source: JAMA Network Open

year: 2019

authors: Deborah Lubeck, Irene Agodoa, Nickhill Bhakta, Mark Danese, Kartik Pappu, Robin Howard, Michelle Gleeson, Marc Halperin, Sophie Lanzkron

Importance:
Individuals with sickle cell disease (SCD) have reduced life expectancy; however, there are limited data available on lifetime income in patients with SCD.

Objective:
To estimate life expectancy, quality-adjusted life expectancy, and income differences between a US cohort of patients with SCD and an age-, sex-, and race/ethnicity-matched cohort without SCD.

Design, Setting, and Participants:
Cohort simulation modeling was used to (1) build a prevalent SCD cohort and a matched non-SCD cohort, (2) identify utility weights for quality-adjusted life expectancy, (3) calculate average expected annual personal income, and (4) model life expectancy, quality-adjusted life expectancy, and lifetime incomes for SCD and matched non-SCD cohorts. Data sources included the Centers for Disease Control and Prevention, National Newborn Screening Information System, and published literature. The target population was individuals with SCD, the time horizon was lifetime, and the perspective was societal. Model data were collected from November 29, 2017, to March 21, 2018, and the analysis was performed from April 28 to December 3, 2018.

Main Outcomes and Measures:
Life expectancy, quality-adjusted life expectancy, and projected lifetime income.

Results:
The estimated prevalent population for the SCD cohort was 87 328 (95% uncertainty interval, 79 344-101 398); 998 were male and 952 were female. Projected life expectancy for the SCD cohort was 54 years vs 76 years for the matched non-SCD cohort; quality-adjusted life expectancy was 33 years vs 67 years, respectively. Projected lifetime income was $1 227 000 for an individual with SCD and $1 922 000 for a matched individual without SCD, reflecting a lost income of $695 000 owing to the 22-year difference in life expectancy. One study limitation is that the higher estimates of life expectancy yielded conservative estimates of lost life-years and income. The analysis only considered the value of lost personal income owing to premature mortality and did not consider direct medical costs or other societal costs associated with excess morbidity (eg, lost workdays for disability, time spent in the hospital). The model was most sensitive to changes in income levels and mortality rates.

Conclusions and Relevance:
In this simulated cohort modeling study, SCD had societal consequences beyond medical costs in terms of reduced life expectancy, quality-adjusted life expectancy, and lifetime earnings. These results underscore the need for disease-modifying therapies to improve the underlying morbidity and mortality associated with SCD.

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