Most new drug approvals are based on data from large randomized clinical trials (RCTs). However, there are sometimes contradictory conclusions from seemingly similar trials and generalizability of conclusions from these trials is limited. These considerations explain, in part, the gap between conclusions from data of RCTs and those from registries termed data (RWD). Recently, real-world evidence (RWE) from RWD processed by artificial intelligence has received increasing attention. We describe the potential of using RWD in haematology concluding RWE from RWD may complement data from RCTs to support regulatory decisions.

中文翻译：

---

在血液学中使用真实世界的证据

大多数新药的批准都是基于大型随机临床试验（RCT）的数据。然而，看似相似的试验有时会得出相互矛盾的结论，而且这些试验的结论的普遍性是有限的。这些考虑因素部分解释了随机对照试验数据的结论与注册登记数据（RWD）的结论之间的差距。最近，由人工智能处理的RWD的真实世界证据（RWE）受到越来越多的关注。我们描述了在血液学中使用 RWD 的潜力，得出的结论是 RWD 的 RWE 可以补充 RCT 的数据以支持监管决策。