Routine clinical care for chronic immune thrombocytopenia purpura in Denmark, 2009-2015

Lessons Learned Using Real-World Data to Emulate Randomized Trials: A Case Study of Treatment Effectiveness for Newly Diagnosed Immune Thrombocytopenia

Regulatory agencies are increasingly considering real-world evidence (RWE) to support label expansions of approved medicines. We conducted a comparative effectiveness study to emulate a proposed randomized trial of romiplostim vs. standard-of-care (SOC) therapy among patients with recently diagnosed (≤12 months) immune thrombocytopenia (ITP), that could support expansion of the romiplostim label. We discuss challenges that we encountered and solutions that were developed to address those challenges. Study size was a primary concern, particularly for romiplostim initiators, given the rarity of ITP and the stringent trial eligibility criteria. For this reason, we leveraged multiple data sources (Nordic Country Patient Registry for Romiplostim; chart review study of romiplostim initiators in Europe; Flatiron Health EMR linked with MarketScan claims). Additionally, unlike the strictly controlled clinical trial setting, platelet counts were not measured at regular intervals in the observational data sources, and therefore the end point of durable platelet response often used in trials could not be reliably measured. Instead, the median platelet count was chosen as the primary end point. Ultimately, while we observed a slightly higher median platelet count in the romiplostim group vs. SOC, precision was limited because of small study size (median difference was 11 × 10⁹ /L (95% CI: -59, 81)). We underscore the importance of conducting comprehensive feasibility assessments to identify fit-for-purpose data sources with sufficient sample size, data elements, and follow-up. Beyond technical challenges, we also discuss approaches to increase the credibility of RWE, including systematic incorporation of clinical expertise into study design decisions, and separation between decision makers and the data.