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  • Change in Testing, Awareness of Hemoglobin A 1c Result, and Glycemic Control in US Adults, 2007-2014

    Abstract Full Text
    JAMA. 2017; 318(18):1825-1827. doi: 10.1001/jama.2017.11927

    This cross-sectional study uses NHANES survey data to examine trends in glycemic control and patient awareness of HbA1c test results and targets between 2007 and 2014.

  • JAMA October 17, 2017

    Figure: Associations of Insulin-Metformin Combination Therapy vs Insulin Monotherapy With Change in Hemoglobin A1c

    The mean differences are between baseline and follow-up for the insulin-metformin combination therapy group vs the insulin monotherapy group. The size of the data markers indicates the weight of the study; NR, not reported.aEpisodes per participant per month.
  • Oral Hypoglycemic Agents Added to Insulin Monotherapy for Type 2 Diabetes

    Abstract Full Text
    JAMA. 2017; 318(15):1489-1490. doi: 10.1001/jama.2017.13463

    This Clinical Evidence Synopsis summarizes a Cochrane review on the effects of adding oral hypoglycemic agents to insulin for patients with type 2 diabetes mellitus who have not achieved optimal glycemic control with insulin alone.

  • Effect of Oral Semaglutide Compared With Placebo and Subcutaneous Semaglutide on Glycemic Control in Patients With Type 2 Diabetes: A Randomized Clinical Trial

    Abstract Full Text
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    JAMA. 2017; 318(15):1460-1470. doi: 10.1001/jama.2017.14752

    This phase 2 randomized trial compared the effects on hemoglobin A1c levels of varying doses of oral once-daily semaglutide vs placebo vs subcutaneous semaglutide in patients with type 2 diabetes.

  • JAMA August 15, 2017

    Figure 2: Hemoglobin A1c Levels for the Lifestyle vs Standard Care Groups Among Participants With Non–Insulin-Dependent Type 2 Diabetes, Intention-to-Treat Analysis

    Data are least squares means derived from mixed linear models and adjusted for baseline hemoglobin A1c and sex. Error bars indicate 95% CIs.
  • Effect of an Intensive Lifestyle Intervention on Glycemic Control in Patients With Type 2 Diabetes: A Randomized Clinical Trial

    Abstract Full Text
    JAMA. 2017; 318(7):637-646. doi: 10.1001/jama.2017.10169

    This randomized clinical trial compared the effects of an intensive lifestyle intervention vs standard care on glycemic control and medication reduction among participants with non–insulin-dependent type 2 diabetes.

  • JAMA July 4, 2017

    Figure 3: Hemoglobin A1c Level Over Time

    Data are observed mean level of hemoglobin A1c for the full analysis set. Error bars indicate 95% confidence intervals. See eFigure 1 in Supplement 1 for the design of the treatment periods.
  • JAMA July 4, 2017

    Figure 3: Mean Hemoglobin A1c and Fasting Plasma Glucose Levels Over Time

    Data are observed means. Error bars indicate 95% CIs for the full analysis set. Statistical analyses were performed using a mixed-model repeated measures with treatment, sex, region, dosing time, pretrial insulin treatment, and visit as factors and with baseline hemoglobin A1c (HbA1c) and age as covariates. All fixed factors and covariates are nested within visit. Analysis of treatment period 1 only included patients having observation time in maintenance period 1; for treatment period 2, all patients having any HbA1c measurements after crossover contributed to the analysis. Severe hypoglycemia was defined according to the ADA definition (see the Methods section). The numbers of patients represent those contributing to the data at that time point.
  • Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013

    Abstract Full Text
    JAMA. 2017; 317(24):2515-2523. doi: 10.1001/jama.2017.7596

    This population epidemiology study uses national survey data to estimate the prevalence and ethnic patterns of diabetes and prediabetes in China in 2013.

  • JAMA March 14, 2017

    Figure: Glucose Management for Patients With Type 2 Diabetes

    DPP4 indicates dipeptidyl peptidase 4 inhibitors; GLP1RA, glucagon-like peptide 1 receptor agonists; HbA1c, hemoglobin A1c; HF, heart failure; MACE, major adverse cardiovascular events; Pio, pioglitazone; SGLT2, sodium glucose transporter 2 inhibitors; and SU, sulfonylureas.aIndicates a higher-cost drug.
  • Association of Type 1 Diabetes vs Type 2 Diabetes Diagnosed During Childhood and Adolescence With Complications During Teenage Years and Young Adulthood

    Abstract Full Text
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    JAMA. 2017; 317(8):825-835. doi: 10.1001/jama.2017.0686

    This cohort study uses diabetes registry data to compare rates of complications related to type 1 vs type 2 diabetes among teenagers and young adults diagnosed with diabetes during childhood and adolescence.

  • JAMA February 14, 2017

    Figure 3: Association of 48-SNP Polygenic Risk Score for WHR Adjusted for BMI With Cardiometabolic Quantitative Traits

    Results are standardized to a 1-SD increase in waist-to-hip ratio (WHR) adjusted for body mass index (BMI) due to polygenic risk score. For systolic blood pressure, a 1-SD genetic increase in WHR adjusted for BMI is associated with a 2.1-mm Hg higher systolic blood pressure (95% CI, 1.2-3.0) or a 0.1-SD increase in systolic blood pressure (95% CI, 0.059-0.15). For anthropometric traits, estimates from Genetic Investigation of Anthropometric Traits (GIANT) derived using inverse variance–weighted fixed-effects meta-analysis) were pooled with data from the UK Biobank (derived instrumental variables regression adjusting for age, sex, 10 principal components of ancestry, and array type) using inverse variance–weighted fixed-effects meta-analysis. For lipids, glycemic, and renal function traits, estimates were derived from genome-wide association studies (Global Lipids Genetics, Meta-analyses of Glucose and Insulin-Related Traits, and Chronic Kidney Genetics Consortia, respectively). For blood pressure, estimates were derived from UK Biobank. Two-hour glucose refers to measured blood glucose levels 2 hours after consumption of dissolved glucose. The threshold of significance was P < .0033 (.05/15 = .0033). Size of data markers is inversely proportional to variance of estimate. To convert total cholesterol, LDL-C, and HDL-C values to mmol/L, multiply by 0.0259; triglyceride values to mmol, multiply by 0.0113; and glucose values to mmol/L, multiply by 0.0555. eGFR indicates estimated glomerular filtration rate; HbA1c, hemoglobin A1c; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; OR, odds ratio; WHR, waist-to-hip ratio.aUnits reported in column 1.bCalculated as weight in kilograms divided by height in meters squared.
  • JAMA February 7, 2017

    Figure 3: Comparison of the Diagnostic Sensitivity of Hemoglobin A1c to Identify Combined Prediabetes or Diabetes by Sickle Cell Trait Status

    A, For fasting glucose of 100 mg/dL or higher, the area under the receiver operating characteristic (AUROC) curve of hemoglobin A1c (HbA1c) was 0.77 (95% CI, 0.75-0.78) among those without sickle cell trait (SCT) and 0.70 (95% CI, 0.65-0.74) among those with SCT. An unpaired comparison of the AUROC curves indicated that the diagnostic ability of HbA1c to identify fasting glucose–defined prediabetes or diabetes was significantly lower among those with SCT than among those without it (P = .007). B, For 2-hour glucose levels of 140 mg/dL or higher, the AUROC of HbA1c was 0.74 (95% CI, 0.71-0.78) among those without SCT and 0.60 (95% CI, 0.47-0.72) among those with SCT. An unpaired comparison of the AUROC curves indicated that the diagnostic ability of HbA1c to identify 2-hour glucose-defined prediabetes or diabetes was significantly lower in those with SCT than in those without it (P = .03). To convert glucose from mg/dL to mmol/L, multiply by 0.0555.
  • JAMA February 7, 2017

    Figure 1: Scatterplot of Observed Data Model of Hemoglobin A1c vs Fasting and 2-Hour Glucose Measures in Participants With or Without Sickle Cell Trait

    Scatterplot of observed data points alongside unadjusted and adjusted regression lines examining the association between sickle cell trait (SCT) and hemoglobin A1c (HbA1c), controlling for fasting or 2-hour glucose values was obtained using generalized estimating equations (GEE) with an exchangeable correlation matrix to account for correlation of repeated measures. All continuous covariates are centered at the population mean. The solid blue lines represent the regression line for those for who did not have SCT and the dashed orange lines for those who had SCT. BMI indicates body mass index; CARDIA, Coronary Artery Risk Development in Young Adults study. To convert glucose from mg/dL to mmol/L, multiply by 0.0555.A, Included 9062 observations, 720 from participants with SCT and 8342 from participants without SCT. The regression equation: predicted HbA1c = 6.01 + (−0.28 × SCT) + (0.03 × fasting glucose) + (−0.004 SCT fasting glucose). B, Included 8460 observations, 683 from participants with SCT and 7777 from participants without SCT. The regression equation: predicted HbA1c = 5.93 + (−0.32 × SCT) + (0.03 × fasting glucose) + (−0.005 × SCT × fasting glucose) + (0.04 × 1 if male) +  (0.008 × age) + (0.01 × BMI) + (−0.0004 × ferritin) + (0.001 × estimated glomerular filtration rate) + (−0.08 × 1 if a CARDIA participant) + (0.46 × 1 if currently using diabetes medications) + (0.14 × 1 if previous diabetes diagnosis). C, Included 2001 observations, 127 from participants with SCT and 1874 from participants without SCT. Regression equation: predicted HbA1c = 5.65 + (−0.28 × SCT) + (0.01 × 2-hour glucose) + (−0.004 × SCT × 2-hour glucose). D, Included 1712 observations, 109 from participants with SCT and 1606 from participants without SCT. Regression equation: predicted HbA1c = 5.66 + (−0.36 × SCT) + (0.01 × 2-hour glucose) × (−0.004 × SCT × 2-hour glucose) +  (0.24 × 1 if male) + (0.02 × age) + (0.006 × BMI) + (−0.0006 × ferritin) + (0.0003 × eGFR) + (0.07 × 1 if previous diabetes diagnosis).
  • JAMA February 7, 2017

    Figure 2: Prevalence of Prediabetes and Diabetes by Sickle Cell Trait Status Among Participants Not Taking Diabetes Medications and With No Prior Diagnosis of Diabetes

    Fasting glucose and hemoglobin A1c analyses included 7499 total observations (6877 observations from participants without sickle cell train [SCT] and 572 from participants with it). Analyses for 2-hour glucose concentrations were only available from CARDIA participants and included 1869 total observations (1752 observations from participants without SCT and 117 from participants with SCT). For the definition of prediabetes and diabetes by glucose measures, see the Methods section. The prevalence of prediabetes and diabetes by fasting glucose and 2-hour glucose concentration was similar in those with and without SCT (P > .10 for all comparisons). However, the prevalence of prediabetes and diabetes as defined by hemoglobin A1c was significantly higher among participants with vs without SCT (P < .001 for both). Error bars indicate 95% CIs.
  • JAMA January 24, 2017

    Figure 2: Hemoglobin A1c Values at Baseline and 24 Weeks, by Group

    A, Scatterplot of 24-week hemoglobin A1c (HbA1c) levels by baseline HbA1c level. The horizontal line at 7.0% represents the American Diabetes Association HbA1c goal for adults with type 1 diabetes. Points below the diagonal line represent cases in which the 24-week HbA1c level was lower than the baseline HbA1c level, points above the diagonal line represent cases in which the 24-week HbA1c level was higher than the baseline HbA1c level, and points on the diagonal line represent cases in which the 24-week and baseline HbA1c values were the same. B, Cumulative distribution of 24-week HbA1c values. For any given 24-week HbA1c level, the percentage of cases in each treatment group with an HbA1c value at that level or lower can be determined from the figure. To convert HbA1c to the SI units of mmol/mol, multiply the HbA1c percentage value × 10.93 and subtract 23.5 from the product.
  • JAMA July 19, 2016

    Figure 3: Efficacy Rankings of Available Glucose-Lowering Drugs for Treatment of Type 2 Diabetes

    Drug rankings for efficacy (cardiovascular mortality, treatment failure, and hemoglobin A1c [HbA1C] levels). Drug classes are stratified according to administration as monotherapy, as dual therapy in addition to metformin, or as triple therapy in addition to metformin and sulfonylurea. The lines show the probability of the drug ranking for each outcome between best and worst (ranking first, second, third, etc), and the peak indicates the ranking with the highest probability for the corresponding drug class. For example, for treatment failure, sodium-glucose–linked transporter 2 (SGLT-2) inhibitor monotherapy demonstrates a higher probability of ranking best than thiazolidinedione monotherapy. Basal insulin monotherapy has a 50% probability of ranking as the best drug for avoiding treatment failure and a 100% probability of ranking the worst (13th best) for hypoglycemia (see Figure 4). Rankogram lines without marked peaks (for example, for all drug classes as monotherapy and their association with odds of cardiovascular mortality) indicate similar probabilities of all rankings and lower confidence in comparative ranking of the relevant drug class for that outcome. Rankograms showing no data indicate observations were insufficient to generate a rankogram for the drug class for the corresponding outcome. For example, there were insufficient data for meglitinides as triple therapy to infer drug rankings for any outcome. Similarly, there were insufficient data to infer drug rankings for α-glucosidase inhibitor treatment in triple therapy for the outcome of cardiovascular mortality. The peak of the rankogram curve can be used to assess probabilities of drug classes between best and worst (for example, for treatment failure, SGLT-2 inhibitors, and glucagon-like peptide 1 (GLP-1) receptor agonists were most likely to be among the best treatments and had similar ranking). DPP-4 indicates dipeptidyl peptidase 4.
  • JAMA December 1, 2015

    Figure: Flow of Study Participants: Metformin for Adolescents With Type 1 Diabetes

    HbA1c indicates hemoglobin A1c; BMI, body mass index.
  • Diabetes Risk Assessment and Glycemic Control

    Abstract Full Text
    JAMA. 2015; 314(17):1861-1862. doi: 10.1001/jama.2015.11518

    This commentary discusses a cluster randomized trial published in JAMA Ophthalmology that compared the effects of personalized education and risk assessment vs usual care during retinal ophthalmologic visits on hemoglobin A1c levels among patients with diabetes.

  • JAMA September 8, 2015

    Figure 1: US Trends in Diabetes Prevalence per 100 Adults Aged 20 Years or Older

    Both diagnosed and undiagnosed cases of diabetes are included in the total cases. Diagnosed diabetes is based on self-report of a previous diagnosis by a physician or other health professional. Undiagnosed diabetes is based on a hemoglobin A1c level of 6.5% or greater or fasting plasma glucose level of 126 mg/dL or greater. All estimates were age standardized to the overall 2011-2012 National Health and Nutrition Examination Survey interview population using the age groups of 20-44 years, 45-64 years, and 65 years or older. Error bars indicate 95% confidence intervals.