Skip Navigation
Department of Health and Human Services www.hhs.gov
 
 

Article Alert

The free Article Alert service delivers a weekly email to your inbox containing the most recently published articles on all aspects of systematic review and comparative effectiveness review methodologies.

  • Medical, psychological, educational, etc., methodology research literatures covered
  • Curated by our seasoned research staff from a wide array of sources: PubMed, journal table of contents, author alerts, bibliographies, and prominent international methodology and grey literature Web sites
  • Averages 20 citations/week (pertinent citations screened from more than 1,500 citations weekly)
  • Saves you time AND keeps you up to date on the latest research


Article Alert records include:

  • Citation information/abstract
  • Links: PMID (PubMed ID) and DOI (Digital Object Identifier)
  • Free Full Text: PubMed Central or  publisher link (when available)
  • RIS file to upload all citations to EndNote, RefWorks, Zotero, or other citation software

To sign up for free email updates of Article Alert, contact the Scientific Center Resource Library at methods@epc-src.org.

 

The Article Alert for the week of July 21, 2014 (sample articles)

Espinoza MA, Manca A, Claxton K, Sculpher MJ.  The Value of Heterogeneity for Cost-Effectiveness Subgroup Analysis: Conceptual Framework and Application. Med.Decis.Making.  Epub 2014 Jun 18.  PMID: 24944196.

This article develops a general framework to guide the use of subgroup cost-effectiveness analysis for decision making in a collectively funded health system. In doing so, it addresses 2 key policy questions, namely, the identification and selection of subgroups, while distinguishing 2 sources of potential value associated with heterogeneity. These are 1) the value of revealing the factors associated with heterogeneity in costs and outcomes using existing evidence (static value) and 2) the value of acquiring further subgroup-related evidence to resolve the uncertainty given the current understanding of heterogeneity (dynamic value). Consideration of these 2 sources of value can guide subgroup-specific treatment decisions and inform whether further research should be conducted to resolve uncertainty to explain variability in costs and outcomes. We apply the proposed methods to a cost-effectiveness analysis for the management of patients with acute coronary syndrome. This study presents the expected net benefits under current and perfect information when subgroups are defined based on the use and combination of 6 binary covariates.  The results of the case study confirm the theoretical expectations. As more subgroups are considered, the marginal net benefit gains obtained under the current information show diminishing marginal returns, and the expected value of perfect information shows a decreasing trend. We present a suggested algorithm that synthesizes the results to guide policy.

 

Mathes T, Walgenbach MD, Antoine SL, Pieper D, Eikermann M.  Methods for Systematic Reviews of Health Economic Evaluations: A Systematic Review, Comparison, and Synthesis of Method Literature.  Med.Decis.Making.  Epub 2014 Apr 8.  PMID: 24713694.

INTRODUCTION: The quality of systematic reviews of health economic evaluations (SR-HE) is often limited because of methodological shortcomings. One reason for this poor quality is that there are no established standards for the preparation of SR-HE.  The objective of this study is to compare existing methods and suggest best practices for the preparation of SR-HE.
METHODS: To identify the relevant methodological literature on SR-HE, a systematic literature search was performed in Embase, Medline, the National Health System Economic Evaluation Database, the Health Technology Assessment Database, and the Cochrane methodology register, and webpages of international health technology assessment agencies were searched. The study selection was performed independently by 2 reviewers. Data were extracted by one reviewer and verified by a second reviewer. On the basis of the overlaps in the recommendations for the methods of SR-HE in the included papers, suggestions for best practices for the preparation of SR-HE were developed.
RESULTS: Nineteen relevant publications were identified. The recommendations within them often differed.  However, for most process steps there was some overlap between recommendations for the methods of preparation. The overlaps were taken as basis on which to develop suggestions for the following process steps of preparation: defining the research question, developing eligibility criteria, conducting a literature search, selecting studies, assessing the methodological study quality, assessing transferability, and synthesizing data.
DISCUSSION: The differences in the proposed recommendations are not always explainable by the focus on certain evaluation types, target audiences, or integration in the decision process. Currently, there seem to be no standard methods for the preparation of SR-HE.  The suggestions presented here can contribute to the harmonization of methods for the preparation of SR-HE.

 

Sadatsafavi M, Marra C, Aaron S, Bryan S.  Incorporating external evidence in trial-based cost-effectiveness analyses: the use of resampling methods.  Trials.  2014 Jun 3;15(1):201.  PMID: 24888356.

BACKGROUND: Cost-effectiveness analyses (CEAs) that use patient-specific data from a randomized controlled trial (RCT) are popular, yet such CEAs are criticized because they neglect to incorporate evidence external to the trial.  A popular method for quantifying uncertainty in a RCT-based CEA is the bootstrap. The objective of the present study was to further expand the bootstrap method of RCT-based CEA for the incorporation of external evidence.
METHODS: We utilize the Bayesian interpretation of the bootstrap and derive the distribution for the cost and effectiveness outcomes after observing the current RCT data and the external evidence. We propose simple modifications of the bootstrap for sampling from such posterior distributions.
RESULTS: In a proof-of-concept case study, we use data from a clinical trial and incorporate external evidence on the effect size of treatments to illustrate the method in action. Compared to the parametric models of evidence synthesis, the proposed approach requires fewer distributional assumptions, does not require explicit modeling of the relation between external evidence and outcomes of interest, and is generally easier to implement. A drawback of this approach is potential computational inefficiency compared to the parametric Bayesian methods.
CONCLUSIONS: The bootstrap method of RCT-based CEA can be extended to incorporate external evidence, while preserving its appealing features such as no requirement for parametric modeling of cost and effectiveness outcomes.