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, other

ritlecitinib tosilate

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

RITLECITINIB

Anatomical Therapeutic Chemical (ATC) code

(L04AF08) ritlecitinib
ritlecitinib
Population studied

Short description of the study population

The study population will include patients with AA initiating ritlecitinib, baricitinib or another approved systemic AA treatment as recorded in the participating data sources in Denmark, France, and Sweden during the cohort accrual period.
Patients will be included between 15 September 2023 until 14 September 2031 and followed through 14 September 2033.
Study design details

Study design

This will be a cohort study based on prospectively collected electronic healthcare data in.
The study population will include a cohort of patients with AA initiating ritlecitinib and, to contextualize the results, cohorts of patients with AA initiating baricitinib or other systemic AA treatments.

Main study objective

Primary objective: to estimate the incidence IRs of safety events of interest among patients with AA initiating ritlecitinib and patients with AA initiating baricitinib or other approved systemic treatments for AA in a real-world setting.

Exploratory objective: to compare the rates of the safety events of interest among patients with AA initiating ritlecitinib and patients with AA initiating baricitinib or other approved systemic treatments for AA, if study size permits.

Setting

This study will use population-based secondary data sources from Denmark, France, and Sweden.
All three study countries have universal healthcare, whereby routinely collected data continuously accrue in the participating nationwide databases.
Loss to follow-up is expected to be minimal and primarily due to emigration, which is expected to be low.
Studies based on secondary electronic healthcare data sources are efficient for monitoring rare events and events that require long-term follow-up, when these types of events are well captured in the data source.
These large real-world data sources are expected to allow robust assessment of the safety events of interest.
Most proposed safety events of interest are likely to be well captured in the data sources, as the majority of the events require immediate treatment in either a hospital or specialized outpatient setting.
Furthermore, safety events such as thromboembolic events have been shown to have high positive predictive values in the Danish and Swedish national registries.

Comparators

Patients with AA initiating baricitinib or other approved systemic treatments for AA, if study size permits.

Outcomes

• Thromboembolic events (including venous thromboembolism [VTE] and arterial thrombosis)
• Herpes zoster
• Serious infections
• Opportunistic infections
• Malignancy
• Malignancy excluding nonmelanoma skin cancer (NMSC)
• NMSC
• Major adverse cardiovascular events (MACE)
• Neurological events of interest
• Peripheral neuropathy
• Sensorineural hearing loss
• Migraine
• Seizures and seizure disorders
• Demyelinating disorders including multiple sclerosis
• Neurodegenerative disorders
• Bone fractures
• Growth metrics in adolescents (Denmark only)

Data analysis plan

Distributions of the characteristics of patients with AA will be reported separately for ritlecitinib and comparator groups at treatment start, using appropriate summary statistics. IRs and cumulative incidences of the safety events of interest will be computed (primary objectives) and the risks will be compared, if study size permits (exploratory objectives), between initiators of ritlecitinib and initiators of comparator AA treatments.
If conducted, measured confounding in the comparative analysis will be controlled using a propensity-score based method; unmeasured confounding will be quantified using the E-value method.