Dataset Information

A Parsimonious Host Inflammatory Biomarker Signature Predicts Incident Tuberculosis and Mortality in Advanced Human Immunodeficiency Virus.

ABSTRACT:

Background

People with advanced human immunodeficiency virus (HIV) (CD4 < 50) remain at high risk of tuberculosis (TB) or death despite the initiation of antiretroviral therapy (ART). We aimed to identify immunological profiles that were most predictive of incident TB disease and death.

Methods

The REMEMBER randomized clinical trial enrolled 850 participants with HIV (CD4 < 50 cells/µL) at ART initiation to receive either empiric TB treatment or isoniazid preventive therapy (IPT). A case-cohort study (n = 257) stratified by country and treatment arm was performed. Cases were defined as incident TB or all-cause death within 48 weeks after ART initiation. Using multiplexed immunoassay panels and ELISA, 26 biomarkers were assessed in plasma.

Results

In total, 52 (6.1%) of 850 participants developed TB; 47 (5.5%) died (13 of whom had antecedent TB). Biomarkers associated with incident TB overlapped with those associated with death (interleukin [IL]-1β, IL-6). Biomarker levels declined over time in individuals with incident TB while remaining persistently elevated in those who died. Dividing the cohort into development and validation sets, the final model of 6 biomarkers (CXCL10, IL-1β, IL-10, sCD14, tumor necrosis factor [TNF]-α, and TNF-β) achieved a sensitivity of 0.90 (95% confidence interval [CI]: .87-.94) and a specificity of 0.71(95% CI: .68-.75) with an area under the curve (AUC) of 0.81 (95% CI: .78-.83) for incident TB.

Conclusion

Among people with advanced HIV, a parsimonious inflammatory biomarker signature predicted those at highest risk for developing TB despite initiation of ART and TB preventive therapies. The signature may be a promising stratification tool to select patients who may benefit from increased monitoring and novel interventions.

Clinical trials registration

NCT01380080.

SUBMITTER: Manabe YC

PROVIDER: S-EPMC7744990 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

A Parsimonious Host Inflammatory Biomarker Signature Predicts Incident Tuberculosis and Mortality in Advanced Human Immunodeficiency Virus.

Manabe Yukari C YC Andrade Bruno B BB Gupte Nikhil N Leong Samantha S Kintali Manisha M Matoga Mitch M Riviere Cynthia C Samaneka Wadzanai W Lama Javier R JR Naidoo Kogieleum K Zhao Yue Y Johnson W Evan WE Ellner Jerrold J JJ Hosseinipour Mina C MC Bisson Gregory P GP Salgame Padmini P Gupta Amita A

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20201201 10

<h4>Background</h4>People with advanced human immunodeficiency virus (HIV) (CD4 < 50) remain at high risk of tuberculosis (TB) or death despite the initiation of antiretroviral therapy (ART). We aimed to identify immunological profiles that were most predictive of incident TB disease and death.<h4>Methods</h4>The REMEMBER randomized clinical trial enrolled 850 participants with HIV (CD4 < 50 cells/µL) at ART initiation to receive either empiric TB treatment or isoniazid preventive therapy (IPT). ...[more]

PMID: 31761933

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Project description:ImportanceBiomarkers would greatly assist decision making in the diagnosis, prevention and treatment of chronic pain.ObjectiveThe present study aimed to undertake analytical validation of a sensorimotor cortical biomarker signature for pain consisting of two measures: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME).DesignIn this cohort study (recruitment period: November 2020-October 2022), participants experienced a model of prolonged temporomandibular pain with outcomes collected over 30 days. Electroencephalography (EEG) to assess PAF and transcranial magnetic stimulation (TMS) to assess CME were recorded on Days 0, 2 and 5. Pain was assessed twice daily from Days 1-30.SettingData collection occurred at a single centre: Neuroscience Research Australia.ParticipantsWe enrolled 159 healthy participants (through notices placed online and at universities across Australia), aged 18-44 with no history of chronic pain, neurological or psychiatric condition. 150 participants completed the protocol.ExposureParticipants received an injection of nerve growth factor (NGF) to the right masseter muscle on Days 0 and 2 to induce prolonged temporomandibular pain lasting up to 4 weeks.Main outcomes and measuresWe determined the predictive accuracy of the PAF/CME biomarker signature using a nested control-test scheme: machine learning models were run on a training set (n = 100), where PAF and CME were predictors and pain sensitivity was the outcome. The winning classifier was assessed on a test set (n = 50) comparing the predicted pain labels against the true labels.ResultsThe final sample consisted of 66 females and 84 males with a mean age of 25.1 ± 6.2. The winning classifier was logistic regression, with an outstanding area under the curve (AUC=1.00). The locked model assessed on the test set had excellent performance (AUC=0.88[0.78-0.99]). Results were reproduced across a range of methodological parameters. Moreover, inclusion of sex and pain catastrophizing as covariates did not improve model performance, suggesting the model including biomarkers only was more robust. PAF and CME biomarkers showed good-excellent test-retest reliability.Conclusions and relevanceThis study provides evidence for a sensorimotor cortical biomarker signature for pain sensitivity. The combination of accuracy, reproducibility, and reliability, suggests the PAF/CME biomarker signature has substantial potential for clinical translation, including predicting the transition from acute to chronic pain.

Dataset Information

A Parsimonious Host Inflammatory Biomarker Signature Predicts Incident Tuberculosis and Mortality in Advanced Human Immunodeficiency Virus.

Background

Methods

Results

Conclusion

Clinical trials registration

Publications

A Parsimonious Host Inflammatory Biomarker Signature Predicts Incident Tuberculosis and Mortality in Advanced Human Immunodeficiency Virus.

Similar Datasets

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