Research Synthesis Methods最新文献_第2页

The hazards of using hazard ratios from proportional hazard models in indirect treatment comparisons. 在间接治疗比较中使用比例风险模型的风险比的危害。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-05-01 Epub Date: 2025-12-17 DOI: 10.1017/rsm.2025.10059

Ziren Jiang, Jialing Liu, Weili He, Joseph Cappelleri, Satrajit Roychoudhury, Yong Chen, Haitao Chu

{"title":"The hazards of using hazard ratios from proportional hazard models in indirect treatment comparisons.","authors":"Ziren Jiang, Jialing Liu, Weili He, Joseph Cappelleri, Satrajit Roychoudhury, Yong Chen, Haitao Chu","doi":"10.1017/rsm.2025.10059","DOIUrl":"10.1017/rsm.2025.10059","url":null,"abstract":"Indirect treatment comparison (ITC) is widely used to estimate the comparative effectiveness of treatments when head-to-head trials are unavailable. For the typical scenario of anchored ITC where one trial compares drug A to drug C (AC trial) and another compares drug B to drug C (BC trial), the comparative effectiveness of drugs A versus B is calculated by subtracting (or dividing) the relative treatment effect of A versus C in the AC trial by that of B versus C in the BC trial, assuming the covariate distributions in both trials are balanced. This operation is valid only if the chosen effect measure is transitive, that is, in a three-arm randomized trial of drugs A, B, and C, the direct treatment effect of A versus B equals the indirect treatment effect of A versus B through their comparisons to C. For survival outcomes, many ITCs use the hazard ratio (HR) as the effect measure. In this article, we demonstrate that HR is generally not transitive and should be used with caution. As more reliable alternatives, we recommend effect measures with better transitivity properties: the restricted mean survival time (RMST) difference, the landmark survival probability difference (or ratio) at a prespecified time point, and the average hazard with survival weights (AH-SW) difference.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":"17 3","pages":"483-497"},"PeriodicalIF":6.1,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13126216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147696937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transforming evidence synthesis: A systematic review of the evolution of automated meta-analysis in the age of AI. 转化证据合成：人工智能时代自动元分析演变的系统回顾。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-05-01 Epub Date: 2026-01-09 DOI: 10.1017/rsm.2025.10065

Lingbo Li, Anuradha Mathrani, Teo Susnjak

{"title":"Transforming evidence synthesis: A systematic review of the evolution of automated meta-analysis in the age of AI.","authors":"Lingbo Li, Anuradha Mathrani, Teo Susnjak","doi":"10.1017/rsm.2025.10065","DOIUrl":"10.1017/rsm.2025.10065","url":null,"abstract":"Exponential growth in scientific literature has heightened the demand for efficient evidence-based synthesis, driving the rise of the field of automated meta-analysis (AMA) powered by natural language processing and machine learning. This PRISMA systematic review introduces a structured framework for assessing the current state of AMA, based on screening 13,216 papers (2006-2024) and analyzing 61 studies across diverse domains. Findings reveal a predominant focus on automating data processing (52.5%), such as extraction and statistical modeling, while only 16.4% address advanced synthesis stages. Just one study (approximately 2%) explored preliminary full-process automation, highlighting a critical gap that limits AMA's capacity for comprehensive synthesis. Despite recent breakthroughs in large language models and advanced AI, their integration into statistical modeling and higher-order synthesis, such as heterogeneity assessment and bias evaluation, remains underdeveloped. This has constrained AMA's potential for fully autonomous meta-analysis (MA). From our dataset spanning medical (67.2%) and non-medical (32.8%) applications, we found that AMA has exhibited distinct implementation patterns and varying degrees of effectiveness in actually improving efficiency, scalability, and reproducibility. While automation has enhanced specific meta-analytic tasks, achieving seamless, end-to-end automation remains an open challenge. As AI systems advance in reasoning and contextual understanding, addressing these gaps is now imperative. Future efforts must focus on bridging automation across all MA stages, refining interpretability, and ensuring methodological robustness to fully realize AMA's potential for scalable, domain-agnostic synthesis.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":"17 3","pages":"403-450"},"PeriodicalIF":6.1,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13126215/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147696943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Aggregating and analysing clinical trials data from multiple public registers using R package ctrdata. 使用R包ctrdata聚合和分析来自多个公共注册的临床试验数据。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-05-01 Epub Date: 2025-12-04 DOI: 10.1017/rsm.2025.10061

Ralf Herold

{"title":"Aggregating and analysing clinical trials data from multiple public registers using R package ctrdata.","authors":"Ralf Herold","doi":"10.1017/rsm.2025.10061","DOIUrl":"10.1017/rsm.2025.10061","url":null,"abstract":"The ctrdata package has been created to boost the use of data available in public registers of clinical trials. It enables user-friendly, reproducible workflows to identify trials of interest, download protocol- and results-related data, and conduct sophisticated analyses, across multiple registers and trials. ctrdata works in the widely used R environment, and its databases can be used with other tools. The package is open source with a permissive licence, to facilitate collaboration.This report provides an overview of ctrdata, including its implementation, cases of interest to researchers in public health, medicines, and regulatory science, as well as potential limitations and further developments. At this time, ctrdata works with the European Union (EU) Clinical Trials Information System (CTIS), the EU Clinical Trials Register (EUCTR), the US Clinicaltrials.Gov (CTGOV), and the ISRCTN-the UK's Clinical Study Registry. The registers are complementary in scope and scientific value, yet differences in data models, variable definitions, search parametrisations, and retrieval options hamper efficient scientific workflows, calling for a scientific-technical, programmatic solution and driving the development of ctrdata.By employing ctrdata to comprehensively use and easily leverage trial register data, researchers can effectively address a variety of questions, gain useful insights into evolving policies and practices of drug development, and inform further clinical research. Patients and their organisations, developers, policymakers, and other interested parties can build on ctrdata to create solutions for their use cases.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":"17 3","pages":"624-656"},"PeriodicalIF":6.1,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13126229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147697135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large language model-based paper classification framework with key-insight extraction and confidence-weighted voting. 基于关键洞察提取和置信度加权投票的大型语言模型论文分类框架。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-04-22 DOI: 10.1017/rsm.2026.10094

Zihan Song, Shan Huang, Ngeemasara Thapa, Xin Zhang, Byung-Kwon Park, Jie Lu, Wenyang Li, Wenbin Liu, Bei Zhan, Jianfei Li

{"title":"Large language model-based paper classification framework with key-insight extraction and confidence-weighted voting.","authors":"Zihan Song, Shan Huang, Ngeemasara Thapa, Xin Zhang, Byung-Kwon Park, Jie Lu, Wenyang Li, Wenbin Liu, Bei Zhan, Jianfei Li","doi":"10.1017/rsm.2026.10094","DOIUrl":"https://doi.org/10.1017/rsm.2026.10094","url":null,"abstract":"Systematic reviews (SRs) are critical for evidence-based research but are time-consuming and labor-intensive. The rapid expansion of academic publications further challenges the performance and applicability of existing screening and classification methods. While large language models (LLMs) present new opportunities for automation, limited research has examined whether they can achieve classification performance comparable to human reviewers in large-scale, multi-class settings. With the goal of improving classification performance, we proposed an LLM-based framework that leverages full-text key-insight extraction to enhance literature classification. We constructed a manually curated dataset of 900 articles from 17 published SRs to quantitatively evaluate the classification capabilities of LLMs. The results provided empirical evidence of LLMs' potential in supporting large-scale SRs and introduced a practical pathway for improving efficiency and reliability in evidence synthesis. Empirical results showed that key-insight-based classification (KBC) significantly outperforms abstract-based classification (ABC). We implemented a confidence-weighted voting (CWV) mechanism using multiple LLMs to improve robustness. The CWV method achieved the highest macro F1-score of 0.796, substantially exceeding KBC (0.732), ABC (0.676), and unsupervised K-means clustering (0.446). By employing zero-shot LLMs, our approach demonstrated the potential for enhanced adaptability across diverse domains and classification tasks without requiring fine-tuning, demonstrating that a carefully designed pipeline can enable LLMs to achieve classification performance comparable to human reviewers.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-19"},"PeriodicalIF":6.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147758474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data management in literature reviews: The C5-DM Framework. 文献综述中的数据管理：C5-DM框架。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-04-17 DOI: 10.1017/rsm.2026.10091

Gerit Wagner, Julian Prester, Roman Lukyanenko, Guy Paré

{"title":"Data management in literature reviews: The C5-DM Framework.","authors":"Gerit Wagner, Julian Prester, Roman Lukyanenko, Guy Paré","doi":"10.1017/rsm.2026.10091","DOIUrl":"https://doi.org/10.1017/rsm.2026.10091","url":null,"abstract":"Effective data management is essential for tasks involving decisions based on data, including knowledge synthesis and literature reviews. Despite this, how to carry out data management in literature reviews effectively remains unclear. With the increasing volume of research papers and the expansion of computational techniques for processing data (e.g., machine learning or large language models), it becomes imperative to consider data management as a crucial element for the advancement of literature review practices and tools. Presently, there are shortcomings related to (1) handling the growth of research to be synthesized, (2) addressing data quality issues when applying computational techniques or facilitating the verification of content produced by generative artificial intelligence, (3) enabling efficient reuse of datasets and innovative recombination of tools, and (4) facilitating transparent collaboration across heterogeneous review teams. To address these shortcomings, we develop the C5-DM Framework with conceptual principles to address data management challenges across five areas relevant to literature reviews: data conceptualization, collection, curation, control, and consumption. Methodological guidance for researchers with respect to these five areas is necessary to reduce errors, save time on repetitive tasks, and allow review teams to develop insightful syntheses.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-23"},"PeriodicalIF":6.1,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147697157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Minimum distance estimation of mean and standard deviation from reported quantiles. 报告分位数的均值和标准差的最小距离估计。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-04-15 DOI: 10.1017/rsm.2026.10090

Xiaoyu Tang, Tiejun Tong, Xin Zhang, Haitao Chu

{"title":"Minimum distance estimation of mean and standard deviation from reported quantiles.","authors":"Xiaoyu Tang, Tiejun Tong, Xin Zhang, Haitao Chu","doi":"10.1017/rsm.2026.10090","DOIUrl":"https://doi.org/10.1017/rsm.2026.10090","url":null,"abstract":"Meta-analysis is a cornerstone of evidence synthesis, yet challenges arise when studies report heterogeneous summary statistics, such as means and standard deviations (SDs) versus medians, interquartile ranges (IQRs), or other percentiles. Excluding studies that report only medians and IQRs can introduce bias and reduce precision, particularly when outcomes are skewed, which is common in clinical research. Although several methods exist to estimate means and SDs from alternative summaries, many rely on strong normality assumptions, exhibit computational burden, or fail to adequately account for the precision of reported quantiles (e.g., extreme values versus medians). To address these limitations, we propose two flexible weighted estimators for estimating the mean and SD from reported quantiles. The methods leverage inverse-variance and inverse-variance-covariance weighting, respectively, to enhance both accuracy and precision. Additionally, our methods are flexible enough to accommodate any set of reported quantiles and various underlying distributions, and they can be readily implemented using standard statistical software. Simulation studies demonstrate that the weighted estimators provide nearly unbiased estimates of the mean and SD with high precision in most cases, especially for large sample sizes. In a real-world meta-analysis, the estimates obtained using the proposed estimators closely aligned with those derived from true sample statistics. These approaches are particularly valuable for skewed outcomes and offer a practical and user-friendly solution for researchers seeking to integrate heterogeneous data while improving accuracy and precision.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-18"},"PeriodicalIF":6.1,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147687258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prompt engineering of large language models for paper screening in medical meta-analyses and systematic reviews: A prospective comparative study. 在医学荟萃分析和系统评价中筛选论文的大型语言模型的快速工程：一项前瞻性比较研究。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-04-14 DOI: 10.1017/rsm.2026.10093

Till J Adam, Salma A S Abosabie, Max Dittmer, Elise Wolf, Sara A Abosabie, Clara Behnke, Felix Baier, Annabelle Weickmann, Ludwig Köser, Christoph U Correll, Niklas Rutsch

{"title":"Prompt engineering of large language models for paper screening in medical meta-analyses and systematic reviews: A prospective comparative study.","authors":"Till J Adam, Salma A S Abosabie, Max Dittmer, Elise Wolf, Sara A Abosabie, Clara Behnke, Felix Baier, Annabelle Weickmann, Ludwig Köser, Christoph U Correll, Niklas Rutsch","doi":"10.1017/rsm.2026.10093","DOIUrl":"https://doi.org/10.1017/rsm.2026.10093","url":null,"abstract":"Interest in large language models (LLMs) as a tool for meta-analyses and systematic reviews (MA/SRs). We prospectively developed 515 unique prompts by predefined screening-related categories and tested with open-access LLMs (Llama, Mistral) against four gold-standard MA/SRs from different medical fields published after the LLMs' training cut-offs, using a Python-based pipeline. Heterogeneity between prompts was quantified, and hypothetical workload/cost reduction with top-performing prompts calculated. Across 12,360 pipeline runs, LLMs versus MA/SRs reached average recall/sensitivity = 83.6 ± 17.0%, precision = 18.5 ± 15.6%, specificity = 36.6 ± 23.7% F1-score = 27.6 ± 17.2%, and accuracy = 61.1 ± 11.0%. F1-scores were significantly higher when prompts focused on methods (0.78 ± 0.40%), explicitly mentioned MA/SR screening (0.81 ± 0.37%), included the comparison MA/SR's title (5.64 ± 0.37%) or selection criteria (8.05 ± 0.68%), and with more LLM parameters (70b = 4.48 ± 0.31%, 123b = 7.77 ± 0.31%), but lower when screening abstracts instead of titles (-3.67 ± 0.28%). In LLM-base preselection, top-performing F1-score prompts (recall/sensitivity = 72.2%, specificity = 66.1%, precision = 28.6%) would reduce screening demands by 34.5%-37.5%, saving 8.4-8.8 weeks of work and 17,592-18,552. Recall/sensitivity increased with less MA/SR information contrasting F1-score results, which highlights a recall/sensitivity-precision/specificity trade-off. F1-score increased with detailed MA/SR information, while recall/sensitivity increased with shorter, zeroshot prompts. We provide the first prospectively assessed prompt engineering framework for early-stage LLM-based paper screening across medical fields. The publicly available Python pipeline and full prompt list used here support further development of LLM-based evidence synthesis.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-18"},"PeriodicalIF":6.1,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147669309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-dissemination in qualitative health research-A retrospective cohort study of conference abstracts. 质性健康研究中的非传播——会议摘要的回顾性队列研究。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-04-14 DOI: 10.1017/rsm.2026.10085

Marwin Weber, Markus Toews, Waldemar Siemens, Andrew Booth, Simon Lewin, Heather Menzies Munthe-Kaas, Claire Glenton, Jane Noyes, Joerg J Meerpohl, Ingrid Toews

{"title":"Non-dissemination in qualitative health research-A retrospective cohort study of conference abstracts.","authors":"Marwin Weber, Markus Toews, Waldemar Siemens, Andrew Booth, Simon Lewin, Heather Menzies Munthe-Kaas, Claire Glenton, Jane Noyes, Joerg J Meerpohl, Ingrid Toews","doi":"10.1017/rsm.2026.10085","DOIUrl":"https://doi.org/10.1017/rsm.2026.10085","url":null,"abstract":"Dissemination bias can occur when qualitative research is published selectively, potentially reducing the confidence in qualitative evidence. This retrospective cohort study aims to quantify the extent of non-dissemination of qualitative health research by following 1,123 conference abstracts. The proportion of non-dissemination, the time to publication, as well as associations between author or study characteristics and full publication were examined. For 22.8% of these studies, no full publication could be identified within at least 6 and up to 8 years after their presentation. For those that were published, median time to publication was 11 months (95% CI 10 to 12). Studies from authors affiliated with institutions in Australia were more likely to be published than those from North America (OR 4.47; 95% CI 1.58 to 18.74). Oral presentations were more likely to be published than poster presentations (OR 3.40; 95% CI 1.57 to 8.20). Studies that used two qualitative data collection methods were more likely to be published than studies that used one qualitative method only (OR 1.53; 95% CI 1.01 to 2.38). Conference abstracts that reported no funding were less likely to be published than those which reported funding (OR 0.71; 95% CI 0.51 to 0.99). Publicly funded research was more likely to be published than privately funded research (OR 2.24; 95% CI 1.16 to 4.28). Given the considerable proportion of unpublished health-related qualitative studies, there is a reason to believe that dissemination bias may impact negatively on qualitative evidence synthesis. This can, in turn, impair decision-making that uses qualitative evidence.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-12"},"PeriodicalIF":6.1,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147669304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Literature-based meta-analysis of adverse events accounting for heterogeneous follow-up duration in oncology clinical trials. 肿瘤临床试验中不同随访时间不良事件的文献荟萃分析。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-04-08 DOI: 10.1017/rsm.2026.10083

Sumika Kawaguchi, Satoshi Hattori

{"title":"Literature-based meta-analysis of adverse events accounting for heterogeneous follow-up duration in oncology clinical trials.","authors":"Sumika Kawaguchi, Satoshi Hattori","doi":"10.1017/rsm.2026.10083","DOIUrl":"https://doi.org/10.1017/rsm.2026.10083","url":null,"abstract":"It is difficult to understand the safety profile of drugs based on a single clinical trial since clinical trials are often designed to prove efficacies, and sample size is not powered for safety assessment. Thus, meta-analysis would be a valuable tool to infer the safety profiles utilizing multiple studies. Individual clinical trials usually report the incidence proportions of adverse events (AEs) observed in the study. The follow-up duration may be study-specific, and furthermore different between the treatment groups within a single study. It often occurs in oncology clinical trials and if this is the case, it is hard to interpret the aggregated relative risk of AEs and compare the risk of AEs between the treatment groups with the standard meta-analysis techniques. The progression-free survival or the overall survival is often used as the primary endpoint in oncology clinical trials and the Kaplan-Meier estimates of the survival functions for the primary endpoint are often demonstrated graphically, which give us information of the follow-up duration of the AEs. We propose novel meta-analysis methods for AEs that address differences in follow-up durations by efficiently utilizing the Kaplan-Meier estimates of the primary endpoint. We adapt our approach using both simulated data and real data from a meta-analysis of bevacizumab. Simulation studies demonstrate that the proposed methods perform well when follow-up time differs between trials and groups.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-28"},"PeriodicalIF":6.1,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147632065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel visualization approach for network meta-analysis: The plate plot and the nmaplateplot R package. 一种新颖的网络元分析可视化方法：板图和nmaplateplot R包。

IF 6.1 2区生物学

Research Synthesis Methods Pub Date : 2026-04-07 DOI: 10.1017/rsm.2026.10088

Yanan Ren, Zhenxun Wang, Lifeng Lin, Shanshan Zhao, Haitao Chu

{"title":"A novel visualization approach for network meta-analysis: The plate plot and the nmaplateplot R package.","authors":"Yanan Ren, Zhenxun Wang, Lifeng Lin, Shanshan Zhao, Haitao Chu","doi":"10.1017/rsm.2026.10088","DOIUrl":"https://doi.org/10.1017/rsm.2026.10088","url":null,"abstract":"Network meta-analysis (NMA) provides a powerful framework for synthesizing evidence across multiple interventions, accommodating both direct and indirect comparisons. However, effectively visualizing the complex, multidimensional results, such as effect magnitudes, uncertainty, p-values, and treatment rankings, remains a significant challenge. Outputs such as relative treatment effects, uncertainty, statistical significance, and treatment rankings are often reported separately, making it difficult for researchers and stakeholders to synthesize findings efficiently. We introduce plate plot, an innovative approach for visualizing key outcomes from NMA in a single, compact format. It enables simultaneous display of point estimates, confidence or credible intervals, significance levels, and surface under the cumulative ranking curve values, thereby facilitating clearer interpretation and communication of NMA findings. Using an example dataset, we demonstrate how the plate plot displays multiple relevant metrics to compare the efficacy and acceptability of various antidepressant interventions in a single, intuitive plot. The plate plot, generated effortlessly via the open-source nmaplateplot R package, enables users to generate customizable, publication-ready graphics with minimal programming. This tool enhances the ability to holistically evaluate and interpret complex comparative effectiveness data, supporting better-informed decision-making in research and clinical practice.","PeriodicalId":226,"journal":{"name":"Research Synthesis Methods","volume":" ","pages":"1-9"},"PeriodicalIF":6.1,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147626481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0