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Clinical trial registries as Scientometric data: A novel solution for linking and deduplicating clinical trials from multiple registries

C. Thiele, G. Hirschfeld, R. von Brachel, Scientometrics 126 (2021).

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Artikel | Veröffentlicht | Englisch
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Abstract - Registries of clinical trials are a potential source for scientometric analysis of medical research and serve important functions for the research community and the public at large. Clinical trials that recruit patients in Germany are usually registered in the German Clinical Trials Register (DRKS) or in international registries such as ClinicalTrials.gov. Furthermore, the International Clinical Trials Registry Platform (ICTRP) aggregates trials from multiple primary registries. We queried the DRKS, ClinicalTrials.gov, and the ICTRP for trials with a recruiting location in Germany. Trials that were registered in multiple registries were linked using the primary and secondary identifiers and a Random Forest model based on various similarity metrics. We identified 35,912 trials that were conducted in Germany. The majority of the trials was registered in multiple databases. 32,106 trials were linked using primary IDs, 26 were linked using a Random Forest model, and 10,537 internal duplicates on ICTRP were identified using the Random Forest model after finding pairs with matching primary or secondary IDs. In cross-validation, the Random Forest increased the F1-score from 96.4% to 97.1% compared to a linkage based solely on secondary IDs on a manually labelled data set. 28% of all trials were registered in the German DRKS. 54% of the trials on ClinicalTrials.gov, 43% of the trials on the DRKS and 56% of the trials on the ICTRP were pre-registered. The ratio of pre-registered studies and the ratio of studies that are registered in the DRKS increased over time.
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Zeitschriftentitel
Scientometrics
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126
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FH-PUB-ID

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Thiele, Christian ; Hirschfeld, Gerrit ; von Brachel, Ruth: Clinical trial registries as Scientometric data: A novel solution for linking and deduplicating clinical trials from multiple registries. In: Scientometrics Bd. 126, Springer Science and Business Media LLC (2021)
Thiele C, Hirschfeld G, von Brachel R. Clinical trial registries as Scientometric data: A novel solution for linking and deduplicating clinical trials from multiple registries. Scientometrics. 2021;126. doi:10.1007/s11192-021-04111-w
Thiele, C., Hirschfeld, G., & von Brachel, R. (2021). Clinical trial registries as Scientometric data: A novel solution for linking and deduplicating clinical trials from multiple registries. Scientometrics, 126. https://doi.org/10.1007/s11192-021-04111-w
@article{Thiele_Hirschfeld_von Brachel_2021, title={Clinical trial registries as Scientometric data: A novel solution for linking and deduplicating clinical trials from multiple registries}, volume={126}, DOI={10.1007/s11192-021-04111-w}, journal={Scientometrics}, publisher={Springer Science and Business Media LLC}, author={Thiele, Christian and Hirschfeld, Gerrit and von Brachel, Ruth}, year={2021} }
Thiele, Christian, Gerrit Hirschfeld, and Ruth von Brachel. “Clinical Trial Registries as Scientometric Data: A Novel Solution for Linking and Deduplicating Clinical Trials from Multiple Registries.” Scientometrics 126 (2021). https://doi.org/10.1007/s11192-021-04111-w.
C. Thiele, G. Hirschfeld, and R. von Brachel, “Clinical trial registries as Scientometric data: A novel solution for linking and deduplicating clinical trials from multiple registries,” Scientometrics, vol. 126, 2021.
Thiele, Christian, et al. “Clinical Trial Registries as Scientometric Data: A Novel Solution for Linking and Deduplicating Clinical Trials from Multiple Registries.” Scientometrics, vol. 126, Springer Science and Business Media LLC, 2021, doi:10.1007/s11192-021-04111-w.

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