Letters Section Editor: Jody W. Zylke, MD, Senior Editor.
Author Affiliations: Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts (Dr Jena; email@example.com); and Medical Oncology Branch, National Cancer Institute, Bethesda, Maryland (Dr Prasad).
In Reply:Falsification hypotheses can help adjudicate whether observational associations are robust or whether they reflect selection bias among patients who receive an intervention. Dr Groenwold thoughtfully expands on a prerequisite to proper falsification analyses: the falsification hypothesis must test a putative mechanism of bias.
Consider, for example, the question posed by Groenwold of whether β-blocker therapy reduces perioperative cardiac risk. Even after adjusting for observed patient demographics and claims-based clinical characteristics, an estimated association between β-blocker therapy and cardiac risk may still be confounded by unobserved patient and physician characteristics, including unmeasured socioeconomic characteristics.
Jena AB, Prasad V. Falsification End Points for Observational Studies—Reply. JAMA. 2013;309(17):1769–1771. doi:10.1001/jama.2013.3112
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