Introduction Cell therapy has been studied in many different research domains. Cellular replacement of damaged solid tissues is at an early stage of development, with much still to be understood. Systematic reviews and meta-analyses are widely used to aggregate data and find important patterns of results within research domains. We set out to find common biological denominators affecting efficacy in preclinical cell therapy studies for renal, neurological and cardiac disease. Methods We used datasets of five previously published meta-analyses investigating cell therapy in preclinical models of chronic kidney disease, spinal cord injury, stroke and ischaemic heart disease. We transformed primary outcomes to ratios of means to permit direct comparison across disease areas. Prespecified variables of interest were species, immunosuppression, cell type, cell origin, dose, delivery and timing of the cell therapy. Results The five datasets from 506 publications yielded data from 13 638 animals. Animal size affects therapeutic efficacy in an inverse manner. Cell type influenced efficacy in multiple datasets differently, with no clear trend for specific cell types being superior. Immunosuppression showed a negative effect in spinal cord injury and a positive effect in cardiac ischaemic models. There was a dose–dependent relationship across the different models. Pretreatment seems to be superior compared with administration after the onset of disease. Conclusions Preclinical cell therapy studies are affected by multiple variables, including species, immunosuppression, dose and treatment timing. These data are important when designing preclinical studies before commencing clinical trials. Data are available in a public, open access repository. All online supplemental tables and figure can be viewed and accessed on the open repository Figshare, and . All data that were used from the existing datasets is available on the open repository Figshare, . The code for our analysis (performed in R and Stata) is available on Figshare,

中文翻译：

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临床前细胞治疗研究的综合荟萃分析显示多种疾病的重叠效应调节剂

简介 细胞疗法已在许多不同的研究领域进行了研究。受损实体组织的细胞替代尚处于发展的早期阶段，仍有许多问题需要了解。系统评价和荟萃分析被广泛用于汇总数据并在研究领域内发现重要的结果模式。我们着手寻找影响肾脏、神经和心脏病临床前细胞治疗研究疗效的共同生物学分母。方法 我们使用了五项先前发表的荟萃分析的数据集，研究慢性肾病、脊髓损伤、中风和缺血性心脏病的临床前模型中的细胞疗法。我们将主要结果转化为均值比率，以允许跨疾病领域进行直接比较。预先指定的感兴趣变量是物种、免疫抑制、细胞类型、细胞疗法的细胞来源、剂量、递送和时间。结果 来自 506 份出版物的五个数据集产生了来自 13 638 只动物的数据。动物大小以相反的方式影响治疗效果。细胞类型对多个数据集的功效有不同的影响，没有明确的趋势表明特定细胞类型更胜一筹。免疫抑制对脊髓损伤有负面影响，对心肌缺血模型有正面影响。不同模型之间存在剂量依赖性关系。与疾病发作后的给药相比，预处理似乎更优越。结论 临床前细胞治疗研究受到多种变量的影响，包括物种、免疫抑制、剂量和治疗时机。在开始临床试验之前设计临床前研究时，这些数据很重要。数据可在公共、开放访问的存储库中获得。所有在线补充表格和图表都可以在开放存储库 Figshare 上查看和访问，和. 现有数据集中使用的所有数据都可在开放存储库 Figshare 中获得，. 我们分析的代码（在 R 和 Stata 中执行）可在 Figshare 上找到，