As the world faced the devastation of the COVID-19 pandemic in late 2019 and early 2020, numerous clinical trials were initiated in many locations in an effort to establish the efficacy (or lack thereof) of potential treatments. As the pandemic has been shifting locations rapidly, individual studies have been at risk of failing to meet recruitment targets because of declining numbers of eligible patients with COVID-19 encountered at participating sites. It has become clear that it might take several more COVID-19 surges at the same location to achieve full enrollment and to find answers about what treatments are effective for this disease. This paper proposes an innovative approach for pooling patient-level data from multiple ongoing randomized clinical trials (RCTs) that have not been configured as a network of sites. We present the statistical analysis plan of a prospective individual patient data (IPD) meta-analysis (MA) from ongoing RCTs of convalescent plasma (CP). We employ an adaptive Bayesian approach for continuously monitoring the accumulating pooled data via posterior probabilities for safety, efficacy, and harm. Although we focus on RCTs for CP and address specific challenges related to CP treatment for COVID-19, the proposed framework is generally applicable to pooling data from RCTs for other therapies and disease settings in order to find answers in weeks or months, rather than years.

中文翻译：

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前瞻性个体患者数据荟萃分析：评估 COVID-19 的恢复期血浆

随着世界在 2019 年末和 2020 年初面临 COVID-19 大流行的破坏，许多地方启动了许多临床试验，以努力确定潜在治疗的有效性（或缺乏有效性）。由于大流行正在迅速转移地点，由于在参与地点遇到的符合条件的 COVID-19 患者数量下降，个别研究面临未能达到招募目标的风险。很明显，可能需要在同一地点再进行几次 COVID-19 激增才能实现全面注册并找到有关哪些治疗对这种疾病有效的答案。本文提出了一种创新方法，用于汇集来自多个未配置为站点网络的正在进行的随机临床试验 (RCT) 的患者水平数据。我们提出了来自正在进行的恢复期血浆 (CP) 随机对照试验的前瞻性个体患者数据 (IPD) 荟萃分析 (MA) 的统计分析计划。我们采用自适应贝叶斯方法通过安全性、有效性和危害性的后验概率持续监控累积的汇总数据。尽管我们专注于 CP 的 RCT 并解决与 COVID-19 的 CP 治疗相关的具体挑战，但建议的框架通常适用于汇集来自其他疗法和疾病环境的 RCT 数据，以便在数周或数月内找到答案，而不是数年. 功效和危害。尽管我们专注于 CP 的 RCT 并解决与 COVID-19 的 CP 治疗相关的具体挑战，但建议的框架通常适用于汇集来自其他疗法和疾病环境的 RCT 数据，以便在数周或数月内找到答案，而不是数年. 功效和危害。尽管我们专注于 CP 的 RCT 并解决与 COVID-19 的 CP 治疗相关的具体挑战，但建议的框架通常适用于汇集来自其他疗法和疾病环境的 RCT 数据，以便在数周或数月内找到答案，而不是数年.