Vanobberghen Fiona, Keter Alfred Kipyegon, Jacobs Bart K M, Glass Tracy R, Lynen Lutgarde, Law Irwin, Murphy Keelin, van Ginneken Bram, Ayakaka Irene, van Heerden Alastair, Maama Llang, Reither Klaus
Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
University of Basel, Basel, Switzerland.
ERJ Open Res. 2024 Jan 8;10(1). doi: 10.1183/23120541.00508-2023. eCollection 2024 Jan.
Use of computer-aided detection (CAD) software is recommended to improve tuberculosis screening and triage, but threshold determination is challenging if reference testing has not been performed in all individuals. We aimed to determine such thresholds through secondary analysis of the 2019 Lesotho national tuberculosis prevalence survey.
Symptom screening and chest radiographs were performed in participants aged ≥15 years; those symptomatic or with abnormal chest radiographs provided samples for Xpert MTB/RIF and culture testing. Chest radiographs were processed using CAD4TB version 7. We used six methodological approaches to deal with participants who did not have bacteriological test results to estimate pulmonary tuberculosis prevalence and assess diagnostic accuracy.
Among 17 070 participants, 5214 (31%) had their tuberculosis status determined; 142 had tuberculosis. Prevalence estimates varied between methodological approaches (0.83-2.72%). Using multiple imputation to estimate tuberculosis status for those eligible but not tested, and assuming those not eligible for testing were negative, a CAD4TBv7 threshold of 13 had a sensitivity of 89.7% (95% CI 84.6-94.8) and a specificity of 74.2% (73.6-74.9), close to World Health Organization (WHO) target product profile criteria. Assuming all those not tested were negative produced similar results.
This is the first study to evaluate CAD4TB in a community screening context employing a range of approaches to account for unknown tuberculosis status. The assumption that those not tested are negative - regardless of testing eligibility status - was robust. As threshold determination must be context specific, our analytically straightforward approach should be adopted to leverage prevalence surveys for CAD threshold determination in other settings with a comparable proportion of eligible but not tested participants.
推荐使用计算机辅助检测（CAD）软件来改善结核病筛查和分流，但如果并非对所有个体都进行了参考检测，那么阈值确定具有挑战性。我们旨在通过对2019年莱索托全国结核病患病率调查进行二次分析来确定此类阈值。
对年龄≥15岁的参与者进行症状筛查和胸部X光检查；有症状或胸部X光异常的参与者提供样本进行Xpert MTB/RIF和培养检测。使用CAD4TB版本7对胸部X光片进行处理。我们采用六种方法来处理没有细菌学检测结果的参与者，以估计肺结核患病率并评估诊断准确性。
在17070名参与者中，5214名（31%）的结核病状况得以确定；142名患有结核病。患病率估计在不同方法之间有所不同（0.83%-2.72%）。对于符合条件但未检测的参与者，使用多重插补法估计结核病状况，并假设不符合检测条件的参与者为阴性，CAD4TBv7阈值为13时，灵敏度为89.7%（95%CI 84.6-94.8），特异度为74.2%（73.6-74.9），接近世界卫生组织（WHO）目标产品简介标准。假设所有未检测的参与者均为阴性产生了类似结果。
这是第一项在社区筛查背景下评估CAD4TB的研究，采用了一系列方法来处理未知的结核病状况。无论检测资格状态如何，假设未检测的参与者为阴性是可靠的。由于阈值确定必须因地制宜，应采用我们这种分析简单的方法，利用患病率调查来确定其他具有相当比例符合条件但未检测参与者的环境中的CAD阈值。
