Two Clinical Prediction Tools to Improve Tuberculosis Contact Investigation.

Two Clinical Prediction Tools to Improve Tuberculosis Contact Investigation.
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DOI:
10.1093/cid/ciz1221
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发表时间:
2020-11-05
期刊:
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
影响因子:
--
通讯作者:
Murray MB
Murray MB
中科院分区:
其他
文献类型:
--
作者:
Li R;Nordio F;Huang CC;Contreras C;Calderon R;Yataco R;Galea JT;Zhang Z;Becerra MC;Lecca L;Murray MB

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有效的接触者调查策略是早期诊断结核病和治疗潜伏性结核感染所必需的。2009年9月至2012年8月,我们在秘鲁利马进行了一项前瞻性队列研究,招募并随访了14044名成人肺结核家庭接触者。我们使用来自该队列子集的信息,通过训练多变量模型,得出两种临床预测工具,通过预测(1)所有家庭接触者的共价结核和(2)成人接触者1年的结核病事件,确定结核病患者进展为活动性疾病风险升高的接触者。我们在一个地理位置不同的亚队列中验证了这些模型,并比较了基于这些工具和现有策略的临床决策的相对效用。在我们的队列中,296名(2.1%)家庭接触者患有共价结核,145名(1.9%)成人接触者在指标患者诊断后1年内发生结核。我们预测共价疾病时,使用的信息可以很容易地获得时,一个索引患者被诊断和预测1年的结核事件,包括额外的接触特异性特征。共价结核和事件结核患者工作特征曲线下面积为0.86(95%可信区间[CI], 0.83 -。[89])和0.72 (95% CI, 0.67 -)。分别为77)。这些临床工具的相对效用比现有方法高5%-10%。我们提出两种工具,仅根据来自患者和接触者的可报告信息确定结核病高危家庭接触者。这些工具的性能与生物标记物相当,而生物标记物比这种方法成本更高,可行性也更低。我们开发并验证了2种临床预测工具,利用从患者和家庭接触者获得的临床和人口统计信息来识别结核病高危接触者。这些工具的功能与成本更高、可行性更低的生物标志物类似。
Efficient contact investigation strategies are needed for the early diagnosis of tuberculosis (TB) disease and treatment of latent TB infections. Between September 2009 and August 2012, we conducted a prospective cohort study in Lima, Peru, in which we enrolled and followed 14 044 household contacts of adults with pulmonary TB. We used information from a subset of this cohort to derive 2 clinical prediction tools that identify contacts of TB patients at elevated risk of progressing to active disease by training multivariable models that predict (1) coprevalent TB among all household contacts and (2) 1-year incident TB among adult contacts. We validated the models in a geographically distinct subcohort and compared the relative utilities of clinical decisions based on these tools to existing strategies. In our cohort, 296 (2.1%) household contacts had coprevalent TB and 145 (1.9%) adult contacts developed incident TB within 1 year of index patient diagnosis. We predicted coprevalent disease using information that could be readily obtained at the time an index patient was diagnosed and predicted 1-year incident TB by including additional contact-specific characteristics. The area under the receiver operating characteristic curves for coprevalent TB and incident TB were 0.86 (95% confidence interval [CI], .83–.89]) and 0.72 (95% CI, .67–.77), respectively. These clinical tools give 5%–10% higher relative utilities than existing methods. We present 2 tools that identify household contacts at high risk for TB disease based on reportable information from patient and contacts alone. The performance of these tools is comparable to biomarkers that are both more costly and less feasible than this approach. We developed and validated 2 clinical prediction tools to identify contacts at high risk for tuberculosis disease using clinical and demographic information obtained from the patient and household contact. These tools perform similarly to more costly and less feasible biomarkers.
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