ArticleBMJ open science2021
Combined meta-analysis of preclinical cell therapy studies shows overlapping effect modifiers for multiple diseases.
Article in BMJ open science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.
- What has preclinical systematic review ever done for us?BMJ open science · 2022Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionCell 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.
methodsWe 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.
resultsThe 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.
conclusionsPreclinical 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.
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Registered trials
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