Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
AIDS. 2024 Jul 15;38(9):1333-1341. doi: 10.1097/QAD.0000000000003917. Epub 2024 Apr 24.
This study was aimed at developing a risk score prediction model for bacteriologically confirmed tuberculosis (TB) among adults with HIV receiving antiretroviral therapy in Ethiopia.
An institutional-based retrospective follow-up study was conducted among 569 adults with HIV on ART. We used demographic and clinical prognostic factors to develop a risk prediction model. Model performance was evaluated by discrimination and calibration using the area under the receiver operating characteristic (AUROC) curve and calibration plot. Bootstrapping was used for internal validation. A decision curve analysis was used to evaluate the clinical utility.
Opportunistic infection, functional status, anemia, isoniazid preventive therapy, and WHO clinical stages were used to develop risk prediction. The AUROC curve of the original model was 87.53% [95% confidence interval (CI): 83.88-91.25] and the calibration plot ( P -value = 0.51). After internal validation, the AUROC curve of 86.61% (95% CI: 82.92-90.29%) was comparable with the original model, with an optimism coefficient of 0.0096 and good calibration ( P -value = 0.10). Our model revealed excellent sensitivity (92.65%) and negative predictive value (NPV) (98.60%) with very good specificity (70.06%) and accuracy (72.76%). After validation, accuracy (74.85%) and specificity (76.27%) were improved, but sensitivity (86.76%) and NPV (97.66%) were relatively reduced. The risk prediction model had a net benefit up to 7.5 threshold probabilities.
This prognostic model had very good performance. Moreover, it had very good sensitivity and excellent NPV. The model could help clinicians use risk estimation and stratification for early diagnosis and treatment to improve patient outcomes and quality of life.
本研究旨在为在埃塞俄比亚接受抗逆转录病毒治疗的 HIV 成人中建立一个用于预测经细菌学证实的结核(TB)风险的评分预测模型。
对 569 名接受 ART 的 HIV 成人进行了基于机构的回顾性随访研究。我们使用人口统计学和临床预后因素来建立风险预测模型。使用接受者操作特征(ROC)曲线和校准图下的面积(AUROC)评估模型性能。使用 Bootstrap 进行内部验证。使用决策曲线分析来评估临床实用性。
机会性感染、功能状态、贫血、异烟肼预防治疗和世界卫生组织临床分期用于开发风险预测。原始模型的 AUROC 曲线为 87.53%(95%置信区间[CI]:83.88-91.25),校准图(P 值=0.51)。经过内部验证,86.61%(95%CI:82.92-90.29%)的 AUROC 曲线与原始模型相当,具有 0.0096 的乐观系数和良好的校准(P 值=0.10)。我们的模型具有出色的敏感性(92.65%)和阴性预测值(NPV)(98.60%),同时具有非常好的特异性(70.06%)和准确性(72.76%)。验证后,准确性(74.85%)和特异性(76.27%)有所提高,但敏感性(86.76%)和 NPV(97.66%)相对降低。风险预测模型在 7.5 个阈值概率下具有净收益。
该预后模型具有非常好的性能。此外,它具有非常好的敏感性和出色的 NPV。该模型可以帮助临床医生使用风险评估和分层进行早期诊断和治疗,以改善患者的结局和生活质量。