Diagnostic accuracy of PCR for Jaagsiekte sheep retrovirus using field data from 125 Scottish sheep flocks

FI Lewis, F Brulisauer, C Cousens, IJ McKendrick, GJ Gunn

Research output: Contribution to journalArticlepeer-review

Abstract

Using a representative sample of Scottish sheep comprising 125 flocks, the sensitivity and specificity of PCR for Jaagsiekte sheep retrovirus (JSRV) was estimated. By combining and adapting existing methods, the characteristics of the diagnostic test were estimated (in the absence of a gold standard reference) using repeated laboratory replicates. As the results of replicates within the same animal cannot be considered to be independent, the performance of the PCR was calculated at individual replicate level. The median diagnostic specificity of the PCR when applied to individual animals drawn from the Scottish flock was estimated to be 0.997 (95% confidence interval [CI] 0.996–0.999), whereas the median sensitivity was 0.107 (95% CI 0.077–0.152). Considering the diagnostic test as three replicates where a positive result on any one or more replicates results in a positive test, the median sensitivity increased to 0.279. Reasons for the low observed sensitivity were explored by comparing the performance of the test as a function of the concentration of target DNA using spiked positive controls with known concentrations of target DNA. The median sensitivity of the test when used with positive samples with a mean concentration of 1.0 target DNA sequence per 25 μL was estimated to be 0.160, which suggests that the PCR had a high true (analytical) sensitivity and that the low observed (diagnostic) sensitivity in individual samples was due to low concentrations of target DNA in the blood of clinically healthy animals.
Original languageEnglish
Pages (from-to)104 - 108
Number of pages5
JournalVeterinary Journal
Volume187
Issue number1
Publication statusFirst published - 2009

Bibliographical note

66060003
66000011

Keywords

  • Diagnostic test validation
  • Jaagsiekte sheep retrovirus
  • Modelling
  • PCR

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