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Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study

BACKGROUND: Severe malaria is a leading cause of childhood mortality in Africa. However, at presentation, it is difficult to predict which children with severe malaria are at greatest risk of death. Dysregulated host inflammatory responses and endothelial activation play central roles in severe mala...

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Autores principales: Erdman, Laura K., Dhabangi, Aggrey, Musoke, Charles, Conroy, Andrea L., Hawkes, Michael, Higgins, Sarah, Rajwans, Nimerta, Wolofsky, Kayla T., Streiner, David L., Liles, W. Conrad, Cserti-Gazdewich, Christine M., Kain, Kevin C.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3045453/
https://www.ncbi.nlm.nih.gov/pubmed/21364762
http://dx.doi.org/10.1371/journal.pone.0017440
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author Erdman, Laura K.
Dhabangi, Aggrey
Musoke, Charles
Conroy, Andrea L.
Hawkes, Michael
Higgins, Sarah
Rajwans, Nimerta
Wolofsky, Kayla T.
Streiner, David L.
Liles, W. Conrad
Cserti-Gazdewich, Christine M.
Kain, Kevin C.
author_facet Erdman, Laura K.
Dhabangi, Aggrey
Musoke, Charles
Conroy, Andrea L.
Hawkes, Michael
Higgins, Sarah
Rajwans, Nimerta
Wolofsky, Kayla T.
Streiner, David L.
Liles, W. Conrad
Cserti-Gazdewich, Christine M.
Kain, Kevin C.
author_sort Erdman, Laura K.
collection PubMed
description BACKGROUND: Severe malaria is a leading cause of childhood mortality in Africa. However, at presentation, it is difficult to predict which children with severe malaria are at greatest risk of death. Dysregulated host inflammatory responses and endothelial activation play central roles in severe malaria pathogenesis. We hypothesized that biomarkers of these processes would accurately predict outcome among children with severe malaria. METHODOLOGY/FINDINGS: Plasma was obtained from children with uncomplicated malaria (n = 53), cerebral malaria (n = 44) and severe malarial anemia (n = 59) at time of presentation to hospital in Kampala, Uganda. Levels of angiopoietin-2, von Willebrand Factor (vWF), vWF propeptide, soluble P-selectin, soluble intercellular adhesion molecule-1 (ICAM-1), soluble endoglin, soluble FMS-like tyrosine kinase-1 (Flt-1), soluble Tie-2, C-reactive protein, procalcitonin, 10 kDa interferon gamma-induced protein (IP-10), and soluble triggering receptor expressed on myeloid cells-1 (TREM-1) were determined by ELISA. Receiver operating characteristic (ROC) curve analysis was used to assess predictive accuracy of individual biomarkers. Six biomarkers (angiopoietin-2, soluble ICAM-1, soluble Flt-1, procalcitonin, IP-10, soluble TREM-1) discriminated well between children who survived severe malaria infection and those who subsequently died (area under ROC curve>0.7). Combinational approaches were applied in an attempt to improve accuracy. A biomarker score was developed based on dichotomization and summation of the six biomarkers, resulting in 95.7% (95% CI: 78.1–99.9) sensitivity and 88.8% (79.7–94.7) specificity for predicting death. Similar predictive accuracy was achieved with models comprised of 3 biomarkers. Classification tree analysis generated a 3-marker model with 100% sensitivity and 92.5% specificity (cross-validated misclassification rate: 15.4%, standard error 4.9%). CONCLUSIONS: We identified novel host biomarkers of pediatric severe and fatal malaria (soluble TREM-1 and soluble Flt-1) and generated simple biomarker combinations that accurately predicted death in an African pediatric population. While requiring validation in further studies, these results suggest the utility of combinatorial biomarker strategies as prognostic tests for severe malaria.
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spelling pubmed-30454532011-03-01 Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study Erdman, Laura K. Dhabangi, Aggrey Musoke, Charles Conroy, Andrea L. Hawkes, Michael Higgins, Sarah Rajwans, Nimerta Wolofsky, Kayla T. Streiner, David L. Liles, W. Conrad Cserti-Gazdewich, Christine M. Kain, Kevin C. PLoS One Research Article BACKGROUND: Severe malaria is a leading cause of childhood mortality in Africa. However, at presentation, it is difficult to predict which children with severe malaria are at greatest risk of death. Dysregulated host inflammatory responses and endothelial activation play central roles in severe malaria pathogenesis. We hypothesized that biomarkers of these processes would accurately predict outcome among children with severe malaria. METHODOLOGY/FINDINGS: Plasma was obtained from children with uncomplicated malaria (n = 53), cerebral malaria (n = 44) and severe malarial anemia (n = 59) at time of presentation to hospital in Kampala, Uganda. Levels of angiopoietin-2, von Willebrand Factor (vWF), vWF propeptide, soluble P-selectin, soluble intercellular adhesion molecule-1 (ICAM-1), soluble endoglin, soluble FMS-like tyrosine kinase-1 (Flt-1), soluble Tie-2, C-reactive protein, procalcitonin, 10 kDa interferon gamma-induced protein (IP-10), and soluble triggering receptor expressed on myeloid cells-1 (TREM-1) were determined by ELISA. Receiver operating characteristic (ROC) curve analysis was used to assess predictive accuracy of individual biomarkers. Six biomarkers (angiopoietin-2, soluble ICAM-1, soluble Flt-1, procalcitonin, IP-10, soluble TREM-1) discriminated well between children who survived severe malaria infection and those who subsequently died (area under ROC curve>0.7). Combinational approaches were applied in an attempt to improve accuracy. A biomarker score was developed based on dichotomization and summation of the six biomarkers, resulting in 95.7% (95% CI: 78.1–99.9) sensitivity and 88.8% (79.7–94.7) specificity for predicting death. Similar predictive accuracy was achieved with models comprised of 3 biomarkers. Classification tree analysis generated a 3-marker model with 100% sensitivity and 92.5% specificity (cross-validated misclassification rate: 15.4%, standard error 4.9%). CONCLUSIONS: We identified novel host biomarkers of pediatric severe and fatal malaria (soluble TREM-1 and soluble Flt-1) and generated simple biomarker combinations that accurately predicted death in an African pediatric population. While requiring validation in further studies, these results suggest the utility of combinatorial biomarker strategies as prognostic tests for severe malaria. Public Library of Science 2011-02-25 /pmc/articles/PMC3045453/ /pubmed/21364762 http://dx.doi.org/10.1371/journal.pone.0017440 Text en Erdman et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Erdman, Laura K.
Dhabangi, Aggrey
Musoke, Charles
Conroy, Andrea L.
Hawkes, Michael
Higgins, Sarah
Rajwans, Nimerta
Wolofsky, Kayla T.
Streiner, David L.
Liles, W. Conrad
Cserti-Gazdewich, Christine M.
Kain, Kevin C.
Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study
title Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study
title_full Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study
title_fullStr Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study
title_full_unstemmed Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study
title_short Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study
title_sort combinations of host biomarkers predict mortality among ugandan children with severe malaria: a retrospective case-control study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3045453/
https://www.ncbi.nlm.nih.gov/pubmed/21364762
http://dx.doi.org/10.1371/journal.pone.0017440
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