RESEARCH ARTICLE


Using and Interpreting Adjusted NNT Measures in Biomedical Research



Ralf Bender1, 2, *
1 Department of Medical Biometry, Institute for Quality and Efficiency in Health Care (IQWiG), Cologne, Germany
2 Faculty of Medicine, University of Cologne, Germany


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Creative Commons License
© Ralf Bender; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the Department of Medical Biometry, Institute for Quality and Efficiency in Health Care (IQWiG), Dillenburger Str. 27, D-51105 Cologne, Germany; Tel: +49 221 35685-451; Fax: +49 221 35685-891; E-mail: Ralf.Bender@iqwig.de


Abstract

The number needed to treat (NNT) is a popular effect measure to present study results in biomedical research. NNTs were originally proposed to describe the absolute effect of a new treatment compared with a standard treatment or placebo in randomized controlled trials (RCTs) with binary outcome. The concept of the NNT measure has been applied to a number of other research areas involving the development of related measures and more sophisticated techniques to calculate and interpret NNT measures in biomedical research. In epidemiology and public health research an adequate adjustment for covariates is usually required leading to the application of adjusted NNT measures. An overview of the recent developments regarding adjustment of NNT measures is given. The use and interpretation of adjusted NNT measures is illustrated by means of examples from dentistry research.

Key Words: Number needed to treat, evidence-based medicine, confounding, adjustment for covariates, regression analysis.