The summary of finding (SoF) table for network meta-analysis (NMA) was developed by the GRADE working group to facilitate and consolidate understanding NMA findings and GRADE certainty of evidence. This paper introduces the development process, the structure of NMA-SoF and limitations. A NMA publication was presented as an example to comprehensively illustrate the application of the NMA-SoF table.
Randomized controlled trials are the gold standard for evaluating the effects of medical interventions, primarily providing estimates of the average effect of an intervention in the overall study population. However, there may be significant differences in the effect of the same intervention across sub-populations with different characteristics, that is, treatment heterogeneity. Traditional subgroup analysis and interaction analysis tend to have low power to examine treatment heterogeneity or identify the sources of heterogeneity. With the recent development of machine learning techniques, causal forest has been proposed as a novel method to evaluate treatment heterogeneity, which can help overcome the limitations of the traditional methods. However, the application of causal forest in the evaluation of treatment heterogeneity in medicine is still in the beginning stage. In order to promote proper use of causal forest, this paper introduces its purposes, principles and implementation, interprets the examples and R codes, and highlights some attentions needed for practice.
近十年，在藥品不良反應監測領域，基于醫療保健數據庫的安全信號檢測方法受到越來越多的關注，已成為彌補自發報告固有局限性的重要手段。目前數據挖掘方法主要基于比值失衡分析法（disproportionality analysis）、傳統藥物流行病學設計（如自身對照設計）、序列對稱分析（sequence symmetry analysis，SSA）、序貫統計檢驗（sequential statistical testing）、時序關聯規則（temporal association rules）、監督機器學習（supervised machine learning，SML）、樹狀掃描統計量方法（tree-based scan statistic）等。本文從應用場景和實用性角度對醫療保健數據庫中安全信號檢測方法及其性能進行介紹。
混合模型框架下的模型，如潛變量增長混合模型（latent growth mixture modeling，LGMM）或潛類別增長分析（latent class growth analysis，LCGA），因估算過程中涉及多個決策過程，導致潛變量軌跡分析結果的報告呈現多樣性。為解決這一問題，指南制訂小組按照系統化的制訂流程，通過 4 輪德爾菲法調查，遵循專家小組意見，提出了各領域報告潛變量軌跡分析結果時需采用統一的標準，最終確定了報告軌跡研究結果必要的關鍵條目，發布了潛變量軌跡研究報告規范（guidelines for reporting on latent trajectory studies，GRoLTS），并利用 GRoLTS 評價了 38 篇使用 LGMM 或 LCGA 研究創傷后應激軌跡的論文的報告情況。
ObjectiveThis study aims to conduct a bibliometric analysis of the dataset obtained from a systematic review of Model-Based Meta-Analysis (MBMA) studies to uncover research trends in MBMA. MethodsWe conducted a systematic search across databases including Embase, MEDLINE, Cochrane Library, Web of Science, CNKI, VIP, WanFang Data, and Sinomed. Relevant literature pertaining to MBMA was screened and included. Qualitative and quantitative analyses were performed to assess author contributions, temporal trends, national distribution, and disease prevalence. ResultsA total of 129 articles were included in the analysis, most published in being China (n=48), the United States (n=47), and the United Kingdom (n=7). The time span covered by these articles ranged from 2005 to 2023. A total of 531 researchers contributed to the included studies, with first authors from 15 different countries. The compilation encompassed 402 keywords, with the three most frequently used being “Meta-analysis” (n=28), “Model-based meta-analysis” (n=27), and “Pharmacokinetics” (n=14). The study covered 16 distinct disease categories, with the top three neoplasms (n=16), neurological disorders (n=14), and endocrine and metabolic diseases (n=13). ConclusionBibliometric analysis showed that the number of MBMA studies has increased significantly over the past three years, using a variety of key diseases as carriers. However, this new type of quantitative research has not yet attracted sufficient attention, and the research power is still concentrated in China and the United States; Moreover, a core group of authors has not yet been formed, it is necessary for scholars from various countries to strengthen multidisciplinary cooperation and communication to promote the production and translation of high-quality evidence.
This paper introduced the preferred reporting items for journal and conference abstracts of systematic reviews and meta-analyses of diagnostic test accuracy studies (PRISMA-DTA for abstracts), which was published in BMJ in March 2021. This paper presented the 12 items of checklist, explanations, and examples of complete reporting, to help domestic researchers to report complete and informative abstracts of systematic reviews and meta-analyses of diagnostic test accuracy studies.
ObjectiveTo systematically review the efficacy of treatments for β-coronaviruses.MethodsPubMed, EMbase, Web of Science, The Cochrane Library, SinoMed, CNKI and WanFang Data databases were electronically searched to collect randomized controlled trials (RCTs) and non-randomized controlled trials (non-RCTs) of treatments for β-coronaviruses from inception to June 17th, 2020. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Meta-analysis was then performed using Stata 14.0 software.ResultsA total of 109 studies invoving 23 210 patients were included. The results of the systematic review showed that compared with standard of care, corticosteroids could reduce mortality and increase cure rate for COVID-19. However, chloroquine could decrease cure rate. In severe acute respiratory syndrome (SARS) patients, corticosteroids could decrease the cure rate. In Middle East respiratory syndrome (MERS) patients, ribavirin/interferon/both drugs showed higher mortality.ConclusionsThe currently limited evidence shows that corticosteroids may be effective to COVID-19 patients while having limited effects on SARS patients. Hydroxychloroquine or chloroquine may have negative effects on COVID-19 patients. Ribavirin/interferon may be harmful to MERS patients. Due to limited quality and quantity of the included studies, more high quality studies are needed to verify the above conclusions.
The PRISMA aims to enhance the transparency and reporting quality of systematic reviews. PRISMA 2020 is an update version of PRISMA 2009, which was published in BMJ in March, 2021. This article compared the PRISMA 2020 and PRISMA 2009, interpreted PRISMA 2020 with representative examples, aiming to help Chinese scholars better understand and apply this reporting guideline, thus to improve the reporting quality of systematic reviews.