Study type

Study type

Non-interventional study

Scope of the study

Effectiveness study (incl. comparative)
Non-interventional study

Non-interventional study design

Cohort
Study drug and medical condition

Name of medicine

MAVENCLAD

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

CLADRIBINE

Anatomical Therapeutic Chemical (ATC) code

(L04AA40) cladribine
cladribine

Medical condition to be studied

Multiple sclerosis
Population studied

Age groups

Adults (18 to < 46 years)
Adults (46 to < 65 years)
Adults (65 to < 75 years)
Adults (75 to < 85 years)
Adults (85 years and over)

Estimated number of subjects

215
Study design details

Main study objective

The aim of the study will be to evaluate the effect of cladribine tablets on patient-reported outcomes (PROs) and their correlation to disability in subjects with highly-active MS (multiple sclerosis) who started their first switch from a disease-modifying drug (DMD) to cladribine tablets as their first second-line treatment in clinical practice.

Outcomes

- To evaluate changes in self-assessed physical impact of highly-active MS in daily life after the switch to cladribine tablets,
- Changes in self-assessed psychological impact, general health, cognitive functions, anxiety and depression, employment status after switch
- Relationship between changes and evaluations from wearable trackers
- Self-assessment and correlation with evaluations from wearable trackers
- Annualized relapse rate Real-world pharmacoeconomic data
- Safety in real-world clinical practice

Data analysis plan

No formal statistical hypothesis will be tested.
Quantitative (continuous) variables will be summarized using descriptive statistics, i.e. number of subjects with non-missing value, no of subjects with missing value, mean, SD, median, min and max, and first and third quartile.
Qualitative (categorical) variables will be displayed as frequency counts and percentages (n,%). Due to longitudinal nature of data, some outcomes data may be missing.
Patterns and degrees of missingness will be summarized.
As primary and secondary outcomes are based on PRO data, this will include the no of items missing for each scale and percentage of computable scale scores.
Descriptive statistics on outcome data may be used to identify potential data outliers. If CIs are to be calculated, these will be 2-sided with confidence probability of 95%.
For continuous data, CIs for mean will be calculated assuming a normal distribution of data. CIs for binary outcomes will be presented using Clopper-Pearson method