Study type

Study topic

Human medicinal product

Study type

Non-interventional study

Scope of the study

Safety study (incl. comparative)

Data collection methods

Secondary use of data
Non-interventional study

Non-interventional study design

Cohort
Study drug and medical condition

Name of medicine

OMVOH

Study drug International non-proprietary name (INN) or common name

MIRIKIZUMAB

Anatomical Therapeutic Chemical (ATC) code

(L04AC24) mirikizumab
mirikizumab

Medical condition to be studied

Colitis ulcerative
Population studied

Short description of the study population

The source population will consist of patients with a diagnosis of UC who are in the claims-based MDV database and have at least one prescription of mirikizumab or a comparator biologic during the patient identification period.

Age groups

Adult and elderly population (≥18 years)
Adults (18 to < 65 years)
Adults (18 to < 46 years)
Adults (46 to < 65 years)
Elderly (≥ 65 years)
Adults (65 to < 75 years)
Adults (75 to < 85 years)
Adults (85 years and over)
Study design details

Study design

This study will employ an incident new user design, limiting the study population to patients who are new users of mirikizumab or the comparator biologic during the patient identification period.

Main study objective

The objective of this study is to describe the incidence of serious infections and estimate the hazard ratio for serious infections among adult patients 18 years of age and older with a diagnosis of UC who are exposed to mirikizumab versus their propensity score-matched comparators (TNF inhibitors, vedolizumab, or ustekinumab) using Cox proportional hazard models.

Setting

The source population will consist of patients with a diagnosis of UC who are in the claims-based MDV database and have at least one prescription of mirikizumab or a comparator biologic during the patient identification period (i.e., on or after 21 June 2023 through 31 May 2026).

Comparators

Three individual comparator cohorts (TNF inhibitor cohort, vedolizumab cohort, and ustekinumab cohort) will be created.

Outcomes

Serious infections

Data analysis plan

Propensity score (PS) matching will be used to balance the covariates between the mirikizumab and comparator cohorts. Three logistic regression models will be used to calculate the propensity of receiving mirikizumab versus receiving (1) a TNF inhibitor, (2) vedolizumab, or (3) ustekinumab.

Each patient in the mirikizumab cohort will be matched with up to 3 patients in the comparator cohort (1:3) based on the PS using nearest neighbour matching (calliper width 0.2 of the standard deviation of the logit score).

Incidence rates of serious infections in matched mirikizumab and comparator cohorts will be computed, defined as number of cases divided by the total person-years of follow-up in each comparison set.

Cox proportional hazard models will be used in all association analyses to estimate hazard ratios and corresponding 95% confidence intervals of serious infections among mirikizumab users compared to PS-matched users of: (1) TNF inhibitors, (2) vedolizumab, and (3) ustekinumab, separately.