Non-insulin Diabetes Research Articles

Telepharmacy and Quality of Medication Use in Rural Areas, 2013-2019.

IntroductionPharmacy closures in rural areas is an increasingly common problem. Closures disrupt medication access and decrease adherence to prescription medications. Telepharmacy is a potential solution to this problem; however, research on the relationship between telepharmacy and the quality of medication use is scarce. Our study sought to address this gap by comparing the quality of telepharmacies serving rural areas and traditional pharmacies that support them.MethodsWe obtained dispensing data for the first 18 months of operation from 3 telepharmacies and 3 traditional pharmacies located in the upper Midwest. We evaluated adherence for noninsulin diabetes medications, renin-angiotensin system antagonists, and statins, as well as inappropriate use of high-risk medications in older adults and statin use in persons with diabetes. All metrics were calculated using Medicare Part D specifications. We estimated the differences between telepharmacies serving rural areas and traditional pharmacies using generalized linear regression. We adjusted our models for potential sociodemographic and clinical confounders.ResultsA total of 2,832 patients contributed 4,402 observations to the quality measures. After covariate adjustment, we observed no significant differences between telepharmacies and traditional pharmacies for noninsulin diabetes medications, renin-angiotensin system antagonists, statins, and high-risk medications. However, statin use in persons with diabetes was higher in telepharmacies than traditional pharmacies.ConclusionWe found that the quality of medication use at telepharmacies that serve rural areas was no worse than at traditional pharmacies. For communities considering the adoption of telepharmacy, results indicate that telepharmacies provide a suitable solution for expanding medication access and that using telepharmacy would not negatively affect the quality of medication use.

Patient outcomes from implementing an enhanced services pharmacy network

ObjectiveTo evaluate the effect of implementing a network of community pharmacies on medication adherence, health service utilization, and health care spending. DesignQuasi-experimental difference-in-difference analysis with a nonequivalent control group. Setting and participantsEligible Medicaid-enrolled patients in North Carolina were attributed to intervention pharmacies between March 2015 and December 2016. A control group was propensity score-matched. Interventions consisted of enhanced services and a more intensive, comprehensive initial pharmacy assessment (CIPA). Outcome measuresOutcomes included hospitalizations; emergency department (ED) visits; health care spending for total medical, inpatient, outpatient, and ED services; and adherence to renin-angiotensin system antagonists (RASA), statins, noninsulin diabetes medications (NIDM), and multiple medications for chronic conditions (MMCC). ResultsThere were 31,509 patients who met eligibility criteria and were attributed to a participating pharmacy. Of these, 3897 received a CIPA. Before matching, patients attributed to participating pharmacies had greater Medicaid enrollment through aged, blind, or disabled status (49.2% vs. 31.5%, P < 0.001); greater case management (10.3% vs. 7%, P < 0.001); and worse rates of chronic disease (P < 0.001). Successful matching removed these differences. Adherence to RASA medications and MMCC increased by 9.5% and 10.3% (P < 0.05), respectively. Adherence did not change for statins and NIDM. The analysis also revealed a slower decline in average total medical spending of 5.7% (P < 0.01) relative to the control group over the same period, owed to a 9.6% (P < 0.001) slower decline in outpatient spending. ED utilization also decreased more slowly relative to controls by 4.8% (P < 0.05) following the intervention. ConclusionThe pharmacy intervention resulted in a statistically significant improvement in medication adherence to RASA and multiple chronic medications, but did not change or may have worsened utilization and spending outcomes. More research is needed to explore patient selection and variation in implementation and heterogeneity of treatment effects when evaluating pharmacy interventions.

1512-P: Severe Hypoglycemia and Hyperglycemia among U.S. Adults with Diabetes and ESRD on Dialysis, 2010-2015

Glycemic management in patients with diabetes and end-stage renal disease (ESRD) is challenging. There is limited evidence about the incidence of severe hypoglycemia and hyperglycemia in this population. Here, we examine rates of emergency department visits and hospitalizations for severe hypoglycemia and hyperglycemia (ascertained using validated ICD-9/10 codes) in a national cohort of adults with diabetes and incident ESRD, included in the United States Renal Data System, between 2010-2015. We then examine risk factors for these events using logistic regression. Among 678,376 patients with ESRD, 59.5% (n=403,490) had diabetes (63.6±13.0 years, 56.4% male, 26.8% Black, and 18.0% Hispanic). Rates of severe hypoglycemia and hyperglycemia were 126.2 and 35.5 per 1000 person-years, respectively. Strongest risk factors for hypoglycemia were insulin therapy (OR 4.5 [95% CI, 4.4-4.6] vs. no medications) and non-insulin diabetes medications (OR 3.7 [3.6-3.8]); Black race (OR 1.3 [1.3-1.4] vs. Caucasian); older age: 65-74 years (OR 1.2 [1.1-1.3] and ≥75 years OR 1.1 [1.1-1.1] vs. 18-44 years); and history of amputation (OR 1.4 [1.4-1.5]) or retinopathy (OR 1.2 [1.2-1.3]). Strongest risk factors for hyperglycemia were insulin (OR 7.7 [7.4-8.2]) and non-insulin diabetes medication use (OR 2.8 [2.6-3.1]) and retinopathy (OR 1.5 [1.4-1.5]). Older age was protective for hyperglycemia (OR 0.1 [0.1-0.1] for age ≥75 and 0.2 [0.2-0.2] for age 65-74 vs. 18-44 years). Patients on peritoneal dialysis had a lower risk (OR 0.8 [0.8-0.9]) of hypoglycemia, but no difference in odds of hyperglycemia, compared to patients on hemodialysis. Hypoglycemia requiring ED/hospital care was 3.6-fold more prevalent than severe hyperglycemia, greatly exceeding rates previously reported for older adults and those with non-end stage chronic kidney disease. There is a critical need for proactive interventions to reduce hypoglycemia and related ED/hospital use in this high-risk population. Disclosure R.J. Galindo: Advisory Panel; Self; Lilly Diabetes. Consultant; Self; Valeritas, Inc. Research Support; Self; Novo Nordisk Inc. Other Relationship; Self; UpToDate. M.K. Ali: Research Support; Self; Merck &amp; Co., Inc. N. Shah: None. S. Funni: None. G.E. Umpierrez: None. R.G. McCoy: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024)

Predictors and consequences of declining insulin therapy by individuals with type 2 diabetes.

To determine the relationship between decline of insulin therapy by individuals with type 2 diabetes and subsequent blood glucose control. We retrospectively studied adults with type 2 diabetes and suboptimal (HbA1c ≥ 53 mmol/mol [7.0%]) glycaemic control followed at two academic hospitals between 2000 and 2014 who were recommended insulin therapy. Decline of insulin therapy recommendations was identified using natural language processing of provider notes. Time to HbA1c < 53 mmol/mol (7.0%) served as the primary outcome. Of 5307 study participants, 2267 (42.7%) declined insulin therapy. Median time to HbA1c control in individuals who declined vs. started insulin therapy was 50 vs. 38 months, respectively (P < 0.001). In multivariable analysis, decline of insulin therapy was associated with hazard ratio for HbA1c control of 0.89 (95% CI 0.82 to 0.97; P = 0.008). Participants were more likely to accept insulin therapy recommendations if they had diabetes complications (OR 1.32; 95% CI 1.13 to 1.53; P < 0.001) or a higher HbA1c (OR 1.10; 95% CI 1.07 to 1.13; P < 0.001), and less likely if they were older (OR 0.81; 95% CI 0.76 to 0.86; P < 0.001) or were taking more non-insulin diabetes medications (OR 0.78; 95% CI 0.74 to 0.83; P < 0.001). Individuals with uncontrolled type 2 diabetes who declined insulin therapy subsequently had worse glycaemic control. These findings highlight the need to improve our understanding of the relationship of this common but poorly explored clinical phenomenon to blood glucose control and ultimately diabetes complications.

Primary Care Provider Encounter Cadence and HbA1c Control in Older Patients With Diabetes

Primary care provider encounters are associated with health and well-being; however, limited evidence guides optimal primary care provider rate of visit, referred to as encounter cadence. This study measures associations between primary care provider encounter cadence and diabetes outcomes among individuals newly diagnosed with type 2 diabetes mellitus. In this retrospective cohort study, 7,106 people enrolled in Medicare Advantage and newly diagnosed with type 2 diabetes mellitus between July 1, 2012 and June 30, 2013 were identified and followed for 36 months. Two methods measured primary care provider encounter cadence: total primary care provider encounters (frequency) and quarters with primary care provider encounter (regularity). Logistic regression measured relationships between primary care provider encounter cadence and non-insulin diabetes medication adherence, HbA1c control, emergency department visits, and inpatient admissions. Non-insulin diabetes medication adherence was defined according to the National Committee for Quality Assurance, Healthcare Effectiveness Data and Information Set specifications and measured using healthcare claims data. Post-hoc models examined adherence and diabetes control among those nonadherent (n=5,212) and with noncontrolled HbA1c (n=326) during the encounter/cadence period. Data were extracted and analyzed in 2017. Adjusted models indicated that both frequency (AOR=1.08, 95% CI=1.06, 1.10) and regularity (AOR=1.18, 95% CI=1.13, 1.22) of primary care provider encounters were associated with increased odds of adherence. Post-hoc analyses indicated that more frequent (AOR=1.12, 95% CI=1.10, 1.15) and regular (AOR=1.27, 95% CI=1.22, 1.33) primary care provider encounters were associated significantly with adherence and were associated directionally with HbA1c control. More frequent and regular primary care provider encounters are associated with an increased likelihood of non-insulin diabetes medication adherence. These findings contribute to data needed to establish evidence-based guidelines for primary care provider encounter cadence for those newly diagnosed with type 2 diabetes mellitus.

Predictors of glycemic control after decline of insulin therapy by patients with type 2 diabetes

AimDecline of insulin therapy by patients is common but poorly investigated. We conducted this study to determine patient and treatment characteristics predictive of glycemic control after declining clinician recommendation to initiate insulin therapy. MethodsWe retrospectively studied adults with type 2 diabetes mellitus treated at two academic medical centers between 1993 and 2014 who declined their healthcare provider recommendation to initiate insulin. ResultsIn a multivariable analysis of 300 study patients adjusted for demographics, comorbidities and clustering within providers, higher baseline HbA1c (OR 1.85; 95% CI 1.40 to 2.39; p < 0.001) and lifestyle changes (OR 8.39; 95% CI 3.26 to 21.55; p < 0.001) were associated with greater, while non-adherence to diabetes medications (OR 0.014; 95% CI 0.0025 to 0.085; p < 0.001) and discontinuation of a non-insulin diabetes medication (OR 0.30; 95% CI 0.11 to 0.80; p = 0.016) were associated with lower probability of HbA1c decrease after declining insulin therapy. ConclusionWe identified patient characteristics and treatment strategies associated with success and failure of glycemic control after insulin therapy decline by the patient. This information can assist in selection of optimal therapeutic approaches for these individuals.

Measuring Adherence: A Proof of Concept Study for Multiple Medications for Chronic Conditions in Alternative Payment Models.

Adherence to renin angiotensin system antagonists (RASA), non-insulin diabetes medications (NIDM) and statins has been included in the Medicare Star Ratings program since 2012. The long-term use of these measures emphasizes adherence to a limited number of chronic medications and may present opportunities for Part D plan sponsors to misuse the measures to influence their Medicare Part D Star Rating. It also does not capture the adherence needs of high-risk patients with multiple chronic conditions. The objective of this study was to describe the development of a new measure to capture adherence to multiple medications for chronic conditions (MMCC). The MMCC measure captures adherence to 71 different therapeutic categories of medication and was constructed using North Carolina Medicaid prescription claims data from 2015 to 2017. This measure was validated against the existing RASA, NIDM and statin adherence measures. This new measure was highly correlated with Star Rating measures, captured a greater number of eligible patients than these existing measures and had a lower proportion of patients meet the adherence threshold than the existing Star Ratings adherence measures. There is an opportunity to develop new measures, which include adherence to multiple medications in populations with multiple chronic conditions.

1243-P: Novel Use of Natural Language Processing to Identify Reasons for Insulin Discontinuation in Patients with T2DM: A Real-World Evidence Study

Insulin is an important part of treatment of type 2 diabetes mellitus (T2DM). Nevertheless, reasons for discontinuation of insulin therapy are poorly understood. We conducted a real-world-evidence analysis of EMR data at Partners HealthCare to study adults with T2DM who were prescribed insulin between 2010 and 2016. Reasons for insulin discontinuation were identified from a combination of structured EMR data and natural language processing analysis of EMR notes using a validated tool (sensitivity 76.9% and positive predictive value 89.7%). The mean age of study patients was 60.2 years; 52.7% were male. Among 7,009 study patients, 2,957 (42.2%) discontinued insulin within 12 months after study start. In multivariable logistic regression analysis adjusted for demographics and comorbidities, patients were more likely to discontinue either basal or bolus insulin if they were on a basal-bolus regimen compared to basal only (OR 1.56, 95% CI 1.33 to 1.83; p &amp;lt; 0.001) or if they were being seen by an endocrinologist (OR 2.58; 95% CI 2.22 to 2.99; p &amp;lt; 0.001). Most patients (2,121/71.7%) had one or more reasons for discontinuation documented. The most common reasons were improving blood glucose (BG) control (33.2%), weight loss (likely ultimately also leading to lower BG) (18.5%) and initiation of non-insulin diabetes medications (16.7%). In multivariable analysis, patients were more likely to stop insulin due to achievement of good BG control if they were treated by an endocrinologist (OR 2.52; 95% CI 2.11 to 3.00; p &amp;lt; 0.001) or by a female physician (OR 1.43; 95% CI 1.26 to 1.63; p &amp;lt; 0.001). This study represents a successful attempt to use natural language processing to understand reasons for insulin discontinuation. Insulin discontinuation is common, and particularly so for patients on a basal-bolus regimen. Achievement of glycemic control, weight loss and initiation of other diabetes medications were the most common reasons for insulin discontinuation. Disclosure J. Wu: None. F.J. Morrison: None. Z. Zhao: Employee; Self; Lilly Diabetes. X. He: Employee; Self; Eli Lilly and Company. M. Shubina: None. S. Malmasi: None. W. Ge: None. X. Peng: None. A. Turchin: Advisory Panel; Self; Monarch Medical Technologies. Research Support; Self; Eli Lilly and Company. Stock/Shareholder; Self; Brio Systems. Funding Eli Lilly and Company

2376-PUB: Glycemic Control after Decline of Insulin Therapy by Patients

Recent evidence shows that many patients with type 2 diabetes (T2DM) initially decline insulin treatment. For some patients this could lead to poor glycemic control, whereas others may be able to lower blood glucose by alternative means. However, it is not currently known what factors affect achievement of glycemic control after decline of insulin therapy by patients. We conducted a retrospective cohort study to determine patient characteristics predictive of glycemic control after they decline insulin treatment. We studied adults with T2DM treated at two academic medical centers between 1993 and 2014 who rejected insulin therapy recommended by their providers. We compared 150 randomly selected patients whose A1c subsequently decreased to 150 patients whose A1c increased or stayed the same. Patients whose A1c decreased had a significantly higher baseline A1c (9.5% vs. 8.5%; p &amp;lt; .001), were more likely to implement lifestyle changes (27.3% vs. 7.3%; p &amp;lt; .001) and less likely to be non-adherent to diabetes medications (1.3% vs. 26.7%; p &amp;lt; .001) or to discontinue a non-insulin diabetes medication (8.0% vs. 16.0%; p = 0.03) after they declined insulin therapy. In a multivariable analysis adjusted for demographics, comorbidities and clustering within providers, higher baseline A1c (OR 1.85; 95% CI 1.41 to 2.42; p &amp;lt;.001) and lifestyle changes (OR 8.49; 95% CI 3.31 to 21.78; p &amp;lt;0.001) were associated with greater, while non-adherence to diabetes medications (OR 0.015; 95% CI 0.0025 to 0.088; p &amp;lt;.001) and discontinuation of a non-insulin diabetes medication (OR 0.30; 95% CI 0.12 to 0.78; p =0.013) were associated with lower probability of A1c decrease after initial decline of insulin therapy by the patient. We identified patient characteristics and treatment strategies associated with success and failure of glycemic control after insulin therapy decline by the patient. This information can help guide care and assist in design of rigorous interventional studies to evaluate optimal therapeutic approaches for these individuals. Disclosure L. Florez: None. A. Turchin: Advisory Panel; Self; Monarch Medical Technologies. Research Support; Self; Eli Lilly and Company. Stock/Shareholder; Self; Brio Systems.

21-OR: Final Results of a Phase 2, Randomized, Double-Blind, Placebo-Controlled Clinical Trial of the MetAP2 Inhibitor ZGN-1061 in Patients with Type 2 Diabetes

ZGN-1061 is a second-generation methionine aminopeptidase 2 (MetAP2) inhibitor in development for treatment of T2D. This clinical trial evaluated ZGN-1061 (0.05, 0.3, 0.9, or 1.8 mg) vs. placebo (PBO) administered SC every 3 days for 12 weeks on change from baseline in A1C in individuals with T2D at multiple sites in Australia/New Zealand. Stable noninsulin diabetes therapy was permitted. Baseline (ITT population N=175): 52% female, 77% white, (mean±SD) age 54±8 y, A1C 8.6±1.1%, BMI 37±7 kg/m2, T2D duration 8±6 y. Interim analysis results (0.05, 0.3, 0.9 mg ZGN-1061) were presented previously. Here, we report additional results with 0.9 and 1.8 mg ZGN-1061. The LS mean±SE A1C change for PBO was 0.2±0.1% (N=42) vs. -0.4±0.1% (N=44) and -0.9±0.2% (N=23) for 0.9 and 1.8 mg ZGN-1061, respectively. The LS mean±SE difference vs. PBO was -0.6±0.2% and 1.1±0.2% for 0.9 mg (p=0.0003) and 1.8 mg (p&amp;lt;0.0001). The LS mean±SE weight change for PBO was -0.6±0.3 kg vs. -1.4±0.3 kg (p=ns) and -2.8±0.5 kg (p&amp;lt;0.001) for 0.9 and 1.8 mg ZGN-1061. Dose-dependent fasting and postprandial glucose reductions were observed for ZGN-1061 (p&amp;lt;0.05 vs. PBO); β-cell function and insulin sensitivity were improved with 1.8 mg ZGN-1061 (p&amp;lt;0.05 vs. PBO). ZGN-1061 also improved triglycerides, hsCRP, adiponectin, and leptin (p&amp;lt;0.05 vs. PBO). Across all ZGN-1061 treatment groups, adverse events (AEs) were primarily mild/moderate without any notable trends. The completion rate was 93% (163/175). Three subjects in ZGN-1061 groups withdrew due to AEs (sensory disturbance, 0.05 mg; upper abdominal pain, 0.9 mg; injection site urticaria, 1.8 mg). There were no reports of venous thrombosis or changes in thrombosis markers indicative of a thrombosis event. ZGN-1061 (1.8 mg) demonstrated statistically significant and clinically meaningful efficacy; the largest reductions in A1C and weight were observed at 12 weeks with no evidence of a waning effect and no notable safety signals. Disclosure T. Kim: Employee; Spouse/Partner; Celgene Corporation. Employee; Self; Zafgen, Inc. D. Zhuang: Employee; Self; Zafgen, Inc. T.L. Haugen: Employee; Self; Zafgen, Inc. D.D. Kim: Employee; Self; Zafgen, Inc. K. Taylor: Employee; Self; Zafgen, Inc.

Impact of medication synchronization programs on proportion of days covered (PDC) scores and Medicare Part D medication-related adherence metrics

ObjectivesThis study aimed to determine if patients enrolled in a medication synchronization program have improvements in proportion of days covered (PDC) score for 3 of the Centers for Medicare and Medicaid Services adherence metrics medication classes: statins, renin-angiotensin-aldosterone system antagonists, and noninsulin diabetes medications. MethodsThis retrospective cohort study used data from members of a Medicare Advantage Prescription Drug plan, who took at least 1 of the key metric medications and had sufficient data to calculate a PDC score. The exposed cohort (“sync”) consisted of patients who enrolled in the medication synchronization program within the plan’s preferred pharmacy network, and the control group consisted of those who did not enroll in the program but met all other criteria. The primary end point was the change in PDC score from 2015 (baseline) to 2017 for each medication class. Secondary end points included the proportion of members with PDC scores of at least 85% and the association of adherence with annual medical and pharmacy costs. ResultsThe largest PDC score increases for the entire study population were seen in all 3 sync groups (RASA, diabetes, and statin) with corresponding statistically significant PDC score increases of 1.6%, 4.8%, and 2.9%, compared with −0.4%, 0.5%, and 1.3% changes in the control groups. In the multiple linear regression analysis, there were significant PDC score differences in the changes from baseline between the sync and control RASA, diabetes, and statin groups (P = 0.005, P = 0.01, and P < 0.001, respectively). The proportion of members achieving the acceptable PDC score threshold increased by 1.1% in the control group and by 4.1% in the sync group. ConclusionIn a population of patients with high baseline adherence, this medication synchronization program was associated with a statistically significant increase in adherence scores for statin, RASA, and noninsulin diabetes medications. There was no significant change in medical or pharmacy costs from the health plan perspective.

Prescribing of diabetes medications to people with type 2 diabetes and chronic kidney disease: a national cross-sectional study

BackgroundPrevious studies in general practice and hospital settings have identified that prescribing of non-insulin diabetes medications may be sub-optimal in people with type 2 diabetes (T2D) and renal impairment. Since these publications, a number of new medications have become available for the management of T2D. Study aims were to, in a cohort of Australians with T2D and renal impairment attending general practice, (1) investigate whether the prescribing of non-insulin diabetes medications is consistent with dosing adjustments recommended within current Australian Diabetes Society (ADS) guidelines; and (2) identify patient socio-demographic and clinical factors associated with at least one prescription of a non-insulin diabetes medication inconsistent with current ADS guidelines for medication doses.MethodsCross-sectional study using data from the MedicineInsight general practice database managed by NPS MedicineWise. Patients with T2D who were aged 18 years and over, with an average eGFR< 60 ml/min/1.73m2 and at least one prescription of a non-insulin diabetes medication between 1st January 2015 and 30th June 2017 were included. Descriptive statistics were used to summarise patient characteristics and medication use. Marginal logistic regression models were used to estimate associations between sociodemographic and clinical factors and prescribing of ≥1non-insulin diabetes medicine not consistent with ADS guidelines.ResultsThe majority of the 3505 patients included (90.4%) had an average eGFR of 30-59 ml/min/1.73m2. In terms of absolute numbers, metformin was the medication most frequently prescribed at a dose not consistent with current ADS guidelines for dosing in renal impairment (n = 1601 patients), followed by DPP4 inhibitors (n = 611) and sulphonylureas (n = 278). The drug classes with the highest proportion of prescriptions with dosage not consistent with ADS guidelines were SGLT2 inhibitors (83%), followed by biguanides (58%) and DPP4 inhibitors (46%). Higher HbA1c, longer known diabetes duration and diagnosis of retinopathy were associated with receiving ≥1prescription with a dosage not consistent with guidelines.ConclusionsPrescribing of non-insulin diabetes medications at doses inconsistent with current ADS guideline recommendations for dosing adjustments for people with renal impairment was common. Further research is needed to understand how general practitioners access, interpret and apply the ADS guidelines and the impact this may have on patient outcomes.

Use of non-insulin diabetes medicines after insulin initiation: A retrospective cohort study.

BackgroundClinical guidelines recommend that metformin be continued after insulin is initiated among patients with type 2 diabetes, yet little is known regarding how often metformin or other non-insulin diabetes medications are continued in this setting.MethodsWe conducted a retrospective cohort study to characterize rates and use patterns of six classes of non-insulin diabetes medications: biguanides (metformin), sulfonylureas, thiazolidinediones (TZDs), glucagon-like peptide 1 receptor agonists (GLP1 receptor agonists), dipeptidyl peptidase 4 inhibitors (DPP4 inhibitors), and sodium-glucose co-transporter inhibitors (SGLT2 inhibitors), among patients with type 2 diabetes initiating insulin. We used the 2010–2015 MarketScan Commercial Claims and Encounters data examining 72,971 patients with type 2 diabetes aged 18–65 years old who initiated insulin and had filled a prescription for a non-insulin diabetes medication in the 90 days prior to insulin initiation. Our primary outcome was the proportion of patients refilling the various non-insulin diabetes medications during the first 90 days after insulin initiation. We also used time-to-event analysis to characterize the time to discontinuation of specific medication classes.ResultsMetformin was the most common non-insulin medication used prior to insulin initiation (N = 53,017, 72.7%), followed by sulfonylureas (N = 25,439, 34.9%) and DPP4 inhibitors (N = 8,540, 11.7%). More than four out of five patients (N = 65,902, 84.7%) refilled prescriptions for any non-insulin diabetes medications within 90 days after insulin initiation. Within that period, metformin remained the most common medication with the highest continuation rate of 84.6%, followed by SGLT2 inhibitors (81.9%) and TZDs (79.3%). Sulfonylureas were the least likely medications to be continued (73.6% continuation) though they remained the second most common medication class used after insulin initiation. The median time to discontinuation varied by therapeutic class from the longest time to discontinuation of 26.4 months among metformin users to the shortest (3.0 months) among SGLT2 inhibitor users.ConclusionWhile metformin was commonly continued among commercially insured adults starting insulin, rates of continuation of other non-insulin diabetes medications were also high. Further studies are needed to determine the comparative effectiveness and safety of continuing insulin secretagogues and newer diabetes medications after insulin initiation.

Management of type 2 diabetes mellitus in the elderly population with cardiovascular diseases

Addressing the glycemic control of the elderly patients with type 2 diabetes mellitus (T2DM) requires creating an individualized plan for each patient due to the heterogeneity among this population. The personalized plan should address topics such as comorbidities, polypharmacy, and cost of medications. One of the major comorbidities that necessitate consideration is cardiovascular disease (CVD), which makes it essential for clinicians to stay updated with literature on cardiovascular safety of diabetes medications. Metformin, along with dietary changes and adequate exercise, should be the first line treatment for patients with T2DM. Glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors should be considered for add-on therapy for elderly patients with CVD whom do not reach their hemoglobin A1c goal on metformin alone. All drugs in these two categories have been shown to be safe in patients with CVD and most of them have shown to reduce adverse cardiovascular events. Sulfonylureas should be used cautiously in elderly due to their high risk of hypoglycemia. Thiazolidinediones, saxagliptin and alogliptin should be avoided in patients with heart failure. With the high rate of major adverse cardiovascular events in elderly population, it is imperative to consider cardiovascular safety and efficacy of non-insulin diabetes medications in formulating management plan for elderly patients with concurrent T2DM and CVD.

The longitudinal relationship between food insecurity in older adults with diabetes and emergency department visits, hospitalizations, hemoglobin A1c, and medication adherence

AimsTo examine the relationship between food insecurity and emergency department (ED) visits, hospitalizations, A1c, and diabetes medication adherence over one year of follow-up among individuals >65 years with diabetes mellitus. MethodsWe conducted a longitudinal cohort study of adults >65 years with diabetes who did (n = 742) or did not (n = 2226) report food insecurity at baseline. We used conditional logistic regression for the ED visits or hospitalization outcomes, and mixed effects models for A1c and non-insulin diabetes medication adherence. ResultsIn bivariate analyses, individuals with food insecurity were more likely to have an ED visit (OR = 1.40, 95% CI 1.15–1.72) or hospitalization (OR = 1.41, 95% CI 1.11–1.78) in the year after the food security assessment. In addition, A1c was higher (7.5% vs. 7.2%, p < 0.001). There was no difference in medication adherence. These differences persisted with adjustment for basic demographic and clinical characteristics, but were attenuated with further adjustment for socioeconomic status. ConclusionsDifferences in diabetes outcomes by food insecurity status were attenuated by adjustment for socioeconomic status. Adverse outcomes in individuals with diabetes and food insecurity may be driven by effects of food insecurity per se or be mediated by a constellation of basic resource needs or lower socioeconomic status.

An analysis of expenditures on primary care prescription drugs in the United States versus ten comparable countries

ObjectiveWe sought to estimate size and sources of differences in per capita expenditures on primary care medications in the US versus ten comparable countries combined: Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, and the United Kingdom. MethodsUsing market research data on year 2015 volumes and sales of medicines, we measure total per capita expenditures on six categories of primary care prescription drugs: hypertension treatments, pain medications, lipid lowing medicines, non-insulin diabetes treatments, gastrointestinal preparations, and antidepressants. We quantified the contributions of five drivers of the observed differences in per capita expenditures. ResultsWe estimated that the US spent 203% more per capita on primary care pharmaceuticals than did the ten comparable countries. Despite the difference in spending levels, on average, Americans actually purchased 12% fewer days of related therapies than residents of the comparator countries. Most of the observed difference in expenditures was due to higher transaction prices of medicines and the use of a more expensive mix of medicines in the US. ConclusionsIf utilization patterns and pharmaceutical prices in the US were similar to those in the 10 comparator countries combined, total spending on primary care pharmaceuticals would fall by 30% or more. Such evidence on the level and drivers of US pharmaceutical expenditures should inform policies in this sector.

Understanding the Relationship between Primary Care Provider (PCP) Encounter Cadence, Medication Adherence, and Diabetes Control

Introduction: Regular PCP encounters are associated with wellbeing; there is limited evidence to support the ideal PCP encounter cadence to optimize patient outcomes. The aim of this study was to measure the association between PCP encounter cadence and medication adherence and diabetes control, among those newly diagnosed with T2DM. Methods: A cohort of 7,106 persons enrolled in a Medicare Advantage health plan and newly diagnosed with T2DM between 7/1/12-6/30/13, was identified and followed for 36 months. Two methods measured PCP encounter cadence: total PCP encounters (frequency) and quarters with PCP encounter (regularity). Proportion of days covered (PDC) assessed noninsulin diabetes medication (NIDM) adherence (PDC ≥80.0%). Diabetes control was defined as A1c ≤ 8.0%. Logistic regression was used to measure the relationship between PCP encounter cadence and outcomes (NIDM adherence, diabetes control). Covariates included patient demographics, Charlson Comorbidity Index score, chronic conditions, healthcare utilization, insulin use, and prior NIDM adherence and diabetes control. Results: Overall, 5,212 and 326 people met inclusion criteria for the NIDM adherence and diabetes control analyses, respectively. Adjusted models indicated that each additional PCP encounter was associated with a 12.3% increase in the likelihood of NIDM adherence (95% CI 1.10, 1.15), and each additional quarter with a PCP encounter was associated with a 27.4% increase in the likelihood of NIDM adherence (95% CI 1.22, 1.33). PCP encounters (OR 1.06; 95% CI 1.00, 1.12) and quarters with a PCP encounter (OR 1.13; 95% CI 0.98, 1.30) were directionally associated with diabetes control. Conclusion: Our findings suggest that frequency and regularity of PCP encounters were associated with medication adherence. This study contributes to the data needed to establish evidence-based guidelines for PCP encounter cadence, for those newly diagnosed with T2DM. Disclosure S.E. Wixson: None. J. Dobbins: Employee; Self; Humana Inc. T.A. Cordier: Employee; Self; Humana Inc.. Stock/Shareholder; Self; Humana Inc.. G. Haugh: None. A. Renda: None. L.E. Happe: Employee; Self; Humana. Other Relationship; Self; Journal of Managed Care Pharmacy. A. Turchin: Research Support; Self; Sanofi-Aventis. Advisory Panel; Self; Merck Sharp &amp; Dohme Corp., Monarch Medical Technologies. Stock/Shareholder; Self; Brio Systems. Research Support; Self; Eli Lilly and Company.

Results of an Interim Analysis of a Phase 2, Randomized, Double-Blind, Placebo-Controlled Clinical Trial of ZGN-1061 in Patients with Obesity and Type 2 Diabetes

ZGN-1061 (1061) is a methionine aminopeptidase 2 (MetAP2) inhibitor being developed to improve glycemic control in type 2 diabetes. This clinical trial investigated the effect of 12 weeks of subcutaneous (SC) 1061 (0.05, 0.3, 0.9 mg or placebo) administered every 3 days on A1C, safety, and tolerability. Stable noninsulin diabetes therapy was permitted. The study included 129 patients; an interim analysis was conducted on a subset of patients at week 8. Baseline characteristics of the interim ITT population (N=57): 54% male, 77% white, (mean±SD) age 54±8 years, A1C 8.7±1.0%, BMI 37.2±6.4 kg/m2. At week 8, the LS mean±SE change in A1C for placebo was 0.2±0.1% (N=13) vs. -0.4±0.2% with 0.9 mg 1061 (N=13, LS mean±SE difference -0.6±0.2%, p&amp;lt;0.02). In patients with week 12 measurements, the change in A1C was 0.4±0.2 (N=12) vs. -0.5±0.2 (N=8, difference -0.9±0.3, p&amp;lt;0.01). There were trends for weight loss and improved fasting plasma glucose with 0.9 mg 1061 vs. placebo as well as improvements in biomarkers, including hsCRP (week 8 -2.1±2.2 mg/L vs. 1.0±2.1, ns), adiponectin (1.0±0.3 ug/mL vs. -0.1±0.3, p&amp;lt;0.05), leptin (-6.9±1.9 ng/mL vs. 2.1±1.7, p&amp;lt;0.05), FGF-21 (0.026±0.014 ng/mL vs. 0.000±0.013; ns), and postprandial glucose AUC (p&amp;lt;0.01). Improvements in efficacy measures with the lower doses of 1061 were variable. There were no serious or severe adverse events (AEs) and no subjects withdrew due to an AE. The most common AE (1061&amp;gt;placebo) was upper respiratory tract infection. The 1061 pharmacokinetic profile indicated that exposure was within target levels for efficacy and safety and there were no changes in thrombosis markers (e.g., D-dimer). In this interim analysis, 1061 produced improvements in glycemic control and metabolic biomarkers consistent with MetAP2 inhibition. 1061 was also well tolerated with no safety signals in all doses tested. Week 12 results from the full analysis dataset will be presented. Disclosure T. Kim: Employee; Self; Zafgen. D. Zhuang: Employee; Self; Zafgen. T.E. Hughes: Board Member; Self; Zafgen. Employee; Self; Zafgen. Stock/Shareholder; Self; Zafgen. D.D. Kim: Employee; Self; Zafgen. K. Taylor: Employee; Self; Zafgen.

Time trends and geographical variation in prescribing of drugs for diabetes in England from 1998 to 2017.

AimsTo measure the variation in prescribing of second‐line non‐insulin diabetes drugs.Materials and MethodsWe evaluated time trends for the period 1998 to 2016, using England's publicly available prescribing datasets, and stratified these by the order in which they were prescribed to patients using the Clinical Practice Research Datalink. We calculated the proportion of each class of diabetes drug as a percentage of the total per year. We evaluated geographical variation in prescribing using general practice‐level data for the latest 12 months (to August 2017), with aggregation to Clinical Commissioning Groups. We calculated percentiles and ranges, and plotted maps.ResultsPrescribing of therapy after metformin is changing rapidly. Dipeptidyl peptidase‐4 (DPP‐4) inhibitor use has increased markedly, with DPP‐4 inhibitors now the most common second‐line drug (43% prescriptions in 2016). The use of sodium‐glucose co‐transporter‐2 (SGLT‐2) inhibitors also increased rapidly (14% new second‐line, 27% new third‐line prescriptions in 2016). There was wide geographical variation in choice of therapies and average spend per patient. In contrast, metformin was consistently used as a first‐line treatment in accordance with guidelines.ConclusionsIn England there is extensive geographical variation in the prescribing of diabetes drugs after metformin, and increasing use of higher‐cost DPP‐4 inhibitors and SGLT‐2 inhibitors compared with low‐cost sulphonylureas. Our findings strongly support the case for comparative effectiveness trials of current diabetes drugs.

National Rates of Initiation and Intensification of Antidiabetic Therapy Among Patients With Commercial Insurance.

Prompt initiation and intensification of antidiabetic therapy can delay or prevent complications from diabetes. We sought to understand the rates of and factors associated with the initiation and intensification of antidiabetic therapy among commercially insured patients in the U.S. Using 2008-2015 commercial claims linked with laboratory and pharmacy data, we created an initiation cohort with no prior antidiabetic drug use and an HbA1c ≥8% (64 mmol/mol) and an intensification cohort of patients with an HbA1c ≥8% (64 mmol/mol) who were on a stable dose of one noninsulin diabetes drug. Using multivariable logistic regression, we determined the rates of and factors associated with initiation and intensification. In addition, we determined the percent of variation in treatment patterns explained by measurable patient factors. In the initiation cohort (n = 9,799), 63% of patients received an antidiabetic drug within 6 months of the elevated HbA1c test. In the intensification cohort (n = 10,941), 82% had their existing antidiabetic therapy intensified within 6 months of the elevated HbA1c test. Higher HbA1c levels, lower generic drug copayments, and more frequent office visits were associated with higher rates of both initiation and intensification. Better patient adherence prior to the elevated HbA1c level, existing therapy with a second-generation antidiabetic drug, and lower doses of existing therapy were also associated with intensification. Patient factors explained 7.96% of the variation in initiation and 7.35% of the variation in intensification. Approximately two-thirds of patients were newly initiated on antidiabetic therapy, and four-fifths of those already receiving antidiabetic therapy had it intensified within 6 months of an elevated HbA1c in a commercially insured population. Patient factors explain 7-8% of the variation in diabetes treatment patterns.