Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Jan 31, 2021
Open Peer Review Period: Jan 30, 2021 - Feb 7, 2021
Date Accepted: Apr 11, 2021
(closed for review but you can still tweet)
Deciphering Chinese herbal medicine's efficacy and mechanisms for diabetic kidney disease: integrating web-based biochemical databases to the real-world clinical data
ABSTRACT
Background:
Diabetic kidney disease (DKD) is one of the most crucial causes of chronic kidney disease (CKD). However, the efficacy and biomedical mechanisms of using CHM for DKD in clinical settings remain unclear.
Objective:
This study aims to analyze the outcome of DKD patients with CHM-only management and the possible molecular pathways of CHM by integrating web-based biomedical databases and the real-world clinical database.
Methods:
A total of 152,357 patients with incident DKD from 2004 to 2012 were identified from the National Health Insurance Research Database (NHIRD) in Taiwan. The risk of mortality was estimated with the Kaplan–Meier method and Cox regression considering demographic covariates. The inverse probability of treatment weighting was used for confounding bias between CHM users and nonusers. Furthermore, to decipher the CHM used for DKD, we analyzed all CHM prescriptions using the Chinese herbal medicine network (CMN), which combined association rule mining and social network analysis among all CHM prescriptions. Further, web-based biomedical databases, including STITCH, STRING, BindingDB, TCMSP, TCM@Taiwan, DisGeNET, were integrated into the CMN and commonly used western medicine (WM) to explore the differences in possible target proteins and molecular pathways between CHM and WM. The application programming interface (API) was used to assess these online databases to obtain the latest biomedical information.
Results:
About 13.7% of patients were classified as CHM users among eligible DKD patients. The median follow-up duration of all patients was 2.49 years. The cumulative incidence of mortality among the CHM cohort was significantly lower than the WM cohort (28% versus 48%, P < .001). The risk of mortality was 0.41 among the CHM cohort with covariates adjustment (99% CI: 0.38-0.43, P < .001). A total of 173,525 CHM prescriptions were used to construct CMN with eleven CHM clusters. CHM covered more DKD-related proteins and pathways than WM; nevertheless, WM aimed at DKD more specifically. From the overrepresentation tests carried by the online website Reactome, the molecular pathways covered by the CHM clusters in CMN and WM seemed distinctive but complementary. The complementary effects were also found among DKD patients with concurrent WM and CHM use. The risks of mortality among CHM users under renin-angiotensin-aldosterone system (RAAS) inhibition therapy were lower than CHM nonusers among DKD patients with hypertension (adjusted HR: 0.47, 99%CI: 0.45-0.51, P < .001), chronic heart failure (adjusted HR: 0.43, 99%CI: 0.37-0.51, P < .001), and ischemic heart disease (adjusted HR: 0.46, 99%CI: 0.41-0.51, P < .001)
Conclusions:
CHM users among DKD patients seemed to have a lower risk of mortality, which may benefit from potentially synergistic renoprotection effects. The framework of integrating real-world clinical databases and web-based biomedical databases could help explore the role of treatments for diseases.
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