Study Design and Patients
This retrospective analysis of computerized clinical databases was carried out at Maccabi Healthcare Services (MHS). MHS covers ~ 25.0% of the population of Israel countrywide and includes ~ 2.1 million members, 160,000 (7.6%) of whom have documented diabetes, suggesting that it is representative of the population. The central computerized database stores data on members’ medical information, including medication [19]; specific inclusion criteria for the MHS diabetes registry are detailed elsewhere [20]. All procedures performed in studies involving human participants were in accordance with the local institutional review board of Bayit Balev Rehabilitation Hospital, Israel, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Individual patient-informed consent was not required because of the anonymized nature of the patient records.
All patient data from those who initiated liraglutide treatment between January 1, 2010, and February 28, 2015, were extracted for the study (n = 5932). Further inclusion criteria required that patients should be Maccabi members for at least 12 months prior to treatment initiation (index date) and until 24 months after treatment initiation, and should be > 18 years old at index date. Patients were required to have HbA1c measurements at baseline (defined as 180 days prior to the index date) and after 24 months from the index date within specified time windows. Patients who were defined in the diabetes registry as having type 1 diabetes, or were taking another GLP-1RA in the 6 months preceding the index date and until 24 months afterwards (including dispensing liraglutide after the discontinuation date), or who underwent bariatric surgery (12 months before/24 months after the index date) were excluded from the study.
Two groups of patients were defined within the cohort: “continuers,” who adhered to liraglutide treatment for ≥ 12 months, as measured by continuous liraglutide dispensed; and “discontinuers,” who stopped liraglutide before completing 12 months of treatment, as measured by a gap of ≥ 120 days between dispenses (after the refill date). Furthermore, the following subgroups were defined: patients above/below median HbA1c at baseline; insulin use at baseline; insulin treatment at 21–24 months after the index date; and liraglutide therapy at 24 months. Continuers were compared with discontinuers overall and within the subgroups.
Variable Definitions
For all laboratory measurements, baseline values were measured ≤ 180 days before the index date (most recent measurement used); early response values (HbA1c) were measured 90-270 days after baseline (the measurement closest to 180 days was used); and 24-month values were measured after 24 months (– 90/+ 180) days. The difference in change in body weight and BMI from baseline to 24 months between continuers and discontinuers was calculated. Low-density lipoprotein (LDL) cholesterol and triglyceride levels were measured at baseline and after 24 months. Values of > 300 mg/dL were recorded as 300 mg/dL for the analyses.
Oral and injectable diabetes medications used at baseline included those medications dispensed in the 180 days before baseline, and diabetes medication usage at 24 months included those medications dispensed 21–24 months after baseline. These included insulin (ATC codes: A10AB, A10AC, A10AD, A10AE), metformin (ATC codes: A10BA, A10BD07, A10BD08, A10BD10, A10BD11, A10BD15, A10BD16, A10BD20), sulfonylurea (ATC code: A10BB), meglitinides (ATC code: A10BX02), dipeptidyl peptidase-4 inhibitors (DPP-4i) (ATC codes: A10BH, A10BD07, A10BD08, A10BD10, A10BD11), sodium-glucose cotransporter-2 inhibitors (ATC codes: A10BX09, A10BX11, A10BX12, A10BD15, A10BD16, A10BD20, A10BK01, A10BK03), acarbose (ATC code: A10BF01), thiazolidinediones (ATC code: A10BG03), and GLP-1RAs (ATC codes: A10BX04, A10BX07, A10BX10, A10BX14, A10BJ01, A10BJ02, A10BJ03, A10BJ05). Medication use was defined as: insulin dispensed at 21–24 months (Y/N); using ≥ 3 oGLDs at 24 months (Y/N); numbers of oGLDs used at 21–24 months.
Hospitalizations 12–24 months after the index date were identified. Hospitalizations related to diabetes were defined according to the International Statistical Classification of Diseases and Related Health Problems (ICD-9) codes (diabetes mellitus with and without complications: 250.X; other specified hypoglycemia: 251.1; hypoglycemia, unspecified: 251.2; secondary diabetes mellitus with other specified manifestations: 249.8; diabetic retinopathy: 362.0; diabetic cataract: 366.41; polyneuropathy in diabetes: 357.2, and other abnormal glucose: 790.29). Other hospitalizations were defined as being unrelated to diabetes. Based on this, two hospitalization variables were defined: the number of overall hospitalizations in the 12–24 months after the index date; and the number of diabetes-related hospitalizations in the 12–24 months after the index date.
Duration of diabetes was defined as number of years in the MHS diabetes registry [21], which was based on diagnoses, medication dispensed, and laboratory measurements. Comorbidities reported within 12 months prior to the index date were defined according to the relevant disease registries (CV disease [22], cerebrovascular disease, chronic kidney disease [CKD], and hypertension [23]), or according to ICD-9 codes (dyslipidemia: 272.X; liver disease: 570.X–573.X; pancreatitis: 577.X; gallbladder disease: 575.X–576.X).
Statistical methods
The two groups were matched 1:1 using a propensity score based on baseline characteristics, including age, sex, baseline HbA1c, diabetes duration, BMI, and insulin use. Subgroups were rematched for subgroup analyses.
Descriptive statistics were reported for all baseline characteristics and clinical outcomes separately for continuers and discontinuers before and after propensity score matching. For continuous variables, mean ± standard deviation (SD) were reported. For categorical variables, n (%) were reported. The magnitude of the effect size for the change from baseline to follow-up measurement in key measures between continuers and discontinuers was calculated as follows [24]:
$$ {\text{Effect}}\;{\text{size}} = \frac{{{\text{Mean}}\;{\text{(continuers)}} - {\text{mean (discontinuers)}}}}{{{\text{SD}}\;{\text{pooled}}}}, $$
where the effect size was categorized as follows: 0.01 = very small, 0.2 = small, 0.5 = medium, 0.8 = large, 1.2 = very large, and 2 = huge.
For each variable, statistical comparisons between continuers and discontinuers were performed using Fisher’s exact test or the χ2 test for categorical variables, and the t test or the Wilcoxon rank-sum test for continuous variables. Analyses were carried out using two-tailed tests, and p values of less than 0.05 were considered statistically significant.
Propensity Scores
Propensity scores were developed using a multivariate logistic regression model where the dependent binary variable indicated whether the patient was a new user of liraglutide who adhered to liraglutide treatment for ≥ 12 months (= 1) or discontinued liraglutide before completing 12 months of treatment (= 0). Propensity scores estimated the probability of adherence to liraglutide treatment for ≥ 12 months or discontinuing liraglutide before completing 12 months of treatment, given the covariates in the model. Independent covariates at the index date were: age, sex, diabetes duration (≤ 2, 2–10, or > 10 years), HbA1c level, BMI (< 25, 25–30, 30–32.5, 32.5–35, 35–40, > 40 kg/m2, or missing), and use of insulin.
Patients were matched 1:1 using the “greedy matching” technique, which randomly selects a treated patient and matches them to the nearest untreated subject—in this case, continuers and discontinuers [25]. Caliper matching was defined as a caliper equal to 0.05 of the logit of the propensity score.
All statistical analyzes were performed using SAS 9.2 (or later versions) statistical software (SAS Institute Inc., Cary, NC, USA).