Study type

Study topic

Human medicinal product

Study type

Non-interventional study

Scope of the study

Assessment of risk minimisation measure implementation or effectiveness

Data collection methods

Secondary use of data
Non-interventional study

Non-interventional study design

Cohort
Other

Non-interventional study design, other

Retrospective, observational, comparative
Study drug and medical condition

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

CODEINE
TRAMADOL
Population studied

Short description of the study population

The study used two variants of the target (tramadol) and comparator (codeine) cohorts among 50-89-year-olds with 365 days of continuous observable time prior to the index date. The first cohort variants (T1, C1) excluded subjects who had been exposed to tramadol, codeine, or other opioids within 365 days prior to the index date, hip fracture, cancer, or opioid abuse diagnoses. The second cohort variants (T2, C2) aimed to make the target and comparator cohorts more comparable by excluding subjects diagnosed with cough or cold within 30 days of initial exposure to the opioids of interest and those prescribed cold or cough medications, antibiotics, or antihistamines within 30 days.

Age groups

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

Special population of interest

Frail population

Estimated number of subjects

1000000
Study design details

Main study objective

Does exposure to tramadol have a different risk of experiencing hip fracture within 1 year, relative to codeine?

Outcomes

Hip fracture

Data analysis plan

This study will follow a retrospective, observational, comparative cohort design . The target cohort is new users of tramadol, the comparator cohort are new users of codeine, and the outcome hip fracture. A Cox proportional hazards regression model will be used to model the time to the first outcome occurrence for the target group relative to the comparator group while accounting for the propensity score (PS) matching. Estimates of risk will be generated as the empirically calibrated hazard ratios (HR), 95% confidence intervals (CI), and p-values. This will be done across four observational datasets.
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