Time Traveling Is Just Too Dangerous but Some Methods Are Worth Revisiting: The Advantages of Expected Loss Curves Over Cost-Effectiveness Acceptability Curves and Frontier

We used the probabilistic sensitivity analysis of the case study to illustrate the limitations of currently recommended methods for communicating uncertainty and then demonstrated how ELCs can address these issues.

Cost-effectiveness
Probabilistic sensitivity analysis (PCA)
Uncertainty quantification
Cost-effectiveness Acceptability Frontier (CEAF)
Authors

Alarid-Escudero F

Enns EA

Kuntz KM

Michaud TL

Jalal H

Published

May 1, 2019

Recommended citation

Alarid-Escudero F, Enns EA, Kuntz KM, Michaud TL, Jalal H. “Time Traveling Is Just Too Dangerous” But Some Methods Are Worth Revisiting: The Advantages of Expected Loss Curves Over Cost-Effectiveness Acceptability Curves and Frontier. Value in Health, 2019;22(5):611-618. Use these methods with the R package dampack.

   

Published in:

 

Abstract

 

Background

Cost-effectiveness acceptability curves (CEACs) and the cost-effectiveness acceptability frontier (CEAF) are the recommended graphical representations of uncertainty in a cost-effectiveness analysis (CEA). Nevertheless, many limitations of CEACs and the CEAF have been recognized by others. Expected loss curves (ELCs) overcome these limitations by displaying the expected foregone benefits of choosing one strategy over others, the optimal strategy in expectation, and the value of potential future research all in a single figure.

 

Methods

We used a probabilistic sensitivity analysis of a CEA comparing 6 cerebrospinal fluid biomarker test-and-treat strategies in patients with mild cognitive impairment. We showed how to calculate ELCs for a set of decision alternatives. We used the probabilistic sensitivity analysis of the case study to illustrate the limitations of currently recommended methods for communicating uncertainty and then demonstrated how ELCs can address these issues.

 

Results

ELCs combine the probability that each strategy is not cost-effective on the basis of current information and the expected foregone benefits resulting from choosing that strategy (ie, how much is lost if we recommended a strategy with a higher expected loss). ELCs display how the optimal strategy switches across willingness-to-pay thresholds and enables comparison between different strategies in terms of the expected loss.

 

Conclusions

ELCs provide a more comprehensive representation of uncertainty and overcome current limitations of CEACs and the CEAF. Communication of uncertainty in CEA would benefit from greater adoption of ELCs as a complementary method to CEACs, the CEAF, and the expected value of perfect information.