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Cai-Rong Zhu

Publications and source records attributed to Cai-Rong Zhu.

2 recordsLinked to original sources
PubMed2005

[A Markov model to access long-term effects of rosiglitazone natrium on the treatment of type 2 diabetes].

OBJECTIVE: The aim of this study was to estimate the long-term treatment effects of Rosiglitazone-natrium in type 2 diabetes. METHODS: A Markov decision model was developed to predict, over 10 years, mortality with or without Rosiglitazone-natrium treatment. RESULTS: During 10 years research, 14.2% patients developed to complications of type 2 diabetes mellitus, 3.8% patients should be dead in Rosiglitazone-natrium treatment group. 22.7% patients developed to complications of type 2 diabetes, 6.6% patients should be dead in non-Rosiglitazone-natrium treatment group. CONCLUSION: Markov decision model should be useful in accessing the long-term effects of drug treatment. Evidence on long-term benefit of Rosiglitazone-natrium could be of importance for future decision making.

Diabetes Mellitus, Type 2↗
PubMed2005

[The multi-level Meta analysis model combining individual level data with aggregative level data].

OBJECTIVE: To explore the multi-level Meta analysis model combining individual level data with aggregative level data and its application in medicine. METHODS: The difference in respect to "decreased hemoglobin A(1c)" between treatment with roglizatone and treatment without roglizatone was obtained by combining individual level data from clinical trial of roglizatone natrium with aggregative level data from literatures. This endeavor was regarded as an example to construct the multi-level Meta analysis model combining individual level data with aggregative level data. RESULTS: The baseline hemoglobin A(1c) was 9% and the dose of drug was 4 mg per day. The average difference in "decreased hemoglobin A(1c)" between treatment with and without roglizatone was 0. 464%, with a 95% CI from 0.168% to 0.760%. CONCLUSION: In case that individual data are available, the multi-level Meta analysis model combining individual level data with aggregative level data can utilize the data resources adequately and the results obtained should be more accurate.

Data Interpretation, Statistical↗