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Info Custom modeling rendering Along with Polynomial Representations as well as Autoregressive Time-Series Representations, in addition to their Connections.
In the past decades, the world has experienced several major virus outbreaks, e.g. West African Ebola outbreak, Zika virus in South America and most recently global coronavirus (COVID-19) pandemic. Many vaccines have been developed to prevent a variety of infectious diseases successfully. However, several infections have not been preventable so far, like COVID-19, which induces an immediate urgent need for effective vaccines. These emerging infectious diseases often pose unprecedent challenges for the global heath community as well as the conventional vaccine development paradigm. With a long and costly traditional vaccine development process, there are extensive needs in innovative vaccine trial designs and analyses, which aim to design more efficient vaccines trials. Featured with reduced development timeline, less resource consuming or improved estimate for the endpoints of interests, these more efficient trials bring effective medicine to target population in a faster and less costly way. In this paper, we will review a few vaccine trials equipped with adaptive design features, Bayesian designs that accommodate historical data borrowing, the master protocol strategy emerging during COVID-19 vaccine development, Real-World-Data (RWD) embedded trials and the correlate of protection framework and relevant research works. We will also discuss some statistical methodologies that improve the vaccine efficacy, safety and immunogenicity analyses. Innovative clinical trial designs and analyses, together with advanced research technologies and deeper understanding of the human immune system, are paving the way for the efficient development of new vaccines in the future.
To describe the methods used to quantify heterogeneity and to propose alternative measures to improve reporting of heterogeneity in Cochrane diagnostic test accuracy (DTA) reviews.

Our metaepidemiological study included all DTA reviews in the Cochrane Library up to October 6th, 2019. We summarized reviews' characteristics focusing on heterogeneity analysis. We selected reviews with a bivariate model and ≥4 studies for reanalysis. In this group, we fitted bivariate random effects models and we quantified heterogeneity by means of logit variances of sensitivity and specificity, bivariate I
, median odds ratio (OR), and the area of the 95% prediction ellipse. We provided a narrative interpretation of these measures in different scenarios.

There were 124 Cochrane DTA reviews of which 91 (73%) included meta-analysis. Only in 5 meta-analyses, variances of the logit sensitivity and specificity were reported, and in 21 meta-analyses (23%), the 95% prediction ellipse was reported without any calculation of its area. We selected 60 of these 91 reviews to explore the behavior of all measures of heterogeneity. Fetuin order We found that most reviews described the subjective heterogeneity as moderate or extreme (n=31/60, 52%), whereas the area of the 95% prediction ellipse and the median OR for sensitivity and specificity showed high variability; the area ranged from 5% to 97%, the median OR of sensitivity ranged from 1.13 to 10.7, and the median OROR of specificity ranged from 1.18 to 19.68.

Cochrane DTA reviews show a poor reporting of between-study heterogeneity. Using median OR and the area of the 95% prediction ellipse will improve reporting and interpretation of this crucial aspect of DTA meta-analysis.
Cochrane DTA reviews show a poor reporting of between-study heterogeneity. Using median OR and the area of the 95% prediction ellipse will improve reporting and interpretation of this crucial aspect of DTA meta-analysis.
Comparing observed and expected distributions of categorical outcome variables in randomized controlled trials (RCTs) has been previously used to assess publication integrity. We applied this technique to withdrawals from RCTs.

We compared the observed distribution of withdrawals with the expected binomial distribution in six sets of RCTs four control sets and two sets with concerns about their publication integrity.

In the control data sets (n=13, 115, 71, and 36 trials, respectively), the observed distributions of withdrawals were consistent with the expected distributions, both for the numbers of withdrawals per trial arm and for the differences in withdrawals between trial arms in two-arm RCTs. In contrast, in both sets of RCTs with concerns regarding publication integrity (n=151 and 35 trials, respectively), there were striking differences between the observed and expected distributions of trial withdrawals. Two-arm RCTs from the two sets with publication integrity concerns were 2.6 (95% confidence interval 2.0-3.3) times more likely to have a difference of 0 or 1 withdrawals between trial arms than control RCTs (P<0.001). Simulating a 50% higher rate of withdrawals in active treatment arms in the largest set of control RCTs still produced an observed distribution of withdrawals per trial arm consistent with the expected distribution.

Comparing the observed and expected distribution of trial withdrawals may be a useful technique when considering publication integrity of a body of RCTs.
Comparing the observed and expected distribution of trial withdrawals may be a useful technique when considering publication integrity of a body of RCTs.
The main aims of this metaresearch study conducted among high-impact rehabilitation journals were 1) to evaluate if the use of reporting guidelines (RGs) was declared and 2) to categorize the declared use as appropriate or inappropriate.

Cross-sectional analysis of a random sample of 200 studies published in the period 2010-2019 in five generic rehabilitation journals with the highest 5-year impact factor. Randomized controlled trials, systematic reviews, observational studies, and diagnostic studies were included. Prevalence with 95% confidence intervals (CIs) was estimated for the main outcomes.

Among the 200 selected studies, 17.5% (95% CI 12.2-22.8%) declared using RGs. Among these studies, 48.6% (95% CI 32-65.1%) declared an appropriate use. There was an increasing trend over time for authors to report the use of RGs (OR 1.31; 95% CI 1.13-1.53). Systematic reviews (n=54) reported more frequently the use of RGs than other study designs (35.2%).

In high-impact rehabilitation journals, a small minority of article authors declared the use of RGs.
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