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How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions?

Bruce R Schackman1, Heather Taffet Gold, Patricia W Stone

  • 1Division of Outcomes and Effectiveness Research, Department of Public Health, Weill Medical College of Cornell University, New York 10021, USA. brs2006@med.cornell.edu

Pharmacoeconomics
|April 6, 2004
PubMed
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Sensitivity analyses in pharmaceutical cost-utility studies are common and often change conclusions. Health-related quality of life and cost changes frequently impact results, unlike discount rates, highlighting the need for better study quality and parameter justification.

Area of Science:

  • Health economics
  • Pharmacoeconomics
  • Decision analysis

Background:

  • Limited evidence exists on the application of sensitivity analysis in cost-effectiveness literature.
  • Sensitivity analyses for health-related quality of life (HR-QOL), cost, and discount rates are crucial for assessing uncertainties.

Purpose of the Study:

  • To examine the use of sensitivity analyses in pharmaceutical cost-utility literature.
  • To determine if changes in economic parameters alter cost-effectiveness conclusions.

Main Methods:

  • Reviewed 70 pharmaceutical cost-utility analyses, auditing 122 base cases for sensitivity analyses.
  • Examined HR-QOL, cost, and discount rate sensitivity analyses (n=133, 99, 128 respectively).
  • Recorded cost-utility thresholds and compared quality ratings of studies where sensitivity analyses crossed thresholds.

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Main Results:

  • Common thresholds were $US20,000, $US50,000, and $US100,000/QALY.
  • Sensitivity analyses crossed thresholds in 31% (HR-QOL), 20% (cost), and 15% (discount rate).
  • Studies with crossed thresholds showed moderate quality and better parameter justification.

Conclusions:

  • Sensitivity analyses are widely used and frequently alter cost-effectiveness conclusions.
  • HR-QOL and cost parameters are key drivers of uncertainty, informing guideline recommendations.
  • Improving study quality and parameter justification enhances the value of sensitivity analyses.