Open challenges for the automatic synthesis of clinical trials
Abstract Objective An important criterion for selecting clinical trials to be compared in systematic reviews and meta-analyses is that they measure the same outcomes. However, this represents a challenge as there is a wide variety of outcomes, and it is difficult to standardize them for comparing cl...
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| Format: | Article |
| Language: | English |
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BMC
2025-02-01
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| Series: | BMC Research Notes |
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| Online Access: | https://doi.org/10.1186/s13104-025-07121-6 |
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| author | Olivia Sanchez-Graillet David M. Schmidt Christian Kullik Philipp Cimiano |
| author_facet | Olivia Sanchez-Graillet David M. Schmidt Christian Kullik Philipp Cimiano |
| author_sort | Olivia Sanchez-Graillet |
| collection | DOAJ |
| description | Abstract Objective An important criterion for selecting clinical trials to be compared in systematic reviews and meta-analyses is that they measure the same outcomes. However, this represents a challenge as there is a wide variety of outcomes, and it is difficult to standardize them for comparing clinical trials containing them. To address this challenge, we utilized our annotated dataset, which includes 211 abstracts of clinical trials related to glaucoma and type 2 diabetes mellitus. We then developed a tool that provides an overview of the annotated clinical trial information and enables users to group them by outcomes. Results Using our visualization tool, we formed groups of outcomes and their respective clinical trials. We were able to determine the most common outcomes in clinical trials for these diseases. As a case study on diabetes, we compared our outcomes with those consented by diabetes stakeholders and found that many of the grouped outcomes are aligned with the consented ones. This demonstrates that tools such as the one presented can help standardize clinical outcomes, which in turn help in the synthesis of clinical trials. Finally, we also offer some recommendations that could help in the automation of clinical trials based on outcome standardization. |
| format | Article |
| id | doaj-art-22a4939ac18d4d5ebd46c247ed5183c0 |
| institution | Kabale University |
| issn | 1756-0500 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Research Notes |
| spelling | doaj-art-22a4939ac18d4d5ebd46c247ed5183c02025-02-09T12:09:58ZengBMCBMC Research Notes1756-05002025-02-011811610.1186/s13104-025-07121-6Open challenges for the automatic synthesis of clinical trialsOlivia Sanchez-Graillet0David M. Schmidt1Christian Kullik2Philipp Cimiano3Semantic Computing Group, Center for Cognitive Interaction Technology, Bielefeld UniversitySemantic Computing Group, Center for Cognitive Interaction Technology, Bielefeld UniversityFaculty of Technology, Bielefeld UniversitySemantic Computing Group, Center for Cognitive Interaction Technology, Bielefeld UniversityAbstract Objective An important criterion for selecting clinical trials to be compared in systematic reviews and meta-analyses is that they measure the same outcomes. However, this represents a challenge as there is a wide variety of outcomes, and it is difficult to standardize them for comparing clinical trials containing them. To address this challenge, we utilized our annotated dataset, which includes 211 abstracts of clinical trials related to glaucoma and type 2 diabetes mellitus. We then developed a tool that provides an overview of the annotated clinical trial information and enables users to group them by outcomes. Results Using our visualization tool, we formed groups of outcomes and their respective clinical trials. We were able to determine the most common outcomes in clinical trials for these diseases. As a case study on diabetes, we compared our outcomes with those consented by diabetes stakeholders and found that many of the grouped outcomes are aligned with the consented ones. This demonstrates that tools such as the one presented can help standardize clinical outcomes, which in turn help in the synthesis of clinical trials. Finally, we also offer some recommendations that could help in the automation of clinical trials based on outcome standardization.https://doi.org/10.1186/s13104-025-07121-6Clinical trial synthesisCore outcome setCOMET taxonomyOutcome grouping |
| spellingShingle | Olivia Sanchez-Graillet David M. Schmidt Christian Kullik Philipp Cimiano Open challenges for the automatic synthesis of clinical trials BMC Research Notes Clinical trial synthesis Core outcome set COMET taxonomy Outcome grouping |
| title | Open challenges for the automatic synthesis of clinical trials |
| title_full | Open challenges for the automatic synthesis of clinical trials |
| title_fullStr | Open challenges for the automatic synthesis of clinical trials |
| title_full_unstemmed | Open challenges for the automatic synthesis of clinical trials |
| title_short | Open challenges for the automatic synthesis of clinical trials |
| title_sort | open challenges for the automatic synthesis of clinical trials |
| topic | Clinical trial synthesis Core outcome set COMET taxonomy Outcome grouping |
| url | https://doi.org/10.1186/s13104-025-07121-6 |
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