This Comment presents a high-level protocol for data harmonization within large cohorts, in which it postulates four main steps including (1) expert review, (2) pre-statistical harmonization, (3) statistical harmonization, and (4) validation.
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Acknowledgements
Funded by the European Union. Complementary funding was received by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (10041392 and 10038599). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Health and Digital Executive Agency (HADEA) or UKRI. The European Union, HADEA or UKRI cannot be held responsible for them. This work received support from the Chinese Ministry for Science and Technology (MOST), the Horizon 2020-funded European Research Council advanced grant ‘STRATIFY’ (695313); the German Research Foundation (COPE; 675346; NE 1383/15-1 and BA 2088/7-1 (CoviDrug)), the National Natural Science Foundation of China grant 82150710554, the Hector II foundation and the German Center for Mental Health (DZPG) (01EE2301A, 01EE2304A, 01EE2301D).
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T.B. served in an advisory or consultancy role for eye level, Infectopharm, Medice, Neurim Pharmaceuticals, Oberberg GmbH and Takeda. He received conference support or speaker’s fee by Janssen-Cilag, Medice and Takeda. He received royalties from Hogrefe, Kohlhammer, CIP Medien and Oxford University Press; the present work is unrelated to these relationships. E.S. received speaker fees from Lundbeckfonden and bfd buchholz-fachinformationsdienst GmbH and editorial fees from Lundbeckfonden. All other authors report no potential conflicts of interest.
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Neidhart, M., Kjelkenes, R., Jansone, K. et al. A protocol for data harmonization in large cohorts. Nat. Mental Health 2, 1134–1137 (2024). https://doi.org/10.1038/s44220-024-00315-0
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DOI: https://doi.org/10.1038/s44220-024-00315-0