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1.
The indirect fluorescent antibody (IFA) test for Theileria equi was evaluated to assess test's suitability for the serological diagnosis of equine piroplasmosis, to provide performance parameters for the purpose of test validation, and to compare it with the complement fixation (CF) test. Using a protocol that included Evan's blue, the specificity of the IFA test was estimated at 99.0% for T. equi by the classical method of analysis, and 96.6% by the Bayesian method. The use of Evan's blue in the test protocol increased test specificity and contributed to an excellent test agreement between two collaborating laboratories (kappa = 0.96). Using Bayesian analysis, the sensitivity estimate for the IFA test was 89.2%. The CF test sensitivity and specificity estimates for T. equi were 63.1 and 96.4%, respectively, as determined by Bayesian analysis. The IFA test was more sensitive than the CF test but the specificity estimates were similar.  相似文献   

2.
Interpretation of the result of a diagnostic test depends not only on the actual test result(s) but also on information external to this result, namely the test's sensitivity and specificity. This external information (also called prior information) must be combined with the data to yield the so-called updated, posterior estimates of the true prevalence and the test characteristics. The Bayesian approach offers a natural, intuitive framework in which to carry out this estimation process. The influence of the prior information on the final result may not be ignored. Guidance for the choice of prior information not in conflict with the data can be obtained from a set of statistics and indices (DIC, p(D), Bayes-p).  相似文献   

3.
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4.
The objectives of the current study were to estimate the sensitivity and specificity of three real-time polymerase chain reaction (PCR) tests for diagnosis of feline immunodeficiency virus (FIV) infection in domestic cats, both individually and when interpreted in series with one of two serological tests, separately in populations of cats at low and high risk of being infected with FIV. One PCR test targeted the pol gene and two targeted the gag gene of FIV. For comparison, sensitivities and specificities of the individual serological tests (IDEXX SNAP(?) test and AGEN Simplify(?) test) were also estimated. The study populations consisted of domestic cats thought to be not vaccinated against FIV. Low-risk (males aged 4 years or less and females; n=128) and high-risk (males over 4 years; n=128) cats were selected from those where blood samples were submitted to a commercial clinical pathology service. Bayesian latent class models were used to obtain posterior probability distributions for sensitivity and specificity for each test, based on prior distributions obtained from three experts. Medians of the posterior sensitivity distributions for the PCR tests based on the pol gene and two regions of the gag gene tests ranged from 0.85 to 0.89, compared to 0.89-0.97 for the two serological tests. The medians of posterior specificity distributions for these PCR tests were 0.94-0.96, and 0.95-0.97 for the serological tests. In contrast, the PCR based on one region of the gag gene had lower median sensitivity. Sensitivities of combinations of these serological and PCR tests interpreted in series were low; medians of posterior sensitivity distributions ranged from 0.75 to 0.83. Relative to the low-risk population, median sensitivities in the high-risk population were lower for all tests other than the AGEN Simplify(?) test; specificities were similar in both populations. We conclude that the sensitivities of the two PCR tests based on the pol gene and two regions of the gag gene, respectively, in non-vaccinated cats are probably lower than the sensitivities of the two serological tests we assessed. We do not recommend screening cats whose FIV vaccination status is uncertain with one of these serological tests and then testing positives with one of these PCR tests because in non-vaccinates, the sensitivities of combinations of these serological and PCR tests interpreted in series are low. Assessment of the validity of these PCR assays in FIV-vaccinated cats is required.  相似文献   

5.
The diagnostic accuracies of the modified agglutination test (MAT) and indirect ELISA test for the detection of serum antibodies against Toxoplasma gondii in sheep were evaluated through Bayesian approaches on two populations of sheep created from three different groups of animals (T. gondii-aborted ewes, colostrums-deprived newborn lambs, and ewe-lambs and adult ewes with unknown T. gondii infection status). Tests showed a high degree of agreement (kappa statistic = 0.93; 95% confidence interval = 0.87, 0.98) and a significant specificity (Sp) correlation (gamma(Sp) = 0.26; 95% credibility interval = 0.017, 0.61). When prior information was used for all unknown parameters the posterior medians for the sensitivity (Se) and Sp of the MAT and ELISA were, respectively, 92.6% (95% credibility interval = 85.2, 96.9), 95.5% (89.9, 98.7), 90.5% (83.4, 95.6), and 97.8% (94.2, 99.5). These estimates remained similar when uninformative priors were included. The Se estimates of the MAT and ELISA were higher than those obtained on pigs in other study using the same approach (Se = 80.6% and Sp = 89.5% for the MAT, and Se = 71.5% and Sp = 85.5% for the ELISA [Georgiadis, M.P., Wesley, O.J., Gardner, I.A., Singh, R., 2003. Correlation-adjusted estimation of sensitivity and specificity of two diagnostic tests. Appl. Stat. 52, 63-78]. This finding supported the believe that test performances may vary when applied on different animal species. Thus, if these tests are planned to be used on animal species other than sheep or pigs, their diagnostic accuracy should be re-assessed to prevent biased inferences from their results.  相似文献   

6.
The success of a Toxoplasma gondii surveillance program in European pig production systems depends partly on the quality of the test to detect infection in the population. The test accuracy of a recently developed serological bead-based assay (BBA) was investigated earlier using sera from experimentally infected animals. In this study, the accuracy of the BBA was determined by the use of sera from animals from two field subpopulations. As no T. gondii infection information of these animals was available, test accuracy was determined through a Bayesian approach allowing for conditional dependency between BBA and an ELISA test. The priors for prevalence were based on available information from literature, whereas for specificity vague non-informative priors were used. Priors for sensitivity were based either on available information or specified as non-informative. Posterior estimates for BBA sensitivity and specificity were (mode) 0.855 (Bayesian 95% credibility interval (bCI) 0.702–0.960) and 0.913 (bCI 0.893–0.931), respectively. Comparing the results of BBA and ELISA, sensitivity was higher for the BBA while specificity was higher for ELISA. Alternative priors for the sensitivity affected posterior estimates for sensitivity of both BBA and ELISA, but not for specificity. Because the difference in prevalence between the two subpopulations is small, and the number of infected animals is small as well, the precision of the posterior estimates for sensitivity may be less accurate in comparison to the estimates for specificity. The estimated value for specificity of BBA is at least optimally defined for testing pigs from conventional and organic Dutch farms.  相似文献   

7.
Latent-class models were used to determine the sensitivity, specificity and predictive values of a polyclonal blocking enzyme-linked immunosorbent assay (ELISA) and a modified complement-fixation test (CFT) when there was no reference test. The tests were used for detection of antibodies against Actinobacillus pleuropneumoniae serotype 2 in a survey of respiratory diseases in Danish finishing pigs. The estimates were obtained by maximum-likelihood and also by a Bayesian method (implemented with Gibbs sampling). Possible dependence of diagnostic errors was investigated by comparing models where independence was assumed to models allowing for conditional dependence, given the true disease status.

No strong evidence of conditional dependence in either test sensitivity or specificity was found. Assuming independence, maximum-likelihood estimates and 95% confidence intervals of the sensitivity and specificity of the ELISA were 100% and 92.8% (90.1–95.5%) and the corresponding values of the CFT were 90.6% (85.8–95.4%) and 98.6% (98.0–99.3%), respectively. Bayesian estimates and posterior 95% credible intervals of the sensitivity and specificity of the ELISA were 99.7% (98.7–100%) and 92.7% (89.9–95.3%) and of the CFT were 90.6% (86.0–95.3%) and 98.7% (98.0–99.3%). The sensitivity and specificity of a combined test, where the CFT is subsequently applied to the pig sera that test positive in the ELISA, were estimated at 90.2% (85.6–95.0%) and 99.9% (99.8–100%), respectively. The cost of the combined test was less than the cost of the use of the CFT alone, at prevalences <54%. Prevalences and predictive values and their 95% limits were estimated in six sub-samples of data. The estimates of sensitivity and specificity obtained in the present investigation generally validate those reported from other sources.  相似文献   


8.
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9.
Latent class analysis to assess the sensitivity and specificity of a diagnostic test can be carried out under different assumptions. An often applied set of assumptions is known as the Hui-Walter paradigm, which essentially states that: (i) the population is divided into two or more populations in which two or more tests are evaluated under assumption that (ii) sensitivity and specificity of the tests are the same in all populations; and (iii) the tests are conditionally independent given the disease status. This study explores the implications of these assumptions. Through simulation studies, it is shown how the size of the difference between disease prevalences within the populations influences the precision of the estimates. It is also illustrated by a simulation study how a difference in a test sensitivity between populations may result in estimates that are biased towards the sensitivity of the test in the population with highest disease prevalence, since that population estimate is supported by most of the data. It is shown that the assumption of conditional independence between tests in general cannot be ignored in latent class models. Failure to impose conditional independence will result in a model that lacks identifiability in a way that cannot be handled by adding more tests or dividing the sample into more populations.  相似文献   

10.
The prevalence of Cryptosporidium in calves and the test properties of six diagnostic assays (microscopy (ME), an immunofluorescence assay (IFA), two ELISA and two PCR assays) were estimated using Bayesian analysis. In a first Bayesian approach, the test results of the four conventional techniques were used: ME, IFA and two ELISA. This four-test approach estimated that the calf prevalence was 17% (95% Probability Interval (PI): 0.1-0.28) and that the specificity estimates of the IFA and ELISA were high compared to ME. A six-test Bayesian model was developed using the test results of the 4 conventional assays and 2 PCR assays, resulting in a higher calf prevalence estimate (58% with a 95% PI: 0.5-0.66) and in a different test evaluation: the sensitivity estimates of the conventional techniques decreased in the six-test approach, due to the inclusion of two PCR assays with a higher sensitivity compared to the conventional techniques. The specificity estimates of these conventional assays were comparable in the four-test and six-test approach. These results both illustrate the potential and the pitfalls of a Bayesian analysis in estimating prevalence and test characteristics, since posterior estimates are variables depending both on the data at hand and prior information included in the analysis. The need for sensitive diagnostic assays in epidemiological studies is demonstrated, especially for the identification of subclinically infected animals since the PCR assays identify these animals with reduced oocyst excretion, which the conventional techniques fail to identify.  相似文献   

11.
The validation of assays for bovine immunodeficiency virus (BIV) in cattle is hampered by the absence of a gold standard. Two tests that often are used to detect BIV are the indirect fluorescent-antibody assay (IFA) and the nested-set polymerase chain-reaction assay (PCR). IFA detects an antibody response whereas PCR detects the provirus in white blood cells.Using Bayesian techniques performed simultaneously on animals from two different dairy herds, we estimated the performance of the IFA and PCR assays and infection prevalence. Bayesian techniques also were used to derive posterior distributions of sensitivities, specificities, and prevalences. The Bayesian estimates were IFA sensitivity=60%, IFA specificity=88%, PCR sensitivity=80%, PCR specificity=86%, Herd A prevalence=20%, and Herd B prevalence=71%. Although PCR was the more sensitive assay, substantial misclassification of infection would be expected in epidemiological studies of BIV regardless of which assay was used.  相似文献   

12.
Lyme disease is a zoonotic, vector-borne disease and occurs in mammals including horses. The disease is induced by infection with spirochetes of the Borrelia burgdorferi sensu lato group. Infection of mammalian hosts requires transmission of spirochetes by infected ticks during tick bites. Lyme disease diagnosis is based on clinical signs, possible exposure to infected ticks, and antibody testing which is traditionally performed by ELISA and Western blotting (WB). This report describes the development and validation of a new fluorescent bead-based multiplex assay for the detection of antibodies to B. burgdorferi outer surface protein A (OspA), OspC and OspF antigens in horse serum. Testing of 562 equine sera was performed blindly and in parallel by using WB and the new multiplex assay. Because a true gold standard is missing for Lyme antibody testing, we performed and compared different statistical approaches to validate the new Lyme multiplex assay. One approach was to use WB results as a 'relative gold standard' in ROC-curve and likelihood-ratio analyses of the new test. Cut-off values and interpretation ranges of the multiplex assay were established by the analysis. The second statistical approach used a Bayesian model for the calculation of diagnostic sensitivities and specificities of the multiplex assay. The Bayesian analysis takes into consideration that no true gold standard exists for detecting antibodies to B. burgdorferi and estimated sensitivities and specificities of both tests that were compared. Therefore, the Bayesian analysis also resulted in an evaluation of diagnostic sensitivity and specificity of WB. Overall, the new assay was characterized by low background values and a wide dynamic quantification range for the detection of antibodies to OspA, OspC and OspF antigens of B. burgdorferi. The diagnostic sensitivity and specificity for the OspA bead-based assay were calculated as 49% and 85%, respectively, and by a standard ROC curve analysis only because the Bayesian model could not be run on this parameter. The Bayesian-derived diagnostic sensitivities of the OspC and OspF assays were 80% and 86%, respectively. For comparison, the Bayesian-derived estimates for WB resulted in sensitivities of 72% for OspC and 80% for OspF. The Bayesian diagnostic specificities of the multiplex assay were 79% and 69% for OspC and OspF, respectively. WB analysis had specificities of 92% for OspC and 77% for OspF. Although the analysis of a new assay in the absence of a true gold standard remains challenging, the approach used here can help to address this problem when new technologies and traditionally used test standards differ significantly in their analytical sensitivities, which consequently causes problems in the calculation of diagnostic sensitivity and sensitivity values for the new assay. In summary, the new multiplex assay for the detection of antibodies to B. burgdorferi OspA, OspC and OspF antigens in horse serum has improved analytical and diagnostic sensitivities compared to WB analysis. Multiplex analysis is a valuable quantitative tool that simultaneously detects antibodies indicative for natural infection with and/or vaccination against the Lyme pathogen.  相似文献   

13.
We review recent Bayesian approaches to estimation (based on cross-sectional sampling designs) of the sensitivity and specificity of one or more diagnostic tests. Our primary goal is to provide veterinary researchers with a concise presentation of the computational aspects involved in using the Bayesian framework for test evaluation. We consider estimation of diagnostic-test sensitivity and specificity in the following settings: (i) one test in one population, (ii) two conditionally independent tests in two or more populations, (iii) two correlated tests in two or more populations, and (iv) three tests in two or more populations, where two tests are correlated but jointly independent of the third test. For each scenario, we describe a Bayesian model that incorporates parameters of interest. The WinBUGS code used to fit each model, which is available at http://www.epi.ucdavis.edu/diagnostictests/, can be altered readily to conform to different data.  相似文献   

14.
Testing of composite fecal (environmental) samples from high traffic areas in dairy herds has been shown to be a cost-effective and sensitive method for classification of herd status for Mycobacterium avium subsp. paratuberculosis (MAP). In the National Animal Health Monitoring System's (NAHMS) Dairy 2007 study, the apparent herd-level prevalence of MAP was 70.4% (369/524 had ≥1 culture-positive composite fecal samples out of 6 tested). Based on these data, the true herd-level prevalence (HP) of MAP infection was estimated using Bayesian methods adjusting for the herd sensitivity (HSe) and herd specificity (HSp) of the test method. The Bayesian prior for HSe of composite fecal cultures was based on data from the NAHMS Dairy 2002 study and the prior for HSp was based on expert opinion. The posterior median HP (base model) was 91.1% (95% probability interval, 81.6 to 99.3%) and estimates were most sensitive to the prior for HSe. The HP was higher than estimated from the NAHMS Dairy 1996 and 2002 studies but estimates are not directly comparable with those of prior NAHMS studies because of the different testing methods and criteria used for herd classification.  相似文献   

15.
Mixed model (co)variance component estimates by REML and Gibbs sampling for two traits were compared for base populations and control lines of Red Flour Beetle (Tribolium castaneum). Two base populations (1296 records in the first replication, 1292 in the second) were sampled from laboratory stock. Control lines were derived from corresponding base populations with random selection and mating for 16 generations. The REML estimate of each (co)variance component for both pupa weight and family size was compared with the mean and 95% central interval of the particular (co)variance estimated by Gibbs sampling with three different weights on the given priors: ‘flat’, smallest, and 3.7% degrees of belief. Results from Gibbs sampling showed that flat priors gave a wider and more skewed marginal posterior distribution than the other two weights on priors for all parameters. In contrast, the 3.7% degree of belief on priors provided reasonably narrow and symmetric marginal posterior distributions. Estimation by REML does not have the flexibility of changing the weight on prior information as does the Bayesian analysis implemented by Gibbs sampling. In general, the 95% central intervals from the three different weights on priors in the base populations were similar to those in control lines. Most REML estimates in base populations differed from REML estimates in control lines. Insufficient information from the data, and confounding of random effects contributed to the variability of REML estimates in base populations. Evidence is presented showing that some (co)variance components were estimated with less precision than others. Results also support the hypothesis that REML estimates were equivalent to the joint mode of posterior distribution obtained from a Bayesian analysis with flat priors, but only when there was sufficient information from data, and no confounding among random effects.  相似文献   

16.
Latent-class models were used to determine the sensitivity, specificity and predictive values of a polyclonal blocking enzyme-linked immunosorbent assay (ELISA) and a modified complement-fixation test (CFT) when there was no reference test. The tests were used for detection of antibodies against Actinobacillus pleuropneumoniae serotype 2 in a survey of respiratory diseases in Danish finishing pigs. The estimates were obtained by maximum-likelihood and also by a Bayesian method (implemented with Gibbs sampling). Possible dependence of diagnostic errors was investigated by comparing models where independence was assumed to models allowing for conditional dependence, given the true disease status.No strong evidence of conditional dependence in either test sensitivity or specificity was found. Assuming independence, maximum-likelihood estimates and 95% confidence intervals of the sensitivity and specificity of the ELISA were 100% and 92.8% (90.1–95.5%) and the corresponding values of the CFT were 90.6% (85.8–95.4%) and 98.6% (98.0–99.3%), respectively. Bayesian estimates and posterior 95% credible intervals of the sensitivity and specificity of the ELISA were 99.7% (98.7–100%) and 92.7% (89.9–95.3%) and of the CFT were 90.6% (86.0–95.3%) and 98.7% (98.0–99.3%). The sensitivity and specificity of a combined test, where the CFT is subsequently applied to the pig sera that test positive in the ELISA, were estimated at 90.2% (85.6–95.0%) and 99.9% (99.8–100%), respectively. The cost of the combined test was less than the cost of the use of the CFT alone, at prevalences <54%. Prevalences and predictive values and their 95% limits were estimated in six sub-samples of data. The estimates of sensitivity and specificity obtained in the present investigation generally validate those reported from other sources.  相似文献   

17.
Time trends in animal-disease surveillance often are evaluated on the basis of crude estimates of apparent prevalence. In addition to possible changes in the true prevalence of the condition, changes in apparent prevalence over time might reflect changes in sensitivity and/or specificity of the diagnostic classification used. To illustrate this, comparative post-mortem meat inspection data from four Danish slaughter plants sampled in 1993-1994 and 1997-1998 were used to obtain latent-class model estimates of the sensitivity and specificity of traditional and extended post-mortem meat inspection of visceral and parietal chronic pleuritis (CP), respectively.True prevalence of CP was estimated for each study period and slaughter plant by latent-class models. Estimated sensitivities of traditional post-mortem meat (TPM) inspection ranged from 28.8 to 61.4% (1993-1994) and 39.2 to 87.3% (1997-1998). An increase in sensitivity with time was seen for all slaughter plants. Estimated sensitivities of extended post-mortem meat (EPM) inspection ranged from 85.7 to 94.8% (1993-1994) and 73.8 to 93.0% (1997-1998). All estimated specificities were >93.3%.The possible association of the estimated true prevalence of CP with time (1993-1994 versus 1997-1998) was investigated with a logistic-regression model with random effects. A slight, but non-significant decrease in the odds of CP from 1994 to 1998 was found (odds ratio=0.9).In this and similar situations, one should consider conducting ongoing double-classification of samples of units followed by statistical estimation of true prevalences, sensitivities and specificities, so that decisions can be based on such estimates rather than on crude apparent prevalences.  相似文献   

18.
Specialised veal producers that purchase and raise calves from several dairy herds are potentially at high risk of delivering Salmonella-infected animals to slaughter. However, the true prevalence of Salmonella infected veal producing herds and the prevalence of infected calves delivered to slaughter from infected herds are unknown in Denmark. Due to uncertainties about test sensitivity and specificity, these prevalences are not straightforward to assess. The objective of this study was to estimate the within-herd- and between-herd prevalence of Salmonella in veal calves delivered for slaughter to abattoirs in Denmark. Furthermore, it was investigated to which extent the estimates differed between a setup using both serological tests and faecal culture, compared to just serological tests, and whether the applied sampling scheme in the national surveillance programme in Denmark was sufficient to establish high posterior estimates of freedom from infection in individual herds. We used Bayesian analysis to avoid bias as a result of fixed test validity estimates. Serological test results from 753 animals and faecal culture from 1233 animals from 68 randomly selected Danish veal producing herds that delivered more than 100 calves to slaughter per year were used to estimate the prevalences and estimates of freedom from Salmonella. Serological test results of 7726 animals from 185 herds were used to compare the difference in prevalence estimates between serology alone vs. faecal culture combined with serology. We estimated that 34-57% of specialised veal producing herds were infected with Salmonella. Within the infected herds, 21-49% of the animals were infected. Few herds obtained high posterior estimates for the probability of freedom from infection given the collected data, with only six of 68 herds obtaining posterior probability of being infected less than 10%. Furthermore, this study indicated that serology is sufficiently sensitive and specific to be used for estimating the prevalence of Salmonella-infected specialised veal producing herds.  相似文献   

19.
The sensitivity and specificity of six ELISA tests for foot-and-mouth disease (FMD) to discriminate between sero-converted (for non-structural FMD virus proteins) and non-sero-converted cattle were evaluated for vaccinated and unvaccinated cattle. Since none of the tests could be considered as a proper reference test and for about half of the tested sera the true status (sero-converted or not for non-structural proteins, i.e. presence of antibodies) of the animals was unknown, a Bayesian analysis employing a latent class model was used that did not rely on the use of a reference test or gold standard. Prior information about prevalence for subsets of the data and specificity of the tests was incorporated into the analysis. The specificity of the six tests for vaccinated and non-vaccinated cattle ranged from 96 to 99%. For vaccinated cattle, one test stood out with an estimated sensitivity of 94% (95% CI from 89.8 to 98.1%). Second best for vaccinated cattle were two tests with estimated sensitivities of 85% (95% CI from 78.9 to 89.7%) and 92% (95% CI from 86.2 to 95.6%). For non-vaccinated cattle, the sensitivities of these three tests were around 97%. The remaining three tests showed lower estimated sensitivity for vaccinated cattle, ranging from 57 to 79%.  相似文献   

20.
The evaluation of newly developed diagnostic tests (tests) commonly involves the comparison of the test outcomes (pos/neg.) of a sample of animals to those of a reference test (gold standard) in order to derive sensitivity and specificity estimates. Often, however, new tests have to be evaluated against an imperfect reference test since a true gold standard test is either too expensive or too costly to apply. This results in bias in the test characteristic estimates. To solve this problem, latent class and Bayesian models can be used to estimate sensitivity and specificity when evaluating a diagnostic test in the absence of a gold standard. They require at least two imperfect reference tests applied to all individuals in the study. In our approach we used a two-test two-population scenario. Both the gold standard and these modelling approaches rely on various assumptions. When violated, biased results will be obtained. The analysis of field data from an Anaplasma marginale outbreak in cattle in Switzerland with four diagnostic procedures (detection of the agent, serology, PCR and hematocrit measurements) was used as a practical example to demonstrate and critically discuss the approaches taken. In this relatively small data set (n = 275) the estimates for the test characteristics obtained by the different methods were quite similar. Overall, the bias in the point estimates depended mainly on the chosen estimation approach. All tests showed a non-negligible correlation mainly in the test sensitivities. This emphasizes the importance of taking into account test dependence even if it seems not biologically plausible at first thought.  相似文献   

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