to reverse, which increases the mortality rate. Therefore, the early diagnosis and effective treatment of severe intestinal aGVHD are directly related to the prognosis of the disease, and play an important role in the treatment of aGVHD. [0003] Currently, the diagnosis of intestinal aGVHD mostly focuses on radiology, endoscopy, and histological biopsy, but the final diagnosis still de...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G16B40/00G16B20/00
CPCG16B40/00G16B20/00
Inventor 管迪李晓博
Owner 北京博富瑞基因诊断技术有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products