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使用常规快速诊断测试数据对结核病耐药性的监测:巴西的方法开发和应用
Sarah E Baum1, Daniele M Pelissari2, Fernanda Dockhorn Costa2
1Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
PLoS computational biology
|December 23, 2024
概括
准确的耐药结核病监测至关重要. 这项研究提出了一种统计方法来纠正偏见的快速诊断测试数据,提供了更可靠的估计结核病患者的利芬辛耐药性.
科学领域:
- 流行病学 流行病学
- 传染性疾病 传染性疾病
- 公共卫生 公共卫生
背景情况:
- 准确监测耐药结核病 (TB) 对于有效控制至关重要.
- 估计抗利芬素耐药性的传统方法依赖于资源密集的调查.
- 常规使用快速诊断测试 (RDTs) 可能会产生偏见的耐药性估计,这是由于患者的非代表性选择.
研究的目的:
- 开发和验证一个统计方法来纠正RTD数据中的偏差.
- 为了获得新的和先前治疗的结核病例中对利芬辛耐药性的公正估计.
- 提高耐药结核病监测的及时性和准确性.
主要方法:
- 开发了一种层次化的通用增量回归模型.
- 使用常规 Xpert MTB/RIF 数据对模拟的利芬辛耐药性进行了统计纠正.
- 使用模型输出对未经测试的个体的假定抵抗结果.
- 利用了2017-2023年巴西超过80万名患者的病例级数据.
主要成果:
- 建模估计显示,与天真估计相比,里法辛耐药性患病率要高得多.
- 估计的患病率在新增病例中高出28%至44%,而在以前治疗过的病例中高出2至17%.
- 与世卫组织估计相比,估计的RR-TB发病率的不确定性间隔较窄.
- 该方法被证明对替代型号规格具有稳定性.
结论:
- 开发的方法有效地利用了常规的RDT数据,以进行无偏见的RR-TB流行率估计.
- 这种方法为非通用结核病耐药性测试的环境提供了可通用的解决方案.
- 为公共卫生干预提供更及时,更准确的估计,这对于公共卫生干预至关重要.
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