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美国罕见病新药申请成功的随机对照试验数据。

Randomized controlled trial data for successful new drug application for rare diseases in the United States.

机构信息

Department of Clinical Medicine (Pharmaceutical Medicine), Graduate School of Pharmaceutical Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo, 108-8641, Japan.

Development, Astellas Pharma Inc, Tokyo, 103-8411, Japan.

出版信息

Orphanet J Rare Dis. 2023 Apr 19;18(1):89. doi: 10.1186/s13023-023-02702-9.

Abstract

BACKGROUND

Randomized controlled trial (RCT) data have important implications in drug development. However, the feasibility and cost of conducting RCTs lower the motivation for drug development, especially for rare diseases. We investigated the potential factors associated with the need for RCTs in the clinical data package for new drug applications for rare diseases in the United States (US). This study focused on 233 drugs with orphan drug designations approved in the US between April 2001 and March 2021. Univariable and multivariable logistic regression analyses were conducted to investigate the association between the presence or absence of RCTs in the clinical data package for new drug applications.

RESULTS

Multivariable logistic regression analysis showed that the severity of the disease outcome (odds ratio [OR] 5.63, 95% confidence interval [CI] 2.64-12.00), type of drug usage (odds ratio [OR] 2.95, 95% confidence interval [CI] 1.80-18.57), and type of primary endpoint (OR 5.57, 95% CI 2.57-12.06) were associated with the presence or absence of RCTs.

CONCLUSIONS

Our results indicated that the presence or absence of RCT data in the clinical data package for successful new drug application in the US was associated with three factors: severity of disease outcome, type of drug usage, and type of primary endpoint. These results highlight the importance of selecting target diseases and potential efficacy variables to optimize orphan drug development.

摘要

背景

随机对照试验(RCT)数据在药物开发中具有重要意义。然而,进行 RCT 的可行性和成本降低了药物开发的动力,尤其是对于罕见病。我们调查了美国(美国)新药申请临床数据包中罕见病 RCT 需求的相关潜在因素。本研究专注于 2001 年 4 月至 2021 年 3 月期间在美国批准的 233 种具有孤儿药设计的药物。采用单变量和多变量逻辑回归分析来研究新药申请临床数据包中 RCT 的存在与否与 RCT 之间的关联。

结果

多变量逻辑回归分析显示,疾病结局严重程度(比值比 [OR] 5.63,95%置信区间 [CI] 2.64-12.00)、药物使用类型(OR 2.95,95%CI 1.80-18.57)和主要终点类型(OR 5.57,95%CI 2.57-12.06)与 RCT 的存在与否相关。

结论

我们的结果表明,美国新药申请临床数据包中 RCT 数据的存在与否与三个因素有关:疾病结局严重程度、药物使用类型和主要终点类型。这些结果强调了选择目标疾病和潜在疗效变量以优化孤儿药开发的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5866/10114466/b98fe8412569/13023_2023_2702_Fig1_HTML.jpg

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