Smith, Steven A.

OBJECTIVE To investigate the pharmacokinetics (PK), pharmacodynamics, and safety of single-dose RM-131 in type 2 diabetic patients with gastrointestinal cardinal symptoms (GCSI) and previously documented delayed gastric emptying (DGE). RESEARCH DESIGN AND METHODS In a randomized crossover study, 10 female patients received RM-131 (100 μg s.c.) or placebo and underwent scintigraphic gastric emptying (GE) and colonic filling at 6 h (CF6) of a solid-liquid meal administered 30 min postdosing. Adverse events, plasma glucose, and hormonal levels were assessed. GCSI daily diary (GCSI-DD) was completed during treatments. PK was assessed in this cohort and healthy volunteers (HVs). RESULTS At screening, HbA1c was 7.2 ± 0.4% (SEM) and total GCSI-DD score was 1.32 ± 0.21. RM-131 accelerated GE t1/2 of solids (P = 0.011); mean difference (Δ) in solid GE t1/2 was 68.3 min (95% CI 20–117) or 66.1%. There were numerical differences in GE lag time, CF6 solids, and GE t1/2 liquids (all P < 0.14). With a significant (P < 0.014) order effect, further analysis of the first treatment period (n = 5 per group) confirmed significant RM-131 effects on GE t1/2 (solids, P = 0.016; liquids, P = 0.024; CF6, P = 0.013). PK was similar in DGE patients and HVs. There were increases in 120-min blood glucose (P = 0.07) as well as 30–90-min area under the curve (AUC) levels of growth hormone, cortisol, and prolactin (all P < 0.02) with single-dose RM-131. Only light-headedness was reported more on RM-131. CONCLUSIONS RM-131 greatly accelerates the GE of solids in patients with type 2 diabetes and documented DGE. PK is similar in diabetic patients and HVs.

OBJECTIVE Hypoglycemia is a cause of significant morbidity among patients with diabetes and may be associated with greater risk of death. We conducted a retrospective study to determine whether patient self-report of severe hypoglycemia is associated with increased mortality. RESEARCH DESIGN AND METHODS Adult patients (N = 1,020) seen in a specialty diabetes clinic between August 2005 and July 2006 were questioned about frequency of hypoglycemia during a preencounter interview; 7 were lost to follow-up and excluded from analysis. Mild hypoglycemia was defined as symptoms managed without assistance, and severe hypoglycemia was defined as symptoms requiring external assistance. Mortality data, demographics, clinical characteristics, and Charlson comorbidity index (CCI) were obtained from the electronic medical record after 5 years. Patients were stratified by self-report of hypoglycemia at baseline, demographics were compared using the two-sample t test, and risk of death was expressed as odds ratio (95% CI). Associations were controlled for age, sex, diabetes type and duration, CCI, HbA1c, and report of severe hypoglycemia. RESULTS In total, 1,013 patients with type 1 (21.3%) and type 2 (78.7%) diabetes were questioned about hypoglycemia. Among these, 625 (61.7%) reported any hypoglycemia, and 76 (7.5%) reported severe hypoglycemia. After 5 years, patients who reported severe hypoglycemia had 3.4-fold higher mortality (95% CI 1.5–7.4; P = 0.005) compared with those who reported mild/no hypoglycemia. CONCLUSIONS Self-report of severe hypoglycemia is associated with 3.4-fold increased risk of death. Patient-reported outcomes, including patient-reported hypoglycemia, may therefore augment risk stratification and disease management of patients with diabetes.

Surveys of physicians are an important tool to assess opinions and self-reported behaviors of this policy-relevant population. However, this population is notoriously difficult to survey and plagued with low and falling response rates. In order to evaluate the potential import of response rate, we examine the presence of nonresponse bias in a survey of physicians providing diabetes care that achieved a 36% response rate. Unlike other studies examining differences in individual characteristics for responding and nonresponding physicians, we also assess differences with respect to aggregate patient demographic, clinical, and behavioral characteristics. We are unable to demonstrate nonresponse bias, even with what could be construed as a relative low response rate. Nonetheless as the threat of nonresponse bias can never be completely assuaged, we believe that it should be monitored as a matter of course in physician surveys and offer a new dimension by which it can be evaluated.

Although US health care expenditures reached 17.6 percent of GDP in 2009, quality measurement in this important service sector remains limited. Studying quality changes associated with 11 years of health care for patients with diabetes, we find that the value of reduced mortality and avoided treatment spending, net of the increase in annual spending, was $9,094 for the average patient. These results suggest that the unit cost of diabetes treatment, adjusting for the value of health outcomes, has been roughly constant. Since input prices have not been declining, our results are consistent with productivity improvement in health care.

Background. Statins are an important part of the treatment plan for patients with type 2 diabetes. However, patients who are prescribed statins often take less than the prescribed amount or stop taking the drug altogether. This suboptimal adherence may decrease the benefit of statin initiation. Objective. To estimate the influence of adherence on the optimal timing of statin initiation for patients with type 2 diabetes. Method. The authors use a Markov decision process (MDP) model to optimize the treatment decision for patients with type 2 diabetes. Their model incorporates a Markov model linking adherence to treatment effectiveness and long-term health outcomes. They determine the optimal time of statin initiation that minimizes expected costs and maximizes expected quality-adjusted life years (QALYs). Results. In the long run, approximately 25% of patients remain highly adherent to statins. Based on the MDP model, generic statins lower costs in men and result in a small increase in costs in women relative to no treatment. Patients are able to noticeably increase their expected QALYs by 0.5 to 2 years depending on the level of adherence. Conclusions. Adherence-improving interventions can increase expected QALYs by as much as 1.5 years. Given suboptimal adherence to statins, it is optimal to delay the start time for statins; however, changing the start time alone does not lead to significant changes in costs or QALYs.

OBJECTIVE The negative results of two randomized controlled trials (RCTs) have challenged current guideline recommendations for using aspirin for primary prevention of cardiovascular events among patients with diabetes. We therefore sought to determine if the effect of aspirin for primary prevention of cardiovascular events and mortality differs between patients with and without diabetes. RESEARCH DESIGN AND METHODS We conducted a systematic search of MEDLINE, EMBASE, Cochrane Library, Web of Science, and Scopus since their inceptions until November 2008 for RCTs of aspirin for primary prevention of cardiovascular events. Blinded pairs of reviewers evaluated studies and extracted data. Random-effects meta-analysis and Bayesian logistic regression were used to estimate the ratios of relative risks (RRs) of outcomes of interest among patients with and without diabetes. A 95% CI that crosses 1.00 indicates that the effect of aspirin does not differ between patients with and without diabetes. RESULTS Nine RCTs with moderate to high methodological quality contributed data to the analyses. The ratios of RRs comparing the benefit of aspirin among patients with diabetes compared with patients without diabetes for mortality, myocardial infarction, and ischemic stroke were 1.12 (95% CI 0.92–1.35), 1.19 (0.82–1.17), and 0.70 (0.25–1.97), respectively. CONCLUSIONS Whereas estimates of benefit among patients with diabetes remain imprecise, our analysis suggests that the relative benefit of aspirin is similar in patients with and without diabetes.

Background. Statin Choice is a decision aid about taking statins. The optimal mode of delivering Statin Choice (or any other decision aid) in clinical practice is unknown. Methods. To investigate the effect of mode of delivery on decision aid efficacy, the authors further explored the results of a concealed 2 × 2 factorial clustered randomized trial enrolling 21 endocrinologists and 98 diabetes patients and randomizing them to 1) receive either the decision aid or pamphlet about cholesterol, and 2) have these delivered either during the office visit (by the clinician) or before the visit (by a researcher). We estimated between-group differences and their 95% confidence intervals (CI) for acceptability of information delivery (1—7), knowledge about statins and coronary risk (0—9), and decisional conflict about statin use (0—100) assessed immediately after the visit. Follow-up was 99%. Results. The relative efficacy of the decision aid v. pamphlet interacted with the mode of delivery. Compared with the pamphlet, patients whose clinicians delivered the decision aid during the office visit showed significant improvements in knowledge (difference of 1.6 of 9 questions, CI 0.3, 2.8) and nonsignificant trends toward finding the decision aid more acceptable (odds ratio 3.1, CI 0.9, 11.2) and having less decisional conflict (difference of 7 of 100 points, CI - 4, 18) than when a researcher delivered the decision aid just before the office visit. Conclusions. Delivery of decision aids by clinicians during the visit improves knowledge and shows a trend toward better acceptability and less decisional conflict.

Background . Clinicians often use validated risk models to guide treatment decisions for cardiovascular risk reduction. The most common risk models for predicting cardiovascular risk are the UKPDS, Framingham, and Archimedes models. In this article, the authors propose a model to optimize the selection of patients for statin therapy of hypercholesterolemia, for patients with type 2 diabetes, using each of the risk models. For each model, they evaluate the role of age, gender, and metabolic state on the optimal start time for statins. Method . Using clinical data from the Mayo Clinic electronic medical record, the authors construct a Markov decision process model with health states composed of cardiovascular events and metabolic factors such as total cholesterol and high-density lipoproteins. They use it to evaluate the optimal start time of statin treatment for different combinations of cardiovascular risk models and patient attributes. Results . The authors find that treatment decisions depend on the cardiovascular risk model used and the age, gender, and metabolic state of the patient. Using the UKPDS risk model to estimate the probability of coronary heart disease and stroke events, they find that all white male patients should eventually start statin therapy; however, using Framingham and Archimedes models in place of UKPDS, they find that for male patients at lower risk, it is never optimal to initiate statins. For white female patients, the authors also find some patients for whom it is never optimal to initiate statins. Assuming that age 40 is the earliest possible start time, the authors find that the earliest optimal start times for UKPDS, Framingham, and Archimedes are 50, 46, and 40, respectively, for women. For men, the earliest optimal start times are 40, 40, and 40, respectively. Conclusions . In addition to age, gender, and metabolic state, the choice of cardiovascular risk model influences the apparent optimal time for starting statins in patients with diabetes.