PMID- 33961275
OWN - NLM
STAT- MEDLINE
DCOM- 20220107
LR  - 20220107
IS  - 1178-1661 (Electronic)
IS  - 1178-1653 (Linking)
VI  - 14
IP  - 6
DP  - 2021 Nov
TI  - The Impact of the Risk Functional Form Assumptions on Maximum Acceptable Risk 
      Measures.
PG  - 827-836
LID - 10.1007/s40271-021-00518-y [doi]
AB  - BACKGROUND: Discrete-choice experiments (DCEs) are increasingly conducted to 
      quantify risk tolerance by computing maximum acceptable risk (MAR) for 
      improvements in efficacy or other benefits gained from new medical treatments. To 
      compute MARs from DCE data, respondents are asked to make choices under 
      uncertainty between treatments. Specific treatment-related harms are included in 
      the choice questions as probabilistic adverse events (AEs), and choice variation 
      with the probability of these outcomes is assumed to indicate their effect on the 
      expected utility of treatments. With a limited number of comparisons between 
      profiles, calculation of MARs requires understanding how outcome probabilities 
      that are not explicitly considered in the DCE can change the value of medical 
      technologies. This study aims to examine how various assumptions on the 
      expected disutility of these excluded probabilities can result in different MAR 
      measures. METHODS: We summarize commonly used empirical specifications for the 
      expected disutility of AEs and derive the resulting MAR functions. We then 
      discuss an empirical application on treatments to delay bone metastases in 
      oncology patients with solid tumors. RESULTS: A total of 187 respondents 
      completed the DCE. Results show the impact of making various assumptions about 
      the expected disutility of AEs, and the resulting MAR values for specific health 
      benefits. As expected, different assumptions resulted in variations in MAR values 
      for specific health benefits. Even with small differences in MAR measures, our 
      results suggest that the assumptions evaluated here can lead to different 
      conclusions about the acceptability of a medical technology. CONCLUSION: Results 
      show possible systematic variations in MARs caused by the assumed form of the 
      effect of changes in the probability of AEs. Furthermore, we find that different 
      assumptions can lead to different conclusions about the acceptability of a 
      medical technology, even when MAR distributions overlap. This result suggests 
      that researchers should evaluate the assumptions they are making for these 
      effects and use sensitivity analysis to evaluate the robustness of risk-tolerance 
      measures from stated-preference data.
CI  - (c) 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
FAU - Gonzalez, Juan Marcos
AU  - Gonzalez JM
AUID- ORCID: 0000-0002-5386-0907
AD  - Duke University, Durham, NC, USA. jm.gonzalez@duke.edu.
FAU - Boeri, Marco
AU  - Boeri M
AUID- ORCID: 0000-0001-7346-2132
AD  - RTI Health Solutions, Belfast, UK.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20210507
PL  - New Zealand
TA  - Patient
JT  - The patient
JID - 101309314
SB  - IM
MH  - *Choice Behavior
MH  - Humans
MH  - Uncertainty
EDAT- 2021/05/08 06:00
MHDA- 2022/01/08 06:00
CRDT- 2021/05/07 12:56
PHST- 2021/04/12 00:00 [accepted]
PHST- 2021/05/08 06:00 [pubmed]
PHST- 2022/01/08 06:00 [medline]
PHST- 2021/05/07 12:56 [entrez]
AID - 10.1007/s40271-021-00518-y [pii]
AID - 10.1007/s40271-021-00518-y [doi]
PST - ppublish
SO  - Patient. 2021 Nov;14(6):827-836. doi: 10.1007/s40271-021-00518-y. Epub 2021 May 
      7.