TY - JOUR
T1 - Combined meta-analysis of preclinical cell therapy studies shows overlapping effect modifiers for multiple diseases
AU - Zwetsloot, Peter Paul
AU - Antonic-Baker, Ana
AU - Gremmels, Hendrik
AU - Wever, Kimberley
AU - Sena, Chris
AU - Jansen Of Lorkeers, Sanne
AU - Chamuleau, Steven
AU - Sluijter, Joost
AU - Howells, David W.
N1 - Funding Information:
Funding This research was partially funded by an Australian NHMRC program grant (ID# 1013621); a grant from the Alexandre Suerman program for MD/ PhD students of the University Medical Center Utrecht, the Netherlands; and the research consortium HUSTCARE, Netherlands CardioVascular Research Initiative (CVON-HUSTCARE): The Dutch Heart Foundation, Dutch Federation of University Medical Centers, the Netherlands Organization for Health Research and Development and the Royal Netherlands Academy of Science. This work is part of the research program ‘More Knowledge, less Animals’, which is (partly) financed by the Netherlands Organisation for Scientific Research (NWO). This research is part of the project SMARTCARE-2 of the research program of the BioMedical Materials institute, co-funded by the Dutch Ministry of Economic Affairs and the Dutch Heart Foundation.
Publisher Copyright:
© 2021 Author(s) (or their employer(s). Re-use permitted under CC BY. Published by BMJ.
PY - 2021/4/19
Y1 - 2021/4/19
N2 - 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.
AB - 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.
KW - cell therapy
KW - preclinical meta-analysis
KW - ratio of means
UR - http://www.scopus.com/inward/record.url?scp=85104642424&partnerID=8YFLogxK
U2 - 10.1136/bmjos-2020-100061
DO - 10.1136/bmjos-2020-100061
M3 - Article
AN - SCOPUS:85104642424
SN - 2398-8703
VL - 5
JO - BMJ Open Science
JF - BMJ Open Science
IS - 1
M1 - e100061
ER -