Journal
INTERNATIONAL JOURNAL OF TECHNOLOGY ASSESSMENT IN HEALTH CARE
Volume 28, Issue 1, Pages 36-43Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0266462311000687
Keywords
-
Categories
Funding
- Agency for Healthcare Research and Quality [AHRQ, 290-02-0016]
- US Agency for Healthcare Research and Quality
- Research Triangle Institute
- RTI International
- US Department of Health and Human Services
Ask authors/readers for more resources
Objectives: The aim of this study was to synthesize best practices for addressing clinical heterogeneity in systematic reviews and health technology assessments (HTAs). Methods: We abstracted information from guidance documents and methods manuals made available by international organizations that develop systematic reviews and HTAs. We searched PubMed (R) to identify studies on clinical heterogeneity and subgroup analysis. Two authors independently abstracted and assessed relevant information. Results: Methods manuals offer various definitions of clinical heterogeneity. In essence, clinical heterogeneity is considered variability in study population characteristics, interventions, and outcome across studies. It can lead to effect-measure modification or statistical heterogeneity, which is defined as variability in estimated treatment effects beyond what would be expected by random erro alone. Clinical and statistical heterogeneity are closely intertwined but they do not have a one-to-one relationship. The presence of statistical heterogeneity does not necessarily indicate that clinical heterogeneity is the causal factor. Methodological heterogeneity, biases, and random error can also cause statistical heterogeneity, alone or in combination with clinical heterogeneity. Conclusions: Identifying potential modifiers of treatment effects (i.e., effect-measure modifiers) is important for researchers conducting systematic reviews and HTAs. Recognizing clinical heterogeneity and clarifying its implications helps decision makers to identify patients and patient populations who benefit the most, who benefit the least, and who are at greatest risk of experiement adverse outcomes from a particular intervention.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available