Quantifying Value of Hope

Abstract

Background: 'Hope' is a construct in patient-centered value frameworks, but few studies have attempted to measure the value of hope separately from treatment-related gains in quality of life and survival to support its application in economic evaluation.

Objective: To generate quantitative information on the "value of hope".

Methods: We designed a discrete-choice experiment in which treatment alternatives varied the probability of achieving 10-year survival, expected survival as the weighted sum of short-term and long-term survival, health status, and out-of-pocket cost. Two-hundred patients with cancer or history of cancer recruited by Cancer Support Community each completed 10 choice questions. We used mixed-logit and latent-class models to analyze the choice data.

Results: Relative to fixed survival periods of two, three or five years with 0% chance of 10-year survival, participants positively valued treatments with 5% and 10% chances of 10-year survival. However, participants negatively valued a 20% chance of 10-year survival that required an offsetting 80% chance of shorter survival. This finding was particularly strong when expected survival was two years. Compared to a 0% chance, dollar-equivalent values of 5% and 10% chances of long-term survival were $5,975 and $12,421, respectively, independent of health status or expected survival. The corresponding value for 20% versus 0% chance of long-term survival was negative. Latent-class analysis revealed 4 groups with distinct preference patterns.

Conclusions: Our findings affirm positive value for hope independent of expected survival and health status. However, this finding does not universally hold in all situations nor across all groups.

Keywords: discrete-choice experiment; hope; patient preferences; value assessment.