TY - JOUR

T1 - In search of fewer independent risk factors

AU - Brotman, Daniel J.

AU - Walker, Esteban

AU - Lauer, Michael S.

AU - O'Brien, Ralph G.

PY - 2005/1/24

Y1 - 2005/1/24

N2 - More than 1100 articles now appear annually investigating "independent risk factors" or "independent predictors" for various clinical outcomes. In medical research, independence is generally defined in a statistical sense: a variable is called an independent risk factor if it has a significant contribution to an outcome in a statistical model that includes established risk factors. As such, independence is based on a specific statistical model and depends on the set of established risk factors included in that model. Even when strong statistical evidence indicates that a variable is an independent risk factor for an outcome, this does not necessarily indicate that the risk factor causally contributes to the outcome. The opposite is also true: risk factors that have causal relationships with the outcome will not necessarily prove to be independent risk factors. These are basic statistical principles that are too often given short shrift in medical research. Herein, we discuss the clinical implications conferred by the above definition of independence, primarily using examples from recent cardiovascular literature. A glossary and schema are provided to help clinicians and researchers understand and discuss these matters effectively.

AB - More than 1100 articles now appear annually investigating "independent risk factors" or "independent predictors" for various clinical outcomes. In medical research, independence is generally defined in a statistical sense: a variable is called an independent risk factor if it has a significant contribution to an outcome in a statistical model that includes established risk factors. As such, independence is based on a specific statistical model and depends on the set of established risk factors included in that model. Even when strong statistical evidence indicates that a variable is an independent risk factor for an outcome, this does not necessarily indicate that the risk factor causally contributes to the outcome. The opposite is also true: risk factors that have causal relationships with the outcome will not necessarily prove to be independent risk factors. These are basic statistical principles that are too often given short shrift in medical research. Herein, we discuss the clinical implications conferred by the above definition of independence, primarily using examples from recent cardiovascular literature. A glossary and schema are provided to help clinicians and researchers understand and discuss these matters effectively.

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U2 - 10.1001/archinte.165.2.138

DO - 10.1001/archinte.165.2.138

M3 - Review article

C2 - 15668358

AN - SCOPUS:12444249943

SN - 2168-6106

VL - 165

SP - 138

EP - 145

JO - Archives of internal medicine (Chicago, Ill. : 1908)

JF - Archives of internal medicine (Chicago, Ill. : 1908)

IS - 2

ER -