Methods for estimating areas under receiver-operating characteristic curves: illustration with somatic-cell scores in subclinical intramammary infections
J. Detilleux et al., Methods for estimating areas under receiver-operating characteristic curves: illustration with somatic-cell scores in subclinical intramammary infections, PREV VET M, 41(2-3), 1999, pp. 75-88
The aim of this study was to demonstrate receiver-operating characteristic
(ROC) methodology in the context of bovine intramammary infection (IMI). Qu
arter somatic cell scores (SCS) were available to evaluate quarter IMI, and
the final IMI diagnosis was made from milk bacteriologic cultures. Data co
nsisted of 11,453 quarter-milk samples collected on 2084 clinically healthy
cows located in 154 Belgian herds. Bacteriological analyses showed 16.2%,
7.2%, and 11.9% of quarters infected with coagulase-positive Staphylococcus
spp,, Streptococcus agalactiae, and coagulase-negative Staphylococcus spp.
, respectively, The ROC curve indicated all the combinations of sensitivity
and specificity that quarter SCS was able to provide as a test to identify
quarter IMI. Among parametric, semi-parametric, and non-parametric methods
to estimate area under ROC curves, the parametric method seemed the least
appropriate for analyzing SCS in this study. With the non-parametric method
, the total area under the ROC curves showed quarter SCS could identify qua
rter IMI with an overall accuracy of 69%, 76%, and 59% for coagulase-positi
ve Staphylococcus spp., S. agalactiae, and coagulase-negative Staphylococcu
s spp., respectively. Parametric and nonparametric statistical tests showed
that overall SCS diagnostic capability was significantly (p<0.01) differen
t from chance and was different (p<0.01) across the three bacteria. However
, the SCS thresholds yielding the highest percentage of quarters correctly
classified as infected (for the observed prevalence and for equal costs ass
igned to false-positive and false-negative results) were so high that they
had no practical value. The major advantage of ROC analysis is the comprehe
nsive description of the discrimination capacity of SCS for all possible ch
oices of critical values. The major disadvantage is the dependency upon the
gold standard used for the final diagnosis - but recent improvements of th
e methodology will correct the problem. (C) 1999 Elsevier Science B.V. All
rights reserved.