Mouse models of diabetes-related ulcers: a systematic review and network meta-analysis.
Animal models
Diabetes
Diabetic foot ulcers
Network meta-analysis
Wound healing
Journal
EBioMedicine
ISSN: 2352-3964
Titre abrégé: EBioMedicine
Pays: Netherlands
ID NLM: 101647039
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
received:
24
04
2023
revised:
09
10
2023
accepted:
13
10
2023
medline:
22
1
2024
pubmed:
22
1
2024
entrez:
22
1
2024
Statut:
ppublish
Résumé
Diabetic foot ulcers (DFUs) are a common complication of diabetes, associated with important morbidity. Appropriate animal models of DFUs may improve drug development, and subsequently the success rate of clinical trials. However, while many models have been proposed, they are extremely heterogeneous, and no standard has emerged. We thus propose a systematic review with a network meta-analysis (NMA) to gather direct and indirect evidence, and compare the different mouse models of diabetes-related ulcers. The systematic search was performed in Pubmed and Embase. The main outcomes were wound size measurement at days 3, 7, 11 and 15 (±1 day). The risk of bias and methodological quality of all included studies was assessed by using the Systematic Review Center for Laboratory animal Experimentation (SYRCLE) risk of bias tool. Meta-regressions were done on prespecified variables, including mouse strain, type of ulcer, sex, age, and use of a splint. We included 295 studies. Among all models, only db/db, ob/ob, streptozotocin (STZ), and STZ + high fat diet mice showed a significantly delayed wound healing, compared with controls, at each time point. Age, sex and ulcer type had influence on wound healing, although not at all time points. In conclusion, the db/db model is associated with the largest delay in wound healing The STZ model also exhibits significantly decreased wound healing. STZ + high fat diet and ob/ob mice may also be relevant models of diabetes-related ulcers, although the results rely on a more limited number of studies. This work was funded by the Agence Nationale de la Recherche (grant ANR-18-CE17-0017).
Sections du résumé
BACKGROUND
BACKGROUND
Diabetic foot ulcers (DFUs) are a common complication of diabetes, associated with important morbidity. Appropriate animal models of DFUs may improve drug development, and subsequently the success rate of clinical trials. However, while many models have been proposed, they are extremely heterogeneous, and no standard has emerged. We thus propose a systematic review with a network meta-analysis (NMA) to gather direct and indirect evidence, and compare the different mouse models of diabetes-related ulcers.
METHODS
METHODS
The systematic search was performed in Pubmed and Embase. The main outcomes were wound size measurement at days 3, 7, 11 and 15 (±1 day). The risk of bias and methodological quality of all included studies was assessed by using the Systematic Review Center for Laboratory animal Experimentation (SYRCLE) risk of bias tool. Meta-regressions were done on prespecified variables, including mouse strain, type of ulcer, sex, age, and use of a splint.
FINDINGS
RESULTS
We included 295 studies. Among all models, only db/db, ob/ob, streptozotocin (STZ), and STZ + high fat diet mice showed a significantly delayed wound healing, compared with controls, at each time point. Age, sex and ulcer type had influence on wound healing, although not at all time points.
INTERPRETATION
CONCLUSIONS
In conclusion, the db/db model is associated with the largest delay in wound healing The STZ model also exhibits significantly decreased wound healing. STZ + high fat diet and ob/ob mice may also be relevant models of diabetes-related ulcers, although the results rely on a more limited number of studies.
FUNDING
BACKGROUND
This work was funded by the Agence Nationale de la Recherche (grant ANR-18-CE17-0017).
Identifiants
pubmed: 38251464
pii: S2352-3964(23)00422-X
doi: 10.1016/j.ebiom.2023.104856
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
104856Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests The authors declare no conflict of interest.