Study Design
This was a retrospective cohort study using US insurance claims data from the IQVIA™ RWD Adjudicated Claims–US database [26]. The database includes information about each physician visit, medical procedure, hospitalization, medication dispensed in the outpatient setting and the date of service/prescription, number of days of medication supplied, and tests performed. Healthcare costs (claims paid) were reported as fee-for-service equivalents. The study included patients with information during the identification period (July 1, 2011, to June 30, 2014) with a 1-year pre-index/baseline period (see Fig. 1; Supplemental Digital Content 1). The 1-year pre-index period (referred to here as baseline) before the first qualifying IBD drug claim allowed clear determination that the first exposure to an IBD agent represented a new or inception treatment.
Patients
Eligible patients consisted of those who, during the identification period, were aged > 18 years, had ≥ 2 medical claims (inpatient or non-diagnostic outpatient ≥ 7 days apart), and were given a diagnosis of ulcerative colitis (ICD-9-CM: 556.x) or Crohn’s disease (ICD-9-CM: 555.x), with > 1 qualifying diagnosis (claim) in the year preceding treatment index date (baseline period). In addition, patients were required to be new users (i.e., they were required to have a new claim for an IBD treatment of interest during the identification period to minimize risk of misclassification of exposure). Patients with Crohn’s disease with ≥ 2 claims of UC and UC patients with ≥ 2 claims of Crohn’s disease were excluded. Treatments of interest included chronic (≥ 60 days) [26] oral corticosteroids (OCS), IS, an anti-TNF or combinations thereof (see Table 1; Supplemental Digital Content 2 for full list). The identification period used in this analysis—July 2011–2014—preceded the licensing of vedolizumab in the United States, and other more recently approved therapies; therefore, these agents are not included in these analyses.
Patients with specific conditions for which biologic or IS therapy could be prescribed or any condition that could complicate treatment assessment or confound the evaluation of AEs of interest were excluded (See “Methods” Section I, Supplemental Digital Content 3 for full details of eligibility criteria). For example, patients who had evidence of an alternative indication requiring aTNF therapy were excluded [e.g., plaque psoriasis (696.1x), psoriatic arthritis (696.0x), rheumatoid arthritis (714.0x), ankylosing spondylitis (720.0x)] were excluded. In addition, patients who had one or more inpatient or outpatient non-diagnostic claim of a chronic IBD treatment-related AE [type 2 diabetes (250.x0, 250.x2), cataract (366.xx, E932.0, CPT 66982, 66983, 66984), glaucoma (365.1x–365.9x), osteoporosis (733.0x), congestive heart failure (428.xx), and venous thromboembolism (415.xx, 451.xx, 453.xx)] prior to the index date were also excluded.
Treatments and Treatment-Attributable At-Risk Period
This was an incident cohort design. Definitions for treatment duration, treatment gaps, and end of therapy were based on claims data (See “Methods” Section II, Supplemental Digital Content 4 for additional details on treatment duration and follow-up period). The index date was the first use of each therapy of interest in the identification period. If 2 medications were dispensed within 30 days of each other and overlapping for at least 60 days, this was classified as combination therapy [27]. Patients who changed treatments during the study identification period could be included in multiple treatment groups if they met the selection criteria.
Patients could not have had a claim for the index therapy during the baseline period (1-year pre-index period). Patients with continuous use of corticosteroids of at least 60 days during the baseline period were excluded. Notably, in the case of corticosteroids, acute exposure (i.e., < 60 days of use) was allowed during the baseline period. Continuous use of drugs for at least 60 days was defined as chronic use [26]. To evaluate the association between treatments and certain AEs of interest (see Tables 2, 3, Supplemental Digital Content 5 for ICD codes related to AEs of interest and their resolution), a minimum exposure to the index treatment of 60 days after the index date was required. To capture all treatment-related AEs, the follow-up period included the time up to 60 days after the end of treatment or until the end of enrollment, the end of the study, or a treatment switch, whichever occurred first. Switching within a drug class was considered continuous treatment within the class, and data were not analyzed at the individual agent level.
Aminosalicylate Reference Group
The reference group comprised patients taking only aminosalicylates, with no record of other treatments of interest. To reduce the probability of capturing only patients who were recently given an IBD diagnosis and who were less sick, aminosalicylate users were not required to be new users; rather, they were selected based on a random aminosalicylate fill date in the identification period.
Outcomes of Interest
The primary outcomes of interest included 5 AE outcomes (any AE, severe infections [20], bone-related conditions [28, 29], arthralgia, and serious hepatic events) and 6 types of healthcare resource utilization (HCRU) [any inpatient hospitalization, any emergency department (ED) visit, any IBD-related hospitalization, any IBD-related gastrointestinal (GI) surgery, any IBD-related ED visit, and any IBD-related procedure (see Tables 4, 5, Supplemental Digital Content 6 for IBD-related procedures and endoscopy codes)], along with 2 annualized costs (all-cause healthcare costs by treatment, and all-cause healthcare costs by AEs) [21]. A more detailed list of the AEs monitored (including selected malignancies [20, 28, 29] and cardiovascular events) [29] and additional details on HCRU outcomes are included in the Supplementary Methods (see Methods Section III, Supplemental Digital Content 7 for additional details of study outcomes). Disease-related and overall HCRU and costs were assessed and included the cost of pharmacologic interventions and inpatient and outpatient services expressed on an annualized basis [21].
Baseline Measures
Recorded baseline data included demographic characteristics, Charlson Comorbidity Index score (this index predicts the 1-year mortality based on 22 comorbid conditions such as heart disease) [30], number of inpatient admissions, proportion of patients with ≥ 1 ED visit, proportion of patients with ≥ 1 IBD-related hospitalization, comorbidities, tobacco use, disease severity [31], behavior parameters, and all medications (see also Methods Section IV and Table 6, Supplemental Digital Content 8 for additional details on baseline measures). Disease severity was expressed as a risk score (range 0–6) that was calculated as a sum of points for individual patients based on the following point assignments, 0 or 1 point each for the absence or presence, respectively, of each of the following at baseline: anemia, requirement for blood transfusion, malnutrition, total parenteral nutrition, occurrence of Clostridioides difficile infection, and occurrence of IBD-related inpatient hospitalization [31].
Statistical Analysis
All analyses were conducted separately for Crohn’s disease and ulcerative colitis patients. Descriptive statistics were reported and included mean and standard deviation (SD) for continuous variables and patient count and percentages for categorical variables, stratified by the treatment groups of interest. Univariate comparisons included statistical tests of significance (χ2, F test, or Kruskal–Wallis rank-sum test). Rates of AEs were reported in units of per-patient-years to account for the variable time that patients are at risk for the event. Healthcare utilization outcomes were annualized to account for variable follow-up time [21]. Multivariate analyses were based on Cox proportional hazards regression, negative binomial regression, logistic regression, or linear regression analysis depending on outcome variable distribution and adjusted by significant sociodemographic, clinical, and disease severity covariates as outlined below.
Two sets of covariates were initially included in all models: (1) a priori: age, sex, region, and proportion of days covered (defined as ratio of total days of supply of index medication dispensed divided by days between the index date and end of follow-up); (2) other: Charlson comorbidity index [30], baseline number of prescriptions, baseline risk score, tobacco use, and Crohn’s disease behavior (for Crohn’s disease patients only) [31]. The final models included all a priori covariates and significant “other” covariates (significance level to drop out a covariate was ≥ 0.05). Based on previous publications [32, 33], which proposed a minimum of 10 events per predictor variable, the categories of anti-TNF plus IS, anti-TNF plus OCS, and anti-TNF plus IS plus OCS were combined into 1 group (anti-TNF combined) to ensure sufficient outcome events for robust multivariate analyses; in addition, multivariate analyses were only carried out for those outcome events occurring in sufficient numbers.
For IBD treatment-related AEs, Cox regression models were used. The proportional hazards assumption was checked for all covariates, and a time-dependent variable (interaction term of covariate with log of time) was included if the proportional hazards assumption was violated. For utilization outcomes, negative binomial regression was conducted to model the event rate (number of events per year of exposure) with the use of offset (log of exposure). A linear regression model with repeated measurement adjustment was used for annualized cost outcomes to account for the correlation between multiple treatment episodes for the same patient. As a sensitivity analysis, the cost models were weighted with the duration of follow-up.
All data transformations and statistical analyses were performed using SAS, v.9.4 (SAS Institute, Cary, NC, USA). Tests performed were 2-sided, with a significance level of 0.05. No corrections for multiple comparisons were applied.
Ethical Considerations
This article is based on real world data and does not contain any studies with human or animal subjects performed by any of the authors. All data analyzed were de-identified, as required under the US Health Insurance Portability and Accountability Act privacy rule. The dataset for this study contained no protected health information, and the use of the data was determined to be exempt from ethical approval.