Pretest expectations strongly influence interpretation of abnormal laboratory results and further management

Contains fulltext : 89631.pdf (publisher's version ) (Open Access)BACKGROUND: Abnormal results of diagnostic laboratory tests can be difficult to interpret when disease probability is very low. Although most physicians generally do not use Bayesian calculations to interpret abnormal results, their estimates of pretest disease probability and reasons for ordering diagnostic tests may--in a more implicit manner--influence test interpretation and further management. A better understanding of this influence may help to improve test interpretation and management. Therefore, the objective of this study was to examine the influence of physicians' pretest disease probability estimates, and their reasons for ordering diagnostic tests, on test result interpretation, posttest probability estimates and further management. METHODS: Prospective study among 87 primary care physicians in the Netherlands who each ordered laboratory tests for 25 patients. They recorded their reasons for ordering the tests (to exclude or confirm disease or to reassure patients) and their pretest disease probability estimates. Upon receiving the results they recorded how they interpreted the tests, their posttest probability estimates and further management. Logistic regression was used to analyse whether the pretest probability and the reasons for ordering tests influenced the interpretation, the posttest probability estimates and the decisions on further management. RESULTS: The physicians ordered tests for diagnostic purposes for 1253 patients; 742 patients had an abnormal result (64%). Physicians' pretest probability estimates and their reasons for ordering diagnostic tests influenced test interpretation, posttest probability estimates and further management. Abnormal results of tests ordered for reasons of reassurance were significantly more likely to be interpreted as normal (65.8%) compared to tests ordered to confirm a diagnosis or exclude a disease (27.7% and 50.9%, respectively). The odds for abnormal results to be interpreted as normal were much lower when the physician estimated a high pretest disease probability, compared to a low pretest probability estimate (OR = 0.18, 95% CI = 0.07-0.52, p < 0.001). CONCLUSIONS: Interpretation and management of abnormal test results were strongly influenced by physicians' estimation of pretest disease probability and by the reason for ordering the test. By relating abnormal laboratory results to their pretest expectations, physicians may seek a balance between over- and under-reacting to laboratory test results

P73 Preliminary results of the Study of Acute Liver Transplant (SALT): NSAID exposure and risk of acute liver failure leading to transplantation in 7 European countries

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Activation of Insulin-Reactive CD8 T-Cells for Development of Autoimmune Diabetes

Objective: We have previously reported a highly diabetogenic CD8 T cell clone, G9C8, in the Non Obese Diabetic (NOD) mouse, specific to low avidity insulin peptide B15-23 and cells responsive to this antigen are among the earliest islet infiltrates. We aimed to study the selection, activation and development of diabetogenic capacity of these insulin-reactive T cells. Research Design and Methods: We generated a TCR transgenic mouse expressing the cloned TCR Vα18/Vβ6 receptor of the G9C8 insulin-reactive CD8 T cell clone. The mice were crossed to TCRCα−/− mice so that the majority of the T cells expressed the clonotypic TCR and the phenotype and function of the cells was investigated. Results: There was good selection of CD8 T cells with a predominance of CD8 single positive thymocytes, in spite of thymic insulin expression. Peripheral lymph node T cells had a naïve phenotype (CD44lo, CD62Lhi) and proliferated to insulin B15-23 peptide and to insulin. These cells produced interferon-γ and TNF-α in response to insulin peptide and were cytotoxic to insulin-peptide coated targets. In vivo, the TCR transgenic mice developed insulitis but not spontaneous diabetes. However, the mice developed diabetes on immunization, and the activated transgenic T cells were able to transfer diabetes to immunodeficient NOD.scid mice. Conclusion: Autoimmune CD8 T cells responding to a low affinity insulin B chain peptide escape from thymic negative selection, and require activation in vivo to cause diabetes

Insulin gene VNTR genotype associates with frequency and phenotype of the autoimmune response to proinsulin

Immune responses to autoantigens are in part controlled by deletion of autoreactive cells through genetically regulated selection mechanisms. We have directly analyzed peripheral CD4+ proinsulin (PI) 76–90 (SLQPLALEGSLQKRG)-specific T cells using soluble fluorescent major histocompatibility complex class II tetramers. Subjects with type I diabetes and healthy controls with high levels of peripheral proinsulin-specific T cells were characterized by the presence of a disease-susceptible polymorphism in the insulin variable number of tandem repeats (INS-VNTR) gene. Conversely, subjects with a ‘protective' polymorphism in the INS-VNTR gene had nearly undetectable levels of proinsulin tetramer-positive T cells. These results strongly imply a direct relationship between genetic control of autoantigen expression and peripheral autoreactivity, in which proinsulin genotype restricts the quantity and quality of the potential T-cell response. Using a modified tetramer to isolate low-avidity proinsulin-specific T cells from subjects with the susceptible genotype, transcript arrays identified several induced pro-apoptotic genes in the control, but not diabetic subjects, likely representing a second peripheral mechanism for maintenance of tolerance to self antigens

Statistical colocalization of monocyte gene expression and genetic risk variants for type 1 diabetes

One mechanism by which disease-associated DNA variation can alter disease risk is altering gene expression. However, linkage disequilibrium (LD) between variants, mostly single-nucleotide polymorphisms (SNPs), means it is not sufficient to show that a particular variant associates with both disease and expression, as there could be two distinct causal variants in LD. Here, we describe a formal statistical test of colocalization and apply it to type 1 diabetes (T1D)-associated regions identified mostly through genome-wide association studies and expression quantitative trait loci (eQTLs) discovered in a recently determined large monocyte expression data set from the Gutenberg Health Study (1370 individuals), with confirmation sought in an additional data set from the Cardiogenics Transcriptome Study (558 individuals). We excluded 39 out of 60 overlapping eQTLs in 49 T1D regions from possible colocalization and identified 21 coincident eQTLs, representing 21 genes in 14 distinct T1D regions. Our results reflect the importance of monocyte (and their derivatives, macrophage and dendritic cell) gene expression in human T1D and support the candidacy of several genes as causal factors in autoimmune pancreatic beta-cell destruction, including AFF3, CD226, CLECL1, DEXI, FKRP, PRKD2, RNLS, SMARCE1 and SUOX, in addition to the recently described GPR183 (EBI2) gene