INHB (Incremental Net Health Benefit)


1. Description

INHB (Incremental Net Health Benefit) calculates the difference in the "incremental" change of benefits to that of risks.[1][2][3] INHB uses QALY specifically to characterise benefits and risks, but other metrics can be used, and generalises as INB (Incremental Net Benefit).[4]

2. Evaluation


2.1 Principle
  • Statistical uncertainty in benefit -risk balance can be dealt with using standard statistical inference if individual benefit and risk measurements are involved, or by simulation means if population benefit and risk parameters are involved.
  • See also QALYs.

2.2 Features
  • The benefit and risk are integrated in INHB.
  • INHB can be extended to multiple benefit criteria and multiple risk criteria.
  • INHB compares two options at a time.
  • To update INHB model with new data may require meta-analysis; alternatively a Bayesian modelling.

2.3 Visualisation
Visualisations similar to the one used for QALYs may be used.
2.4 Assessability and accessibility
  • INHB is easy to perform and understand.
  • The acceptability and interpretability of the results depend on the actual health index used in the calculations of INHB.

A variation of this method was tested in the Rimonabant case study.

3. References

[1] Garrison LP, Towse A, Bresnahan BW. Assessing a structured, quantitative health outcomes approach to drug risk-benefit analysis. Health Aff (Millwood ) 2007 May;26(3):684-95.
[2] Lynd LD, Marra CA, Najafzadeh M, Sadatsafavi M. A quantitative evaluation of the regulatory assessment of the benefits and risks of rofecoxib relative to naproxen: an application of the incremental net-benefit framework. Pharmacoepidemiol Drug Saf 2010 Nov;19(11):1172-80.
[3] Minelli C, Abrams KR, Sutton AJ, Cooper NJ. Benefits and harms associated with hormone replacement therapy: clinical decision analysis. BMJ 2004 Feb 14;328(7436):371.
[4] Lynd LD, Najafzadeh M, Colley L, Byrne MF, Willan AR, Sculpher MJ, et al. Using the incremental net benefit framework for quantitative benefit-risk analysis in regulatory decision-making--a case study of alosetron in irritable bowel syndrome. Value Health 2010 Jun;13(4):411-7.