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Romdhani et al. (2015) used the Generalized Structured Component Analysis (GSCA) developed by Hwang and Takane (2004). This method uses component-based path modelling rather than traditional covariance-based SEM, allowing adequate model fit to be achieved when using smaller samples ( Chin & Newstead, 1999; Tenenhaus et al., 2005). The measurement models in the SEM framework are not typical regression format using latent factors; instead they are fitted using alternating least squares to estimate the weights and parameters, which is similar to principal components analysis. The advantage of this approach is that it does not attempt to fit the whole covariance matrix for observed and latent variables, but rather fits a separate measurement model for the contribution of observed variables to each latent factor, as well as a covariance model for the latent factors. Hence, we do not estimate the contribution of individual SNPs in each gene to the phenotype; rather, their influence is represented via the weighted sum. Similarly, the latent phenotypic factor (termed Neuro in Figure 4) is a weighted sum of the three measures of the phenotype. We will estimate the significance of one direct pathway from the CNTNAP2 gene to the latent phenotype, and one from NRXN1 to the latent phenotype. This method thus gives a single estimate of the overall impact of SNPs in a region of the phenotype.
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Unlike current diagnostic tests, new diagnostic tests for the detection of COVID-19 must be sensitive enough to detect the presence of the virus and thus prevent its spread, as well as being affordable enough and of easy execution to allow multiple repetitions for as many times as necessary. The use of diagnostic technology using aptamers has practical advantages over other technologies [6,7,8].
Using a similar analysis, the proportions of positive and negative cases were broken down and expressed as percentages in frequency plots (Figure 4) for each experimental condition used. The proportions of positive and negative cases were classified with RTqPCR, which correspond to the ideal result, are shown in the upper panel and the FLAA classification can be seen in the lower panel. Again, bars in the FLAA test should be as similar as possible to those in the RTqPCR. It can be seen that the proportion of FLAA in the direct protocol is more similar to that of RTqPCR (yellow rectangle), while the swab samples (red rectangle) are better than those of saliva with a slight advantage of the D-swab (purple rectangle) (Figure 5).
The updated PFS, using a cut-off of 1 February 2016 (96.7 months follow up) continues to show a PFS advantage: HR = 0.57 (95% CI 0.47, 0.68; p
Updated OS results, using a cut-off of 01 May 2018 (84.2 months median follow-up for surviving subjects) continue to show an OS advantage favouring RVd: HR = 0.73 (95% CI 0.57, 0.94; p=0.014). The proportion of subjects alive after 7 years was 54.7% in the RVd arm versus 44.7% in the Rd arm.
In this pooled extended follow-up analysis, the median TTP was 60.1 weeks (95% CI: 44.3, 73.1) in patients treated with len/dex (N = 353) versus 20.1 weeks (95% CI: 17.7, 20.3) in patients treated with placebo/dex (N = 351). The median progression free survival was 48.1 weeks (95% CI: 36.4, 62.1) in patients treated with len/dex versus 20.0 weeks (95% CI: 16.1, 20.1) in patients treated with placebo/dex. The median duration of treatment was 44.0 weeks (min: 0.1, max: 254.9) for len/dex and 23.1 weeks (min: 0.3, max: 238.1) for placebo/dex. Complete response (CR), partial response (PR) and overall response (CR+PR) rates in the len/dex arm remain significantly higher than in the placebo/dex arm in both studies. The median overall survival in the extended follow-up analysis of the pooled studies is 164.3 weeks (95% CI: 145.1, 192.6) in patients treated with len/dex versus 136.4 weeks (95% CI: 113.1, 161.7) in patients treated with placebo/dex. Despite the fact that 170 out of the 351 patients randomised to placebo/dex received lenalidomide after disease progression or after the studies were unblinded, the pooled analysis of overall survival demonstrated a statistically significant survival advantage for len/dex relative to placebo/dex (HR = 0.833, 95% CI = [0.687, 1.009], p=0.045). 2ff7e9595c
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