CORRESPONDENCE: LETTER TO THE EDITOR
Reply
Gregg C. Fonarow, MD, FACC*,
Jie Lena Sun, MS and
Karen Pieper, MS
* Ahmanson-UCLA, Cardiomyopathy Center, Medicine-Cardiology, 47-123 CHS, 10833 LeConte Avenue, Los Angeles, California 90095-1679 (Email: gfonarow{at}mednet.ucla.edu).
We are grateful to Dr. Bouzas-Mosquera and colleagues for their interest in our article (1). They raise several important issues and request additional details regarding the propensity score analysis used in this study to adjust for potential treatment selection bias. As noted in the article, although most variables of prognostic importance (e.g., age, systolic blood pressure, heart rate, creatinine, sodium) were similar between patients in the group continued on beta-blocker drugs and those withdrawn, left ventricular ejection fraction was lower (2.7 unit absolute difference), and a few other variables differed in patients withdrawn from beta-blocker therapy. Although withdrawal of beta-blocker drugs was associated with a few indicators of more severe heart failure, it remained significantly and independently associated with increased mortality after adjustment for multiple covariates and propensity score. The variables used for the propensity score are posted at the OPTIMIZE-HF (Organized Program To Initiate life-saving treatMent In hospitaliZEd patients with Heart Failure) website (2). We applied accepted modeling techniques to obtain the best fit for each variable in the model. The c-index of the propensity scores for the treatment assignment in this study was 0.649. Weitzen et al. (3) have shown that the c-index is not a good measure of the likelihood of omitted variables. One way to view this is that the best case scenario for estimating treatment differences would be under the assumption of randomization. A propensity score for this situation should have a c-index of 0.50, because no factor should be associated with receiving the randomized therapy. We have performed a sensitivity analysis (4). This indicates that an unknown covariate would need to have an odds ratio in the model of approximately 5 before we could obtain the opposite interpretation for the use of withdrawing beta-blocker drugs on post-discharge mortality. It seems fairly unlikely, although certainly possible, that a factor of such great importance was missed. We fully agree that the specific rationale for beta-blocker continuation and withdrawal during hospital stay were not collected, and this might have influenced the findings. Furthermore, despite covariate and propensity score adjustment, other measured and unmeasured factors might have influenced improvements in clinical outcomes associated with continuation or withdrawal of beta-blocker therapy. Nevertheless the findings of this OPTIMIZE-HF study are consistent with prior studies and current heart failure guidelines. Routine discontinuation of beta-blocker therapy on hospital admission is neither necessary nor advisable, and the majority of patients hospitalized for heart failure are eligible for beta-blocker therapy to be continued.
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Footnotes
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Please note: The OPTIMIZE-HF trial was funded by GlaxoSmithKline, Philadelphia, Pennsylvania. Dr. Fonarow has received research funding, consulting fees, and honorarium from GlaxoSmithKline; Ms. Sun and Ms. Pieper are employees of the Duke Clinical Research Institute, Durham, North Carolina.
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References
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1. Fonarow GC, Abraham WT, Albert NM, et al. OPTIMIZE-HF Investigators and Coordinators Influence of beta-blocker continuation or withdrawal on outcomes in patients hospitalized with heart failure: findings from the OPTIMIZE-HF program J Am Coll Cardiol 2008;52:190-199.[Abstract/Free Full Text]2. Organized Program to Initiate Life-Saving Treatment in Hospitalized Patients With Heart Failure https://www.optimize-hf.org/rul_html_OCSlogon.cgi 2008Accessed October 2, 2008.[Abstract/Free Full Text] 3. Weitzen S, Lapane KL, Toledano AY, Hume AL, Mor V. Principles for modeling propensity scores in medical research: a systematic literature review Pharmacoepidemiol Drug Saf 2004;13:841-853.[CrossRef][Web of Science][Medline] 4. Lin DY, Psaty BM, Kronmal RA. Assessing the sensitivity of regression results to unmeasured confounders in observational studies Biometrics 1998;54:948-963.[CrossRef][Web of Science][Medline]
Related Article
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Continuation or Withdrawal of Beta-Blocker Therapy in Patients Admitted for Heart Failure
- Alberto Bouzas-Mosquera, Jesús Peteiro, and Nemesio Álvarez-García
J. Am. Coll. Cardiol. 2008 52: 2044.
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