@article {7502, title = {Comparing methods to address bias in observational data: statin use and cardiovascular events in a US cohort.}, journal = {Int J Epidemiol}, year = {2017}, month = {2017 Sep 08}, abstract = {

Background: The theoretical conditions under which causal estimates can be derived from observational data are challenging to achieve in the real world. Applied examples can help elucidate the practical limitations of methods to estimate randomized-controlled trial effects from observational data.

Methods: We used six methods with varying design and analytic features to compare the 5-year risk of incident myocardial infarction among statin users and non-users, and used non-cardiovascular mortality as a negative control outcome. Design features included restriction to a statin-eligible population and new users only; analytic features included multivariable adjustment and propensity score matching.

Results: We used data from 5294 participants in the Cardiovascular Health Study from 1989 to 2004. For non-cardiovascular mortality, most methods produced protective estimates with confidence intervals that crossed the null. The hazard ratio (HR) was 0.92, 95\% confidence interval: 0.58, 1.46 using propensity score matching among eligible new users. For myocardial infarction, all estimates were strongly protective; the propensity score-matched analysis among eligible new users resulted in a HR of 0.55 (0.29, 1.05)-a much stronger association than observed in randomized controlled trials.

Conclusions: In designs that compare active treatment with non-treated participants to evaluate effectiveness, methods to address bias in observational data may be limited in real-world settings by residual bias.

}, issn = {1464-3685}, doi = {10.1093/ije/dyx179}, author = {Kaiser, Paulina and Arnold, Alice M and Benkeser, David and Zeki Al Hazzouri, Adina and Hirsch, Calvin H and Psaty, Bruce M and Odden, Michelle C} } @article {8285, title = {The association of prediagnosis social support with survival after heart failure in the Cardiovascular Health Study.}, journal = {Ann Epidemiol}, volume = {42}, year = {2020}, month = {2020 Feb}, pages = {73-77}, abstract = {

PURPOSE: Although social support has been shown to be associated with survival among persons with cardiovascular disease, little research has focused on whether social support, measured before the onset of heart failure, can enhance survival after diagnosis. The objective of this study was to assess the association between prediagnosis social support and postdiagnosis survival among older adults with heart failure.

METHODS: We obtained the data from the Cardiovascular Health Study, which included noninstitutionalized adults aged 65 years or older from four sites in the United States with primary enrollment in 1989-1990. We used two measures of social support, the Lubben Social Network Scale and the Interpersonal Support Evaluation List. The analytic data set included 529 participants with a social support measure within two years before diagnosis of heart failure.

RESULTS: After adjustment for demographic covariates, cardiovascular risk factors, and general health status, mortality rates were lower among participants in the highest tertile of social network scores (HR 0.74, 95\% CI: 0.59, 0.93) and the middle tertile (HR 0.73 [0.58, 0.90]), compared with the lowest tertile. Results with interpersonal support were null.

CONCLUSIONS: These findings suggest that prediagnosis structural social support may modestly buffer heart failure patients from mortality.

}, issn = {1873-2585}, doi = {10.1016/j.annepidem.2019.12.013}, author = {Kaiser, Paulina and Allen, Norrina and Delaney, Joseph A C and Hirsch, Calvin H and Carnethon, Mercedes and Arnold, Alice M and Odden, Michelle C} } @article {8840, title = {Statins and cognitive decline in the Cardiovascular Health Study: A comparison of different analytical approaches.}, journal = {J Gerontol A Biol Sci Med Sci}, year = {2021}, month = {2021 Jul 31}, abstract = {

BACKGROUND: Despite their well-established benefits for the prevention of cardiovascular disease, robust evidence on the effects of statins on cognition is largely inconclusive. We apply various study designs and analytical approaches to mimic randomized controlled trial (RCT) effects from observational data.

METHODS: We used observational data from 5,580 participants enrolled in the Cardiovascular Health Study from 1989/90 to 1999/2000. We conceptualized the cohort as an overlapping sequence of non-randomized trials. We compared multiple selection (eligible population, prevalent users, new-users) and analytic approaches (multivariable adjustment, inverse probability treatment weights, propensity score matching) to evaluate the association between statin use and 5-year change in global cognitive function, assessed using the Modified Mini-Mental State (3MS) examination.

RESULTS: When comparing prevalent users to non-users (N=2,772), statin use was associated with slower cognitive decline over 5 years (adjusted annual change in 3MSE = 0.34 points/year; 95\% CI:0.05;0.63). Compared to prevalent user design, estimates from new user designs (e.g. comparing eligible statin initiators to non-initiators) were attenuated showing either null or negative association, though not significant. For example, in a propensity score-matched sample of statin-eligible individuals (N=454), annual 3MS change comparing statin initiators to non-initiators was -0.21 points/year (95\% CI:-0.81;0.39).

CONCLUSIONS: The association of statin use and cognitive decline is attenuated towards the null when using rigorous analytical approaches that more closely mimic RCTs. Point estimates, even within the same study, may vary depending on the analytical methods used. Further studies that leverage natural or quasi experiments around statin use are needed to replicate our findings.

}, issn = {1758-535X}, doi = {10.1093/gerona/glab220}, author = {Zeki Al Hazzouri, Adina and Jawadekar, Neal and Grasset, Leslie and Kaiser, Paulina and Kezios, Katrina and Calonico, Sebastian and Glymour, M Maria and Hirsch, Calvin and Arnold, Alice M and Varadhan, Ravi and Opoodden, Michelle C} }