OBJECTIVES: Sickle cell disease (SCD) is a blood disorder characterized by sickle hemoglobin (HbS) polymerization that leads to hemolytic anemia, acute complications, and end-organ damage. Therapies targeting HbS polymerization, the cause of SCD pathophysiology, potentially impact multiple body systems and clinical outcomes, making health-state modeling complex. This study evaluated available cost-effectiveness analyses (CEAs) to determine optimal model types to assess treatments targeting HbS polymerization in SCD.

METHODS: A targeted literature review was conducted comprising (i) structured searches using Google Scholar and PubMed for the period 2018–2023, with search terms that included SCD and cost effectiveness studies, and (ii) recent, pertinent health economic evaluations performed or cited by the Institute for Clinical and Economic Review (ICER) or the National Institute for Health and Care Excellence (NICE).

RESULTS: In total, 12 unique CEAs were reviewed (8 from structured searches and 4 from ICER/NICE reports). CEAs included 8 Markov cohort, 2 individual patient simulation (IPS), and 2 discrete event simulation (DES) models. Most cohort-based models described the course of SCD by incorporating disease states using annual numbers of vaso-occlusive crises or aggregated acute and/or chronic complications. Patient-level simulations, encompassing both IPS (state-based) and DES (event-based) approaches, explicitly modeled specific complications and/or co-occurring events while considering patient characteristics/medical history. IPS models presented challenges in managing competing risks/events within a cycle and inefficiencies in processing event-free cycles. DES models overcame these challenges; one developed to assess an HbS polymerization inhibitor measured treatment effect through time-to-event equations and incorporated 15 distinct complications.

CONCLUSIONS: Cohort-based and IPS approaches are not well-suited for modeling therapies targeting HbS polymerization in SCD because of the need to account for multiple and/or co-occurring complications, patient history, and event-free cycles. DES-based CEAs address these limitations and can more accurately reflect the unpredictable and heterogenous course of SCD and its impact on individuals and health systems.