Brief report
A propensity score-matched cohort study of the effect of statins, mainly fluvastatin, on the occurrence of acute myocardial infarction

https://doi.org/10.1016/j.amjcard.2003.08.057Get rights and content

Abstract

This investigation quantified the effect of statins on acute myocardial infarction (AMI) in an observational setting where fluvastatin represented most of the statin use. The study applied propensity scores to match statin initiators to statin noninitiators and followed them for the occurrence of AMI. Serum low-density lipoprotein levels were reduced by statin therapy, and there were fewer incidents of AMI in statin initiators than in noninitiators.

References (20)

  • P. Jones et al.

    Comparative dose efficacy study of atorvastatin versus simvastatin, pravastatin, lovastatin, and fluvastatin in patients with hypercholesterolemia (the CURVES Study)

    Am J Cardiol

    (1998)
  • K.M. Newton et al.

    The use of automated data to identify complications and comorbidities of diabetesa validation study

    J Clin Epidemiol

    (1999)
  • D.J. Maron et al.

    Current perspectives on statins

    Circulation

    (2000)
  • Randomised trial of cholesterol lowering in 4444 patients with coronary heart diseasethe Scandinavian Simvastatin Survival Study (4S)

    Lancet

    (1994)
  • J. Shepherd et al.

    Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. West of Scotland Coronary Prevention Study Group

    N Engl J Med

    (1995)
  • F.M. Sacks et al.

    The effect of pravastatin on coronary events after myocardial infarction in patients with average cholesterol levels. Cholesterol and Recurrent Events Trial Investigators

    N Engl J Med

    (1996)
  • J.R. Downs et al.

    Primary prevention of acute coronary events with lovastatin in men and women with average cholesterol levelsresults of AFCAPS/TexCAPS. Air Force/Texas Coronary Atherosclerosis Prevention Study

    JAMA

    (1998)
  • Prevention of cardiovascular events and death with pravastatin in patients with coronary heart disease and a broad range of initial cholesterol levels

    N Engl J Med

    (1998)
  • MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20, 536 high-risk individualsa randomised placebo-controlled trial

    Lancet

    (2002)
  • D.B. Rubin

    Estimating causal effects from large data sets using propensity scores

    Ann Intern Med

    (1997)
There are more references available in the full text version of this article.

Cited by (48)

  • Propensity score methods to control for confounding in observational cohort studies: a statistical primer and application to endoscopy research

    2019, Gastrointestinal Endoscopy
    Citation Excerpt :

    In particular, we demonstrate that propensity score matching was effective in removing baseline imbalances in measured covariates, thereby controlling for measured confounding between patients treated with esophageal dilation and those who were not. Propensity score methods have been used widely in comparative effectiveness research and pharmacoepidemiology7,19,36,45-49 and can be viewed in part as an extension of more “traditional” methods used to control for confounding, such as matching and stratification. By summarizing a large set of patient characteristics into a single score, the propensity score offers a more efficient and effective method for performing matching and stratification.

  • Testosterone Therapy and Risk of Acute Myocardial Infarction in Hypogonadal Men: An Administrative Health Care Claims Study

    2017, Journal of Sexual Medicine
    Citation Excerpt :

    The index date for TT-treated patients was identified as first prescription dispensing of TT. The index date for untreated patients was based on the equal probability of them receiving a TT prescription, which was the date of hypogonadism diagnosis during the first 6-month calendar block (if they were matched initially) or the randomly assigned date of any clinical or hospital visit within the subsequent 6-month calendar block (ie, if the patient was not matched initially and rolled over to the subsequent 6-month calendar block and remained untreated).34 Follow-up after the index date concluded at the first occurrence of any of the following events: acute MI, death from any cause, discontinuous enrollment (gap > 31 days),35 discontinuation of TT use or gap in TT use (≥90 days), any change in exposure status (ie, TT-treated patients discontinuing TT [change in route of administration was not considered a change in status, except for subgroup analysis] or untreated patients beginning TT), or end of data period (December 31, 2013).

  • Comparative Analysis of Calendar Time-Specific and Conventional Propensity Score Analysis for Thiazolidinedione Use in Diabetes

    2014, Value in Health Regional Issues
    Citation Excerpt :

    CTS-PS is an appropriate option when researchers conduct a study with a long study period and the probability of receiving exposure changes overtime. Previous studies have been conducted using a time-specific approach to estimate PS [17,18]. The rationale was that the time-specific approach was more flexible and able to account for changes in the way medications were used over time.

  • Policymaker, please consider your needs carefully: Does outcomes research in relapsed or refractory multiple myeloma reduce policymaker uncertainty regarding value for money of bortezomib?

    2014, Value in Health
    Citation Excerpt :

    Furthermore, as expected, our results confirm previous concerns [25–28] that great heterogeneity and a lack of randomization in everyday practice resulted in incomparable patient groups. Although other observational studies successfully used the propensity score matching technique [29–33], essential prerequisites [34], such as large patient numbers and consistency in comparator, were missing in our study. Despite applying different adjustment techniques to the Cox multivariate regression model, none succeeded in correcting for differences between patient groups mainly on account of small patient numbers, extensive treatment variation, and missing data.

View all citing articles on Scopus

This report was supported by a Harvard School of Public Health (Boston, Massachusetts) Pharmacoepidemiology Training Grant.

View full text