RESUMO

The likelihood ratio (LR) is a measure of association that quantifies how many more times likely a particular test result is from an infected animal compared to one that is uninfected. They are ratios of conditional probabilities and cannot be interpreted at the individual animal level without information concerning pretest probabilities. Their usefulness is that they can be used to update the prior belief that the individual has the outcome of interest through a modification of Bayes' theorem. Bayesian analytic techniques can be used for the evaluation of diagnostic tests and estimation of LRs when information concerning a gold standard is not available. As an example, these techniques were applied to the estimation of LRs for a competitive ELISA (c-ELISA) for diagnosis of Brucella abortus infection in cattle and water buffalo in Trinidad.Sera from four herds of cattle (n = 391) and four herds of water buffalo (n = 381) in Trinidad were evaluated for Brucella-specific antibodies using a c-ELISA. On the basis of previous serologic (agglutination) test results in the same animals, iterative simulation modeling was used to classify animals as positive or negative for Brucella infection. LRs were calculated for six categories of the c-ELISA proportion inhibition (PI) results pooled for cattle and water buffalo and yielded the following estimations (95% probability intervals): <0.10 PI, 0.05 (0ùC0.13); 0.10ùC0.249 PI, 0.11 (0.04ùC0.20); 0.25ùC0.349 PI, 0.77 (0.23ùC1.63); 0.35-0.499 PI, 3.22 (1.39ùC6.84); 0.50ùC0.749 PI, 17.9 (6.39ùC77.4); ­í0.75 PI, 423 (129ùC­è). LRs are important for calculation of post-test probabilities and maintaining the quantitative nature of diagnostic test results.

Assuntos

RESUMO

The likelihood ratio (LR) is a measure of association that quantifies how many more times likely a particular test result is from an infected animal compared to one that is uninfected. They are ratios of conditional probabilities and cannot be interpreted at the individual animal level without information concerning pretest probabilities. Their usefulness is that they can be used to update the prior belief that the individual has the outcome of interest through a modification of Bayes' theorem. Bayesian analytic techniques can be used for the evaluation of diagnostic tests and estimation of LRs when information concerning a gold standard is not available. As an example, these techniques were applied to the estimation of LRs for a competitive ELISA (c-ELISA) for diagnosis of Brucella abortus infection in cattle and water buffalo in Trinidad. Sera from four herds of cattle (n=391) and four herds of water buffalo (n=381) in Trinidad were evaluated for Brucella-specific antibodies using a c-ELISA. On the basis of previous serologic (agglutination) test results in the same animals, iterative simulation modeling was used to classify animals as positive or negative for Brucella infection. LRs were calculated for six categories of the c-ELISA proportion inhibition (PI) results pooled for cattle and water buffalo and yielded the following estimations (95% probability intervals): <0.10 PI, 0.05 (0-0.13); 0.10-0.249 PI, 0.11 (0.04-0.20); 0.25-0.349 PI, 0.77 (0.23-1.63); 0.35-0.499 PI, 3.22 (1.39-6.84); 0.50-0.749 PI, 17.9 (6.39-77.4); > or =0.75 PI, 423 (129-infinity). LRs are important for calculation of post-test probabilities and maintaining the quantitative nature of diagnostic test results.

Assuntos

RESUMO

Thirty-two young domestic water buffalo (Bubalus bubalis) were obtained from a brucellosis-free farm to determine effectiveness of RB51 vaccination for prevention of Brucella infection under natural-exposure conditions in Trinidad. Study animals (20 males and 12 females 5-20 months old) were assigned to vaccination or control groups, using a block randomization design ensuring equal sex distributions between groups. The vaccination group received commercially available RB51 at the recommended calfhood dose of (1.0-3.4)x10(10) colony-forming units (CFU) and controls received 2ml sterile saline. Vaccination did not result in positive serologic results as measured by four traditional agglutination tests: standard tube agglutination test (STAT), standard plate agglutination test (SPAT), buffered plate agglutination test (BPAT), and card agglutination. Study animals were maintained in a brucellosis-positive herd in southern Trinidad with an estimated 56% prevalence to allow for natural exposure to B. abortus, which was evaluated using STAT, SPAT, BPAT, and card tests. Animals were sampled seven times over 2 years and were classified as positive if they had persistent agglutination titers or had Brucella isolated from specimens collected at completion of the study. Five of the original 32 study animals were lost to follow-up during the field trial. Six of the 14 (43%) vaccinated animals completing the study were classified as positive for Brucella infection-as were two of the 13 (15%) control animals (P=0.21). Isolates from four vaccinates and one control were confirmed as B. abortus biovar 1.

Assuntos

Assuntos

RESUMO

A case-control study was conducted in the Mexicali Valley to identify risk factors for goat-herd seropositivity for Brucella melitensis. Nineteen case herds (> or = 2 positive results with the 8% rose bengal plate test (RBT)) and 55 control herds (zero positive results in RBT), matched for herdsize and geographic location, were enrolled. Conditional logistic regression was used to construct a multivariable model of the odds of seropositivity using variables assessed in a questionnaire administered to goat ranchers. The final model for herd seropositivity included increased risk from importation of goats from other Mexican states, the presence of La Mancha breed does, and the presence of does born outside the herd. Increasing herdsize was also highly significant (p < 0.01). In addition, a significant (p < 0.05) positive association was found between the presence of seropositive dogs (as assessed by RBT) and seropositive goats on the same ranch.

Assuntos