Dataset - Comparative Effectiveness of Surgical and Combined Interventions for Mandibular Angle Fractures: A Frequentist Network Meta-Analysis

This dataset was curated to support CINeMA assessments and complementary network meta-analysis for two subnetworks (“M” and “S”). Data were provided in two CSV files (cinema_M.csv, cinema_S.csv) at the study–arm level, including study and arm identifiers, treatment codes, numbers of responders and total participants, a risk-of-bias code (1 = low, 2 = some concerns, 3 = high), and an indicator of indirectness when available. For the M subnetwork, evidence was assembled from 7 studies and 44 arms across 5 treatments, comprising 647 participants and 639 responders. Arm-level risk of bias was distributed as 13.6% low, 72.7% some concerns, and 13.6% high. The most frequently observed direct comparison was M1S versus M3D, followed by M1S versus M2 and M1L versus M1S. For the S subnetwork, 13 studies and 63 arms across 7 treatments were included, totaling 2,107 participants and 1,986 responders. The risk-of-bias profile indicated 71.4% low and 28.6% some concerns, with no high-risk arms. The most common direct comparison involved S1S versus S2, with additional emphasis on S1L versus S1S and S1L versus S3D. Beyond risk-of-bias profiling, the network geometry was characterized to describe the distribution of evidence across treatments and comparisons, revealing centrally connected interventions with comparatively larger information contributions and peripheral nodes with sparser evidence. Random-effects network meta-analysis models were fitted to estimate pooled relative effects, and between-study heterogeneity was quantified to reflect variability beyond sampling error. Consistency was examined using global and local approaches (including design-by-treatment evaluations and node-splitting where appropriate) to assess agreement between direct and indirect evidence. Small-study effects were explored with comparison-adjusted and network funnel plots. Treatment ranking probabilities were estimated and summarized using SUCRA to communicate the relative standing of interventions under model assumptions. Sensitivity analyses were conducted to assess robustness, including the exclusion of high risk-of-bias studies, alternative assumptions for heterogeneity, and restriction to adequately informed contrasts. Overall, the evidence base in both subnetworks was predominantly characterized by low to moderate risk of bias, with the principal methodological concern concentrated in the M subnetwork for the M1S versus M3D contrast due to the presence of high and moderate risk contributions. The S subnetwork displayed a more favorable profile without high-risk arms. The dataset enabled reproducible derivation of network structures, risk-of-bias summaries by treatment and comparison, model-based effect estimates, consistency diagnostics, ranking summaries, and robustness checks, supported by accompanying figures that documented network structure and risk-of-bias distributions.本数据集旨在为两个子网络("M"与"S")的CINeMA评估与配套网络Meta分析(network meta-analysis)提供数据支持。数据集以研究-臂水平(study-arm level)存储于两个CSV文件(cinema_M.csv、cinema_S.csv)中，包含研究与臂标识符、干预措施代码、应答者人数与总参与者人数、偏倚风险代码(1=低风险，2=存在一定担忧，3=高风险)，以及可获取的间接性指标。 对于M子网络，其证据来自5种干预措施下的7项研究、44个研究臂，共纳入647名参与者与639名应答者。研究臂水平的偏倚风险分布为：低风险占13.6%，存在一定担忧占72.7%，高风险占13.6%。最常见的直接比较为M1S vs M3D，其次为M1S vs M2与M1L vs M1S。 对于S子网络，其纳入7种干预措施下的13项研究、63个研究臂，总计2107名参与者与1986名应答者。其偏倚风险特征为：低风险占71.4%，存在一定担忧占28.6%，无高风险研究臂。最常见的直接比较为S1S vs S2，此外重点关注的比较包括S1L vs S1S与S1L vs S3D。 除偏倚风险特征分析外，本数据集还对网络拓扑结构(network geometry)进行了表征，以描述证据在不同干预措施与比较中的分布情况，结果显示中心连接的干预措施具有相对更大的信息贡献，而外围节点的证据则较为稀疏。本数据集支持拟合随机效应网络Meta分析模型以估算合并相对效应，并量化研究间异质性，以反映抽样误差之外的变异程度。通过全局与局部方法(包括设计-干预措施评估、适当时机的节点拆分法)检验一致性，以评估直接证据与间接证据之间的一致性。采用比较校正漏斗图与网络漏斗图探索小研究效应。采用SUCRA(Surface Under the Cumulative Ranking Area)估算并总结干预措施的排序概率，以呈现模型假设下各干预措施的相对排名。开展敏感性分析以评估结果稳健性，具体包括排除高偏倚风险研究、采用异质性替代假设、限定为信息充分的比较。 总体而言，两个子网络的证据基础均以低至中等偏倚风险为主要特征，其中M子网络的M1S vs M3D比较存在高与中等风险贡献，为主要的方法学担忧点。S子网络的偏倚风险特征更为良好，无高风险研究臂。本数据集可实现网络结构、按干预措施与比较分组的偏倚风险汇总、基于模型的效应估计、一致性诊断、排序汇总与稳健性检验的可复现推导，并配有展示网络结构与偏倚风险分布的辅助图表。