How to plan and manage an individual participant data meta-analysis: an illustrative toolkit
Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognost...
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| Main Authors: | , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2023
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| In: |
Research synthesis methods
Year: 2023, Pages: 1-9 |
| ISSN: | 1759-2887 |
| DOI: | 10.1002/jrsm.1670 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1002/jrsm.1670 Verlag, kostenfrei, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/jrsm.1670 
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| Author Notes: | Lauren Maxwell, Priya Shreedhar, Mabel Carabali, Brooke Levis |
| Summary: | Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognostic model development and evaluation. However, IPD-MAs are resource-intensive and require careful budgeting of time from data contributing groups, a dedicated management team, diversity of expertise, clearly documented data sharing and authorship agreements, and consistent and clear communication. We present a toolkit to facilitate the implementation and management of IPD-MAs, from study recruitment to retrospective harmonization. The toolkit was developed and refined over our work on multiple multinational IPD-MA projects over the last 13 years. The toolkit's budget and email templates, agreements, project management spreadsheets, and standard operating procedures are meant to facilitate routine IPD-MA tasks to expedite implementing and managing future IPD-MA projects. |
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| Item Description: | Online veröffentlicht: 12. September 2023 Gesehen am 28.11.2023 |
| Physical Description: | Online Resource |
| ISSN: | 1759-2887 |
| DOI: | 10.1002/jrsm.1670 |