Statistical inference in brain graphs using threshold-free network-based statistics

The description of brain networks as graphs where nodes represent different brain regions and edges represent a measure of connectivity between a pair of nodes is an increasingly used approach in neuroimaging research. The development of powerful methods for edge‐wise group‐level statistical inference in brain graphs while controlling for multiple‐testing associated false‐positive rates, however, remains a difficult task. In this study, we use simulated data to assess the properties of threshold‐free network‐based statistics (TFNBS). The TFNBS combines threshold‐free cluster enhancement, a method commonly used in voxel‐wise statistical inference, and network‐based statistic (NBS), which is frequently used for statistical analysis of brain graphs. Unlike the NBS, TFNBS generates edge‐wise significance values and does not require the a priori definition of a hard cluster‐defining threshold. Other test parameters, nonetheless, need to be set. We show that it is possible to find parameters that make TFNBS sensitive to strong and topologically clustered effects, while appropriately controlling false‐positive rates. Our results show that the TFNBS is an adequate technique for the statistical assessment of brain graphs.

The utility of genotypic tropism testing in clinical practice

A review of a large number of HIV-1 tropism test requests (n = 1148) performed at a London tertiary referral centre was carried out. The aim was to establish whether these were being performed in line with recommendations from published guidelines and whether this represented the most cost-effective use of these tests in informing prescribing decisions of the CCR5 antagonist drug, maraviroc. The cost of these assays within the UK was covered by commercial funding until April 2013 which has subsequently been withdrawn. Furthermore, all healthcare settings are under increasing cost constraints and hence establishing the real utility and appropriate use of these tests is of vital importance.

Comparative evaluation of the performance of the Abbott real-time human immunodeficiency virus type 1 (HIV-1) assay for measurement of HIV-1 plasma viral load following automated specimen preparation

The performance of the new Abbott real-time human immunodeficiency virus type 1 (HIV-1) assay for HIV-1 RNA load determination in plasma was compared to that of the Abbott LCx HIV-1 RNA quantitative assay following automated RNA isolation by the Abbott m1000 extractor. The measured viral loads of 89 clinical specimens differed by mean 0.19 log10 copies/ml (95% confidence interval, 0.12 to 0.26 log10 copies/ml). Although the difference in viral load determinations was positively skewed in favor of the LCx assay, it did not reach statistical significance (P = 0.42). Results were linearly associated (R2 = 0.94) and strongly correlated (R = 0.96). Good performance was observed with HIV-1 subtypes other than B and circulating recombinant forms, although results obtained with two subtype G specimens and one H specimen showed a more substantial difference.