GBR (Global Benefit-Risk)

1. Description

GBR (Global Benefit Risk) refers to three trade-off metrics constructed around individual patients' outcomes in clinical trials: linear, ratio and composite ratio scores.[1][2][3] The application of GBR requires a pre-determined proportionality constant to rescale risk to the same unit as benefit.

2. Evaluation

2.1 Principle
  • The mathematical principle of GBR is logically sound and simple as it aims to put measurements in different dimensions on the same scale, through a choice of the proportional constant in the GBR expressions.
  • GBR is calculated for each individual, so any appropriate statistical modelling techniques could be used to estimate statistical uncertainties.
  • Value judgements in benefit-risk models using GBR would implicitly be in the choice of what constitute benefit or risk and in the choice of constant in the expressions. Allowing individuals to choose their own weights also contribute to this.

2.2 Features
  • GBR integrates benefit and risk for the assessment.
  • Multiple benefits and risks are not differentiated using these measures, but regarded as collective criteria.
  • The proposed sensitivity analysis is by varying the choice of the constants over an acceptable range.

2.3 Visualisation
  • A snapshot of data for GBR analysis can be shown in a table to represent outcomes of the patients.

2.4 Assessability and accessibility
  • GBR is very specific to the three functional forms, and therefore knowledge of which functional form and the underlying assumptions used is essential when making comparisons or when generalising the results.
  • GBR metrics do not distinguish the extent of severity or seriousness of adverse events although individual-level data are present.

3. References

[1] Chuang-Stein C, Entsuah R, Pritchett Y. Measures for conducting comparative benefit: Risk assessment. Drug Information Journal 2008;42(3):223-33.
[2] Chuang-Stein C, Mohberg NR, Sinkula MS. Three measures for simultaneously evaluating benefits and risks using categorical data from clinical trials. Stat Med 1991 Sep;10(9):1349-59.
[3] Chuang-Stein C. A New Proposal for Benefit-Less-Risk Analysis in Clinical Trials. Controlled Clinical Trials 1994;15:30-43.