LNSLNS

Many thanks to Dr. Traut for his contribution. As correctly noted, it is important to consider both absolute effects (absolute risk reduction [ARR], number needed to treat [NNT]) and relative effects (e.g. relative risk, relative risk reduction). For all outcomes, we reported relative estimates of effect; for all-cause pneumonia, invasive pneumococcal disease, and acute otitis media, for example, we calculated absolute effects in the form of NNT, from which one can easily deduce ARR (NNT = 1/ARR).

Whereas a relative measure (e.g. relative risk) generally remains stable across various risk groups (1), ARR underestimates the effect for patients with high baseline risk and overestimates the effect for patients with low baseline risk (2). The preferred strategy is therefore to perform a meta-analysis with a relative measure of effect size and then, by population and setting, to apply the relative treatment effect to a specific health risk within a population, as we did in our article for three outcomes, for example (1, 3). Some health risks vary greatly between different populations or settings. NNTs are generally smaller in high-risk populations and larger in low-risk populations. Vaccination is usually performed in low-risk populations that nevertheless typically include a large number of individuals. From a public health perspective, NNTs of 1500 or 2000 individuals to be vaccinated in order to prevent one case of disease therefore certainly do have great practical significance. Population-relevant issues such as herd effects (i.e. the fact that unvaccinated individuals also benefit from vaccination if the vaccination rate is high enough), which are often overlooked by opponents of vaccination, should also be a factor in primary care physicians’ decision-making processes.

DOI: 10.3238/arztebl.2016.0559b

Hannah Ewald, MPH

Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel

Switzerland

Hannah.Ewald@usb.ch

Viktoria Gloy, PhD

Basel Institute for Clinical Epidemiology and Biostatistics

University Hospital Basel
Institute of Nuclear Medicine, University Hospital Bern
Bern, Switzerland

Matthias Briel MD, MSc
Basel Institute for Clinical Epidemiology and Biostatistics
Department of Clinical Research
University Hospital Basel, Switzerland

Department of Epidemiology and Biostatistics
McMaster University, Hamilton, ON, Canada

Conflict of interest statement

The authors of both contributions declare that no conflict of interest exists.

1.
Higgins JPT GSe: Cochrane handbook for systematic reviews of
interventions version 5.1.0 (updated March 2011), chapter 12.5.3 „Expressing absolute risk reductions“. The Cochrane Collaboration, 2011 available from
www.cochrane-handbook.org.
2.
Alonso-Coello P, Carrasco-Labra A, Brignardello-Petersen R, et al.: Systematic reviews experience major limitations in reporting absolute effects. J Clin Epidemiol 2016; 72: 16–26 CrossRef MEDLINE
3.
Ewald H, Briel M, Vuichard D, Kreutle V, Zhydkov A, Gloy V: The clinical effectiveness of pneumococcal conjugate vaccines—a systematic review and meta-analysis of randomized controlled trials. Dtsch Arztebl Int 2016; 113: 139–46. VOLLTEXT
1.Higgins JPT GSe: Cochrane handbook for systematic reviews of
interventions version 5.1.0 (updated March 2011), chapter 12.5.3 „Expressing absolute risk reductions“. The Cochrane Collaboration, 2011 available from
www.cochrane-handbook.org.
2.Alonso-Coello P, Carrasco-Labra A, Brignardello-Petersen R, et al.: Systematic reviews experience major limitations in reporting absolute effects. J Clin Epidemiol 2016; 72: 16–26 CrossRef MEDLINE
3.Ewald H, Briel M, Vuichard D, Kreutle V, Zhydkov A, Gloy V: The clinical effectiveness of pneumococcal conjugate vaccines—a systematic review and meta-analysis of randomized controlled trials. Dtsch Arztebl Int 2016; 113: 139–46. VOLLTEXT

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