Analysis of Treatment Drugs for Type 2 Diabetes Based on Complex Network
10.6039/j.issn.1001-0408.2018.12.19
- VernacularTitle:基于复杂网络的2型糖尿病治疗药物分析
- Author:
Shaojie XU
1
;
Fan YANG
;
Haiying LI
;
Zhaozhong ZOU
;
Yiqin LI
Author Information
1. 中山市博爱医院药学部
- Keywords:
Complex network;
Data mining;
Type 2 diabetes;
Medication rules;
Subnetwork;
Overlapping community;
Core drugs
- From:
China Pharmacy
2018;29(12):1668-1672
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To excavate the drug use rules of type 2 diabetes,and to provide reference for clinical treatment. METHODS:Clinical data of 807 patients with type 2 diabetes were collected from our hospital during Jan. 2012-Jun. 2017. Complex network and subnetworks for drug compatibility and their visual chromatograms were established by Gephi 0.9.1 software. MATLAB R2014a software was used for topic model mining. The complex network,subnetworks and the overlapping structures of community were analyzed in respects of node distance and degree centrality. Core drugs for type 2 diabetes were screened. RESULTS & CONCLUSIONS:The drug complication complex network established in the study included 119 nodes and 24 412 edges with maximum edge weight of 378. Drugs with high frequency included Insulin aspart injection,Fluvastatin sodium extended release tablets,Metformin hydrochloride tablets,Acarbose tablets,etc. Average distance of network was 1.89,and maximum distance was 4. The distance of 89.90% drugs was 1 or 2,and the links between the various drugs were close. Insulin aspart injection(0.914),Metformin hydrochloride tablets(0.887)and Voglibose tablets(0.866)were core drugs of the network. Totally 4 typical topics were excavated, including peripheral neuropathy, peripheral vascular disease, abnormal lipid metabolism and microangiopathy. Results of subnetwork analysis showed that typical topics were based on hypoglycemic therapy and supplemented by neurotrophic drugs,antihypertensive drugs,lipid regulating drugs and drugs for improvement of retinopathy. Complex network analysis showed that drug use regularity was in line with related guideline of type 2 diabetes and clinical practice. The method has practical significance of data mining in clinic.
