A lung cancer risk prediction kit for high-risk groups in rural China based on biomarker profiles
A high-risk, rural technology, applied in the field of medical biology, can solve problems such as unreported, difficult to achieve, loss of radical surgery, etc., and achieve the effect of simple expression level
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0031] The composition of kit of the present invention:
[0032] Composed of biomarkers and their enzyme-labeled antibodies, carbonate buffer solution with a pH value of 9.6, phosphate buffer solution with a pH value of 7.4, serum protein dilution, stop solution, tetramethylbenzidine substrate solution, and normal people Serum and positive control serum composition.
[0033] The biomarkers include gastrin-releasing propeptide, carcinoembryonic antigen, cytokeratin 19 fragments and squamous cell carcinoma antigen; Add 2.93 grams of sodium bicarbonate to 1L of distilled water and obtain; the phosphate buffer solution with a pH value of 7.4 is 0.2 grams of potassium dihydrogen phosphate, 2.9 grams of disodium hydrogen phosphate dodecahydrate, 8.0 grams of sodium chloride, 0.2 gram potassium chloride, 0.5mL Tween-20 was added to 1L distilled water and obtained; the serum protein dilution was 0.1 gram bovine serum, goat serum or rabbit serum protein added to 100mL phosphate buffer...
Embodiment 2
[0048]The present invention collects 715 rural population patients with high risk factors of lung cancer determined clinically, and finally diagnoses 434 cases of lung cancer through pathology, and samples the serum of 154 lung cancer patients through a randomized method; at the same time, in the serum bank of 281 non-lung cancer patients, Sera from 235 normal persons were sampled by random method. Chemiluminescent microparticle immunoassay was used to detect 4 biomarkers in serum, and clinical information such as age, smoking history, and gender of patients were collected at the same time. The sensitivity and specificity of the obtained models are shown in Table 1. The ROC curve of the lung cancer risk prediction model for high-risk groups in rural China based on biomarker profiles is as follows: figure 1 shown.
[0049] Table 1 The validity of the lung cancer risk prediction model based on biomarker profiles for high-risk groups in rural China
[0050]
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com