Abstract
Most cost-effectiveness analyses consist of a baseline model that represents the absolute natural history under a standard treatment in a comparator set and a model for relative treatment effects. We review synthesis issues that arise on the construction of the baseline natural history model. We cover both the absolute response to treatment on the outcome measures on which comparative effectiveness is defined and the other elements of the natural history model, usually downstream of the shorter-term effects reported in trials. We recommend that the same framework be used to model the absolute effects of a standard treatment or placebo comparator as that used for synthesis of relative treatment effects and that the baseline model is constructed independently from the model for relative treatment effects, to ensure that the latter are not affected by assumptions made about the baseline. However, simultaneous modeling of baseline and treatment effects could have some advantages when evidence is very sparse or when other research or study designs give strong reasons for believing in a particular baseline model. The predictive distribution, rather than the fixed effect or random effects mean, should be used to represent the baseline to reflect the observed variation in baseline rates. Joint modeling of multiple baseline outcomes based on data from trials or combinations of trial and observational data is recommended where possible, as this is likely to make better use of available evidence, produce more robust results, and ensure that the model is internally coherent.
| Original language | English |
|---|---|
| Pages (from-to) | 657-670 |
| Number of pages | 14 |
| Journal | Medical Decision Making |
| Volume | 33 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Jul 2013 |
Keywords
- cost-effectiveness analysis
- Bayesian meta-analysis
- multiparameter evidence synthesis
- random effects metanalysis
- immunodeficiency virus prevalence
- cost effectiveness
- transition-probabilities
- multiparameter synthesis
- economic evaluation
- surveillance data
- outcomes
- interventions
- example
Fingerprint
Dive into the research topics of 'Evidence Synthesis for Decision Making 5: The Baseline Natural History Model'. Together they form a unique fingerprint.Research output
- 82 Citations
- 1 Commissioned report
-
NICE DSU Technical Support Document 5: Evidence Synthesis in the Baseline Natural History Model
Dias, S., Welton, N. J., Sutton, A. J. & Ades, A. E., Aug 2011, National Institute for Health and Clinical Excellence. 29 p. (NICE DSU Technical Support Document in Evidence Synthesis; no. TSD5)Research output: Book/Report › Commissioned report
Open AccessFile
Projects
- 2 Finished
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MRC METHODOLOGY RESEARCH FELLOWSHIP
Welton, N. J. (Principal Investigator)
4/05/09 → 4/11/13
Project: Research
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COLLABORATION AND INNOVATION IN DIFFICULT OR RANDOMISED CONTROLLED TRIALS
Blazeby, J. (Principal Investigator)
1/04/09 → 1/04/14
Project: Research
Activities
- 2 Participation in workshop, seminar, course
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35th Annual Meeting of the Society for Medical Decision Making
Dias, S. (Speaker)
20 Oct 2013Activity: Participating in or organising an event types › Participation in workshop, seminar, course
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Evidence Synthesis for Decision Making Short Course
Welton, N. J. (Participant)
20 Oct 2013Activity: Participating in or organising an event types › Participation in workshop, seminar, course
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