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  • 學位論文

人類免疫不全病毒感染者之潛伏性結核感染

Latent Tuberculosis Infection in HIV-infected persons

指導教授 : 方啟泰

摘要


背景: 目前缺乏單一檢驗方法來預測人類免疫病毒(HIV)感染者得到結核病的風險。我們發展和驗證了一個臨床風險評估流程,利用CD4細胞數目,HIV病毒載量 (pVL),和丙型干擾素釋放檢驗(IGRA),來辨識在低到中負荷結核病情境,且已接受高效能抗反轉錄酶病毒治療(HAART)之HIV感染者,那些人具有得到結核病的高風險。 方法: 此為前瞻性五年之世代研究,在兩家醫院之HIV感染者進行,研究時間為2006年至2012年。HAART的啟用依據當時的治療準則(CD4細胞數目<=350/μL)。我們使用Cox迴歸分析來找出活動性結核的預測因子並建立評估流程。採用之驗證世代包括1455位已在國際雜誌發表之研究中的HIV感染者。我們計算模式以操作特徵曲線下面積(area under the receiver operating characteristic (ROC)curve)進行。 結論: 總共772位進入研究追蹤中位數為5.21年,其中17位發生活動性結核。CD4細胞數 < 350/μL 或 pVL ≥ 100,000/mL可以預測活動性結核發生(adjusted HR 4.87, 95% CI 1.49-15.90, P=0.009)。在CD4 ≥ 350/μL或 pVL < 100,000/mL (adjusted HR 6.09, 95% CI 1.52-24.40, P=0.01)的條件下,IGRA的結果陽性能正確預測潛伏性結核感染。比起僅使用IGRA的策略,此評估流程可使敏感度增加從37.5%到76.5%, 陰性預測值可增加從98.5%至99.2%。比起全面預防性治療策略,此評估流程可以避免468 (60.6%)人接受到不需要的結核病預防性治療。本研究世代的操作特徵曲線下面積為0.692 (95% CI: 0.587-0.798) ,在兩個驗證世代中分別為0.792 (95% CI: 0.776-0.808) 和0.766。 結論: 一個經過驗證的評估流程,包含CD4細胞數目,HIV病毒載量,和IGRA結果可以應用在低到中度結核病負荷情境,針對有例行接受HAART的HIV感染者,來引導結核病預防性治療的給予。此評估流程的實施將可避免低風險病患曝觸到不需要的藥物毒性,同時減少全面治療造成的醫療系統的負荷。

並列摘要


Background: Predicting the risk of tuberculosis (TB) in people living with HIV (PLHIV) using a single test is currently not possible. We aimed to develop and validate a clinical algorithm, using baseline CD4 cell counts, HIV viral load (pVL), and interferon-gamma release assay (IGRA), to identify PLHIV who are at high risk for incident active TB in low-to-moderate TB burden settings where highly active antiretroviral therapy (HAART) is routinely provided. Methods: A prospective, 5-year, cohort study of adult PLHIV was conducted from 2006 to 2012 in two hospitals in Taiwan. HAART was initiated based on contemporary guidelines (CD4 count <= 350/μL). Cox regression was used to identify the predictors of active TB and to construct the algorithm. The validation cohorts included 1455 HIV-infected individuals from previous published studies. Area under the receiver operating characteristic (ROC) curve was calculated. Results: Seventeen of 772 participants developed active TB during a median follow-up period of 5.21 years. Baseline CD4 < 350/μL or pVL ≥ 100,000/mL was a predictor of active TB (adjusted HR 4.87, 95% CI 1.49-15.90, P=0.009). A positive baseline IGRA predicted TB in patients with baseline CD4 ≥ 350/μL and pVL < 100,000/mL (adjusted HR 6.09, 95% CI 1.52-24.40, P=0.01). Compared with an IGRA-alone strategy, the algorithm improved the sensitivity from 37.5% to 76.5%, the negative predictive value from 98.5% to 99.2%. Compared with an untargeted strategy, the algorithm spared 468 (60.6%) from unnecessary TB preventive treatment. Area under the ROC curve was 0.692 (95% CI: 0.587-0.798) for the study cohort and 0.792 (95% CI: 0.776-0.808) and 0.766 in the 2 validation cohorts. Conclusions: A validated algorithm incorporating the baseline CD4 cell count, HIV viral load, and IGRA status can be used to guide targeted TB preventive treatment in PLHIV in low-to-moderate TB burden settings where HAART is routinely provided to all PLHIV. The implementation of this algorithm will avoid unnecessary exposure of low-risk patients to drug toxicity and simultaneously, reduce the burden of universal treatment on the healthcare system.

並列關鍵字

latent tuberculosis HIV IGRA algorithm

參考文獻


18. Centers for Disease Control R.O.C. (Taiwan). Taiwan Tuberculosis Control Report 2013. Taipei: Taiwan Center for Disease Control,
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