OBJECTIVES: The average age of the population that dies from COVID-19 is approximately 72 years old, whereas the average age of the population that is hospitalized with moderate-to-severe COVID-19 symptoms is approximately 59 years old. The objective of this work is to develop a method to account for this differential age between those who survive and those who die using a Markov model that estimates the cost-effectiveness of a novel treatment for COVID-19 patients.

METHODS: We assumed the novel treatment was associated with a survival benefit (hazard ratio = 0.91) as compared to usual care with all other treatment inputs resembling that of remdesivir. We estimated the average age of those who survived the COVID-19 hospitalization (novel treatment plus usual care versus usual care alone) as a function of the average age of COVID-19 hospitalized patients, the average age of hospitalized COVID-19 patients that died, and the differential percent of the population that died from COVID-19 in each treatment arm. Incremental costs and quality-adjusted life years (QALYs) were estimated over a lifetime time horizon from the third-party payer perspective.

RESULTS: The average age of those who survived was 57.4 for the novel treatment plus usual care versus 57.2 for usual care alone. Without accounting for the survivor differential age, the incremental cost-effectiveness ratio for this novel treatment is $35,000 per QALY gained. When accounting for the survivor differential age, the incremental cost-effectiveness ratio increases by 43% to $50,200.

CONCLUSIONS: Cost-effectiveness analyses should account for this differential survivor age when modeling clinical areas where the treatment is associated with a survival benefit and where the average age of those that die from the disease is different from the average age of those who receive treatment. This work provides the steps necessary to account for this situation.