Biomedical subjects

William H Herman

Publications and source records attributed to William H Herman.

57 records · Page 4Linked to original sources

PubMed2002

A diabetes outcome progression trial (ADOPT): an international multicenter study of the comparative efficacy of rosiglitazone, glyburide, and metformin in recently diagnosed type 2 diabetes.

OBJECTIVE: Therapies with metformin, sulfonylureas, or insulin improve glycemic control in the short term but do not prevent progressive islet beta-cell failure or long-term deterioration in glycemia. Our goal was to evaluate, in patients recently diagnosed with type 2 diabetes (<3 years), the long-term efficacy of monotherapy with rosiglitazone on glycemic control and on the progression of pathophysiological abnormalities associated with type 2 diabetes as compared with metformin or glyburide monotherapy. RESEARCH DESIGN AND METHODS: A Diabetes Outcome Progression Trial (ADOPT) is a randomized, double-blind, parallel-group study consisting of a screening visit, a 4-week placebo run-in, a 4-year treatment period, and an observational follow-up of approximately 3,600 drug-naïve patients with type 2 diabetes diagnosed within the previous 3 years. After run-in, patients will be randomized to rosiglitazone, glyburide, or metformin titrated to the maximum effective daily doses (8 mg rosiglitazone, 15 mg glyburide, or 2 g metformin). The primary outcome is time to monotherapy failure, defined as the time following titration to the maximal effective or tolerated dose when fasting plasma glucose exceeds 180 mg/dl (10 mmol/l). Secondary outcomes include measures of islet beta-cell function, insulin sensitivity, dyslipidemia, changes in urinary albumin excretion, plasminogen activator inhibitor-1 antigen, fibrinogen, and C-reactive protein. Safety and tolerability will also be evaluated. Patient-reported outcomes and resource utilization data will be collected and analyzed. CONCLUSIONS: ADOPT will provide data on the effect of mechanistically differing treatment options on metabolic control, beta-cell function, and markers of macrovascular disease risk in type 2 diabetes.

Albuminuria↗

PubMed2002

A multivariate logistic regression equation to screen for diabetes: development and validation.

OBJECTIVE: To develop and validate an empirical equation to screen for diabetes. RESEARCH DESIGN AND METHODS: A predictive equation was developed using multiple logistic regression analysis and data collected from 1,032 Egyptian subjects with no history of diabetes. The equation incorporated age, sex, BMI, postprandial time (self-reported number of hours since last food or drink other than water), and random capillary plasma glucose as independent covariates for prediction of undiagnosed diabetes. These covariates were based on a fasting plasma glucose level >/=126 mg/dl and/or a plasma glucose level 2 h after a 75-g oral glucose load >/=200 mg/dl. The equation was validated using data collected from an independent sample of 1,065 American subjects. Its performance was also compared with that of recommended and proposed static plasma glucose cut points for diabetes screening. RESULTS: The predictive equation was calculated with the following logistic regression parameters: P = 1/(1 - e(-x)), where x = -10.0382 + [0.0331 (age in years) + 0.0308 (random plasma glucose in mg/dl) + 0.2500 (postprandial time assessed as 0 to >/=8 h) + 0.5620 (if female) + 0.0346 (BMI)]. The cut point for the prediction of previously undiagnosed diabetes was defined as a probability value >/=0.20. The equation's sensitivity was 65%, specificity 96%, and positive predictive value (PPV) 67%. When applied to a new sample, the equation's sensitivity was 62%, specificity 96%, and PPV 63%. CONCLUSIONS: This multivariate logistic equation improves on currently recommended methods of screening for undiagnosed diabetes and can be easily implemented in a inexpensive handheld programmable calculator to predict previously undiagnosed diabetes.

Blood Glucose↗

PubMed2002

Valuing health-related quality of life in diabetes.

OBJECTIVE: Cost-utility analyses use information on health utilities to compare medical treatments that have different clinical outcomes and impacts on survival. The purpose of this study was to describe the health utilities associated with diabetes and its treatments, complications, and comorbidities. RESEARCH DESIGN AND METHODS: We studied 2,048 subjects with type 1 and type 2 diabetes recruited from specialty clinics at a university medical center. We administered a questionnaire to each individual to assess demographic characteristics, type and duration of diabetes, treatments, complications, and comorbidities, and we used the Self-Administered Quality of Well Being index (QWB-SA) to calculate a health utility score. We then created regression models to fit the QWB-SA-derived health utility scores to indicator variables for type 1 and type 2 diabetes and each demographic variable, treatment, and complication. The coefficients were arranged in clinically meaningful ways to develop models to describe penalties from the health utility scores for nonobese diabetic men without additional treatments, complications, or comorbidities. RESULTS: The utility scores for nonobese diet-controlled men and women with type 2 diabetes and no microvascular, neuropathic, or cardiovascular complications were 0.69 and 0.65, respectively. The utility scores for men and women with type 1 diabetes and no complications were slightly lower (0.67 and 0.64, respectively). Blindness, dialysis, symptomatic neuropathy, foot ulcers, amputation, debilitating stroke, and congestive heart failure were associated with lower utility scores. CONCLUSIONS: Major diabetes complications are associated with worse health-related quality of life. The health utility scores provided should facilitate studies of the health burden of diabetes and the cost-utility of alternative strategies for the prevention and treatment of diabetes.

Adult↗