The proportion, species distribution and dynamic trends of bloodstream infection cases in a tertiary hospital in China, 2010-2019.

BACKGROUND: Recent epidemiological studies on bloodstream infection (BSI) that include the proportion, species distribution and dynamic changes are scarce in China. This study was performed to understand these epidemiological data of BSI over the past 10 years in China. METHODS: Using a prospective nosocomial infection surveillance system, this study was retrospectively performed in one of the largest hospitals in China. The time trend was tested using the Cochran-Armitage trend test in R Programming Language. RESULTS: From 2010 to 2019, there were totally 9381 episodes of BSI cases out of 1,437,927 adult-hospitalized patients in the hospital, the total proportion of BSI cases was 6.50‰ (6.50 episodes per 1000 adult-hospitalized patients) and the proportion had significantly decreased (8.24-6.07‰, time trend P < 0.001). Among the 9381 episodes of BSI, 93.1% were bacteremia and others were fungemia (6.9%). As the most common species, the composition ratios of coagulase-negative staphylococcus (25.6-32.5%), Escherichia coli (9.8-13.6%) and Klebsiella pneumoniae (5.3-10.4%) had been dynamically increased (all time trends P < 0.05) and the proportion of Pseudomonas aeruginosa had decreased (4.0-2.4%, time trend P = 0.032). However, Staphylococcus aureus (3.3-3.1%) and Acinetobacter baumannii (4.4-4.2%) had not changed significantly (P > 0.05). These common species were consistent with China Antimicrobial Surveillance Network reported in 2018 (2018 CHINET report), but their composition ratios were different. In addition, among bacteremia, the proportion of multidrug-resistant bacteria gradually increased from 52.9 to 68.4% (time trend P < 0.001). CONCLUSION: The proportion and species distribution of BSI were dynamically changing along certain trends. These trends deserved more attention from clinicians and researchers.

Power comparison of Cochran-Armitage trend test against allelic and genotypic tests in large-scale case-control genetic association studies.

The Cochran-Armitage trend test (CA) has become a standard procedure for association testing in large-scale genome-wide association studies (GWAS). However, when the disease model is unknown, there is no consensus on the most powerful test to be used between CA, allelic, and genotypic tests. In this article, we tackle the question of whether CA is best suited to single-locus scanning in GWAS and propose a power comparison of CA against allelic and genotypic tests. Our approach relies on the evaluation of the Taylor decompositions of non-centrality parameters, thus allowing an analytical comparison of the power functions of the tests. Compared to simulation-based comparison, our approach offers the advantage of simultaneously accounting for the multidimensionality of the set of features involved in power functions. Although power for CA depends on the sample size, the case-to-control ratio and the minor allelic frequency (MAF), our results first show that it is largely influenced by the mode of inheritance and a deviation from Hardy-Weinberg Equilibrium (HWE). Furthermore, when compared to other tests, CA is shown to be the most powerful test under a multiplicative disease model or when the single-nucleotide polymorphism largely deviates from HWE. In all other situations, CA lacks in power and differences can be substantial, especially for the recessive mode of inheritance. Finally, our results are illustrated by the comparison of the performances of the statistics in two genome scans.

[Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study].

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value

Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study / 中华流行病学杂志

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis,and the results were compared.Based on actual population,CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value＜linear regression P value).The statistical power of CAT test decreased,while the result of linear regression analysis remained the same when population size was reduced by 100 times and AMI incidence rate remained unchanged.The two statistical methods have their advantages and disadvantages.It is necessary to choose statistical method according the fitting degree of data,or comprehensively analyze the results of two methods.

Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study / 中华流行病学杂志

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis,and the results were compared.Based on actual population,CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value＜linear regression P value).The statistical power of CAT test decreased,while the result of linear regression analysis remained the same when population size was reduced by 100 times and AMI incidence rate remained unchanged.The two statistical methods have their advantages and disadvantages.It is necessary to choose statistical method according the fitting degree of data,or comprehensively analyze the results of two methods.

Testing for association in case-control genome-wide association studies with shared controls.

The statistical analysis of genome-wide association studies (GWASs) with multiple diseases and shared controls (SCs) is discussed. The usual method for analyzing data from these studies is to compare each individual disease with either the SCs or the pooled controls which include other diseases. We observed that applying individual association tests can be problematic because these tests may suffer from power loss in detecting significant associations between diseases and single-nucleotide polymorphism or copy number variant. We propose here a two-stage procedure wherein we first apply an overall chi-square test for multiple diseases with SCs; if the overall test is rejected, then individual tests using the chi-square partition method will be applied to each disease against SCs. A real GWAS data set with SCs and a Monte Carlo simulation study are used to demonstrate that the proposed method is more effective and preferable than other existing methods for analyzing data from GWASs with multiple diseases and SCs.

Sample size calculation in dose-response research / 中国临床药理学与治疗学

AIM:To introduce and evaluate two methods for sample size calculation in doseresponse research.METHODS:The methods used for sample size calculation in dose-response research include Cochran-Armitage trend(CAT) test proposed by Jun-mo Nam and the Unified contrast(CUC) method proposed by Chang. This paper takes the example of binary data,uses the two methods to calculate the required sample size and evaluate the power by simulation under the assumption that the response rate had a linear relationship with dosage under the logit scale.RESULTS:When the probability of response followed a linear trend on the logit scale, the sample sizes estimated from the two methods are approximately equal in various parameter's settings.The simulated power of CAT test was close to the expected one,however,the simulated power of CUC method was obviously affected by the values of contrast coefficient,if a contrast whose coefficients parallel the expected response, the CUC method was more powerful. CONCLUSION:When the probability of response follows a linear trend over dosage on the logit scale,the two methods reach almost the same result,in such circumstance,the Chang's unified contrast method will obtain an increasing power.