Synthesizing evidence from clinical trials with dynamic interactive argument trees

Sanchez Graillet O, Witte C, Grimm F, Grautoff S, Ell B, Cimiano P (2022)
Journal of Biomedical Semantics 13(1): 16.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
**Background**
Evidence-based medicine propagates that medical/clinical decisions are made by taking into account high-quality evidence, most notably in the form of randomized clinical trials. Evidence-based decision-making requires aggregating the evidence available in multiple trials to reach –by means of systematic reviews– a conclusive recommendation on which treatment is best suited for a given patient population. However, it is challenging to produce systematic reviews to keep up with the ever-growing number of published clinical trials. Therefore, new computational approaches are necessary to support the creation of systematic reviews that include the most up-to-date evidence.We propose a method to synthesize the evidence available in clinical trials in an ad-hoc and on-demand manner by automatically arranging such evidence in the form of ahierarchical argumentthat recommends a therapy as being superior to some other therapy along a number of key dimensions corresponding to the clinical endpoints of interest. The method has also been implemented as a web tool that allows users to explore the effects of excluding different points of evidence, and indicating relative preferences on the endpoints. **Results**
Through two use cases, our method was shown to be able to generate conclusions similar to the ones of published systematic reviews. To evaluate our method implemented as a web tool, we carried out a survey and usability analysis with medical professionals. The results show that the tool was perceived as being valuable, acknowledging its potential to inform clinical decision-making and to complement the information from existing medical guidelines. **Conclusions**
The method presented is a simple but yet effective argumentation-based method that contributes to support the synthesis of clinical trial evidence. A current limitation of the method is that it relies on a manually populated knowledge base. This problem could be alleviated by deploying natural language processing methods to extract the relevant information from publications.
Stichworte
Argument-based systems; Aggregation of clinical trial evidence; Evidence synthesis; Systematic review automation
Erscheinungsjahr
2022
Zeitschriftentitel
Journal of Biomedical Semantics
Band
13
Ausgabe
1
Art.-Nr.
16
eISSN
2041-1480
Page URI
https://pub.uni-bielefeld.de/record/2963654

Zitieren

Sanchez Graillet O, Witte C, Grimm F, Grautoff S, Ell B, Cimiano P. Synthesizing evidence from clinical trials with dynamic interactive argument trees. Journal of Biomedical Semantics. 2022;13(1): 16.
Sanchez Graillet, O., Witte, C., Grimm, F., Grautoff, S., Ell, B., & Cimiano, P. (2022). Synthesizing evidence from clinical trials with dynamic interactive argument trees. Journal of Biomedical Semantics, 13(1), 16. https://doi.org/10.1186/s13326-022-00270-8
Sanchez Graillet, O., Witte, C., Grimm, F., Grautoff, S., Ell, B., and Cimiano, P. (2022). Synthesizing evidence from clinical trials with dynamic interactive argument trees. Journal of Biomedical Semantics 13:16.
Sanchez Graillet, O., et al., 2022. Synthesizing evidence from clinical trials with dynamic interactive argument trees. Journal of Biomedical Semantics, 13(1): 16.
O. Sanchez Graillet, et al., “Synthesizing evidence from clinical trials with dynamic interactive argument trees”, Journal of Biomedical Semantics, vol. 13, 2022, : 16.
Sanchez Graillet, O., Witte, C., Grimm, F., Grautoff, S., Ell, B., Cimiano, P.: Synthesizing evidence from clinical trials with dynamic interactive argument trees. Journal of Biomedical Semantics. 13, : 16 (2022).
Sanchez Graillet, Olivia, Witte, Christian, Grimm, Frank, Grautoff, Steffen, Ell, Basil, and Cimiano, Philipp. “Synthesizing evidence from clinical trials with dynamic interactive argument trees”. Journal of Biomedical Semantics 13.1 (2022): 16.
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