OBJECTIVES : The process to discover and gain approval for secondary indications is time-consuming and burdensome. This analysis aimed to quantify the prevalence of a TNF-inhibitor secondary indication conditions during the years between initial approval and each subsequent secondary indication approval using U.S. real-world data.

METHODS : This was a retrospective analysis using U.S. claims data from the IBM® MarketScan® Commercial and Medicare Supplemental Databases. For this analysis, we selected a TNF-inhibitor with a primary indication for rheumatoid arthritis (RA) and multiple secondary indications: juvenile idiopathic arthritis (JIA), psoriatic arthritis (PsA), ankylosing spondylitis (AS), and plaque psoriasis. The dates of the U.S. Food and Drug Administration primary and secondary indication approvals were identified. The number of patients with diagnoses for the secondary indications, and no existing diagnoses for RA, during the time between the primary and the corresponding secondary indication date, represented the lost market size. Patient conditions were identified via diagnosis codes on medical claims during the time periods corresponding to each secondary indication. The prevalence results from the database were projected to the U.S. population with employer-sponsored insurance.

RESULTS : The secondary indication dates ranged from 1-18 years following the primary indication (RA) approval. During the 6 years between the RA and adult plaque psoriasis approvals, there were N=113,240 adult patients in the database with plaque psoriasis and no diagnoses for RA. Projected to the U.S. population, this represents N=1,930,821 patients of lost market size during these years. In total, considering JIA, PsA, AS and plaque psoriasis indications, the lost market size in the time between primary and secondary indication dates was projected to be 2.5 million U.S. patients.

CONCLUSIONS : These results show a large missed market opportunity due to delays in secondary indication approvals. There is a need to develop data-driven techniques to quickly identify potential secondary indication conditions.