This paper summarizes the Risk of Bias of Individual Studies in Systematic Reviews of Health Care Interventions revised by the Agency for Healthcare Research and Quality (AHRQ) and introduces how to use Revman software make risk of bias graph or risk of bias summary. AHRQ tool can be used to evaluate following study designs: RCTs, cohort study, case-control study (including nested case-control), case series study and cross-sectional study. The tool evaluates the risk of bias of individual studies from selection bias, performance bias, attrition bias, detection bias and reporting bias. Each of the bias domains contains different items, and each item is available for the assessment of one or more study designs. It is worth noting that the appropriate items should be selected for evaluation different study designs instead of using all items to directly assess the risk of bias. AHRQ tool can be used to evaluate risk of bias individual studies when systematic reviews of health care interventions is including different study designs. Moreover, the tool items are relatively easy to understand and the assessment process is not complicated. AHRQ recommends the use of high, medium and low risk classification methods to assess the overall risk of bias of individual studies. However, AHRQ gives no recommendations on how to determine the overall bias grade. It is expected that future research will give corresponding recommendations.
Bias ; Evidence-Based Medicine/standards* ; Health Services Research ; Systematic Reviews as Topic

To evaluate the intervention effects of randomized controlled trials (RCT) involved in theoretical efficacy and actual clinical outcome (effectiveness). Pragmatic-Explanatory Continuum Indicator Summary (PRECIS) is a tool to help researchers make decisions in study design which is consistent with the intended purpose of their trial which can be used in the design of RCT to balance the internal validity and external validity. The role of PRECIS has been gradually recognized in the practice of designing clinical trials. To ensure that the design choices are concordant with the intention and the facilitation of use set by patients, clinicians and policy makers, a new PRECIS-2 tool has been developed by mangy international team experts under modification and upgrading the existing PRECIS. The PRECIS-2 tool mainly focuses on trial design choices which determining the applicability of a trial. PRECIS-2 has nine domains, with each of them intends to help the researchers consider the consequences of that design decision in terms of the applicability of the results under particular setting. The purpose of this paper is to introduce the development, basic principle, characteristics and application of PRECIS-2 for the designers and decision makers when working on clinical trials.
Communication ; Decision Making ; Humans ; Randomized Controlled Trials as Topic/methods* ; Research Design/standards*

Objective: Chronic obstructive pulmonary disease, asthma, interstitial lung disease and pulmonary thromboembolism are the most common and severe respiratory diseases, which seriously jeopardizing the health of the Chinese citizens. Large-scale prospective cohort studies are needed to explore the relationships between potential risk factors and respiratory disease outcomes and to observe disease prognoses through long-term follow-ups. We aimed to develop a common data model (CDM) for cohort studies on respiratory diseases, in order to harmonize and facilitate the exchange, pooling, sharing, and storing of data from multiple sources to serve the purpose of reusing or uniforming those follow-up data appeared in the cohorts. Methods: The process of developing this CDM of respiratory diseases would follow the steps as: ①Reviewing the international standards, including the Clinical Data Interchange Standards Consortium (CDISC), Clinical Data Acquisition Standards Harmonization (CDASH) and the Observational Medical Outcomes Partnership (OMOP) CDM; ②Summarizing four cohort studies of respiratory diseases recruited in this research and assessing the data availability; ③Developing a CDM related to respiratory diseases. Results: Data on recruited cohorts shared a few similar domains but with various schema. The cohorts also shared homogeneous data collection purposes for future follow-up studies, making the harmonization of current and future data feasible. The derived CDM would include two parts: ①thirteen common domains for all the four cohorts and derived variables from disparate questions with a common schema, ②additional domains designed upon disease-specific research needs, as well as additional variables that were disease-specific but not initially included in the common domains. Conclusion: Data harmonization appeared essential for sharing, comparing and pooled analyses, both retrospectively and prospectively. CDM was needed to convert heterogeneous data from multiple studies into one harmonized dataset. The use of a CDM in multicenter respiratory cohort studies would make the constant collection of uniformed data possible, so to guarantee the data exchange and sharing in the future.
Data Collection/standards* ; Databases, Factual/standards* ; Delivery of Health Care/organization & administration* ; Humans ; Information Dissemination ; Pulmonary Disease, Chronic Obstructive

This paper introduced the Revised Cochrane Risk of Bias Tool RoB2.0 for cluster-randomized control trials (CRCT) and compared RoB2.0 of CRCT with individually randomized, parallel group trials, and illustrated the application of RoB2.0 for CRCT in a published CRCT. Special signal questions were designed for CRCT according to its specialty that different from individually randomized, parallel group trials in RoB2.0 and also providing information on risk of bias about CRCT in systematic reviews for the synthesis of evidence.
Bias ; Humans ; Randomized Controlled Trials as Topic ; Risk ; Risk Assessment/methods*

This paper summaries the Risk Of Bias In Non-randomized Studies-of Interventions (ROBINS-I), a tool for evaluating risk of bias about Non-randomized Studies-of Interventions (NRSI), and introduces the application of ROBINS-I in a published NRSI. According to the characteristics of NRSI, evaluation field and signaling question were designed in ROBINS-I to provide essential information about risk of bias for NRSI included in systematic reviews. ROBINS-I is the tool in assessment of risk of bias in observational studies and quasi-randomised studies. Although the tool has been used in practice to some extent, but it still needs further improvement. Attention should be paid to its update and progress.
Animals ; Bias ; Controlled Clinical Trials as Topic ; Humans ; Reproducibility of Results ; Risk Assessment/methods* ; Selection Bias

This paper introduced the Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2), including the development and comparison with the original QUADAS, and illustrated the application of QUADAS-2 in a published paper related to the study on diagnostic accuracy which was included in systematic review and Meta-analysis. QUADAS-2 presented considerable improvement over the original tool. Confused items that included in QUADAS had disappeared and the quality assessment of the original study replaced by the rating of risk on bias and applicability. This was implemented through the description on the four main domains with minimal overlapping and answering the signal questions in each domain. The risk of bias and applicability with 'high','low' or 'unclear' was in line with the risk of bias assessment of intervention studies in Cochrane, so to replace the total score of quality assessment in QUADAS. Meanwhile, QUADAS-2 was also applicable to assess the diagnostic accuracy studies in which follow-up without prognosis was involved in golden standard. It was useful to assess the overall methodological quality of the study despite more time consuming than the original QUADAS. However, QUADAS-2 needs to be modified to apply in comparative studies on diagnostic accuracy and we hope the users would follow the updates and give their feedbacks on line.
Bias ; Diagnostic Tests, Routine/standards* ; Humans ; Quality Assurance, Health Care ; Research Report ; Risk

Objective: To analyze the spatial distribution and identify the high risk areas of pulmonary tuberculosis at the township level in Beijing during 2005-2015. Methods: Data on pulmonary tuberculosis cases was collected from the tuberculosis information management system. Global autocorrelation analysis, local indicators of spatial association and Kulldorff's Scan Statistics were applied to map the spatial distribution and detect the space-time clusters of the pulmonary tuberculosis cases during 2005-2015. Results: Spatial analysis on the incidence of pulmonary tuberculosis at the township level demonstrated that the spatial autocorrelation was positive during the study period. The values of Moran's I ranged from 0.224 3 to 0.291 8 with all the P values less than 0.05. Hotspots were primarily distributed in 8 towns/streets as follows: Junzhuang, Wangping, Yongding and Tanzhesi in Mentougou district, Yancun in Fangshan district, Wangzuo town in Fengtai district, Tianqiao street in Xicheng district and Tianzhu town in Shunyi district. Spatiotemporal clusters across the entire study period were identified by using Kulldorff's spatiotemporal scan statistic. The primary cluster was located in Chaoyang and Shunyi districts, including 17 towns/streets, as follows: Cuigezhuang, Maizidian, Dongfeng, Taiyanggong, Zuojiazhuang, Hepingjie, Xiaoguan, Xiangheyuan, Dongba, Jiangtai, Wangjing, Jinzhan, Jiuxianqiao, Laiguangying, Sunhe towns/streets in Chaoyang district, Houshayu and Tianzhu town in Shunyi district, during January to December 2005. Conclusion: Incidence rates of pulmonary tuberculosis displayed spatial and temporal clusterings at the township level in Beijing during 2005-2015, with high risk areas relatively concentrated in the central and southern parts of Beijing.
Beijing ; China ; Cluster Analysis ; Humans ; Incidence ; Spatial Analysis ; Spatio-Temporal Analysis ; Tuberculosis ; Tuberculosis, Pulmonary/ethnology*

Objective: To investigate the utilization of antibiotics in emergency departments (EDs) of class Ⅲ general hospitals in China. Methods: Data from a national monitoring network for rational use of drugs was used. The data included prescriptions of EDs from 114 class Ⅲ general hospitals in 30 provinces (autonomous regions, municipalities) of China. A total of 10 260 595 prescriptions from October 1, 2014 to December 31, 2016 were extracted. The Anatomical Therapeutic Chemical Classification/Defined Daily Dose (DDD) system was used for the classification of antibiotics and calculation of antibiotic use intensity. An auto-regression model was used to analyze the trend over time and seasonal variation of antibiotic use in EDs. Results: The rate of antibiotic prescriptions was 27.82% in EDs, among the antibiotics prescribed, 25.58% were for the combination therapy with 2 or more antibiotic agents, and injectable antibiotic prescriptions accounted for 60.59%. Besides, the number of DDDs per 100 patient visits was 81.84. Broad-spectrum agents were the most commonly used antibiotics, among which the second and third generation cephalosporins, quinolones and macrolides accounted for 23.83%, 21.68%, 19.17% and 7.89% of all prescribed antibiotics, respectively. The use of antibiotics, including prescription frequency and use intensity, in EDs had a slight but significant increase tendency (P<0.05), and the seasonal variation of antibiotic use in EDs was obvious, characterized by the highest frequency and intensity of antibiotic use in winter, the differences were significant (P<0.05). Conclusion: The antibiotic prescription rate in EDs of classⅢ general hospitals in China was controlled at a low level, but the proportions of broad-spectrum antibiotics and injectable antibiotics were high, and a significant increase trend in antibiotic use in EDs was found.
Anti-Bacterial Agents/therapeutic use* ; China ; Drug Prescriptions ; Drug Utilization ; Emergency Service, Hospital ; Hospitals ; Hospitals, General ; Humans

This paper introduces the tools related to Quality In Prognosis Studies (QUIPS) to assess the risk of bias in studies of prognostic factors and the relevant points of assessment and to illustrate the application of QUIPS in published prognostic research. The QUIPS tool identified 6 important areas to consider when evaluating validity and bias in studies of prognostic factors including participation, attrition, measurement on prognostic factors, outcomes, confounding factors, statistical analysis and reporting. It also provided a new method for evaluation on bias in the areas of prognostic research.
Bias ; Humans ; Prognosis ; Quality Improvement ; Research Design

This paper introduces the Risk of Bias in Systematic Review (ROBIS), including: 1) the development of ROBIS, 2) three phases of ROBIS tool judging the overall risk of bias that related to systematic reviews, and 3) illustration on the application of ROBIS in a published systematic review. ROBIS is the first rigorously developed tool which is specifically designed to assess the risk of bias in systematic reviews. ROBIS will help improve the process of risk assessment on bias which appeared in overviews and guidelines.
Humans ; Bias ; Risk Assessment/methods* ; Systematic Reviews as Topic