Diabetes Clinical Trials Research Articles

Transcriptomic analysis of human primary breast cancer identifies fatty acid oxidation as a target for metformin

BackgroundEpidemiological studies suggest that metformin may reduce the incidence of cancer in patients with diabetes and multiple late phase clinical trials assessing the potential of repurposing this drug are underway. Transcriptomic profiling of tumour samples is an excellent tool to understand drug bioactivity, identify candidate biomarkers and assess for mechanisms of resistance to therapy.MethodsThirty-six patients with untreated primary breast cancer were recruited to a window study and transcriptomic profiling of tumour samples carried out before and after metformin treatment.ResultsMultiple genes that regulate fatty acid oxidation were upregulated at the transcriptomic level and there was a differential change in expression between two previously identified cohorts of patients with distinct metabolic responses. Increase in expression of a mitochondrial fatty oxidation gene composite signature correlated with change in a proliferation gene signature. In vitro assays showed that, in contrast to previous studies in models of normal cells, metformin reduces fatty acid oxidation with a subsequent accumulation of intracellular triglyceride, independent of AMPK activation.ConclusionsWe propose that metformin at clinical doses targets fatty acid oxidation in cancer cells with implications for patient selection and drug combinations.Clinical Trial RegistrationNCT01266486.

Selection of the optimal personalized treatment from multiple treatments with multivariate outcome measures

ABSTRACTIn this work, we propose a novel method for individualized treatment selection when the treatment response is multivariate. For the K treatment (K ≥2) scenario we compare quantities that are suitable indexes based on outcome variables for each treatment conditional on patient-specific scores constructed from collected covariate measurements. Our method covers any number of treatments and outcome variables, and it can be applied for a broad set of models. The proposed method uses a rank aggregation technique to estimate an ordering of treatments based on ranked lists of treatment performance measures such as smooth conditional means and conditional probability of a response for one treatment dominating others. The method has the flexibility to incorporate patient and clinician preferences to the optimal treatment decision on an individual case basis. A simulation study demonstrates the performance of the proposed method in finite samples. We also present data analyses using HIV and Diabetes clinical trials data to show the applicability of the proposed procedure for real data.

PDB96 THE IMPACT OF ADJUNCT DAPAGLIFLOZIN ON TREATMENT SATISFACTION IN TYPE 1 DIABETES MELLITUS

The Dapagliflozin Evaluation in Patients With Inadequately Controlled Type 1 Diabetes (DEPICT) clinical trial programme, showed that for patients with type 1 diabetes mellitus (T1DM) inadequately controlled by insulin alone, adjunct dapagliflozin (10mg or 5mg) reduced body weight and improved glycaemic control, without increased risk of hypoglycaemia versus placebo. Incidence and related fear of hypoglycaemia and weight gain are among factors that influence patient-reported outcomes, such as quality of life and treatment satisfaction. This study aimed to assess the impact of dapagliflozin on patient-reported treatment satisfaction in DEPICT. Patient treatment satisfaction was measured via the Diabetes Treatment Satisfaction Questionnaire (DTSQ) total score. All patients from DEPICT (consisting of the DEPICT-1 and DEPICT-2 trials) with complete DTSQ measurements were eligible for inclusion in the analysis. The proportion of patients achieving a 3-point improvement in DTSQ total score from baseline was evaluated at week 24 and week 52. Statistical significance of differences in observed proportions between study arms was assessed using a Z-test of proportions. A higher proportion of patients treated with dapagliflozin achieved at least a 3-point increase in DTSQ total score compared to placebo over 24 weeks (dapagliflozin 10mg: 37%; dapagliflozin 5mg; 39%, placebo: 28%) and 52 weeks (dapagliflozin 10mg: 43%; dapagliflozin 5mg: 37%; placebo: 32%). At both doses, statistically significant differences were observed between dapagliflozin and placebo at 24 weeks (10mg: p=0.002; 5mg: p<0.001). At 52 weeks a significant difference was observed between dapagliflozin 10mg and placebo (p=0.001), but the difference between dapagliflozin 5mg and placebo was not statistically significant. The results of this study demonstrated that treatment with dapagliflozin was associated with an improvement in treatment satisfaction compared to placebo. Together with improvements in glycaemic control, weight and incidence of hypoglycaemia, improvements in patient-reported outcomes support the role of dapagliflozin in T1DM management.

Homotaurine Treatment Enhances CD4+ and CD8+ Regulatory T Cell Responses and Synergizes with Low-Dose Anti-CD3 to Enhance Diabetes Remission in Type 1 Diabetic Mice.

Immune cells express γ-aminobutyric acid receptors (GABA-R), and GABA administration can inhibit effector T cell responses in models of autoimmune disease. The pharmacokinetic properties of GABA, however, may be suboptimal for clinical applications. The amino acid homotaurine is a type A GABA-R (GABAA-R) agonist with good pharmacokinetics and appears safe for human consumption. In this study, we show that homotaurine inhibits in vitro T cell proliferation to a similar degree as GABA but at lower concentrations. In vivo, oral homotaurine treatment had a modest ability to reverse hyperglycemia in newly hyperglycemic NOD mice but was ineffective after the onset of severe hyperglycemia. In severely diabetic NOD mice, the combination of homotaurine and low-dose anti-CD3 treatment significantly increased 1) disease remission, 2) the percentages of splenic CD4+ and CD8+ regulatory T cells compared with anti-CD3 alone, and 3) the frequencies of CD4+ and CD8+ regulatory T cells in the pancreatic lymph nodes compared with homotaurine monotherapy. Histological examination of their pancreata provided no evidence of the large-scale GABAA-R agonist–mediated replenishment of islet β-cells that has been reported by others. However, we did observe a few functional islets in mice that received combined therapy. Thus, GABAA-R activation enhanced CD4+ and CD8+ regulatory T cell responses following the depletion of effector T cells, which was associated with the preservation of some functional islets. Finally, we observed that homotaurine treatment enhanced β-cell replication and survival in a human islet xenograft model. Hence, GABAA-R agonists, such as homotaurine, are attractive candidates for testing in combination with other therapeutic agents in type 1 diabetes clinical trials.

Incorporating and interpreting regulatory guidance on estimands in diabetes clinical trials: The PIONEER 1 randomized clinical trial as an example.

Regulatory guidelines describe the use of estimands in designing and conducting clinical trials. Estimands ensure alignment of the objectives with the design, conduct and analysis of a trial. An estimand is defined by four inter‐related attributes: the population of interest, the variable (endpoint) of interest, the way intercurrent events are handled and the population level summary. A trial may employ multiple estimands to evaluate treatment effects from different perspectives in order to address different scientific questions. As estimands may be an unfamiliar concept for many clinicians treating diabetes, this paper reviews the estimand concept and uses the PIONEER 1 phase 3a clinical trial, which investigated the efficacy and safety of oral semaglutide vs placebo, as an example of the way in which estimands can be implemented and interpreted. In the PIONEER 1 trial, two estimands were employed for each efficacy endpoint and were labelled as: (a) the treatment policy estimand, used to assess the treatment effect regardless of use of rescue medication or discontinuation of trial product, and provides a broad perspective of the treatment effect in the population of patients with type 2 diabetes in clinical practice; and (b) the trial product estimand, used to assess the treatment effect if all patients had continued to use trial product for the planned duration of the trial without rescue medication, thereby providing information on the anticipated treatment effect of the medication. Both approaches are complementary to understanding the effect of the studied treatments.

The Use of Computer Simulation Modeling to Estimate Complications in Patients with Type 2 Diabetes Mellitus: Comparative Validation of the Cornerstone Diabetes Simulation Model.

ObjectiveThe objective of this study was to assess the validity of the Cornerstone Diabetes Simulation (CDS), a Microsoft Excel®-based patient-level simulation for type 2 diabetes mellitus based on risk equations from the revised United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS-OM2, also known as UKPDS 82).MethodsThree levels of validation were conducted. Internal validation was assessed through independent review and model stress-testing. External validation was addressed by populating the CDS with baseline characteristics and treatment effects from three major diabetes clinical trials used in the Fifth Mount Hood Diabetes Challenge (MH5) for computer simulation models. Cross-validation of predicted outcomes was tested versus eight models that participated in the MH5. Simulated results were compared with observed clinical outcomes via the coefficient of determination (R2) for both the absolute risk of each clinical outcome and the difference in absolute risk between control and intervention arm in each trial. We ensured transparency of all model inputs and assumptions in reporting.ResultsThe CDS could be used to predict 18 of 39 single and composite endpoints across the three trials. The model obtained an R2 of 0.637 for predicted versus observed absolute risks, and an R2 of 0.442 for predicted versus observed risk differences between control and intervention. Among the other eight models, only one obtained a higher R2 value under both definitions, albeit based on only four predicted endpoints.ConclusionsThe CDS provides good predictions of diabetes-related complications when compared to observed trial outcomes and previously validated models. The model has value as a validated tool in cost-effectiveness evaluations.Electronic supplementary materialThe online version of this article (10.1007/s41669-019-0156-x) contains supplementary material, which is available to authorized users.

The Usage of Type 2 Diabetes Medication for Outpatients at the Ministry of Public Security Traditional Medicine Hospital

This study aimes to analyse the usage of type 2 diabetes medication for outpatients at the Ministry of Public Security Traditional Medicine Hospital and to rate their adherence to the treatment. In this study, Type 2 diabetic patients were treated as outpatients and managed for at least 12 months at the clinic of the hospital. The results show that after 12 months of treatment, the average fasting blood glucose value decreased from 7.6 ± 1.76 mmol/l to 7.42 ± 1.81 mmol/l and the percentage of the patients either with blood glucose changes or reached the FPG target, increased from 38.3% to 70.0%, a statistically significant difference with p &lt;0.05. After 6 months of treatment from the time of T-6 to T0, HbA1c index decreased by 7.1 ± 1.0 to 6.4 ± 0.9% and the percentage of the patients either with HbA1C value changes or achieved the target, increased from 50.0% to 75.0%. The percentage of the patients who had good compliance was 60.8%. With an additional drug in the regimen, the adherence reduced by 29% (OR = 0.71; 95% CI 0.56 - 0.89; p = 0.002). The adherence of the 1-year-older patients decreased by 9% (OR = 0.91; 95% CI 0.84 - 0.97; p = 0.03). The study concludes that most of the patients received stable treatment; the regimens promoted maximum therapeutic effect. The two factors affecting the level of compliance of the patients with the drug were the age and the number of diabetes medicines used in the application.&#x0D; Keywords&#x0D; Type 2 diabetes, adherence to treatment, outpatients.&#x0D; References&#x0D; [1] Association. American Diabetes, Standards of medical care in diabetes - 2018, https://diabetesed.net/wp-content/uploads/2017/12/2018-ADA-Standards-of-Care.pdf, 2018 (accessed 25 May 2019).[2] A. Jafarian-Amirkhizi, A. Sarayani, K. Gholami, M. Taghizadeh-Ghehi, K. Heidari, A. Jafarzadeh-Kohneloo, D.E.Morisky, Adherence to medications, self-care activity, and HbA1c status among patients with type 2 diabetes living in an urban area of Iran, J Diabetes Metab Disord. 17(2) (2018) 165-172. https://doi: 10.1007/s40200-018-0356-4.[3] D.E. Morisky, M.R. Di Matteo, Improving the measurement of self-reported medication nonadherence: Response to Authors, J Clin Epidemiol. 64(3) (2011) 255-257; discussion 258-63. https:// doi: 10.1016/j.jclinepi.2010.09.002.[4] Y. Tominaga, T. Aomori, T. Hayakawa, D.E. Morisky, K. Takahashi, M. Mochizuki, Relationship between medication adherence and glycemic control in Japanese patients with type 2 diabetes. Pharmazie. 73(10) (2018) 609-612. https://doi: 10.1691/ph.2018.8587. [5] M.C. Govern Andrew, T. Zayd, Systematic review of adherence rates by medication class in type 2 diabetes: a study protocol, BMJ Open, 6(2) (2016) e010469. https://doi: https://doi: 10.1136/bmjopen-2015-010469.[6] M. Tiktin, S. Celik, Understanding adherence to medications in type 2 diabetes care and clinical trials to overcome barriers: a narrative review, Curr Med Res Opin. 32(2) (2016) 277-287. https:// doi: https:// doi: 10.1185/03007995.2015.1119677.&#x0D; &#x0D; &#x0D;

1689-P: Assessments of Alternative C-Peptide (C-P) Endpoints for New-Onset Type 1 Diabetes (T1D) Clinical Trials

The mean 2-hour MMTT AUC C-P at 12 months of follow-up has been the primary endpoint for all TrialNet clinical trials of individuals newly diagnosed with T1D. However, it is possible that other measures of C-P responsiveness from MMTTs could provide useful efficacy information for such trials. Thus, we assessed other C-P measures as potential endpoints by substituting them in place of the AUC C-P in completed trials that showed effects of interventions (Rituximab, Abatacept, ATG and ATG+GCSF). These measures included the 30-0 min C-P, AUC C-P partitioned for a response during the first and second hours, peak C-P, as well as AUC C-P/AUC glucose. Estimates for the differences between the treatment and placebo arms were expressed in standard deviation units. The Table below shows differences between treatment and placebo arms along with the significance of the AUC C-P and the substituted endpoint measures for the trials. We found that the differences and their statistical significance were similar to the 2-hour AUC C-P. However, the peak C-P tended to show a wider divergence between the treatment and placebo arms for ATG+GCSF. Our findings show that additional measures of C-P responses could serve as clinical trial endpoints. Other measures of the C-P response besides the AUC could be helpful in assessing the effects of interventions and has potential implications for trials previously considered negative. Disclosure H.M. Ismail: None. B.N. Bundy: None. M.A. Atkinson: None. W.V. Moore: None. M.J. Haller: Advisory Panel; Self; Pancreum, SAB Biotherapeutics. W.E. Russell: None. S.E. Gitelman: Advisory Panel; Self; Avortes, Intermountain Therapeutics, Lilly Diabetes, Tolerion, Inc. Research Support; Self; Caladrius Biosciences, Inc., Janssen Research &amp; Development. Other Relationship; Self; Novo Nordisk Inc. K.C. Herold: Consultant; Self; Provention Bio, Roche Pharma. M.J. Redondo: None. J.M. Sosenko: None. Funding National Institutes of Health

A Genetic Locus on Chromosome 2q24 Predicting Peripheral Neuropathy Risk in Type 2 Diabetes: Results From the ACCORD and BARI 2D Studies.

Genetic factors have been postulated to be involved in the etiology of diabetic peripheral neuropathy (DPN), but their identity remains mostly unknown. The aim of this study was to conduct a systematic search for genetic variants influencing DPN risk using two well-characterized cohorts. A genome-wide association study (GWAS) testing 6.8 million single nucleotide polymorphisms was conducted among participants of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial. Included were 4,384 white case patients with type 2 diabetes (T2D) and prevalent or incident DPN (defined as a Michigan Neuropathy Screening Instrument clinical examination score >2.0) and 784 white control subjects with T2D and no evidence of DPN at baseline or during follow-up. Replication of significant loci was sought among white subjects with T2D (791 DPN-positive case subjects and 158 DPN-negative control subjects) from the Bypass Angioplasty Revascularization Investigation in Type 2 Diabetes (BARI 2D) trial. Association between significant variants and gene expression in peripheral nerves was evaluated in the Genotype-Tissue Expression (GTEx) database. A cluster of 28 SNPs on chromosome 2q24 reached GWAS significance (P < 5 × 10−8) in ACCORD. The minor allele of the lead SNP (rs13417783, minor allele frequency = 0.14) decreased DPN odds by 36% (odds ratio [OR] 0.64, 95% CI 0.55–0.74, P = 1.9 × 10−9). This effect was not influenced by ACCORD treatment assignments (P for interaction = 0.6) or mediated by an association with known DPN risk factors. This locus was successfully validated in BARI 2D (OR 0.57, 95% CI 0.42–0.80, P = 9 × 10−4; summary P = 7.9 × 10−12). In GTEx, the minor, protective allele at this locus was associated with higher tibial nerve expression of an adjacent gene (SCN2A) coding for human voltage-gated sodium channel NaV1.2 (P = 9 × 10−4). To conclude, we have identified and successfully validated a previously unknown locus with a powerful protective effect on the development of DPN in T2D. These results may provide novel insights into DPN pathogenesis and point to a potential target for novel interventions.

Establishing an electronic health record-supported approach for outreach to and recruitment of persons at high risk of type 2 diabetes in clinical trials: The vitamin D and type 2 diabetes (D2d) study experience.

To establish recruitment approaches that leverage electronic health records in multicenter prediabetes/diabetes clinical trials and compare recruitment outcomes between electronic health record-supported and conventional recruitment methods. Observational analysis of recruitment approaches in the vitamin D and type 2 diabetes (D2d) study, a multicenter trial in participants with prediabetes. Outcomes were adoption of electronic health record-supported recruitment approaches by sites, number of participants screened, recruitment performance (proportion screened who were randomized), and characteristics of participants from electronic health record-supported versus non-electronic health record methods. In total, 2423 participants were randomized: 1920 from electronic health record (mean age of 60 years, 41% women, 68% White) and 503 from non-electronic health record sources (mean age of 56.9 years, 58% women, 61% White). Electronic health record-supported recruitment was adopted by 21 of 22 sites. Electronic health record-supported recruitment was associated with more participants screened versus non-electronic health record methods (4969 vs 2166 participants screened), higher performance (38.6% vs 22.7%), and more randomizations (1918 vs 505). Participants recruited via electronic health record were older, included fewer women and minorities, and reported higher use of dietary supplements. Electronic health record-supported recruitment was incorporated in diverse clinical environments, engaging clinicians either at the individual or the healthcare system level. Establishing electronic health record-supported recruitment approaches across a multicenter prediabetes/diabetes trial is feasible and can be adopted by diverse clinical environments.

Identifying individual risk rare variants using protein structure guided local tests (POINT).

Rare variants are of increasing interest to genetic association studies because of their etiological contributions to human complex diseases. Due to the rarity of the mutant events, rare variants are routinely analyzed on an aggregate level. While aggregation analyses improve the detection of global-level signal, they are not able to pinpoint causal variants within a variant set. To perform inference on a localized level, additional information, e.g., biological annotation, is often needed to boost the information content of a rare variant. Following the observation that important variants are likely to cluster together on functional domains, we propose a protein structure guided local test (POINT) to provide variant-specific association information using structure-guided aggregation of signal. Constructed under a kernel machine framework, POINT performs local association testing by borrowing information from neighboring variants in the 3-dimensional protein space in a data-adaptive fashion. Besides merely providing a list of promising variants, POINT assigns each variant a p-value to permit variant ranking and prioritization. We assess the selection performance of POINT using simulations and illustrate how it can be used to prioritize individual rare variants in PCSK9, ANGPTL4 and CETP in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial data.

Connecting the Dots: Validation of Time in Range Metrics With Microvascular Outcomes.

The landmark Diabetes Control and Complications Trial (DCCT) identified the relationship between intensive diabetes management for those with type 1 diabetes (T1D) and a delay in the onset or progression of microvascular complications, shifting the paradigm of clinical care for this chronic medical condition (1). Importantly, the data from that trial continue to have a lasting legacy as they can now be analyzed to inform present-day questions. An example of this comes from the article by Beck et al. in this issue of Diabetes Care (2) that concisely states the primary implication of the article in its title, “Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.” In recent years, and with increasing use of continuous glucose monitoring (CGM), the ability to classify sensor glucose levels into various ranges has been feasible. Yet, some have questioned the validity of using these measures as a surrogate outcome measure in ongoing and future clinical trials. Indeed, some have called for a “modern-day” DCCT assessing whether CGM and a greater time in range (TIR) would result in fewer microvascular end points compared with self-monitoring of blood glucose (with intermittent masked CGM). Unfortunately, the duration of time, funds required, and ethical concerns given clinical equipoise regarding the benefits of the technology would make completion of a rigorous randomized controlled trial a near-impossible feat. Recognizing the wealth of data that the DCCT affords, Beck et al. (2) found a creative solution to assess the hypothesis of whether TIR could serve as an outcome measure for future trials. Specifically, they capitalized on the glucose values captured seven times daily every 3 months during the course of the 6+ years of the DCCT. This allowed them to calculate the percent TIR of glucose values between 70 and 180 mg/dL and show a robust …

Incorporating and interpreting regulatory guidance on estimands in diabetes clinical trials: The PIONEER 1 randomized clinical trial as an example

Incorporating and interpreting regulatory guidance on estimands in diabetes clinical trials: The PIONEER 1 randomized clinical trial as an example

Automated safety event monitoring using electronic medical records in a clinical trial setting: Validation study using the VA NEPHRON-D trial.

Electronic medical records are now frequently used for capturing patient-level data in clinical trials. Within the Veterans Affairs health care system, electronic medical record data have been widely used in clinical trials to assess eligibility, facilitate referrals for recruitment, and conduct follow-up and safety monitoring. Despite the potential for increased efficiency in using electronic medical records to capture safety data via a centralized algorithm, it is important to evaluate the integrity and accuracy of electronic medical record-captured data. To this end, this investigation assesses data collection, both for general and study-specific safety endpoints, by comparing electronic medical record-based safety monitoring versus safety data collected during the course of the Veterans Affairs Nephropathy in Diabetes (VA NEPHRON-D) clinical trial. The VA NEPHRON-D study was a multicenter, double-blind, randomized clinical trial designed to compare the effect of combination therapy (losartan plus lisinopril) versus monotherapy (losartan) on the progression of kidney disease in individuals with diabetes and proteinuria. The trial's safety outcomes included serious adverse events, hyperkalemia, and acute kidney injury. A subset of the participants (~62%, n = 895) enrolled in the trial's long-term follow-up sub-study and consented to electronic medical record data collection. We applied an automated algorithm to search and capture safety data using the VA Corporate Data Warehouse which houses electronic medical record data. Using study safety data reported during the trial as the gold standard, we evaluated the sensitivity and precision of electronic medical record-based safety data and related treatment effects. The sensitivity of the electronic medical record-based safety for hospitalizations was 65.3% without non-VA hospitalization events and 92.3% with the non-VA hospitalization events included. The sensitivity was only 54.3% for acute kidney injury and 87.3% for hyperkalemia. The precision of electronic medical record-based safety data was 89.4%, 38%, and 63.2% for hospitalization, acute kidney injury, and hyperkalemia, respectively. Relative treatment differences under the study and electronic medical record settings were 15% and 3% for hospitalization, 123% and 29% for acute kidney injury, and 238% and 140% for hyperkalemia, respectively. The accuracy of using automated electronic medical record safety data depends on the events of interest. Identification of all-cause hospitalizations would be reliable if search methods could, in addition to VA hospitalizations, also capture non-VA hospitalizations. However, hospitalization is different from a cause-specific serious adverse event that could be more sensitive to treatment effects. In addition, some study-specific safety events were not easily identified using the electronic medical records. This limits the effectiveness of the automated central database search for purposes of safety monitoring. Hence, this data captured approach should be carefully considered when implementing endpoint data collection in future pragmatic trials.

Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.

This study evaluated the association of time in range (TIR) of 70-180 mg/dL (3.9-10 mmol/L) with the development or progression of retinopathy and development of microalbuminuria using the Diabetes Control and Complications Trial (DCCT) data set in order to validate the use of TIR as an outcome measure for clinical trials. In the DCCT, blood glucose concentrations were measured at a central laboratory from seven fingerstick samples (seven-point testing: pre- and 90-min postmeals and at bedtime) collected during 1 day every 3 months. Retinopathy progression was assessed every 6 months and urinary microalbuminuria development every 12 months. Proportional hazards models were used to assess the association of TIR and other glycemic metrics, computed from the seven-point fingerstick data, with the rate of development of microvascular complications. Mean TIR of seven-point profiles for the 1,440 participants was 41 ± 16%. The hazard rate of development of retinopathy progression was increased by 64% (95% CI 51-78), and development of the microalbuminuria outcome was increased by 40% (95% CI 25-56), for each 10 percentage points lower TIR (P < 0.001 for each). Results were similar for mean glucose and hyperglycemia metrics. Based on these results, a compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials. Although hemoglobin A1c remains a valuable outcome metric in clinical trials, TIR and other glycemic metrics-especially when measured with continuous glucose monitoring-add value as outcome measures in many studies.

Continuous Glucose Monitoring (CGM) Provides Enhanced Sensitivity Compared with Self-Monitored Blood Glucose (SMBG) for Detecting Hypoglycemia during T2D Clinical Trials

Documenting hypoglycemia during clinical trials relies primarily on SMBG ≤ 70 mg/dL (3.9 mmol/L) with or without symptoms; however, hypoglycemia unawareness, sleep, and prandial-based sampling might lead to underestimation and lower detection of treatment differences. To quantify sensitivity and detection rates using CGM vs. SMBG, we analyzed hypoglycemia (Hypo: glucose ≤ 70 mg/dL) data from 73,941 SMBG samples collected simultaneously with masked CGM (iPro®2) during four 6-day CGM sessions (10,830 person-days) in 682 T2D patients participating in three 20-26 week trials testing insulin regimens [glargine with/without metformin, lispro, and peglispro (n = 539)] and triple oral combination therapy (n = 143). For SMBG vs. CGM, total Hypo events were 864 (n = 296 patients) vs. 2,935 (n = 494) at any time of day (daily), and 1(n = 61) vs. 1,209 (n = 383) nocturnally 12:01-6:00 AM. Poisson regression of Hypos and exposure time, with study regimen, time of day and monitoring method as independent variables, indicated CGM nocturnal Hypo risk [IRR (SE), 95% CI] was higher than CGM daily Hypo risk [1.665 (0.057), 1.558 to 1.781]. However, SMBG detected only 29.4% of CGM daily Hypos [0.294 (0.011), 0.273 to 0.318]. The interaction term indicated that the SMBG nocturnal detection bias resulted in 70% fewer Hypo events [0.303 (0.033), 0.246 to 0.375] than CGM, thereby detecting only 8.9% of those detected by CGM [0.089 (0.009), 0.073 to 0.109]. CGM also detected higher Hypo risk for insulin and metformin compared to triple oral combination therapy [daily = 1.16 (0.085), 1.007 to 1.340, p = 0.04; nocturnal = 1.247 (0.131), 1.015 to 1.531, p = 0.04] when A1C levels were comparable. SMBG did not detect these differences (p = 0.09 and p = 0.94). Using CGM vs. SMBG to detect hypoglycemia can improve comparative safety and risk-benefit assessments during diabetes clinical trials by providing greater sensitivity and representative 24-hour sampling. Disclosure M.A. Testa: Stock/Shareholder; Spouse/Partner; GI Windows, Inc.. Stock/Shareholder; Self; Phase V Technologies, Inc.. S. Saldivar-Salazar: None. M. Su: None. J.F. Hayes: None. D.C. Simonson: Advisory Panel; Self; GI Windows, Inc.. Stock/Shareholder; Self; GI Windows, Inc.. Stock/Shareholder; Spouse/Partner; Phase V Technologies, Inc.

Semaglutide: Review and Place in Therapy for Adults With Type 2 Diabetes.

Guidelines increasingly highlight the importance of multifactorial management in type 2 diabetes, in contrast to the more traditional focus on glycemic control. Semaglutide, a recently approved glucagon-like peptide-1 receptor agonist, is indicated in Canada for adults with type 2 diabetes to improve glycemic control as monotherapy with diet and exercise when metformin is inappropriate or as an add-on to either metformin alone or metformin plus a sulfonylurea or basal insulin. The Semaglutide Unabated Sustainability in Treatment of Type 2 Diabetes (SUSTAIN) clinical trial program for semaglutide comprises 6 pivotal global phase 3a trials (SUSTAIN 1 through 6) and 2 Japanese phase 3a trials. Phase 3b trials include SUSTAIN 7, and SUSTAIN 8 and 9 (both ongoing). Results from the completed trials support the superiority of semaglutide for reduction of glycated hemoglobin levels and weight loss vs. placebo as well as active comparators, including sitagliptin, exenatide extended-release, dulaglutide and insulin glargine. SUSTAIN 6 trial data confirmed cardiovascular safety and demonstrated significant reductions in major cardiovascular events with semaglutide vs. placebo, an outcome that confirmed the noninferiority of semaglutide. The robust and sustained effects of semaglutide on glycated hemoglobin levels and weight loss vs. comparators, as well as its safety and possible cardiovascular benefit, address an unmet need in the treatment of type 2 diabetes. This article overviews data from across the semaglutide clinical trial program, including efficacy and safety results and findings from post hoc analyses. The potential place of semaglutide in clinical practice is discussed.

How Should We Assess Glycemic Variability in Type 1 Diabetes? Contribution of Principal Component Analysis for Interstitial Glucose Indices in 142 Children.

Glycemic variability (GV) can be used to assess glycemic control in diabetes, but there is no clear consensus concerning the methods to use for its assessment. Methodological differences have resulted in differences in the outcome of GV metrics used in research studies, controversies over clinical impact, and an absence of integration into routine care. To identify the indicators of GV most meaningful for clinicians, patients, and clinical researchers. Continuous glucose monitoring data were collected during the first 3 months of a pediatric diabetes clinical trial (Start-In!; n = 142). We used principal component analysis (PCA) to analyze weekly averages for 22 parameters relating to GV. PCA identified five groups of parameters and three components explaining 85.7% of the variance. These components represented the amplitude, direction (hypoglycemia vs. hyperglycemia), and timing (within-day vs. between-days) of glucose excursions. This study provides elements that could make GV parameters more useful in clinical practice and research. No single parameter was sufficient to represent the complexity of GV, but it was possible to restrict the number of indicators required. The five groups of parameters identified by PCA could facilitate the choice of the most relevant outcomes for GV analysis in pediatric diabetes according to the purpose of the analysis (e.g., exploration of GV associated with hypo- or hyperglycemia, with short- or long-term periodicity, or GV in its entirety).

Genetic Variants in CPA6 and PRPF31 Are Associated With Variation in Response to Metformin in Individuals With Type 2 Diabetes.

Metformin is the first-line treatment for type 2 diabetes (T2D). Although widely prescribed, the glucose-lowering mechanism for metformin is incompletely understood. Here, we used a genome-wide association approach in a diverse group of individuals with T2D from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial to identify common and rare variants associated with HbA1c response to metformin treatment and followed up these findings in four replication cohorts. Common variants in PRPF31 and CPA6 were associated with worse and better metformin response, respectively (P < 5 × 10-6), and meta-analysis in independent cohorts displayed similar associations with metformin response (P = 1.2 × 10-8 and P = 0.005, respectively). Previous studies have shown that PRPF31(+/-) knockout mice have increased total body fat (P = 1.78 × 10-6) and increased fasted circulating glucose (P = 5.73 × 10-6). Furthermore, rare variants in STAT3 associated with worse metformin response (q <0.1). STAT3 is a ubiquitously expressed pleiotropic transcriptional activator that participates in the regulation of metabolism and feeding behavior. Here, we provide novel evidence for associations of common and rare variants in PRPF31, CPA6, and STAT3 with metformin response that may provide insight into mechanisms important for metformin efficacy in T2D.

Endogenous factors and mechanisms of renoprotection and renal repair.

An imbalance between renal damaging molecules and nephroprotective factors contributes to the development and progression of kidney diseases. Molecules with renoprotective properties might serve as biomarkers, drug targets as well as therapeutic options themselves. For this review, we generated a set of renoprotective factors based on GeneRIF (Gene Reference Into Function) information available at NCBI's PubMed. The final set of manually curated renoprotective factors was investigated with respect to tissue-specific expression, subcellular location distribution and involvement in biological processes using information from gene ontology as well as information from protein-protein interaction databases. We furthermore investigated the factors in the context of clinical trials of renal disease and diabetes. One hundred and ninety-three factors could be retrieved from the set of GeneRIFs on nephroprotection and renal repair. A large number of factors were either secretory molecules or plasma membrane receptors. Next to the elevated expression in renal tissue, also higher expression in connective tissue and pancreas was observed. The proteins could be assigned to the broad functional categories of cell proliferation and signalling, inflammatory response, apoptosis, blood pressure regulation as well as cellular response to different kinds of insults such as hypoxia, heat or mechanical stimulus. Eight factors are studied in clinical trials with additional ones being targeted by compounds. We have generated a set of renoprotective factors based on the literature information, which was functionally annotated and evaluated with respect to tested compounds in kidney disease and diabetes clinical trials.