Chromatin three-dimensional genome structure plays a key role in cell function and gene regulation. Single-cell Hi-C techniques can capture genomic structure information at the cellular level, which provides an opportunity to study changes in genomic structure between different cell types. Recently, some excellent computational methods have been developed for single-cell Hi-C data analysis. In this paper, the available methods for single-cell Hi-C data analysis were first reviewed, including preprocessing of single-cell Hi-C data, multi-scale structure recognition based on single-cell Hi-C data, bulk-like Hi-C contact matrix generation based on single-cell Hi-C data sets, pseudo-time series analysis, and cell classification. Then the application of single-cell Hi-C data in cell differentiation and structural variation was described. Finally, the future development direction of single-cell Hi-C data analysis was also prospected.
ObjectiveTo analyze the relation between the place of residence of patients with colorectal cancer (CRC) and patient compliance or regimen decision-making or outcomes for neoadjuvant therapy (NAT) in the current version of the Database from Colorectal Cancer (DACCA). MethodsThe version of DACCA selected for this analysis was updated on June 29, 2022. The patients were enrolled according to the established screening criteria and then assigned into inside and outside of Sichuan Province groups as well as inside and outside of Chengdu City groups. The differences in the patient compliance or regimen decision-making or outcomes (changes of symptom and imaging, and cancer marker carcinoembryonic antigen) for NAT were analyzed. ResultsA total of 3 574 data that met the screened criteria were enrolled, 3 142 (87.91%) and 432 (12.09%) were inside of Sichuan Province group and outside of Sichuan Province group, respectively; 1 340 (42.65%) and 1 802 (57.35%) were inside of Chengdu City group and outside of Chengdu City group in Sichuan Province, respectively. ① The constituent ratios of the patient compliance for NAT had no statistical differences between the inside and outside of Sichuan Province groups (χ2=0.299, P=0.585) as well as between the inside and outside of Chengdu City groups (χ2=3.109, P=0.078). ② In terms of the impact of the place of residence on the decision-making of NAT: For the patients with targeted therapy or not, there was a statistical difference between the inside and outside of Sichuan Province groups (χ2=5.047, P=0.025), but which had no statistical difference between the inside and outside of Chengdu City groups (χ2=0.091, P=0.762); For the patients with radiotherapy or not, there were no statistical differences in the constituent ratios of patients between the inside and outside of Sichuan Province groups as well as between the inside and outside of Chengdu City groups (χ2=2.215, P=0.137; χ2=2.964, P=0.085); For the neoadjuvant intensity, there was a statistical difference between the inside and outside of Sichuan Province groups (χ2=12.472, P=0.002), but which had no statistical difference between the inside and outside of Chengdu City groups (χ2=2.488, P=0.288). ③ The outcomes for NAT: The changes of carcinoembryonic antigen had no statistical differences between the inside and outside of Sichuan Province groups as well as between the inside and outside of Chengdu City groups (H=1.762, P=0.184; H=3.531, P=0.060); In the symptom changes, there was a statistical difference between the inside and outside of Sichuan Province groups (χ2=3.896, P=0.048), which had no statistical difference between the inside and outside of Chengdu City groups (χ2=0.016, P=0.900); In the image changes, the difference was statistically significant between the inside and outside of Chengdu City groups (χ2=7.975, P=0.005), but which had no statistical difference between the inside and outside of Sichuan Province groups (χ2=0.063, P=0.802). ConclusionsThrough data analysis in DACCA in this study, it is found that there are no statistical differences in compliance and carcinoembryonic antigen changes. However, decision-making of NAT for patients of inside and outside of Sichuan Province has different choices on whether to assist targeted therapy and chemotherapy intensity for NAT; Symptom changes of NAT in patients of inside of Sichuan Province has a better effect than in patients of outside of Sichuan Province; Imaging change of NAT in patients of inside of Chengdu City has a better effect than in patients of outside of Chengdu City.
ObjectiveTo analyze the relation between educational level of patients with colorectal cancer (CRC) and decision-making and curative effect of neoadjuvant therapy (NAT) in the current version of the Database from Colorectal Cancer (DACCA). MethodsThe eligible CRC patients were collected from June 29, 2022 updated DACCA according to the screening criteria and were assigned into 4 groups according to their educational level, namely, uneducated, primary educated, secondary educated, and tertiary educated. The differences in NAT decision-making, cancer marker change, symptomatic change, gross change, imaging change, and tumor regression grade (TRG) among the CRC patients with different educational levels were compared. ResultsA total of 2 816 data that met the screening criteria were collected, 138 of whom were uneducated, 777 of whom were primary educated, 1 414 of whom were secondary educated, and 487 of whom were tertiary educated. The analysis results revealed that the difference in the composition ratio of patients choosing NAT regimens by educational level was statistically significant (χ2=30.937, P<0.001), which was reflected that the composition ratio of choosing a simple chemotherapy regimen in the uneducated CRC patients was highest, while which of choosing combined targeted therapy regimen in the tertiary educated CRC patients was highest. In terms of treatment outcomes, the composition ratios of changes in cancer markers (H=4.795, P=0.187), symptoms (H=1.722, P=0.632), gross (H=2.524, P=0.471), imaging (H=2.843, P=0.416), and TRG (H=2.346, P=0.504) had no statistical differences. ConclusionsThrough data analysis in DACCA, it is found that the educational level of patients with CRC can affect the choice of NAT scheme. However, it is not found that the educational level is related to the changes in the curative effect of patients with CRC before and after NAT, and further analysis is needed to determine the reasons for this.
ObjectiveTo analyze the association between preoperative staging (cTNM) and neoadjuvant therapy regimen decision-making and efficacy in patients with rectal cancer in the current version of Database from Colorectal Cancer (DACCA). MethodsThe data analysis for this study selected the DACCA version updated on April 20, 2024. The patient information was collected and categorized into three stages (Ⅱ, Ⅲ, and Ⅳ). The differences in neoadjuvant treatment decision-making and therapeutic effects, including gross changes, imaging changes, and tumor regression grade (TRG), were analyzed. ResultsA total of 3 158 eligible cases were collected in this study, with complete preoperative staging and neoadjuvant therapy decision-making data available for 2 370 patients. There were statistically significant differences in the overall comparison among the patients with rectal cancer in terms of the selection of combined targeted therapy, radiotherapy regimens, and the intensity of neoadjuvant chemotherapy by patients at different preoperative stages (χ2=42.239, P<0.001; χ2=41.615, P<0.001; H=1.161, P=0.004). Specifically, the proportion of patients choosing combined targeted therapy and combined radiotherapy gradually increased as the stage advanced. Among patients at different stages, the proportion of those choosing medium-course chemotherapy was the highest, and the proportion of patients choosing long-course chemotherapy was the highest among those with more advanced stages. Regarding the gross changes, imaging changes, and TRG results after neoadjuvant treatment in the patients at different preoperative stages, there were statistically significant differences in the overall comparison among patients with stage Ⅱ, Ⅲ, and Ⅳ rectal cancer (H=7.860, P=0.020; H=9.845, P=0.007; H=6.680, P=0.035). The proportion of partial response was the highest across all response metrics (macroscopic, radiographic, and TRG) in each stage. Notably, stage Ⅱ patients demonstrated the highest rate of complete response. For TRG evaluation, grade 2 (TRG2) was the most common outcome across all stages. ConclusionsData analysis from DACCA reveals that patients with advanced stages are more likely to choose chemotherapy combined with targeted therapy or radiotherapy, and had a higher proportion of intermediate range chemotherapy and the intensity of neoadjuvant chemotherapy is stronger. In terms of neoadjuvant treatment effects, the earlier the staging, the better the gross and imaging changes, and the lower the TRG level.
Objective To analyze the primary status of database in multi-disciplinary team （MDT） of colorectal cancer, and to explore the tendency in construction of database in the future. Methods Described the current status of different database respectively, and analyzed the data statistically, involving the patients’ general information, essential information of duration of hospital stay, therapy and MDT from the database of patients. Results The development of different database was uncoordinated. Among the total, the database of patients was advanced, the database of reference and the database of specialists were also developing in certain. Conclusion The primary reason, which results in the lag of construction of database currently, is the long span of database and the cost of much time in data acquisition. The direction of development of database involves consummation of database gradually, refreshment of it promptly, and expanding the research of informatics related clinical medicine.
ObjectiveTo analyze the relation between the age of patients with colorectal cancer and neoadjuvant therapy (NAT) regimen decision-making and outcomes in the current version of the Database from Colorectal Cancer (DACCA). MethodsThe version of DACCA selected for this analysis was updated on January 5, 2022. The patients were enrolled according to the established screening criteria and then assigned to 3 age groups: ≤45, 45–65, and ≥65 years old groups. The differences in the NAT regimen decision-making and changes of symptom, imaging, and cancer markers in these 3 age groups were analyzed. ResultsA total of 4 882 data that met the screened criteria were enrolled. The results of statistical analysis showed that the difference in the constituent ratio of patients chosen NAT strategies among 3 age groups was not statistically significant (χ2=8.885, P=0.180). There was a statistical difference in the constituent ratio of patients chosen combined target drug among 3 age groups (χ2=8.530, P=0.014), it was found that the proportion of the patients with ≤45 years old adopting combined target drug regimen was higher. Although the changes of symptom (H=12.299, P=0.056), image (H=1.775, P=0.412), and cancer markers (H=11.351, P=0.183) had no statistical differences of the 3 age groups after NAT, it was found that the proportions of patients with ≥65 years old with progresses of symptom and imaging changes and elevated cancer markers after NAT were higher, and the proportions of patients with ≤45 years old with complete and partial remissions of symptom and imaging changes and with normal cancer markers after NAT were higher. ConclusionsThrough analysis of DACCA data, it is found that in the selection of NAT strategy for colorectal cancer, the lower age group, the higher proportion of patients adopting combined target drug regimen. Although it is not found that age is related to changes of symptoms, imaging, and cancer markers after NAT, it still shows a trend of better outcomes in younger patients.
ObjectiveTo compare and evaluate the discrimination, validity, and reliability of different data envelopment analysis (DEA) models for measuring the effectiveness of models by selecting different input and output indicators of the model.MethodsData from health statistical reports and pilot program of diagnosis-related groups of tertiary hospitals in Hubei Province from 2017 to 2018 were used to analyze the discrimination, content and structure validity, and reliability of the models. Six DEA models were established by enriching the details of input and output on the basis of the input and output indicators of the conventional DEA model of hospitals.ResultsFrom the view of discrimination, the results of all models were left-skewed, the cost-efficiency model had the lowest left-skewed degree (skewness coefficient: -0.14) and was the flattest (kurtosis coefficient: -1.02). From the view of structure validity, the results of the cost-efficiency model were positively correlated with total weights, outpatient visits, and inpatient visits (r=0.328, 0.329, 0.315; P<0.05). From the perspective of content validity, the interpretation of model was more consistent with theory of production after revision of input and output indicators. From the view of reliability, the cost efficiency model had the largest correlation coefficient between the data of 2017 and 2018 (r=0.880, P<0.05).ConclusionsAfter refining the input and output indicators of the DEA model, the discrimination, validity, and reliability of the model are higher, and the results are more reasonable. Using indicators such as discrimination, validity, and reliability can measure the effectiveness of the DEA model, and then optimize the model by selecting different input and output indicators.
Based on previous evidence-based researches and teaching experience, our team conducted literature and book review, and summarized 4 requirements, 1) effect measure calculation and conversion, 2) registration of evidence-based research, 3) evidence-based research database and 4) quality evaluation tools and reporting guidelines. We developed an online platform of evidence-based medicine research helper using the front-end and back-end technology, which can be accessed using www.ebm-helper.cn. Currently, the online tool has included 46 scenarios for effect measure calculation and conversion, introduction of 7 evidence-based research registration platforms, 26 commonly used databases for evidence-based research and 29 quality evaluation tools and reporting guidelines. This online tool can help researchers to solve specific problems encountered in different stages of evidence-based medicine research. Promoting the application of this platform in evidence-based medicine will help researchers to use the tool scientifically and improve research efficiency.
Data management system is a major factor affecting the quality of clinical trial. Development of data management system include a steering group and data safety and monitoring board, data collection, database, performance of the data safety and monitoring, as well as locking of database. This article provides key issues of the five parts so as to help researchers understand the clinical trial data management system.
ObjectiveTo provide method references for data visualization of multiple linear regression analysis.MethodsAfter importing data to R Studio, this paper conducted general descriptive statistics analysis, then constructed a linear model between independent variables and the target. After checking independence of observations, the normality of the target, and the linearity between variables, this paper estimated coefficients of independent variables, dealt with multicollinearity, tested significance of estimates and performed residual analysis to guarantee that the regression met its assumptions, and eventually used the fitted model for prediction.ResultsThe multiple linear regression analysis implemented by R Studio software had better visualization functions and easier operation than traditional R language software.ConclusionsR Studio software has good application value in realizing multiple linear regression analysis data visualization.
