The use of marginal structural model to determine the effect of non-steroidal anti-inflammatory drug use on the risk of prostate and ovarian cancer
Principal Investigator
Name
Omonefe Omofuma
Degrees
B.Pharm., M.Sc.
Institution
University of south Carolina
Position Title
Graduate Research Assistant
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-265
Initial CDAS Request Approval
Mar 17, 2017
Title
The use of marginal structural model to determine the effect of non-steroidal anti-inflammatory drug use on the risk of prostate and ovarian cancer
Summary
The use of NSAIDs has been suggested to have an inverse association with cancer risks and experimental studies have shown inhibitory effects of aspirin on the growth of prostate cancer cells and also on its progression to aggressive disease. This association has also been observed in other cancers. However, epidemiological studies examining the association of NSAIDs on cancer have produced inconsistent results possibly due to limitations on dosing information and different pharmacological classes of NSAIDs.
In this study, we will obtain information on NSAIDs used in the previous year collected at baseline and will be defined by type, duration and frequency of use. Types of NSAIDs will include aspirin, ibuprofen and celecoxib containing drugs. Potential confounders to be evaluated will include age, race, education, smoking status, body mass index (BMI) and family history. We intend to use a weighted cox proportional hazards model to estimate the hazard ratios (HRs) and 95% CI for prostate and ovarian cancer as it relates to NSAID use and frequency.
In this study, we will obtain information on NSAIDs used in the previous year collected at baseline and will be defined by type, duration and frequency of use. Types of NSAIDs will include aspirin, ibuprofen and celecoxib containing drugs. Potential confounders to be evaluated will include age, race, education, smoking status, body mass index (BMI) and family history. We intend to use a weighted cox proportional hazards model to estimate the hazard ratios (HRs) and 95% CI for prostate and ovarian cancer as it relates to NSAID use and frequency.
Aims
We hypothesize that the use of NSAIDS would have a causal effect on the risk of prostate and ovarian cancer.
Thus the primary aim is to use a marginal structural model using time dependent inverse probability weights to estimate the causal effect of the use of NSAIDs on the risk of prostate and ovarian cancer.
We would also examine the relationship between the self-reported uses of the different types of NSAIDs to assess the strength of the relationship by pharmacological class and also assess presence of a dose response relationship between increased frequency of use and prostate and ovarian cancer.
Collaborators
Tsion Kidanie
University of South Carolina
Jourdyn Lawrence
University of South Carolina