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Series 04: Allen & Unwin Further publisher files, ca. 1977-1990

Series 02: Allen & Unwin Further Production files, ca. 1976-1990

OBJECTIVE: To identify the Hyperglycemia and Its Effect After Acute Myocardial Infarction on Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus (HEART2D) trial subgroups with treatment difference. RESEARCH DESIGN AND METHODS: In 1,115 type 2 diabetic patients who had suffered from an acute myocardial infarction (AMI), the HEART2D trial compared two insulin strategies targeting postprandial or fasting/premeal glycemia on time until first cardiovascular event (cardiovascular death, nonfatal MI, nonfatal stroke, coronary revascularization, or hospitalization for acute coronary syndrome). The HEART2D trial ended prematurely for futility. We used the classification and regression tree (CART) to identify baseline subgroups with potential treatment differences. RESULTS: CART estimated the age of >65.7 years to best predict the difference in time to first event. In the subgroup aged >65.7 years (prandial, n = 189; basal, n = 210), prandial patients had a significantly longer time to first event and a lower proportion experienced a first event (n = 56 [29.6%] vs. n = 85 [40.5%]; hazard ratio 0.69 [95% CI 0.49-0.96]; P = 0.029), despite similar A1C levels. CONCLUSIONS: Older type 2 diabetic AMI survivors may have a lower risk for a subsequent cardiovascular event with insulin targeting postprandial versus fasting/premeal glycemia.

Diabetes care, 2011-07, Vol.34 (7), p.1511-1513

Post Hoc Subgroup Analysis of the HEART2D Trial Demonstrates Lower Cardiovascular Risk in Older Patients Targeting Postprandial Versus Fasting/Premeal Glycemia

Gene expression patterns can reflect gene regulations in human tissues under normal or pathologic conditions. Gene expression profiling data from studies of primary human disease samples are particularly valuable since these studies often span many years in order to collect patient clinical information and achieve a large sample size. Disease-to-Gene Expression Mapper (DGEM) provides a beneficial community resource to access and analyze these data; it currently includes Affymetrix oligonucleotide array datasets for more than 40 human diseases and 1400 samples. The data are normalized to the same scale and stored in a relational database. A statistical-analysis pipeline was implemented to identify genes abnormally expressed in disease tissues or genes whose expressions are associated with clinical parameters such as cancer patient survival. Data-mining results can be queried through a web-based interface at http://dgem.dhcp.iupui.edu/. The query tool enables dynamic generation of graphs and tables that are further linked to major gene and pathway resources that connect the data to relevant biology, including Entrez Gene and Kyoto Encyclopedia of Genes and Genomes (KEGG). In summary, DGEM provides scientists and physicians a valuable tool to study disease mechanisms, to discover potential disease biomarkers for diagnosis and prognosis, and to identify novel gene targets for drug discovery. The source code is freely available for non-profit use, on request to the authors.

Molecular diagnosis & therapy, 2007-01, Vol.11 (3), p.145-149

DGEM — A Microarray Gene Expression Database for Primary Human Disease Tissues

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Series 04: Allen & Unwin Further publisher files, ca. 1977-1990

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Series 02: Allen & Unwin Further Production files, ca. 1976-1990

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Post Hoc Subgroup Analysis of the HEART2D Trial Demonstrates Lower Cardiovascular Risk in Older Patients Targeting Postprandial Versus Fasting/Premeal Glycemia

Export this record

Export record to excel

DGEM — A Microarray Gene Expression Database for Primary Human Disease Tissues

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