Literature DB >> 10929854

Representing both first- and second-order uncertainties by Monte Carlo simulation for groups of patients.

E F Halpern1, M C Weinstein, M G Hunink, G S Gazelle.   

Abstract

Actual implementation of probabilistic sensitivity analysis may lead to misleading or improper conclusions when it is applied to groups of patients rather than individual patients. The practice of combining first- and second-order simulations when modeling the outcome for a group of more than one patient yields an erroneous marginal distribution whenever the parameter values are randomly sampled for each patient while the results are presented as simulated means for the group of patients. This practice results in underrepresenting the second-order uncertainty. It may also distort the shape (especially the symmetry or extent of the tails) in the simulated distribution. As a result, it may lead to premature or incorrect conclusions of superiority. It may also result in inappropriate estimates of the value of further research to inform parameter values.

Entities:  

Mesh:

Year:  2000        PMID: 10929854     DOI: 10.1177/0272989X0002000308

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  25 in total

Review 1.  Advantages of using the net-benefit approach for analysing uncertainty in economic evaluation studies.

Authors:  Niklas Zethraeus; Magnus Johannesson; Bengt Jönsson; Mickael Löthgren; Magnus Tambour
Journal:  Pharmacoeconomics       Date:  2003       Impact factor: 4.981

Review 2.  Cost-effectiveness analyses of vaccination programmes : a focused review of modelling approaches.

Authors:  Sun-Young Kim; Sue J Goldie
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

Review 3.  Modelling methods for pharmacoeconomics and health technology assessment: an overview and guide.

Authors:  James E Stahl
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

4.  Continuous time simulation and discretized models for cost-effectiveness analysis.

Authors:  Marta O Soares; Luísa Canto E Castro
Journal:  Pharmacoeconomics       Date:  2012-12-01       Impact factor: 4.981

5.  Cost effectiveness of herpes zoster vaccine in Canada.

Authors:  Mehdi Najafzadeh; Carlo A Marra; Eleni Galanis; David M Patrick
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

6.  The cost-effectiveness of directly observed highly-active antiretroviral therapy in the third trimester in HIV-infected pregnant women.

Authors:  Caitlin J McCabe; Sue J Goldie; David N Fisman
Journal:  PLoS One       Date:  2010-04-13       Impact factor: 3.240

7.  Estimation of the burden of cardiovascular disease attributable to modifiable risk factors and cost-effectiveness analysis of preventative interventions to reduce this burden in Argentina.

Authors:  Adolfo Rubinstein; Lisandro Colantonio; Ariel Bardach; Joaquín Caporale; Sebastián García Martí; Karin Kopitowski; Andrea Alcaraz; Luz Gibbons; Federico Augustovski; Andrés Pichón-Rivière
Journal:  BMC Public Health       Date:  2010-10-20       Impact factor: 3.295

8.  Interpreting the results of cost-effectiveness studies.

Authors:  David J Cohen; Matthew R Reynolds
Journal:  J Am Coll Cardiol       Date:  2008-12-16       Impact factor: 24.094

9.  Estimating dementia-free life expectancy for Parkinson's patients using Bayesian inference and microsimulation.

Authors:  Ardo van den Hout; Fiona E Matthews
Journal:  Biostatistics       Date:  2009-07-31       Impact factor: 5.899

10.  Cost-effectiveness of pregabalin versus venlafaxine in the treatment of generalized anxiety disorder: findings from a Spanish perspective.

Authors:  Montserrat Vera-Llonch; Ellen Dukes; Javier Rejas; Oleg Sofrygin; Marko Mychaskiw; Gerry Oster
Journal:  Eur J Health Econ       Date:  2009-06-09
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.