开发和验证贝叶斯临床风险预测模型,用于两个加拿大省份的关键人群中的三个性传播感染
Fiorella Vialard1,2, Qihuang Zhang1,3, Duncan Webster4
1School of Population and Global Health, McGill University, Montreal, Quebec, Canada.
Sexually transmitted infections
|April 24, 2025
概括
一种新的临床风险预测模型有效地识别了艾滋病毒,C型肝炎病毒 (HCV) 和梅毒的高风险个体. 过去的注射药物和以前的性传播感染是关键预测因素,改善了加拿大的STBBI查策略.
科学领域:
- 公共卫生 公共卫生
- 传染性疾病 传染性疾病
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 过去十年来,包括梅毒,型肝炎病毒 (HCV) 和艾滋病毒在内的性传播和血液感染 (STBBI) 在加拿大发生率上升或停滞.
- 关键人群,如同性恋,双性恋和其他与男性发生性关系的男性,跨性别和性别多元的个人,以及注射毒品的人面临不成比例地更高的STBBI风险.
- 准确的风险预测对于针对性查和在这些弱势群体中有效管理STBBIs至关重要.
研究的目的:
- 开发和验证诊断临床风险预测模型 (CRPM) 以估计艾滋病毒,HCV和梅毒的风险.
- 评估该模型在两个加拿大省份的关键人口中识别高风险个人的表现.
主要方法:
- 一项涉及新不伦瑞克省和北克省400名参与者的横截面研究进行,收集了20个变量和STBBI测试结果的数据.
- 数据被随机分为开发 (n=300) 和验证 (n=100) 数据集,使用临床分层抽样.
- 贝叶斯预测投影被用于预测器选择,模型性能使用接收器操作曲线 (AUC) 下的面积,灵敏度和特异性进行评估.
主要成果:
- 在400名参与者中,有73人感染了HIV (16),HCV (60),和/或梅毒 (5).
- 一个内部验证的子模型,包括"过去的药物注射"和"过去的性传播感染类型",表现强 (AUC: 0.79,敏感性: 0.85,特异性: 0.30).
- "过去的药物注射"成为STBBI风险的最重要的预测因素,其概率比率为7.62.
结论:
- 开发的基于贝叶斯的CRPM是第一个有效识别艾滋病毒,HCV和梅毒高风险个体的模型,表现出良好的整体表现并最大限度地减少遗漏病例.
- 这种模型显示出作为一种用于预先选关键人群的新工具的前景.
- 进一步验证可能会导致加拿大STBBI多重查策略的改进.
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