Related Experiment Video
Updated: Oct 21, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
A guide to extending and implementing generalized risk-adjusted cost-effectiveness (GRACE)
Darius N Lakdawalla1,2, Charles E Phelps3,4
1School of Pharmacy, Sol Price School of Public Policy, The Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA, USA. dlakdawa@usc.edu.
Abstract:
The generalized risk-adjusted cost-effectiveness (GRACE) model generalizes conventional cost-effectiveness analysis (CEA) by introducing diminishing returns to Health-Related Quality of Life (QoL). This changes CEA practice in three ways: (1) Willingness to pay (WTP) increases exponentially with untreated illness severity or pre-existing permanent disability, and WTP ends up lower for mild diseases but higher for severe diseases compared with conventional CEA; (2) Average treatment effectiveness should be adjusted for uncertainty in outcomes; and (3) The marginal rate of substitution between life expectancy and QoL varies with health state. Implementing GRACE requires new parameters describing risk preferences over QoL, the marginal rate of substitution between life expectancy (LE) and QoL, and the variance and skewness of treatment outcomes distributions. In this paper, we provide: (1) a generalized WTP threshold incorporating the possibility of permanent disability; (2) a simpler method to estimate the tradeoff rate between QoL and LE, eliminating the need to carry out treatment-by-treatment estimates; (3) a more-general method to adjust WTP for illness severity that permits non-constant relative risk-aversion in QoL; (4) a new approach to estimating risk-preferences over QoL, leveraging established empirical methods from "happiness" economics; and (5) a step-by-step guide for practitioners wishing to implement multi-period GRACE analyses.
More Related Videos
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Relative Risk
Comparing the Survival Analysis of Two or More Groups
Hazard Ratio
For example, in a clinical trial...
Cancer Survival Analysis

