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Supplements Real-World Evidence in Type 2 Diabetes: Focus on SGLT2 inhibitors and GLP-1 Receptor Agonists
A Retrospective Real-World Study of Dapagliflozin Versus Other Oral Antidiabetic Drugs Added to Metformin in Patients with Type 2 Diabetes
Huan Huang, PhD; Kelly F. Bell, PharmD, MSPhr; Ray Gani, PhD; Cathy W. Tugwell, RN, BSN; James M. Eudicone, MS, MBA; and Michelle R. Krukas-Hampel, MA
Eligibility Varies Among the 4 Sodium-Glucose Cotransporter-2 Inhibitor Cardiovascular Trials: Implications for the General Type 2 Diabetes US Population
Eric T. Wittbrodt, PharmD, MPH; James M. Eudicone, MS, MBA; Kelly F. Bell, PharmD, MSPhr; Devin M. Enhoffer, PharmD; Keith Latham, PharmD; and Jennifer B. Green, MD
Generalizability of Glucagon-Like Peptide-1 Receptor Agonist Cardiovascular Outcome Trials Enrollment Criteria to the US Type 2 Diabetes Population
Eric T. Wittbrodt, PharmD, MPH; James M. Eudicone, MS, MBA; Kelly F. Bell, PharmD, MSPhr; Devin M. Enhoffer, PharmD; Keith Latham, PharmD; and Jennifer B. Green, MD
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Comparison of Low-Dose Liraglutide Use Versus Other GLP-1 Receptor Agonists in Patients Without Type 2 Diabetes
Eric T. Wittbrodt, PharmD, MPH; James M. Eudicone, MS, MBA; Sepehr Farahbakhshian, MS; and Carrie McAdam-Marx, PhD, MSCI, RPh

Comparison of Low-Dose Liraglutide Use Versus Other GLP-1 Receptor Agonists in Patients Without Type 2 Diabetes

Eric T. Wittbrodt, PharmD, MPH; James M. Eudicone, MS, MBA; Sepehr Farahbakhshian, MS; and Carrie McAdam-Marx, PhD, MSCI, RPh
Objectives: The objective was to compare the use of low-dose liraglutide (LD-L) (Victoza) to the other glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in patients without a type 2 diabetes (T2D) diagnosis in the post approval period for high-dose liraglutide (HD-L) (Saxenda), which is not indicated for T2D.
Study Design: This was a retrospective, repeated cross-sectional, cohort study.
Methods: Adult patients with T2D with more than 1 prescription for a GLP-1 RA in the Optum Humedica database between December 2014 and March 2016 were included. The proportions of patients without a T2D diagnosis who were prescribed L-DL versus the other GLP-1 RAs and within each cohort were computed. Logistic regression models estimated the predictive value of either treatment in those without a T2D diagnosis, controlling for multiple factors. To supplement these findings, administrative claims data were extracted from the Truven Health MarketScan database.
Results: Analyses identified 11,245 patients prescribed LD-L and 4134 patients prescribed other GLP-1 RAs. For the entire study period, Humedica data revealed that patients without T2D accounted for 2.7% of the GLP-1 RA cohort and 17.5% of the LD-L cohort. Multivariable logistic regression analyses identified that patients receiving LD-L were more than 6 times likely to have no indication of T2D relative to patients taking other GLP-1 RAs. Claims data from MarketScan corroborated the Humedica results.
Conclusions: In patients without a T2D diagnosis, LD-L use was significantly greater than that with other GLP-1 RAs within 6 months after approval of HD-L; differences persisted until the end of the study. Increased payer scrutiny of appropriate LD-L use is warranted.
Am J Manag Care. 2018;24:-S0
Low-dose liraglutide (LD-L) (Victoza) is a glucagon-like peptide-1 receptor agonist (GLP-1 RA) approved in January 2010 as an adjunct to diet and exercise to improve glycemic control in adults with type 2 diabetes (T2D). It is available as a multidose pen that delivers doses of 0.6 mg, 1.2 mg, or 1.8 mg1 liraglutide and it enjoys broad formulary access, in part because it was the first once-daily GLP-1 RA on the US market. While weight loss with LD-L in patients with diabetes was demonstrated in trials and in the real-world setting,2,3 LD-L is not indicated for weight management. Liraglutide 3 mg (Saxenda, high-dose liraglutide [HD-L]), approved in December 2014, is indicated as an adjunct to a reduced-calorie diet and increased physical activity for chronic weight management in adult patients with an initial body mass index (BMI) of at least 30 kg/m2 or at least 27 kg/m2 in the presence of at least 1 weight-related comorbid condition. It is also available as a multidose pen that delivers doses of 0.6 mg, 1.2 mg, 1.8 mg, 2.4 mg, or 3.0 mg liraglutide.4 HD-L contains the same active ingredient as Victoza and is not indicated for the treatment of T2D. The introduction of Saxenda to the US market, with the subsequent promotional campaign initiated in April 2015, may have led to increased use of LD-L among patients who do not have T2D.

Based on a business analytics analysis of discrete monthly data from January 2014 to June 2015 (Optum Humedica Diabetes Database), the proportion of patients prescribed LD-L without a diagnosis of T2D increased nearly 2-fold during the first 6 months of 2015. Payers who do not offer favorable access to obesity treatments including HD-L may not be fully aware of LD-L use in patients without T2D, and therefore would be particularly interested in this proportion of patients who are prescribed and use LD-L most likely for weight loss. The objective of this study was to expand upon the previous analysis by evaluating prescribing patterns and prescription claims of LD-L compared with other GLP-1 RAs in 2 large national datasets from 2014 to 2016, which encompasses the approval and launch of HD-L.

Methods

This retrospective, repeated cross-sectional cohort study assessed information from patients in 2 databases. Prescription orders and clinical data were extracted from the Humedica Diabetes Integrated Database, which included EMR and claims data for approximately 6.8 million patients between 2014 and 2016. Clinical data were provided by integrated delivery networks that were composed of hospitals, physician offices, small group practices, and multispecialty practices. Clinical data included medication orders and prescriptions, medications administered, laboratory results, vital signs, body measurements, diagnoses, and procedures. The EMR dataset was linked to Optum claims, which included medical and pharmacy claims data from Optum affiliated health plans. Patients were included if they had data in both datasets based on direct patient matching through a trusted third party, and had diabetes, as defined by meeting 1 or more of the following criteria: diagnosis code for type 1 or type 2 diabetes mellitus (International Classification of Diseases, Ninth Version [ICD-9]: 249.0-249.9 and 250.0-250.9); a medication order or prescription claim for an antihyperglycemic medication; a documented glycated hemoglobin (A1C) level of 5.7% or greater; or a fasting plasma glucose of 100 mg/dL or greater.

In the Humedica dataset, we focused on identifying GLP-1 RA prescribing patterns; thus, we limited assessment of GLP-1 RA use to prescription orders. To identify patients whose GLP-1 RA prescriptions were filled and reimbursed by a third-party payer and to improve generalizability, we supplemented findings from the Humedica data with administrative claims data from the Truven Health MarketScan Commercial Claims and Encounters (Commercial) and Medicare Supplemental and Coordination of Benefits (Medicare Supplemental) databases (hereafter referred to as MarketScan). These data included enrollment information, demographic information and inpatient medical, outpatient medical, and outpatient pharmacy claims data from more than 300 large self-insured US employers and more than 25 US health plans.5

The Humedica and MarketScan databases satisfy the conditions set forth in Sections 164.514 (a) to (b)1ii of the Health Insurance Portability and Accountability Act (HIPAA) of 1996 privacy rule regarding the determination and documentation of statistically de-identified data. Thus, the study did not require external institutional review board or ethics review.

Patient inclusion criteria for the study were: (1) age at least 18 years as of the index date; (2) at least 12 months of database enrollment; (3) at least 1 prescription order (in Humedica) or prescription claim (in MarketScan) for LD-L or another GLP-1 RA issued between January 2014 and December 2016 (for the Humedica Database) or September 2016 (for the MarketScan Database); and (4) had never received GLP-1 RA treatment, as evidenced by no GLP-1 RA prescriptions ordered or filled in the 12 months prior to the index date. (The date of the first such prescription was identified as the index date, and censoring by the date of the most recent update differed between the 2 databases). Patient exclusion criteria were: (1) receipt of insulin at any time during the study period; (2) a diagnosis of type 1 diabetes (T1D), as determined by diagnosis codes for T1D at any time pre- or postindex date; and (3) evidence of subsequent switching between LD-L and another GLP-1 RA following the index date.

Study variables were measured from the databases using enrollment records, International Classification of Diseases, Ninth and Tenth Revisions (depending on calendar time), Clinical Modification (ICD-9-CM/ICD-10-CM) codes, Current Procedural Technology 4th Edition (CPT-4) codes, Healthcare Common Procedure Coding System (HCPCS) codes, and National Drug Codes (NDCs), as appropriate. The dependent variable in this study was evidence of T2D diagnosis, which was determined in a hierarchical manner by the presence of at least 1 of the following: an ICD-9 or ICD-10 code for T2D with a diagnosis prior to the index date; prescription order or claim for an oral antihyperglycemic medication at any time; or a fasting plasma glucose level greater than 126 mg/dL or an A1C level greater than 6.5% prior to the index date.

Baseline characteristics captured to describe the study cohorts included demographic data (age, sex, US region of residence), comorbidities, and use of weight loss medications. BMI was also captured from the Humedica data. Diagnosis code searches were identified for any position. NDCs were searched to identify diabetes medications for inclusion/exclusion criteria, and weight loss medications. Additionally, searches of drug name and generic name fields were conducted in addition to NDC searches when identifying index medications for the Humedica analysis. To control for disease severity, values for Charlson Comorbidity Index (CCI)6 and Diabetes Complication Severity Index (DCSI) were calculated.7

Continuous data were analyzed using a t test, and categorical data were analyzed using a χ2 test for the assessment of demographic characteristics among users of LD-L and other GLP-1 RAs who did not have evidence of T2D. Logistic regression was performed to model the predictive value of either treatment on having no T2D diagnosis, controlled for month of initiation (MOI), age, sex, geographical region, and treatment multiplied by MOI interaction. Differences in the proportions of patients with comorbid conditions between both treatment groups were assessed using Fisher’s exact test. Differences in the proportions of patients using concomitant weight loss medications between both treatment groups were assessed using Fisher’s exact test.

Results

The study identified 126,178 patients in the Humedica dataset and 245,236 patients in the MarketScan dataset with 1 or more prescription orders or claims for LD-L or another GLP-1 RA between 2014 and 2016 (Table 1). Of those in the Humedica dataset, 40,322 met the study inclusion criteria of least a 1-year history in the database, aged at least 18 years, without indication of T1D, and did not switch to LD-L (for the GLP-1 RA cohort) or to another GLP-1 RA (for the LD-L cohort). This group included 13,772 and 26,550 patients with prescription orders between 2014 and 2016 for GLP-1 RA or LD-L, respectively. Applying the same criteria to patients with 1 or more GLP-1 RA or LD-L prescription claim in MarketScan yielded 58,311 patients using a GLP-1 RA other than liraglutide and 84,671 using LD-L.

Patients without indication of T2D by diagnosis, drug treatment, or laboratory data were identified in both datasets. For the entire study period using the Humedica data, patients without T2D accounted for 376 (2.7%) of the GLP-1 RA cohort and 4651 (17.5%) of the LD-L cohort. In the MarketScan dataset, 1531 (2.6%) of the GLP-1 RA cohort and 4497 (5.3%) of the LD-L cohort lacked an indication of T2D (Table 1).

Baseline characteristics of patients without T2D are presented in Table 2. In the Humedica dataset, the mean (SD) age of patients receiving the GLP-1 RAs was 49 (13) years, which was significantly higher than the mean age of 42 (12) years observed in the LD-L group (P <.001). The proportions who were female exceeded males in both cohorts, and were significantly higher in the LD-L group (74.7%) than in the GLP-1 RA group (71.0%; P <.001). Mean BMI was also higher in the LD-L group at 38.1 (8.2) kg/m2 compared with the GLP-1 RA group at 36.7 (8.5) kg/m2 (P = .002), but the proportions with a prescription for a weight loss medication did not differ. In terms of comorbidities and complications, the LD-L cohort had a higher prevalence of hypertension and obesity (P <.001 for both), but fewer had documentation of a hypoglycemic event in the baseline period than the GLP-1 RA group (0.8% vs 1.4%; P = .017). The mean CCI and DCSI were numerically similar between cohorts.

In the MarketScan dataset, the mean (SD) age of patients receiving a GLP-1 RA was 48 (12) years versus 47 (12) years for the LD-L group (P <.001). The proportions of patients who were female were higher than males in both cohorts and were significantly higher in the LD-L group (78.4%) than in the GLP-1 RA group (75.1%; P = .008). Geographic region did not differ between groups. Use of prescription weight loss medications did not differ, but the prevalence of obesity per diagnosis was significantly higher in the LD-L group (11.3% vs 8.6%; P = .003). The LD-L cohort had a higher prevalence of hypertension (P = .040) and dyslipidemia (P = .013), but fewer patients had a diagnosis for hypoglycemia in the baseline period (1.7% vs 2.7%; P = .014). Mean CCI and DCSI were similar between groups.

 
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