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Open Access Correspondence

A framework for organizing and selecting quantitative approaches for benefit-harm assessment

Milo A Puhan1*, Sonal Singh2, Carlos O Weiss3, Ravi Varadhan4 and Cynthia M Boyd4

Author Affiliations

1 Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Room E6153, Baltimore, MD, 21205, USA

2 Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, USA

3 Geriatric Medicine and Gerontology, Michigan State University, Grand Rapids, USA

4 Division of Geriatrics, Johns Hopkins School of Medicine, Baltimore, USA

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BMC Medical Research Methodology 2012, 12:173  doi:10.1186/1471-2288-12-173

Published: 19 November 2012

Abstract

Background

Several quantitative approaches for benefit-harm assessment of health care interventions exist but it is unclear how the approaches differ. Our aim was to review existing quantitative approaches for benefit-harm assessment and to develop an organizing framework that clarifies differences and aids selection of quantitative approaches for a particular benefit-harm assessment.

Methods

We performed a review of the literature to identify quantitative approaches for benefit-harm assessment. Our team, consisting of clinicians, epidemiologists, and statisticians, discussed the approaches and identified their key characteristics. We developed a framework that helps investigators select quantitative approaches for benefit-harm assessment that are appropriate for a particular decisionmaking context.

Results

Our framework for selecting quantitative approaches requires a concise definition of the treatment comparison and population of interest, identification of key benefit and harm outcomes, and determination of the need for a measure that puts all outcomes on a single scale (which we call a benefit and harm comparison metric). We identified 16 quantitative approaches for benefit-harm assessment. These approaches can be categorized into those that consider single or multiple key benefit and harm outcomes, and those that use a benefit-harm comparison metric or not. Most approaches use aggregate data and can be used in the context of single studies or systematic reviews. Although the majority of approaches provides a benefit and harm comparison metric, only four approaches provide measures of uncertainty around the benefit and harm comparison metric (such as a 95 percent confidence interval). None of the approaches considers the actual joint distribution of benefit and harm outcomes, but one approach considers competing risks when calculating profile-specific event rates. Nine approaches explicitly allow incorporating patient preferences.

Conclusion

The choice of quantitative approaches depends on the specific question and goal of the benefit-harm assessment as well as on the nature and availability of data. In some situations, investigators may identify only one appropriate approach. In situations where the question and available data justify more than one approach, investigators may want to use multiple approaches and compare the consistency of results. When more evidence on relative advantages of approaches accumulates from such comparisons, it will be possible to make more specific recommendations on the choice of approaches.