Cluster randomized trial (CRT) is one of the most common design for complex intervention. This paper mainly introduced:the definition of CRT, two designs of CRT including the completely randomization and the restricted randomization (such as stratified randomization and matching randomization), and the statistical analysis methods (such as the general statistical analysis and mixed effect model/multi-level model). This paper also introduced how to estimate the sample size of a CRT, how to report a CRT, and how to apply it into a clinical or community study.
An N-of-1 trial was conducted in a single patient. Statistical analysis is one of the most important parts of N-of-1 trials. The methods of statistical analysis for N-of-1 trials were reported in some reviews. However, there was still a lack of comparative analysis of these methods. In this study, we introduced the characteristics of statistical methods commonly used as well as some statistical problems which should be paid attention in N-of-1 trials. It is useful to provide some reference for statistical methods in order to high quality N-of-1 trials.
There are so many biomechanical risk factors related with glaucoma and their relationship is much complex. This paper reviewed the state-of-the-art research works on glaucoma related mechanical effects. With regards to the development perspectives of studies on glaucoma biomechanics, a completely novel biomechanical evaluation factor -- Fractional Flow Reserve (FPR) for glaucoma was proposed, and developing clinical application oriented glaucoma risk assessment algorithm and application system by using the new techniques such as artificial intelligence and machine learning were suggested.
Research of generating real-world evidence using real world data has attracted considerable attention globally. Outcome research of treatment based on existing health and medical data or registries has become one of the most important topics. However, there exists certain confusions in this line of research on how to design and implement appropriate statistical analysis. Therefore, in the fourth chapter of the series technical guidance to develop real world evidence by China REal world data and studies Alliance (ChinaREAL), we aim to provide an guidance on statistical analysis in the study to assess therapeutic outcomes based on existing health and medical data or registries.In this chapter, we first emphasize the significance of pre-specified statistical analysis plan, recommending key components of the statistical analysis plan. We then summarize the issue of sample size calculation in this content and clarify the interpretation of statistical p-value. Secondly, we recommend procedures to be considered to tackle the issue related to the selection bias, information bias and most importantly, confounding bias. We discuss the multivariable regression analysis as well as the popular causal inference models. We also suggest that careful consideration should be made to deal with missing data in real-world databases. Finally, we list core content of the statistical report.
The study aims to investigate whether there is difference in pre-treatment white matter parameters in treatment-resistant and treatment-responsive schizophrenia. Diffusion tensor imaging (DTI) was acquired from 60 first-episode drug-naïve schizophrenia (39 treatment-responsive and 21 treatment-resistant schizophrenia patients) and 69 age- and gender-matched healthy controls. Imaging data was preprocessed via FSL software, then diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted. Besides, structural network matrix was constructed based on deterministic fiber tracking. The differences of diffusion parameters and topology attributes between three groups were analyzed using analysis of variance (ANOVA). Compared with healthy controls, treatment-responsive schizophrenia showed altered white matter mainly in anterior thalamus radiation, splenium of corpus callosum, cingulum bundle as well as superior longitudinal fasciculus. While treatment-resistant schizophrenia patients showed white matter abnormalities in anterior thalamus radiation, cingulum bundle, fornix and pontine crossing tract relative to healthy controls. Treatment-resistant schizophrenia showed more severe white matter abnormalities in anterior thalamus radiation compared with treatment-responsive patients. There was no significant difference in white matter network topological attributes among the three groups. The performance of support vector machine (SVM) showed accuracy of 63.37% in separating the two patient subgroups (P = 0.04). In this study, we showed different patterns of white matter alterations in treatment-responsive and treatment-resistant schizophrenia compared with healthy controls before treatment, which may help guiding patient identification, targeted treatment and prognosis improvement at baseline drug-naïve state.
Epigenetics refers to the modification effect of external and internal environmental factors on genes under the premise of the unaltered genetic sequence, leading to changes in gene expression level or function, and thereby affecting various phenotypes or disease outcomes. In recent years, epigenetics has attracted increasing attention. Among them, DNA methylation has been shown to be closely related to human development and the development of disease. However, the high-dimensional omics data generated by genome-wide methylation detection can comprehensively reflect the overall and local epigenetic modifications at the genome level, which has become one of the main research contents in this field. Based on genome-wide methylation chip data, this paper summarized the quality control process of this omics data, common epigenetic omics correlation statistical analysis methods and ideas, and visualization realization of main results based on SAS JMP Genomics 10 software, so as to provide reference for similar studies.
ObjectiveTo explore the abilities of thesis writing of postgraduate medical freshpeople and their factors, and provide a basis for postgraduate education and course design of thesis writing.MethodsA designed questionnaire was administered to postgraduate medical freshpeople enrolled in West China Medical School of Sichuan University in 2020. The general characteristics, current status of skills or experiences related to thesis writing, and abilities including literature retrieval and reading, statistical analysis, diagramming, research paper writing, and journal selection and submission of the postgraduates were collected in September 2020. Logical regression was conducted to analyze the factors affecting the abilities of thesis writing.ResultsA total of 503 valid questionnaires were collected. Over one half of the graduate students (58.3%) were satisfied with the ability of literature retrieval and reading, with the highest score among the five abilities [median (lower quartile, upper quartile) was 3 (2, 3)]. Less than 20% of the students were satisfied with the remaining four abilities, with the lowest scores in the abilities of diagramming, research paper writing, and journal selection and submission [each median (lower quartile, upper quartile) was 1 (1, 2)]. Research experience and acknowledge of reporting guidelines were independent factors for all abilities related to thesis writing (P<0.05). Proficiency in statistical software was an independent factor for the abilities of data statistical analysis, diagramming, research paper writing, and journal selection and submission (P<0.05). Having published scientific paper was an independent factor for ability of journal selection and submission [odds ratio=4.695, 95% confidence interval (2.166, 10.180), P<0.001].ConclusionsThe postgraduate medical freshpeople of West China Medical School are not satisfied with the ability of statistical analysis, diagramming, paper writing, or journal selection and submission. Attention should be paid to research practice and learning of reporting guidelines, while statistical courses and diagramming courses should be set up expressly.
The correct and reasonable statistical analysis method can make the results of comparative diagnosis test accuracy more convincing. In this paper, the accuracy of diagnostic tests is divided into 2 forms: binary-scale outcomes and ordinal-scale/continuous-scale outcomes. Taking diagnostic indicators such as sensitivity, specificity, receiver operating characteristic (ROC) curves and area under curve (AUC) values as entry points, combined with examples, this paper introduced how to compare the diagnostic results of tests by parameter estimation and hypothesis testing, with the aim of providing references for the comparative diagnosis test accuracy.
Stepped wedge cluster randomized trials (SW-CRT) is a kind of cluster randomized controlled trial mainly applied in the field of public health policy that has emerged in recent years, which has gradually attracted the attention of workers in the field of health and wellness. At present, this trial method is not widely used at home and abroad, and there are various ways of sample size calculation and statistical analysis. This paper describes the principles, categories, and differences between SW-CRT and traditional randomized controlled trials, and outlines sample size calculation and statistical analysis methods. In general, SW-CRT is characterized by clustering, cross-design, and measurement of results at multiple time points. In terms of sample size calculation, it is necessary to distinguish between clusters with the same and different sizes, and commonly used sample size calculation procedures can be implemented in Stata, R, and SAS software, as well as in fixed online websites, including the "Steppedwedge" program, the "swCRTdesign" program, the "Swdpwr" program, the "CRTpowerdist" program, and the "Shiny CRT Calculator" tool and so on. Based on the design characteristics of SW-CRT, the researcher should also consider the confounding factors of time effects and repeated measurements of result. Therefore, the statistical analysis methods are often based on generalized linear mixed model (GLMM) and generalized estimating equations (GEE). However, most of the above models have been proposed based on cross-sectional studies, there is a lack of statistical methods for queue design and SW-CRT with transitional period now, and more comprehensive methodological exploration is still needed in the future.