Preimplantation genetic testing for sickle cell disease: a cost-effectiveness analysis.

OBJECTIVE

To evaluate the cost-effectiveness of in vitro fertilization with preimplantation genetic testing for monogenic disease (IVF + PGT-M) in the conception of a nonsickle cell disease (non-SCD) individual compared with standard of care treatment for a naturally conceived, sickle cell disease (SCD)-affected individual.

DESIGN

A Markov simulation model was constructed to evaluate a one-time IVF + PGT-M treatment compared with the lifetime standard of care costs of treatment for an individual potentially born with SCD. Using an annual discount rate of 3% for cost and outcome measures, quality-adjusted life years were constructed from utility weights and life expectancy values and then used as the effectiveness measurement. An incremental cost-effectiveness ratio was calculated for both treatment arms, and a willingness-to-pay threshold of $50,000 per quality-adjusted life year was assumed.

SETTING

Tertiary care or university medical center.

PATIENTS: A hypothetical cohort of 10,000 patients was analzyed over a lifetime horizon using yearly cycles.

INTERVENTIONS: In vitro fertilization with preimplantation genetic testing for monogenic disease use in conception of a non-SCD individual.

MAIN OUTCOME MEASURES: The primary outcomes of interest were the incremental cost and effectiveness of an IVF+PGT-M conception compared with the SOC treatment of an SCD-affected individual.

RESULTS

In vitro fertilization with preimplantation genetic testing for monogenic disease was the optimal strategy in 93.17% of the iterations. An incremental savings of $137,594 was demonstrated with a gain of 1.96 QALYs and 3.69 life years over a lifetime. Sensitivity analysis demonstrated that SOC treatment never met equivalent cost-effectiveness.

CONCLUSIONS

Our model demonstrates that IVF + PGT-M for selection against SCD, compared with lifetime SOC treatment for those affected, is the most cost-effective strategy within the United States healthcare sector.