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Table 3 Assessment by ROC curve analyses of the individual prediction performance of each of the eight plasma proteins to differentiate between clinical malaria conditions

From: Plasma levels of eight different mediators and their potential as biomarkers of various clinical malaria conditions in African children

Test result variables AUROCC ± Std error Asymptomatic 95 % lower bound Asymptomatic 95 % upper bound
A
 Fractalkine 0.985 ± 0.015 0.956 1.000
 sCD163 0.959 ± 0.019 0.922 0.996
 Neopterin 0.857 ± 0.050 0.760 0.954
 sCD14 0.842 ± 0.049 0.745 0.939
 MIG 0.788 ± 0.062 0.666 0.910
 sTREM-1 0.605 ± 0.081 0.446 0.764
 suPAR 0.485 ± 0.075 0.337 0.632
 Pentraxin 0.233 ± 0.05 0.135 0.331
B
 Pentraxin 0.979 ± 0.010 0.958 0.999
 suPAR 0.958 ± 0.018 0.922 0.994
 sCD14 0.876 ± 0.030 0.817 0.936
 sTREM-1 0.832 ± 0.037 0.759 0.905
 sCD163 0.499 ± 0.053 0.395 0.602
 MIG 0.490 ± 0.053 0.387 0.593
 Fractalkine 0.314 ± 0.049 0.218 0.410
 Neopterin 0.246 ± 0.049 0.149 0.343
C
 Neopterin 1.000 ± 0.000 1.000 0.000
 sTREM-1 0.957 ± 0.019 0.919 0.994
 suPAR 0.678 ± 0.053 0.575 0.782
 MIG 0.566 ± 0.069 0.431 0.702
 Pentraxin 0.401 ± 0.053 0.297 0.504
 sCD163 0.308 ± 0.049 0.213 0.404
 sCD14 0.100 ± 0.027 0.047 0.154
 Fractalkine 0.000 ± 0.000 0.000 0.000
  1. Plasma levels of eight proteins were quantified in 80 AM children, 69 UM patients and 66 SM or CM patients. Receiver operator characteristics (ROC) curves were used to estimate the power of each of the eight mediators to individually distinguish between two distinct clinical malaria conditions. Results of ROC curve analyses are indicated for AM children versus Controls (A), UM patients versus AM children (B) and SM–CM versus UM patients (C)