Detalhe da pesquisa
1.
Exploiting relationships between outcomes in Bayesian multivariate network meta-analysis with an application to relapsing-remitting multiple sclerosis.
Stat Med
; 39(24): 3329-3346, 2020 10 30.
Artigo
em Inglês
| MEDLINE | ID: mdl-32672370
2.
Recommendations for benefit-risk assessment methodologies and visual representations.
Pharmacoepidemiol Drug Saf
; 25(3): 251-62, 2016 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-26800458
3.
A Bayesian approach to probabilistic sensitivity analysis in structured benefit-risk assessment.
Biom J
; 58(1): 28-42, 2016 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-25631038
4.
A case study using the PrOACT-URL and BRAT frameworks for structured benefit risk assessment.
Biom J
; 58(1): 8-27, 2016 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-25619173
5.
Benefit-risk assessment in a post-market setting: a case study integrating real-life experience into benefit-risk methodology.
Pharmacoepidemiol Drug Saf
; 23(9): 974-83, 2014 Sep.
Artigo
em Inglês
| MEDLINE | ID: mdl-25043919
6.
A proposal for using benefit-risk methods to improve the prominence of adverse event results when reporting trials.
Trials
; 25(1): 409, 2024 Jun 22.
Artigo
em Inglês
| MEDLINE | ID: mdl-38909232
7.
Challenges and Opportunities of Real-World Data: Statistical Analysis Plan for the Optimise:MS Multicenter Prospective Cohort Pharmacovigilance Study.
Front Neurol
; 13: 799531, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-35418938
8.
Evaluating the feasibility of a real world pharmacovigilance study (OPTIMISE:MS).
Mult Scler Relat Disord
; 63: 103894, 2022 Jul.
Artigo
em Inglês
| MEDLINE | ID: mdl-35636271
9.
OPTIMISE: MS study protocol: a pragmatic, prospective observational study to address the need for, and challenges with, real world pharmacovigilance in multiple sclerosis.
BMJ Open
; 11(11): e050176, 2021 11 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-34824113