sTREM-1: A Biomarker of Mortality in Severe Malaria Impacted by Acute Kidney Injury

Abstract

Background: Malaria is an important cause of mortality in African children. Identification of biomarkers to identify children at risk of mortality has the potential to improve outcomes.

Methods: We evaluated 11 biomarkers of host response in 592 children with severe malaria. The primary outcome was biomarker performance for predicting mortality. Biomarkers were evaluated using receiver operating characteristic (ROC) curve analysis comparing the area under the ROC curve (AUROC).

Results: Mortality was 7.3% among children in the study with 72% of deaths occurring within 24 hours of admission. Among the candidate biomarkers, soluble triggering receptor expressed on myeloid cells 1 (sTREM-1) had the highest AUROC (0.78 [95% confidence interval, .70-.86]), outperforming several other biomarkers including C-reactive protein and procalcitonin. sTREM-1 was the top-performing biomarker across prespecified subgroups (malaria definition, site, sex, nutritional status, age). Using established cutoffs, we evaluated mortality across sTREM-1 risk zones. Among children with acute kidney injury, 39.9% of children with a critical-risk sTREM-1 result had an indication for dialysis. When evaluated relative to a disease severity score, sTREM-1 improved mortality prediction (difference in AUROC, P = .016).

Conclusions: sTREM-1 is a promising biomarker to guide rational allocation of clinical resources and should be integrated into clinical decision support algorithms, particularly when acute kidney injury is suspected.

Keywords: acute kidney injury; mortality; risk stratification; sTREM-1; severe malaria.

Figure 1.

Flowchart of study population. A, Study flowchart showing participant enrollment by site and the corresponding mortality rate. B, Kernel density plots showing the distribution of candidate biomarkers of mortality in critical illness–based clinical outcome (survivors on bottom, deaths on top) by category: those already in clinical use (C-reactive protein [CRP], procalcitonin), immune activation (soluble triggering receptor expressed on myeloid cells 1 [sTREM-1], chitinase-3-like 1 [CHI3L1], soluble tumor necrosis factor receptor 1 [sTNFR-1], interleukin 8 [IL-8], interleukin 6 [IL-6]), and endothelial activation (angiopoietin 2 [Angpt-2], soluble fms-like tyrosine kinase 1 [sFlt-1], soluble vascular cellular adhesion molecule 1 [sVCAM-1], soluble intercellular adhesion molecule 1 [sICAM-1]). C, A priori–defined subgroup analyses to evaluate the performance of biomarkers based on site, sex, nutritional status (stunting), age, and clinical complications (coma, anemia, acute kidney injury, acidosis).

Figure 2.

Performance of mortality biomarkers by subgroup. Plots display the area under the receiver operating characteristic curve (AUROC with 95% confidence interval) for each subgroup according to severe malaria definition, site, sex, nutritional status, and age category. The light blue–shaded area represents improved performance (AUROC >0.70). The dotted black line represents an AUROC of 0.50. Differences between triggering receptor expressed on myeloid cells 1 (sTREM-1) as the top-ranking marker and other biomarkers were tested, and an asterisk (*) and lighter color shade indicate the AUROC is significantly lower than that of sTREM-1 (P < .05). The difference in effects of biomarker levels (log₁₀-transformed) on mortality between subgroups were tested using binary logistic regression models with interaction terms between biomarker and subgroup, with daggers (†) indicating a significant interaction (P < .05). Data are also presented in Supplementary Table 1. Abbreviations: Angpt-2, angiopoietin 2; AUROC, area under the receiver operating characteristic curve; CHI3L1, chitinase-3-like 1; CI, confidence interval; CRP, C-reactive protein; IL-6, interleukin 6; IL-8, interleukin 8; sFlt-1, soluble fms-like tyrosine kinase 1; sICAM-1, soluble intercellular adhesion molecule 1; SM, severe malaria; sTNFR-1, soluble tumor necrosis factor receptor 1; sTREM-1, soluble triggering receptor expressed on myeloid cells 1; sVCAM-1, soluble vascular cellular adhesion molecule 1.

Figure 3.

Performance of mortality biomarkers in clinical subgroups. Plots display the area under the receiver operating characteristic curve (AUROC with 95% confidence interval) for each clinical subgroup according to coma, severe malarial anemia, acute kidney injury, acidosis, high-risk neutrophil gelatinase–associated lipocalin (NGAL), and hyperlactatemia. The light blue–shaded area represents improved performance (AUROC >0.70). The dotted black line represents an AUROC of 0.50. Differences between soluble triggering receptor expressed on myeloid cells 1 (sTREM-1) as the top-ranking marker and other biomarkers were tested, and an asterisk (*) and lighter color shade indicate the AUROC is significantly lower than that of sTREM-1 (P < .05). The difference in effects of biomarker levels (log₁₀-transformed) on mortality between subgroups were tested using binary logistic regression models with interaction terms between biomarker and subgroup, with daggers (†) indicating a significant interaction (P < .05). Data are also presented in Supplementary Table 2. Abbreviations: Angpt-2, angiopoietin 2; AKI, acute kidney injury; AUROC, area under the receiver operating characteristic curve; CHI3L1, chitinase-3-like 1; CI, confidence interval; CRP, C-reactive protein; IL-6, interleukin 6; IL-8, interleukin 8; NGAL, neutrophil gelatinase–associated lipocalin; sFlt-1, soluble fms-like tyrosine kinase 1; sICAM-1, soluble intercellular adhesion molecule 1; SMA, severe malarial anemia; sTNFR-1, soluble tumor necrosis factor receptor 1; sTREM-1, soluble triggering receptor expressed on myeloid cells 1; sVCAM-1, soluble vascular cellular adhesion molecule 1.

Figure 4.

Mortality across soluble triggering receptor expressed on myeloid cells 1 (sTREM-1) risk zones is mediated by acute kidney injury (AKI) status. A, Histograms depicting log₁₀ sTREM-1 levels in the entire cohort (left) and stratified by AKI status (right) and categorized into risk zones using previously established cutoffs: low risk (<239 pg/mL, “green zone”), moderate risk (239 to <629 pg/mL, “yellow zone”), or critical risk (≥ 629 pg/mL, “red zone”). The corresponding change in mortality across the risk zones is presented on the graph with mortality depicted on the right y-axis. B, Receiver operating characteristic curve analysis of the Lambaréné Organ Dysfunction Score (LODS) to predict mortality on its own and with the sTREM-1 risk zones incorporated. C, Proposed risk stratification algorithms based on the availability of resources and integration of clinical severity scores to facilitate more targeted sTREM-1 testing. In the initial screening of a sick child with fever and malaria, ascertainment of AKI status can lead to more focused testing and identification of a more selected group at highest risk of adverse outcomes to focus attention and resources.