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比较传统的多变量模型和七种基于倾向分数的模型的结果,以估计COVID-19疫苗的有效性
Daniele Petrone1, Chiara Sacco1, Alberto Mateo-Urdiales1
1Dipartimento di Malattie Infettive, Istituto Superiore di Sanità, Rome, Italy.
Annali dell'Istituto superiore di sanita
|December 15, 2025
概括
在老年人中估计疫苗有效性 (VE) 是至关重要的. 多变量考克斯模型被证明与倾向得分方法一样可靠,用于评估双价mRNA疫苗.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 疫苗学 疫苗学 疫苗学
背景情况:
- 准确的疫苗有效性 (VE) 估计对于公共卫生至关重要,特别是在老年人群中.
- 观察性研究面临偏见的挑战,统计方法对 VE 结果产生影响.
- 评估新的疫苗助推剂需要强大的分析方法.
研究的目的:
- 将多变量Cox模型与基于倾向分数 (PS) 的方法进行比较,以估计VE.
- 为了评估二价mRNA助推剂 (原始/欧米克朗BA.4-5) 的相对疫苗有效性 (rVE),作为第二剂或第三剂.
- 分析 VE 随着时间的推移的趋势,并评估不同的统计模型性能.
主要方法:
- 对多变量考克斯比例危险模型和七个基于PS的模型进行比较分析.
- 利用了意大利11,879,461名60岁以上的个人 (2023年4月至6月) 的现实数据.
- 估计了一种双价mRNA疫苗的rVE作为第二/第三次增剂,与之前接受≥120天的第一次增剂相比.
主要成果:
- 所有模型都产生了一致的rVE估计在16.4%和22.1%之间.
- 随着时间的推移,助推剂的有效性显著下降,从参考模型中的45.6% (15-60天) 下降到14.3% (181-265天).
- PS方法提高了共变量平衡,但在精度或可解释性方面没有超过考克斯模型.
结论:
- 多变量模型在大型,平衡的数据集中对 VE 估计具有稳定性.
- 倾向性评分方法提供理论上的好处,但在管理混时,可能不会在传统模型上提供实际优势.
- 这项研究证实了传统的统计方法对真实世界的疫苗有效性研究的可靠性.
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