Study type

Study type

Non-interventional study
Non-interventional study

Scope of the study

Assessment of risk minimisation measure implementation or effectiveness
Drug utilisation

Non-interventional study design

Cohort
Study drug and medical condition

Name of medicine

Adtralza

Name of medicine, other

Adbry

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

TRALOKINUMAB

Anatomical Therapeutic Chemical (ATC) code

200000016031
tralokinumab

Medical condition to be studied

Dermatitis atopic
Population studied

Age groups

Preterm newborn infants (0 – 27 days)
Term newborn infants (0 – 27 days)
Infants and toddlers (28 days – 23 months)
Adults (18 to < 46 years)
Adults (46 to < 65 years)

Special population of interest

Pregnant women

Estimated number of subjects

11880
Study design details

Main study objective

The study will investigate whether maternal exposure to tralokinumab during pregnancy in women with AD is associated with an increased risk of major congenital malformations, minor congenital malformations, infants born small for gestational age, preterm births, spontaneous abortions, or stillbirths

Outcomes

Major congenital malformations, Minor congenital malformations, infants born small for gestational age, preterm births, spontaneous abortions, stillbirths

Data analysis plan

Descriptive analyses will be conducted for the progress reports to monitor counts of tralokinumab-exposed pregnancies and live births. The following analyses will be conducted for the final study report: • Descriptive analyses of demographic and baseline characteristics and the number of dispensations of the exposure medications will be conducted for each cohort and will include counts, frequency, mean and 95% CI, median, Q1 and Q3, minimum, and maximum. Results will be presented by data source. • Comparative analyses, including crude and adjusted RRs and risk differences and 95% CIs will be calculated for all pregnancy and infant outcomes by data source. • For each study outcome, the effect estimates from each data source will be pooled using meta-analytic techniques.