{"title":"埃塞俄比亚接受抗逆转录病毒疗法的艾滋病毒感染成人中经细菌学确诊的结核病的风险评分预测:预后模型的开发。","authors":"Nebiyu Mekonnen Derseh, Muluken Chanie Agimas, Tigabu Kidie Tesfie","doi":"10.1097/QAD.0000000000003917","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":7502,"journal":{"name":"AIDS","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Risk score prediction for bacteriologically confirmed tuberculosis among adults with HIV on antiretroviral therapy in northwest Ethiopia: prognostic model development.\",\"authors\":\"Nebiyu Mekonnen Derseh, Muluken Chanie Agimas, Tigabu Kidie Tesfie\",\"doi\":\"10.1097/QAD.0000000000003917\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":7502,\"journal\":{\"name\":\"AIDS\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AIDS\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/QAD.0000000000003917\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/4/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIDS","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/QAD.0000000000003917","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/24 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Risk score prediction for bacteriologically confirmed tuberculosis among adults with HIV on antiretroviral therapy in northwest Ethiopia: prognostic model development.
Objective: 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.
Methods: 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.
Results: 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.
Conclusion: 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.
期刊介绍:
Publishing the very latest ground breaking research on HIV and AIDS. Read by all the top clinicians and researchers, AIDS has the highest impact of all AIDS-related journals. With 18 issues per year, AIDS guarantees the authoritative presentation of significant advances. The Editors, themselves noted international experts who know the demands of your work, are committed to making AIDS the most distinguished and innovative journal in the field. Submitted articles undergo a preliminary review by the editor. Some articles may be returned to authors without further consideration. Those being considered for publication will undergo further assessment and peer-review by the editors and those invited to do so from a reviewer pool.