Longitudinal changes in glycated haemoglobin following treatment intensification after inadequate response to two oral antidiabetic agents in patients with type 2 diabetes.

AIMS: To identify change in glycated haemoglobin (HbA1c) for 1 year after treatment intensification in patients with HbA1c >53 mmol/mol (7.0%) while on two classes of oral antidiabetic drugs (OADs). MATERIAL AND METHODS: A retrospective cohort study was conducted using a regional health plan claims database for the period January 1, 2010 to March 31, 2017. Patients with type 2 diabetes (T2DM) whose treatment was intensified with insulin, a glucagon-like peptide-1 receptor agonist or a third OAD within 365 days of having HbA1c ≥53 mmol/mol (7.0%) on two OADs were included. The HbA1c trajectory for 1 year after intensification was estimated using a mixed-effects regression model. RESULTS: The analysis included 1226 patients with a mean ± SD HbA1c at treatment intensification of 74.2 ± 18.7 mmol/mol (8.93 ± 1.7%). HbA1c was higher in the insulin group (74.2 mmol/mol) than in the non-insulin group (70.6 mmol/mol), as was the HbA1c decrease (P < 0.01) over the 1-year follow-up, particularly in patients with baseline HbA1c >9%. After intensification, insulin- and non-insulin-treated patients achieved an average change by month in HbA1c of -4.7 mmol/mol and -2.6 mmol/mol points, respectively. The analysis predicted HbA1c to be the lowest at 6 to 10 months post intensification, depending on intensification treatment and HbA1c at intensification; however, on average, HbA1c remained above 64.0 mmol/mol (8.0%). CONCLUSION: In patients with T2DM, intensification following an HbA1c value ≥53 mmol/mol (7.0%) while on two OADs was associated with a significant improvement in glycaemic control. Patients intensified with insulin had a higher baseline HbA1c but greater HbA1c reduction than those intensified with a non-insulin agent. However, HbA1c remained above 64 mmol/mol (8.0%) overall. Additional opportunity exists to further intensify therapy to improve glycaemic control.

Influence of Treatment Intensification on A1c in Patients with Suboptimally Controlled Type 2 Diabetes After 2 Oral Antidiabetic Agents.

BACKGROUND: In the United States, more than 50% of patients with type 2 diabetes mellitus (T2DM) have hemoglobin A1c (A1c) levels that fail to achieve the recommended target of < 7.0%. Of these, 30%-45% have an A1c > 9.0%, the threshold for poorly controlled T2DM per National Committee for Quality Assurance (NCQA) measures. Treatment inertia is a known challenge. However, recent treatment intensification patterns and outcomes after treatment fails 2 classes of oral antidiabetic agents (OADs) are not well understood. OBJECTIVE: To characterize treatment intensification patterns and glycemic control outcomes in patients with A1c ≥ 7.0% on 2 OADs. METHODS: A retrospective cohort study was conducted in patients with T2DM from a regional health plan claims dataset augmented with A1c results between January 1, 2010, and March 31, 2017. Patients were identified with an A1c ≥ 7.0% (baseline), while on 2 OADs, and whose treatment was intensified with basal/biphasic insulin (insulin), glucagon-like peptide-1 receptor antagonist (GLP-1RA), or a third OAD within 365 days after the baseline A1c ≥ 7.0%. Patients had at least 1 A1c value 60-365 days (follow-up period) after treatment intensification. The proportion of patients with an A1c < 7.0% and < 9.0% at follow-up were identified by therapeutic intensification strategy. Odds ratios for achieving A1c < 7.0% and < 9.0% were calculated. RESULTS: 1,226 patients were included in the analysis, and 33.5% of the patients had a baseline A1c ≥ 9.0%. 24% of patients received insulin; 16% received GLP-1RA; and 60% received a third OAD for the treatment intensification. Overall, 26.0% achieved A1c < 7.0% and 76.1% of patients achieved < 9.0%, with a median follow-up of 119 days. The proportion of patients intensified with insulin who had an A1c ≥ 9.0% at follow-up was 34.6% versus 53.2% at baseline (P < 0.01). The corresponding percentages for those intensified with a GLP-1RA and OAD were 21.6% versus 27.1% (P = 0.24) and 20.1% versus 27.3% (P < 0.01). After controlling for baseline characteristics, the odds ratio (95% CI) of achieving A1c < 7.0% and < 9.0% was 2.05 (1.45-2.90) for GLP-1RA and 0.92 (0.61-1.40) for OAD. The association between goal attainment and GLP-1RA versus OAD intensification was influenced by the time to the A1c follow-up and baseline A1c. CONCLUSIONS: Treatment intensification was associated with improved glycemic control in patients after therapy failed 2 OADs. Patients with higher A1c at baseline were likely to initiate insulin, which was associated with a greater drop in A1c. GLP-1RA was associated with a higher likelihood of achieving NCQA-suggested glycemic control compared with a third OAD. However, the association varied by the follow-up period. These findings are important to health plans seeking to improve patient outcomes as reflected in high performance on NCQA diabetes quality measures by promoting effective and timely treatment intensification. DISCLOSURES: Research funding was provided by Sanofi to the Pharmacotherapy Outcomes Research Center at the University of Utah and SelectHealth to conduct this study. Thomas, Sterling, and Johnstone are employees and stock/shareholders of Sanofi. Kim, Unni, McAdam-Marx, and Brixner are employees of the Department of Pharmacotherapy at the University of Utah. Brixner also has served as an advisory board member and presenter for Sanofi. McAdam-Marx also reports grants to the Department of Pharmacotherapy, University of Utah, from AstraZeneca and Janssen, outside of the submitted work. Olsen is employed by SelectHealth. Part of the results of this study was presented at the Academy of Managed Care & Specialty Pharmacy Annual Meeting 2018 in Boston, MA, during April 23-26, 2018.

Identification of Patients with Statin Intolerance in a Managed Care Plan: A Comparison of 2 Claims-Based Algorithms.

BACKGROUND: While statins are safe and efficacious, some patients may experience statin intolerance or treatment-limiting adverse events. Identifying patients with statin intolerance may allow optimal management of cardiovascular event risk through other strategies. Recently, an administrative claims data (ACD) algorithm was developed to identify patients with statin intolerance and validated against electronic medical records. However, how this algorithm compared with perceptions of statin intolerance by integrated delivery networks remains largely unknown. OBJECTIVE: To determine the concurrent validity of an algorithm developed by a regional integrated delivery network multidisciplinary panel (MP) and a published ACD algorithm in identifying patients with statin intolerance. METHODS: The MP consisted of 3 physicians and 2 pharmacists with expertise in cardiology, internal medicine, and formulary management. The MP algorithm used pharmacy and medical claims to identify patients with statin intolerance, classifying them as having statin intolerance if they met any of the following criteria: (a) medical claim for rhabdomyolysis, (b) medical claim for muscle weakness, (c) an outpatient medical claim for creatinine kinase assay, (d) fills for ≥ 2 different statins excluding dose increases, (e) decrease in statin dose, or (f) discontinuation of a statin with a subsequent fill for a nonstatin lipid-lowering therapy. The validated ACD algorithm identified statin intolerance as absolute intolerance with rhabdomyolysis; absolute intolerance without rhabdomyolysis (i.e., other adverse events); or as dose titration intolerance. Adult patients (aged ≥ 18 years) from the integrated delivery network with at least 1 prescription fill for a statin between January 1, 2011, and December 31, 2012 (first fill defined the index date) were identified. Patients with ≥ 1 year pre- and ≥ 2 years post-index continuous enrollment and no statin prescription fills in the pre-index period were included. The MP and ACD algorithms were applied to the population, and concordance was examined using individual (i.e., sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) and overall performance measures (i.e., accuracy, Cohen's kappa coefficient, balanced accuracy, F-1 score, and phi coefficient). RESULTS: After applying the inclusion criteria, 7,490 patients were evaluated for statin intolerance. The mean (SD) age of the population was 51.1 (8.5) years, and 55.7% were male. The MP and ACD algorithms classified 11.3% and 5.4% of patients as having statin intolerance, respectively. The concordance of the MP algorithm was mixed, with negative classification of statin intolerance measures having high concordance (specificity 0.91, NPV 0.97) and positive classification of statin intolerance measures having poor concordance (sensitivity 0.45, PPV 0.21). Overall performance measures showed mixed agreement between the algorithms. CONCLUSIONS: Both algorithms used a mix of pharmacy and medical claims and may be useful for organizations interested in identifying patients with statin intolerance. By identifying patients with statin intolerance, organizations may consider a variety of options, including using nonstatin lipid-lowering therapies, to manage cardiovascular event risk in these patients. DISCLOSURES: This study was funded by Regeneron Pharmaceuticals and Sanofi US. Boklage is employed by, and owns stock in, Regeneron, and Charland is employed by Sanofi. Bellows has received fees from Avenir for advisory board membership and grants from Myriad Genetics, Biogen, Janssen, and National Institutes of Health. Brixner reports advisory board and consultancy fees and grants from Sanofi. Mitchell reports consultancy fees from Sanofi. Study concept and design were contributed by Bellows, Boklage, Charland, and Brixner. Bellows, Sainski-Nguyen, and Olsen took the lead in data collection, along with Mitchell. Data interpretation was performed by Mitchell, along with the other authors. The manuscript was written by Bellows, Sainski-Nguyen, and Olsen and revised by all the authors.

Antihyperlipidemic Medication Treatment Patterns and Statin Adherence Among Patients with ASCVD in a Managed Care Plan After Release of the 2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol.

BACKGROUND: The American College of Cardiology (ACC) and American Heart Association (AHA) released a new blood cholesterol treatment guideline in November 2013. It is unknown how the new recommendations have affected cholesterol medication use and adherence in a commercial health plan. OBJECTIVE: To evaluate the effect of the 2013 guideline release on antihyperlipidemic treatment patterns and statin adherence in patients with atherosclerotic cardiovascular disease (ASCVD) compared with a historical control group. METHODS: This study was a historical cohort analysis of adult patients (aged 21-75 years) with clinical ASCVD enrolled in a SelectHealth commercial health plan. Patients were included in the guideline implementation cohort if they had a medical claim with an ICD-9-CM diagnosis of ASCVD in the year before the November 2013 ACC/AHA guideline release. The index date was defined as the first outpatient medical claim with an ICD-9-CM for ASCVD in the first 6 months after the guideline was released. Patients were required to have continuous enrollment for ≥ 1 year before and after the index date. These same criteria were applied to patients exactly 4 years earlier to identify a historical control group. Patients meeting these criteria formed the antihyperlipidemic treatment patterns cohort. Of these, patients who also had ≥1 pharmacy claim for a statin in the 1-year pre- and post-index periods were included in the statin adherence cohort. Antihyperlipidemic treatment patterns were assessed using pharmacy claims for antihyperlipidemic medications in the 1-year pre- and post-index periods. Antihyperlipidemic medication claims were classified as a nonstatin cholesterol medication, low-intensity statin, moderate-intensity statin, or high-intensity statin. To address differences in pre-index antihyperlipidemic medications between the guideline implementation and historical control groups, patients were randomly matched 1:1 based on pre-index classification in a post hoc analysis. Post-index antihyperlipidemic classifications were compared between groups using a Stuart-Maxwell test. The change in mean statin adherence (proportion of days covered [PDC]) was compared within and between groups using paired and independent t-tests, respectively. The proportion of adherent patients (PDC ≥ 0.80) in the pre- and post-index periods was compared between groups using a chi-square test. A multivariable logistic regression was used to compare the likelihood of being adherent in the post-index period while controlling for pre-index adherence and other potential confounders. RESULTS: A total of 7,818 adult members with ASCVD in the index period and 1 year before the index period were identified. Of those, 1,841 patients met the criteria to be included in the analysis, and 1,526 patients were matched on antihyperlipidemic classification and included in the antihyperlipidemic treatment patterns analysis. Baseline characteristics were similar, although the guideline implementation group was younger (58.3 vs. 60.5 years, P < 0.001), and more were male (74.8% vs. 71.3%, P = 0.106) than the historical control group. In the matched cohort, there was a significant difference in the post-index antihyperlipidemic classification (P < 0.001), which appeared to be a result of the difference in nonstatin cholesterol medications (guideline 6.9% vs. historical 13.0%) and high-intensity statins (guideline 23.7% vs. historical 16.3%). Of the 1,841 patients in the antihyperlipidemic treatment patterns cohort, 919 patients met inclusion criteria for the statin adherence analysis. Although PDC decreased over time in both groups, significantly more patients in the guideline implementation group were adherent in the post-index period than the historical control group (66.5% vs. 57.3%, respectively; P = 0.005). Additionally, patients in the guideline implementation group were more likely than the historical control to be adherent in the post-index period when adjusting for potential confounders (OR = 1.49, 95% CI = 1.10-2.03; P = 0.011). CONCLUSIONS: Since the release of the updated ACC/AHA treatment guideline, more commercial health plan patients with ASCVD used high-intensity statins and fewer used nonstatin cholesterol medications than historical controls. Additionally, since the guideline release, more patients are adherent to statin therapy than historical controls. This study provides managed care organizations with valuable information regarding the effect of the 2013 ACC/AHA guideline. DISCLOSURES: No outside funding or services were received for this work. Outside of the current study, Bellows has received research funding from Biogen Idec, Regeneron Pharmaceuticals, Myriad Genetic Laboratories, Shire Development, and Bristol-Myers Squibb and an honorariam from Avanir Pharmaceuticals. Voelker received summer intern support from Pfizer and the AMCP Foundation during the time of this study. The remaining authors have nothing to disclose. All authors contributed to study concept and design and to the revision of the manuscript. Bellows, Olsen, and Voelker collected the data, assisted by Wander; data interpretation was performed primarily by Bellows, along with Olsen and Voelker and assisted by Wander. The manuscript was primarily written by Bellows, along with the other authors.