Time-to-event outcomes are a key component in survival analyses. Effect modification by time, also known as interaction between effect and time, can exist in time-to-event data and influence the analysis process. Our objective is to discuss the proper methods to conduct evidence synthesis of time-to-event data when effect modification by time exists.
Aiming at the problem of low recognition accuracy of motor imagery electroencephalogram signal due to individual differences of subjects, an individual adaptive feature representation method of motor imagery electroencephalogram signal is proposed in this paper. Firstly, based on the individual differences and signal characteristics in different frequency bands, an adaptive channel selection method based on expansive relevant features with label F (ReliefF) was proposed. By extracting five time-frequency domain observation features of each frequency band signal, ReliefF algorithm was employed to evaluate the effectiveness of the frequency band signal in each channel, and then the corresponding signal channel was selected for each frequency band. Secondly, a feature representation method of common space pattern (CSP) based on fast correlation-based filter (FCBF) was proposed (CSP-FCBF). The features of electroencephalogram signal were extracted by CSP, and the best feature sets were obtained by using FCBF to optimize the features, so as to realize the effective state representation of motor imagery electroencephalogram signal. Finally, support vector machine (SVM) was adopted as a classifier to realize identification. Experimental results show that the proposed method in this research can effectively represent the states of motor imagery electroencephalogram signal, with an average identification accuracy of (83.0±5.5)% for four types of states, which is 6.6% higher than the traditional CSP feature representation method. The research results obtained in the feature representation of motor imagery electroencephalogram signal lay the foundation for the realization of adaptive electroencephalogram signal decoding and its application.
Objective To investigate the relationship between single nucleotide polymorphism (SNP) and therapy response of some conventional chemotherapy drugs in breast cancer, and to explore the value of SNP in guiding individualized treatment. Methods Pub-Medline and Chinese CHKD periodical electronic databases were searched. Representative researches in this field were sorted out and concluded. Results Varied genes related to drug metabolism have SNP phenomenon, which are closely associated with interindividual diversity in drug response. Race, section, environment, and drug-drug or gene-gene interactions may have effect on the association.Conclusion The study on SNP has important application prospect in optimizing the individual drug-delivery. However, the combinatorial analyses of multi-SNPs and multi-genes and the prospective studies with large-scale samples and random controls are still needed.
Objective To explore the value of chemosensitivity assay in vitro on breast cancer. Methods In vitro chemosensitivity of 6 species of chemotherapeutic agents applied to 38 cases of breast cancer patients were detected by tissue culture-end point staining-computer image analysis (TECIA). Results The sensitivity to chemotherapeutic agents commonly used in the breast cancer level from high to low was as follow: Doxorubicin (ADM), Paclitaxel (TAX), Vinorelbine (NVB), Cyclophosphamide (CTX), Cisplatin (DDP) and Fluorouracil (FU). Conclusion Drugs sensitivity experiment of cancer in vitro by TECIA has an important value to instruct clinical medication and individual chemotherapy for breast cancer.
ObjectiveTo explore the clinical phenotype of patients with acute exacerbation of chronic obstructive pulmonary disease (COPD) by cluster analysis and provide a basis for individualized treatment.MethodsA total of 515 patients with acute exacerbation of COPD admitted to this department from January 2014 to December 2016 were enrolled. The age, duration, smoking index, number of hospitalizations in the past 1 year, hospitalization days, treatment costs and other information were collected for cluster analysis.ResultsThe patients were divided into three categories of phenotype: " mild-glucocorticoid resistance-antibiotic dependent”," mild-glucocorticoid sensitive”, and " serious complication”. The patients with the first two phenotypes had a milder condition and lower hospitalization costs. There were differences in the time and cumulative dose of glucocorticoids in different pathways, antibiotic use time and usage rate. The third phenotype was the most serious, with the highest cost of hospitalization, and may merge or co-exist with other diseases such as cardiovascular disease and digestive tract disease.ConclusionCluster analysis may identify different phenotypes of acute exacerbation of COPD to provide a reference for clinical individualized treatment.
To aim directly at the individualized character and tendency about clinical assessment of Traditional Chinese Medicine (TCM), we draw off a new pathway which is evidence-based goal attainment scale(EBGAS) in the text. i.e., we will develop clinical individualized assessment method of TCM on account of GAS by the approach of evidence based medicine.
Network meta-analysis (NMA) is a statistical technique that integrates data from multiple clinical studies and compares the efficacy and safety of multiple interventions, which can provide pro and con ranking results for all intervention options in the evidence network and provide direct evidence support for clinical decision-making. At present, NMA is usually based on the aggregation of the same type of data set, and there are still methodological and software difficulties in achieving cross-study design and cross-data format data set merging. The crossnma package of R programming language is based on Bayesian framework and Markov chain Monte Carlo algorithm, extending the three-level hierarchical model to the standard NMA data model to achieve differential merging of varied data types. The crossnma package fully considers the impact of risk bias caused by the combination of different types of data on the results by introducing model variables. In addition, the package provides functions such as result output and easy graphing, which makes it possible to combine NMA across study designs and evidence across data formats. In this study, the model based on crossnma package method and software operation will be demonstrated and explained through the examples of four individual participant datasets and two aggregate datasets.
The method of evaluating clinical efficacy of traditional Chinese medicine is one of the hotspots in the field of traditional Chinese medicine in recent years. How to dynamically evaluate individual efficacy is one of the key scientific problems to explain the clinical efficacy of traditional Chinese medicine. At present, there are no recognized methods of evaluating individual efficacy of traditional Chinese medicine. In this study, we provided a method of dynamically evaluating individual efficacy of traditional Chinese medicine based on Bayesian N-of-1 trials after analyzing the current status of researches on methods of evaluating individual efficacy of traditional Chinese medicine. This method has the advantages of both N-of-1 trials and Bayesian multilevel models. It is feasible to evaluate individual efficacy of traditional Chinese medicine from the perspective of the design and analysis method. This study can provide an important basis for enriching and improving the methodology of evaluating individual efficacy of traditional Chinese medicine.
Chronic obstructive pulmonary disease (COPD) is one of the common chronic airway disorders, which accounts for the third to fourth cause of death worldwide. Recently, the focuses of researches are on the multi-factorial risks for development of COPD, mechanisms related to COPD development, early detection and early intervention of COPD, individualized use of long-term maintenance medications as well as phenotypes of acute exacerbation of COPD and their corresponding management. There are huge amount of COPD patients with variety of risk factors or different phenotypes in China, which makes it possible to establish a network for cohort study or real life registration study of COPD. The results will provide new information on the characteristics of COPD in China. Individualized treatment could be recommended according to the phenotypes or endotypes information. All these new findings or progresses could provide impetus for improvement of the ability of research and clinical management of COPD to the worldwide top level.
The prominent feature and form of clinical diagnosis and treatment of traditional Chinese medicine is individualization, which has generated difficulty for clinical evaluation and has restricted the production of high-level evidence for traditional Chinese medicine for a long time. Based on the complexity and dynamics of individualized information under the characteristics of time and space, this paper references the theory of space-time of system science to analyze the individualized data of diagnosis and treatment of traditional Chinese medicine and summarizes the concept of the long time course for clinical evaluation. Based on the concept of the long time course, this paper starts with the origin of clinical evaluation, which is the construction of clinical problem elements named PICO, introduces dynamic evaluation factors, explores the construction of individualized dynamic evaluation method of traditional Chinese medicine, and provides demonstration and examples for the design and implementation of individualized clinical research in future.