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亚人群的因果推断:孕期接种疟疾疫苗对女性的影响。

Causal Inference Over a Subpopulation: The Effect of Malaria Vaccine in Women During Pregnancy.

机构信息

National Institute of Allergy and Infectious Diseases, National Institutes of Health, Maryland, USA.

出版信息

Stat Med. 2024 Nov 30;43(27):5193-5202. doi: 10.1002/sim.10228. Epub 2024 Oct 7.

DOI:10.1002/sim.10228
PMID:39375758
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11583954/
Abstract

Preventing malaria during pregnancy is of critical importance, yet there are no approved malaria vaccines for pregnant women due to lack of efficacy results within this population. Conducting a randomized trial in pregnant women throughout the entire duration of pregnancy is impractical. Instead, a randomized trial was conducted among women of childbearing potential (WOCBP), and some participants became pregnant during the 2-year study. We explore a statistical method for estimating vaccine effect within the target subpopulation-women who can naturally become pregnant, namely, women who can become pregnant under a placebo condition-within the causal inference framework. Two vaccine effect estimators are employed to effectively utilize baseline characteristics and account for the fact that certain baseline characteristics were only available from pregnant participants. The first estimator considers all participants but can only utilize baseline variables collected from the entire participant pool. In contrast, the second estimator, which includes only pregnant participants, utilizes all available baseline information. Both estimators are evaluated numerically through simulation studies and applied to the WOCBP trial to assess vaccine effect against pregnancy malaria.

摘要

在怀孕期间预防疟疾至关重要,但由于在这一人群中缺乏疗效结果,因此没有针对孕妇的经批准的疟疾疫苗。在整个怀孕期间对孕妇进行随机试验是不切实际的。相反,在育龄妇女(WOCBP)中进行了一项随机试验,一些参与者在 2 年的研究期间怀孕。我们在因果推理框架内探讨了一种针对目标亚人群(即可以在安慰剂条件下自然怀孕的妇女)的疫苗效果估计的统计方法。两种疫苗效果估计器可有效地利用基线特征,并考虑到某些基线特征仅可从怀孕参与者处获得的事实。第一个估计器考虑了所有参与者,但只能利用从整个参与者群体中收集的基线变量。相比之下,第二个仅包括怀孕参与者的估计器利用了所有可用的基线信息。通过模拟研究对这两个估计器进行了数值评估,并将其应用于 WOCBP 试验,以评估针对妊娠疟疾的疫苗效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/7b8b486ea7c7/SIM-43-5193-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/b1cab0b2d2a2/SIM-43-5193-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/78cba97acb01/SIM-43-5193-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/e605c5610b13/SIM-43-5193-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/e8656108a8da/SIM-43-5193-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/7b8b486ea7c7/SIM-43-5193-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/b1cab0b2d2a2/SIM-43-5193-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/78cba97acb01/SIM-43-5193-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/e605c5610b13/SIM-43-5193-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/e8656108a8da/SIM-43-5193-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e759/11583954/7b8b486ea7c7/SIM-43-5193-g002.jpg

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