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Quantitative benefit-risk assessment of methylprednisolone in multiple sclerosis relapses
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Uppsala Monitoring Centre (UMC), Sweden.
Number of Authors: 2
2015 (English)In: BMC Neurology, ISSN 1471-2377, E-ISSN 1471-2377, Vol. 15, 206Article in journal (Refereed) Published
Abstract [en]

Background: High-dose short-term methylprednisolone is the recommended treatment in the management of multiple sclerosis relapses, although it has been suggested that lower doses may be equally effective. Also, glucocorticoids are associated with multiple and often dose-dependent adverse effects. This quantitative benefit-risk assessment compares high-and low-dose methylprednisolone (at least 2000 mg and less than 1000 mg, respectively, during at most 31 days) and a no treatment alternative, with the aim of determining which regimen, if any, is preferable in multiple sclerosis relapses. Methods: An overall framework of probabilistic decision analysis was applied, combining data from different sources. Effectiveness as well as risk of non-serious adverse effects were estimated from published clinical trials. However, as these trials recorded very few serious adverse effects, risk intervals for the latter were derived from individual case reports together with a range of plausible distributions. Probabilistic modelling driven by logically implied or clinically well motivated qualitative relations was used to derive utility distributions. Results: Low-dose methylprednisolone was not a supported option in this assessment; there was, however, only limited data available for this treatment alternative. High-dose methylprednisolone and the no treatment alternative interchanged as most preferred, contingent on the risk distributions applied for serious adverse effects, the assumed level of risk aversiveness in the patient population, and the relapse severity. Conclusions: The data presently available do not support a change of current treatment recommendations. There are strong incentives for further clinical research to reduce the uncertainty surrounding the effectiveness and the risks associated with methylprednisolone in multiple sclerosis relapses; this would enable better informed and more precise treatment recommendations in the future.

Place, publisher, year, edition, pages
2015. Vol. 15, 206
Keyword [en]
Glucocorticoids, Corticosteroids, MS, Neurology, Neuropathy, Demyelinating diseases, Pharmacoepidemiology, Pharmacovigilance, Clinical epidemiology, Decision analysis
National Category
Neurology
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-122922DOI: 10.1186/s12883-015-0450-xISI: 000362870500001OAI: oai:DiVA.org:su-122922DiVA: diva2:871666
Available from: 2015-11-16 Created: 2015-11-11 Last updated: 2017-12-01Bibliographically approved
In thesis
1. Quantitative methods to support drug benefit-risk assessment
Open this publication in new window or tab >>Quantitative methods to support drug benefit-risk assessment
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Joint evaluation of drugs’ beneficial and adverse effects is required in many situations, in particular to inform decisions on initial or sustained marketing of drugs, or to guide the treatment of individual patients. This synthesis, known as benefit-risk assessment, is without doubt important: timely decisions supported by transparent and sound assessments can reduce mortality and morbidity in potentially large groups of patients. At the same time, it can be hugely complex: drug effects are generally disparate in nature and likelihood, and the information that needs to be processed is diverse, uncertain, deficient, or even unavailable. Hence there is a clear need for methods that can reliably and efficiently support the benefit-risk assessment process. For already marketed drugs, this process often starts with the detection of previously unknown risks that are subsequently integrated with all other relevant information for joint analysis.

In this thesis, quantitative methods are devised to support different aspects of drug benefit-risk assessment, and the practical usefulness of these methods is demonstrated in clinically relevant case studies. Shrinkage regression is adapted and implemented for large-scale screening in collections of individual case reports, leading to the discovery of a link between methylprednisolone and hepatotoxicity. This adverse effect is then considered as part of a complete benefit-risk assessment of methylpredniso­lone in multiple sclerosis relapses, set in a general framework of probabilistic decision analysis. Two methods devised in the thesis substantively contribute to this assessment: one for efficient generation of utility distributions for the considered clinical outcomes, driven by modelling of qualitative information; and one for computing risk limits for rare and otherwise non-quantifiable adverse effects, based on collections of individual case reports.

Place, publisher, year, edition, pages
Stockholm: Department of Computer and Systems Sciences, Stockholm University, 2014. 94 p.
Series
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526 ; 14-001
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-100286 (URN)978-91-7447-856-3 (ISBN)
Public defence
2014-03-21, Sal C, Forum 100, Isafjordsgatan 39, Kista, 10:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defence the following papers were unpublished and had a status as follows: Paper 6: Manuscript; Paper 7: Manuscript.

Available from: 2014-02-27 Created: 2014-01-31 Last updated: 2015-11-16Bibliographically approved

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