Diagnostic tests for hepatitis C: Recent trends in electrochemical immunosensor and genosensor analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparison of diferent diagnostic tests in dogs uninfected and naturally infected with visceral leishmaniasis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

Performance of six diagnostic tests to screen for Chagas disease in blood banks and prevalence of Trypanosoma cruzi infection among donors with inconclusive serology screening based on the analysis of epidemiological variables

OBJECTIVE: The frequent occurrence of inconclusive serology in blood banks and the absence of a gold standard test for Chagas'disease led us to examine the efficacy of the blood culture test and five commercial tests (ELISA, IIF, HAI, c-ELISA, rec-ELISA) used in screening blood donors for Chagas disease, as well as to investigate the prevalence of Trypanosoma cruzi infection among donors with inconclusive serology screening in respect to some epidemiological variables. METHODS: To obtain estimates of interest we considered a Bayesian latent class model with inclusion of covariates from the logit link. RESULTS: A better performance was observed with some categories of epidemiological variables. In addition, all pairs of tests (excluding the blood culture test) presented as good alternatives for both screening (sensitivity > 99.96% in parallel testing) and for confirmation (specificity > 99.93% in serial testing) of Chagas disease. The prevalence of 13.30% observed in the stratum of donors with inconclusive serology, means that probably most of these are non-reactive serology. In addition, depending on the level of specific epidemiological variables, the absence of infection can be predicted with a probability of 100% in this group from the pairs of tests using parallel testing. CONCLUSION: The epidemiological variables can lead to improved test results and thus assist in the clarification of inconclusive serology screening results. Moreover, all combinations of pairs using the five commercial tests are good alternatives to confirm results.

Accuracy of diagnostic tests for clinically suspected upper extremity deep vein thrombosis: a systematic review

The best available test for the diagnosis of upper extremity deep venous thrombosis (UEDVT) is contrast venography. The aim of this systematic review was to assess whether the diagnostic accuracy of other tests for clinically suspected UEDVT is high enough to justify their use in clinical practise and to evaluate if any test can replace venography.

Bivariate meta-analysis of predictive values of diagnostic tests can be an alternative to bivariate meta-analysis of sensitivity and specificity

Meta-analysis of predictive values is usually discouraged because these values are directly affected by disease prevalence, but sensitivity and specificity sometimes show substantial heterogeneity as well. We propose a bivariate random-effects logitnormal model for the meta-analysis of the positive predictive value (PPV) and negative predictive value (NPV) of diagnostic tests.

RANDOM EFFECTS MODELS IN A META-ANALYSIS OF THE ACCURACY OF DIAGNOSTIC TESTS WITHIN A GOLD STANDARD IN THE PRESENCE OF MISSING DATA

In evaluating the accuracy of diagnosis tests, it is common to apply two imperfect tests jointly or sequentially to a study population. In a recent meta-analysis of the accuracy of microsatellite instability testing (MSI) and traditional mutation analysis (MUT) in predicting germline mutations of the mismatch repair (MMR) genes, a Bayesian approach (Chen, Watson, and Parmigiani 2005) was proposed to handle missing data resulting from partial testing and the lack of a gold standard. In this paper, we demonstrate an improved estimation of the sensitivities and specificities of MSI and MUT by using a nonlinear mixed model and a Bayesian hierarchical model, both of which account for the heterogeneity across studies through study-specific random effects. The methods can be used to estimate the accuracy of two imperfect diagnostic tests in other meta-analyses when the prevalence of disease, the sensitivities and/or the specificities of diagnostic tests are heterogeneous among studies. Furthermore, simulation studies have demonstrated the importance of carefully selecting appropriate random effects on the estimation of diagnostic accuracy measurements in this scenario.

A review identifies and classifies reasons for ordering diagnostic tests

OBJECTIVE: To consider the reasons and context for test ordering by doctors when faced with an undiagnosed complaint in primary or secondary care. STUDY DESIGN AND SETTING: We reviewed any study of any design that discussed factors that may affect a doctor's decision to order a test. Articles were located through searches of electronic databases, authors' files on diagnostic methodology, and reference lists of relevant studies. We extracted data on: study design, type of analysis, setting, topic area, and any factors reported to influence test ordering. RESULTS: We included 37 studies. We carried out a thematic analysis to synthesize data. Five key groupings arose from this process: diagnostic factors, therapeutic and prognostic factors, patient-related factors, doctor-related factors, and policy and organization-related factors. To illustrate how the various factors identified may influence test ordering we considered the symptom low back pain and the diagnosis multiple sclerosis as examples. CONCLUSIONS: A wide variety of factors influence a doctor's decision to order a test. These are integral to understanding diagnosis in clinical practice. Traditional diagnostic accuracy studies should be supplemented with research into the broader context in which doctors perform their work.

Rapid diagnostic tests for the home-based management of malaria, in a high-transmission area

Rapid diagnostic tests (RDT) are sometimes recommended to improve the home-based management of malaria. The accuracy of an RDT for the detection of clinical malaria and the presence of malarial parasites has recently been evaluated in a high-transmission area of southern Mali. During the same study, the cost-effectiveness of a 'test-and-treat' strategy for the home-based management of malaria (based on an artemisinin-combination therapy) was compared with that of a 'treat-all' strategy. Overall, 301 patients, of all ages, each of whom had been considered a presumptive case of uncomplicated malaria by a village healthworker, were checked with a commercial RDT (Paracheck-Pf). The sensitivity, specificity, and positive and negative predictive values of this test, compared with the results of microscopy and two different definitions of clinical malaria, were then determined. The RDT was found to be 82.9% sensitive (with a 95% confidence interval of 78.0%-87.1%) and 78.9% (63.9%-89.7%) specific compared with the detection of parasites by microscopy. In the detection of clinical malaria, it was 95.2% (91.3%-97.6%) sensitive and 57.4% (48.2%-66.2%) specific compared with a general practitioner's diagnosis of the disease, and 100.0% (94.5%-100.0%) sensitive but only 30.2% (24.8%-36.2%) specific when compared against the fulfillment of the World Health Organization's (2003) research criteria for uncomplicated malaria. Among children aged 0-5 years, the cost of the 'test-and-treat' strategy, per episode, was about twice that of the 'treat-all' (U.S.$1.0. v. U.S.$0.5). In older subjects, however, the two strategies were equally costly (approximately U.S.$2/episode). In conclusion, for children aged 0-5 years in a high-transmission area of sub-Saharan Africa, use of the RDT was not cost-effective compared with the presumptive treatment of malaria with an ACT. In older patients, use of the RDT did not reduce costs. The question remains whether either of the strategies investigated can be made affordable for the affected population.

Natural anti-FcepsilonRIalpha autoantibodies may interfere with diagnostic tests for autoimmune urticaria.

IgG autoantibodies against the alpha-chain of the high affinity IgE receptor are claimed to play a pathogenetic role in autoimmune urticaria. The best methods for detection of functional autoantibodies are currently the autologous serum skin test and the basophil histamine release assay. A simplified and feasible screening test would facilitate the diagnosis of autoimmune urticaria. Here we offer an explanation for the difficulties in establishing a screening test for autoantibodies directed against the alpha-chain of the high affinity IgE receptor in autoimmune urticaria. Identical autoantibodies in chronic urticaria patients and healthy donors belonging to the natural autoantibody repertoire were found by sequence analysis of anti-alpha-chain autoantibodies isolated by repertoire cloning from antibody libraries. These natural autoantibodies bound to the receptor and triggered histamine release but only if IgE was previously removed from the receptor. Diagnostic assays used for detection of antibodies directed against the IgE receptor may require signal comparison with and without the artificial removal of IgE, immune complexes, and complement in order to avoid false positive or negative results. After IgE removal diagnostic tests will detect natural autoantibodies against the high affinity IgE receptor regardless of whether they are pathogenic or not.

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

Proceedings of the First Conference on Cancer Diagnostic Tests /

Mode of access: Internet.

Genetic diversity of Plasmodium falciparum histidine-rich protein 2 (PfHRP2) and its effect on the performance of PfHRP2-based rapid diagnostic tests

Rising costs of antimalarial agents are increasing the demand for accurate diagnosis of malaria. Rapid diagnostic tests (RDTs) offer great potential to improve the diagnosis of malaria, particularly in remote areas. Many RDTs are based on the detection of Plasmodium falciparum histidine-rich protein (PfHRP) 2, but reports from field tests have questioned their sensitivity and reliability. We hypothesize that the variability in the results of PfHRP2-based RDTs is related to the variability in the target antigen. We tested this hypothesis by examining the genetic diversity of PfHRP2, which includes numerous amino acid repeats, in 75 P. falciparum lines and isolates originating from 19 countries and testing a subset of parasites by use of 2 PfHRP2-based RDTs. We observed extensive diversity in PfHRP2 sequences, both within and between countries. Logistic regression analysis indicated that 2 types of repeats were predictive of RDT detection sensitivity (87.5% accuracy), with predictions suggesting that only 84% of P. falciparum parasites in the Asia-Pacific region are likely to be detected at densities