Page 109 - Invited Paper Session (IPS) - Volume 2

IPS186 Fagbamigbe, A. F.
3. Data Analysis
There were a total of 7,011 children aged 6-59 months across all the
households visited during the survey. Basic descriptive statistics were used to
describe the under-five children with respect to the characteristics of their
mothers. The McNemar paired test and the Kappa statistics were used to test
the hypothesis of non-agreement and to determine the level of agreement
between the outcomes of the diagnostic tests respectively. Diagnostic test
parameters including sensitivity, specificity, positive predictive value (PPV),
and negative predictive value (NPV) was used to determine the accuracy of
the malaria RDT results in comparison with the “Gold standard” results from
microscopy tests. Let X denote the true state of a person (microscopy test
results) with microscopy positive = D+ and negative = D-. Also, let Y be the
outcome of the RDT test, with RDT positive = T+ and negative = T-. Then,

+
−
+
Sensitivity = ( = T |X = D ); pecificity = ( = T | = D ). The positive
−
likelihood ratio (LR+) and the negative likelihood ratio (LR-) are calculated as
1−
LR+= = and LR-= =
1−

as proposed by Simel et al. [23]. The unique statistics produced by the
likelihood ratios have made it the optimal choice for reporting diagnostic
accuracy for clinically meaningful thresholds[18].
However, there is a need to determine the predictive values since
sensitivities and specificities are not measures of prediction[18]. Predictive
values depend on disease prevalence, and their conclusions are transposable
to other settings. The predictive values help to determine how likely the
disease is, given the test result. The PPV is the probability that the disease is
present, given that the diagnostic test is positive. It is computed as TP/ (TP+FP)
while the NPV is the probability that the disease is not present given that the
test is negative, computed as TN/ (TN+FN). A diagnostic test could be said to
be perfect if it can predict perfectly, i.e., if PPV = NPV=1. The PPV decreases
with decreasing prevalence.
+
+
−
PPV = ( D |T ); NPV = ( D |T ) .
−
The accuracy of a test = (TP+TN)/(TP+TN+FP+FN) and its confidence
intervals are the standard logits as given by Mercaldo et al[24]. The pretest
probability is the same as the prevalence as determined by the gold standard,
the pretest odds is prevalence/(1-prevalence), posttest odds= pretest odds
*likelihood ratio and the posttest probability=posttest odds/(1+positive
odds).
The ROC analysis is used in diagnostic screening evaluation to quantify the
accuracy of diagnostic
95 tests [25].

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