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- W4312061410 abstract "Individual participant data (IPD) from randomised controlled trials (RCTs) can be used in network meta-analysis (NMA) to underpin patient care and are the best analyses to support the development of guidelines about the use of healthcare interventions for a specific condition. However, barriers to IPD retrieval pose a major threat. The aim of this study was to present barriers we encountered during retrieval of IPD from RCTs in two published systematic reviews with IPD-NMA.We evaluated retrieval of IPD from RCTs for IPD-NMA in Alzheimer's dementia and type 1 diabetes. We requested IPD from authors, industry sponsors and data repositories, and recorded IPD retrieval, reasons for IPD unavailability, and retrieval challenges.In total, we identified 108 RCTs: 78 industry sponsored, 11 publicly sponsored and 19 with no funding information. After failing to obtain IPD from any trial authors, we requested it from industry sponsors. Seven of the 17 industry sponsors shared IPD for 12 950 participants (59%) through proprietary-specific data sharing platforms from 26 RCTs (33%). We found that lack of RCT identifiers (eg, National Clinical Trial number) and unclear data ownership were major challenges in IPD retrieval. Incomplete information in retrieved datasets was another important problem that led to exclusion of RCTs from the NMA. There were also practical challenges in obtaining IPD from or analysing it within platforms, and additional costs were incurred in accessing IPD this way.We found no clear evidence of retrieval bias (where IPD availability was linked to trial findings) in either IPD-NMA, but because retrieval bias could impact NMA findings, subsequent decision-making and guideline development, this should be considered when assessing risk of bias in IPD syntheses." @default.
- W4312061410 created "2023-01-04" @default.
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- W4312061410 date "2022-12-21" @default.
- W4312061410 modified "2023-10-10" @default.
- W4312061410 title "Retrieval barriers in individual participant data reviews with network meta-analysis" @default.
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- W4312061410 doi "https://doi.org/10.1136/bmjebm-2022-112024" @default.
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