Literature DB >> 31264541

Reviewing the Mechanistic Evidence Assessors E-Synthesis and EBM+: A Case Study of Amoxicillin and Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS).

Ahmad Y Abdin1, Daniel Auker-Howlett2, Jürgen Landes3, Glorjen Mulla1, Claus Jacob1, Barbara Osimani3,4.   

Abstract

BACKGROUND: Basic science has delivered unprecedented insights into intricate relationships on the smallest scales within well-controlled environments. Addressing pressing societal decision problems requires an understanding of systems on larger scales in real-world situations.
OBJECTIVE: To assess how well the evidence assessors E-Synthesis and EBM+ assess basic science findings to support medical decision making.
METHODS: We demonstrate the workings of E-Synthesis and EBM+ on a case study: the suspected causal connection between the widely-used drug amoxicillin (AMX) and the putative adverse drug reaction: Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS).
RESULTS: We determine an increase in the probability that AMX can cause DRESS within the E-Synthesis approach and using the EBM+ standards assess the basic science findings as supporting the existence of a mechanism linking AMX and DRESS.
CONCLUSIONS: While progress is made towards developing methodologies which allow the incorporation of basic science research in the decision making process for pressing societal questions, there is still considerable need for further developments. A continued dialogue between basic science researchers and methodologists, philosophers and statisticians seems to offer the best prospects for developing and evaluating continuously evolving methodologies. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

Keywords:  DRESS; E-synthesis; EBM+; Evidence aggregation; adverse drug reactions; amoxicillin; bradford hill guidelines; causal inference; drugzzm321990monitoring; drug safety; pharmacosurveillance; pharmacovigilance.

Year:  2019        PMID: 31264541     DOI: 10.2174/1381612825666190628160603

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  4 in total

1.  E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance.

Authors:  Francesco De Pretis; Jürgen Landes; Barbara Osimani
Journal:  Front Pharmacol       Date:  2019-12-17       Impact factor: 5.810

2.  EA3: A softmax algorithm for evidence appraisal aggregation.

Authors:  Francesco De Pretis; Jürgen Landes
Journal:  PLoS One       Date:  2021-06-17       Impact factor: 3.240

3.  The use of mechanistic reasoning in assessing coronavirus interventions.

Authors:  Jeffrey K Aronson; Daniel Auker-Howlett; Virginia Ghiara; Michael P Kelly; Jon Williamson
Journal:  J Eval Clin Pract       Date:  2020-07-15       Impact factor: 2.336

4.  Complicated Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) Syndrome History in a 14-Year-Old.

Authors:  Michael Tomani; Cristina Caridi; Oksana Tatarina-Nulman; Cascya Charlot; Pramod Narula
Journal:  Am J Case Rep       Date:  2021-02-24
  4 in total

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