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Potential Bias Associated with Modeling the Effectiveness of Healthcare Interventions in Reducing Mortality Using an Overall Hazard Ratio.

Authors :
Alarid-Escudero, Fernando
Kuntz, Karen M.
Source :
PharmacoEconomics; Mar2020, Vol. 38 Issue 3, p285-296, 12p
Publication Year :
2020

Abstract

<bold>Background: </bold>Clinical trials often report intervention efficacy in terms of the reduction in all-cause mortality between the treatment and control arms (i.e., an overall hazard ratio [oHR]) instead of the reduction in disease-specific mortality (i.e., a disease-specific hazard ratio [dsHR]). Using oHR to reduce all-cause mortality beyond the time horizon of the trial may introduce bias if the relative proportion of other-cause mortality increases with age. We sought to quantify this oHR extrapolation bias and propose a new approach to overcome this bias.<bold>Methods: </bold>We simulated a hypothetical cohort of patients with a generic disease that increased background mortality by a constant additive disease-specific rate. We quantified the bias in terms of the percentage change in life expectancy gains with the intervention under an oHR compared with a dsHR approach as a function of the cohort start age, the disease-specific mortality rate, dsHR, and the duration of the intervention's effect. We then quantified the bias in a cost-effectiveness analysis (CEA) of implantable cardioverter-defibrillators based on efficacy estimates from a clinical trial.<bold>Results: </bold>For a cohort of 50-year-old patients with a disease-specific mortality of 0.05, a dsHR of 0.5, a calculated oHR of 0.55, and a lifetime duration of effect, the bias was 28%. We varied these key parameters over wide ranges and the resulting bias ranged between 3 and 140%. In the CEA, the use of oHR as the intervention's effectiveness overestimated quality-adjusted life expectancy by 9% and costs by 3%, biasing the incremental cost-effectiveness ratio by - 6%.<bold>Conclusions: </bold>The use of an oHR approach to model the intervention's effectiveness beyond the time horizon of the trial overestimates its benefits. In CEAs, this bias could decrease the cost of a QALY, overestimating interventions' cost effectiveness. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11707690
Volume :
38
Issue :
3
Database :
Complementary Index
Journal :
PharmacoEconomics
Publication Type :
Academic Journal
Accession number :
141752640
Full Text :
https://doi.org/10.1007/s40273-019-00859-5