Читать книгу Infectious Disease Management in Animal Shelters - Группа авторов - Страница 124

The accuracy of diagnostic test results is commonly assessed through calculation of sensitivity, specificity, and predictive value reported as percentages. Sensitivity refers to a test's ability to report a positive test result in an animal that is actually infected. It can be calculated by dividing the number of true positive test results by the total number of cases that are actually positive (true positives + false negatives). A test with high sensitivity will report few false negative results. Specificity refers to a test's ability to report a negative test result in an animal that is not infected. It can be calculated by dividing the number of true negative test results by the total number of cases that are actually negative (false positives + true negatives). A test with high specificity will report few false positive results. Sensitivity and specificity refer to the characteristics of a specific diagnostic test, clinical sign, or disease syndrome, and remain constant regardless of the population being evaluated (Rothman 2012).

Predictive value refers to the usefulness of a particular test, sign, or syndrome in classifying animals with the infection or disease of interest. As such, predictive value is highly dependent on the prevalence of disease within the population being evaluated (Rothman 2012). Whereas sensitivity and specificity report the percentage of accurate test results, predictive value reports the percentage of patients that are likely to have accurate results. Positive predictive value can be calculated by dividing the number of true positive test results by the total number of positive test results (true positives + false positives). A test will have a high positive predictive value when the disease is common in the population and the diagnostic test utilized has high specificity. Negative predictive value can be calculated by dividing the number of true negative test results by the total number of negative test results (true negatives + false negatives). A test will have a high negative predictive value when the disease is not common in the population and the diagnostic test utilized has high sensitivity. See Figure 4.2.

Figure 4.2 Sensitivity, specificity and predictive value. TP, true positives; TN, true negatives; FP, false positives; TN, true negatives.

Understanding these measures of accuracy is critical to designing rational diagnostic testing strategies for both individual animals and the shelter population as a whole. With each diagnostic test employed, there comes a risk of either false positive or false negative test results that may have a far‐reaching impact. Therefore, such decisions should only be made after an assessment of the cost–benefit ratio for the individual animal or shelter population and the acceptance of the risk posed by erroneous results. The following questions should be considered:

 Could an inaccurate test result lead to euthanasia?

 How would an inaccurate test result impact other animals in the shelter or community?

 Could treatment for a disease not present or lack of treatment for a disease that is present negatively affect the animal's well‐being in the shelter or its disposition? How might that treatment impact other animals in the shelter or community?

 How could an inaccurate test result burden an adopter? Might it discourage adoption altogether?

 What are the costs of both accurate and inaccurate test results (e.g. money, time)?

Once it has been decided to perform diagnostic testing and the consequences of both positive and negative test results have been considered, a strategy can be developed. When there is a substantial risk for negative consequences from a false negative result, then a strategy that results in a high negative predictive value should be developed. An example of this can be seen with canine parvovirus testing in a dog with vomiting and diarrhea. Obtaining a false negative test result would allow the disease to progress and allow for continued transmission to other dogs in the shelter or community. If a negative antigen test result is obtained, repeating the original diagnostic test or using additional diagnostics such as a complete blood count or blood smear evaluation to acquire evidence in support of the original negative test result will increase the sensitivity of the testing strategy, minimize the risk of a false negative, and increase the negative predictive value of the result. When there is a substantial risk for negative consequences from a false positive result, then a strategy that results in a high positive predictive value should be developed. An example of this can be seen with canine parvovirus testing in a shelter for which treatment is not possible and infected puppies are euthanized. In this case, the consequences of a false positive result are extreme, so limiting testing to dogs with clinical signs of GI disease will limit testing to a population in which the disease is more common, minimizing the risk of false positives and increasing the positive predictive value of test results.