Accuracy of B-type natriuretic peptide tests to exclude congestive heart failure: systematic review of test accuracy studies

BACKGROUND: Congestive heart failure (CHF) is a major public health problem. The use of B-type natriuretic peptide (BNP) tests shows promising diagnostic accuracy. Herein, we summarize the evidence on the accuracy of BNP tests in the diagnosis of CHF and compare the performance of rapid enzyme-linked immunosorbent assay (ELISA) and standard radioimmunosorbent assay (RIA) tests. METHODS: We searched electronic databases and the reference lists of included studies, and we contacted experts. Data were extracted on the study population, the type of test used, and methods. Receiver operating characteristic (ROC) plots and summary ROC curves were produced and negative likelihood ratios pooled. Random-effect meta-analysis and metaregression were used to combine data and explore sources of between-study heterogeneity. RESULTS: Nineteen studies describing 22 patient populations (9 ELISA and 13 RIA) and 9093 patients were included. The diagnosis of CHF was verified by echocardiography, radionuclide scan, or echocardiography combined with clinical criteria. The pooled negative likelihood ratio overall from random-effect meta-analysis was 0.18 (95% confidence interval [CI], 0.13-0.23). It was lower for the ELISA test (0.12; 95% CI, 0.09-0.16) than for the RIA test (0.23; 95% CI, 0.16-0.32). For a pretest probability of 20%, which is typical for patients with suspected CHF in primary care, a negative result of the ELISA test would produce a posttest probability of 2.9%; a negative RIA test, a posttest probability of 5.4%. CONCLUSIONS: The use of BNP tests to rule out CHF in primary care settings could reduce demand for echocardiography. The advantages of rapid ELISA tests need to be balanced against their higher cost.

Neospora caninum IgG avidity tests: an interlaboratory comparison

Avidity tests can be used to discriminate between cattle that are acutely and chronically infected with the intracellular parasite Neospora caninum. The aim of this study was to compare the IgG avidity ELISA tests being used in four European laboratories. A coded panel of 200 bovine sera from well documented naturally and experimentally N. caninum infected animals were analysed at the participating laboratories by their respective assay systems and laboratory protocols. Comparing the numeric test results, the concordance correlation coefficients were between 0.479 and 0.776. The laboratories categorize the avidity results into the classes "low" and "high" which are considered indicative of recent and chronic infection, respectively. Three laboratories also use an "intermediate" class. When the categorized data were analysed by Kappa statistics there was moderate to substantial agreements between the laboratories. There was an overall better agreement for dichotomized results than when an intermediate class was also used. Taken together, this first ring test for N. caninum IgG avidity assays showed a moderate agreement between the assays used by the different laboratories to estimate the IgG avidity. Our experience suggests that avidity tests are sometimes less robust than conventional ELISAs. Therefore, it is essential that they are carefully standardised and their performance continuously evaluated.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

ASSOCIATON TESTS THAT ACCOMMODATE GENOTYPING ERRORS

High-throughput SNP arrays provide estimates of genotypes for up to one million loci, often used in genome-wide association studies. While these estimates are typically very accurate, genotyping errors do occur, which can influence in particular the most extreme test statistics and p-values. Estimates for the genotype uncertainties are also available, although typically ignored. In this manuscript, we develop a framework to incorporate these genotype uncertainties in case-control studies for any genetic model. We verify that using the assumption of a “local alternative” in the score test is very reasonable for effect sizes typically seen in SNP association studies, and show that the power of the score test is simply a function of the correlation of the genotype probabilities with the true genotypes. We demonstrate that the power to detect a true association can be substantially increased for difficult to call genotypes, resulting in improved inference in association studies.