Study type

Study topic

Disease /health condition
Human medicinal product

Study type

Non-interventional study

Scope of the study

Assessment of risk minimisation measure implementation or effectiveness

Data collection methods

Secondary data collection
Non-interventional study

Non-interventional study design

Cohort
Study drug and medical condition

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

NICOTINE
BUPROPION
VARENICLINE

Medical condition to be studied

Cardiovascular disorder
Population studied

Short description of the study population

Exposure group: Smokers with no past history of cardiovascular disease (CVD) and no recorded smoking cessation attempts using pharmacological aids in the prior year, whose first recorded smoking cessation intervention was a cessation attempt assisted by either NRT (using any of, or a combination of products) or another pharmacological smoking cessation intervention (e.g. bupropion, varenicline) at the index date. Patients must meet the following criteria:
• Aged: 18–75 years
• Have at least one year of up-to-standard (UTS) baseline data as defined by GPRD (prior to the IPD) and at least 4 weeks’ of UTS outcome data (following the IPD) or UTS data up to the time of death if death occurred within the outcome period

Non-exposure group: smokers with no past history of CVD and no recorded smoking cessation attempts using pharmacological aids in the prior year, whose first recorded smoking cessation intervention involved receipt of smoking cessation advice that resulted in a quit attempt unaided by pharmacological therapies at the IPD and during the outcome periods. Patients must meet the following criteria:
tients must also meet the following inclusion criteria:
• Aged: 18–75 years.
• Current smoker throughout the prior year (any quantity of cigarettes)
• Received smoking cessation advice at IPD
• Have at least one year of UTS baseline data as defined by GPRD (prior to the IPD) and at least 4 weeks’ of UTS outcome data (following the IPD), or UTS data up to the time of death if death occurred within the follow-up period(s)

Age groups

Adults (18 to < 46 years)
Adults (46 to < 65 years)
Adults (65 to < 75 years)

Estimated number of subjects

61050
Study design details

Main study objective

To compare the CVD event rate in smokers undertaking unaided smoking cessation attempts (controls) with the event rate in those attempting cessation supported by nicotine replacement therapy (NRT) (any of: nasal spray, transdermal patches, inhaler or gum and tablets) or other pharmacological smoking cessation aids (buproion or varenecline) in a representative primary care population

Outcomes

The incident of the following CV events over a 4-week outcome period: CHD diagnosis and No of days from IPD, CHD-related death and No Of days from IPD, CerebroVD diagnosis and No Of Days from IPD, CerebroVD death and No of Days from IPD, Recorded GP consultations or hospital attendances for CHD or CebebroVD, including admission, A&E attendance, out-of-hours or Out-Patient Department attendance. The incident of the following CV events over a 52-week outcome period: CHD diagnosis and No of days from IPD, CHD-related death and No Of days from IPD, CerebroVD diagnosis and No Of Days from IPD, CerebroVD death and No of Days from IPD, Recorded GP consultations or hospital attendances for CHD or CebebroVD, including admission, A&E attendance, out-of-hours or Out-Patient Department attendance.

Data analysis plan

All times until diagnosis (CHD or CerebroVD) and survival times (until death due to CHD or CerebroVD) will be analysed using Cox’s Proportional Hazards Models, adjusting for baseline confounders. Censored times will be 4/52 weeks (primary/secondary outcomes). Total number of GP consultations and hospital attendances for CHD or CerebroDisease during the outcome periods will be compared between treatment groups using a Poisson regression model (conditional Poisson regression model for matched analyses) to obtain estimates of consultation / hospitalisation rates relative to the control group. The model will be adjusted for over-dispersion using robust standard errors and adjustments will be made for potential baseline confounders. For all models, variables that are strongly predictive of the outcome or that are significantly different (or show trend to significance, ie. p<0.01) between the treatment groups over baseline will be treated as potential confounders.
Documents
Study publications
Dollerup, J., Vestbo, J., Murray-Thomas, T., Kaplan, A., Martin, R.J., Pizzichi…