Practical Application of Nonrandomized Research to Patient Care: A Case Study of Nesiritide
Abstract
Prospective, randomized clinical trials are the gold standard for establishing cause‐and‐effect relationships between therapeutic interventions and specific outcomes. Unfortunately, these types of studies are not always available to evaluate important clinical end points such as mortality. Meta‐analyses and observational studies are often used in an attempt to fill the gap in the literature when no prospective, randomized trials exist to answer a research question. A rapid increase in the number of published meta‐analyses and observational studies has occurred in recent years. In the absence of prospective, randomized studies, it is essential for the clinician to understand the important issues involved in interpreting these other types of studies. When evaluating a meta‐analysis, the clinician should assess for several different forms of bias, clinical heterogeneity, and use of appropriate methodology. When evaluating an observational study, sources of bias and confounding should be identified. If the potential for confounding is present, the methods used to minimize the impact of confounders should be evaluated for appropriateness. Mortality associated with nesiritide in the treatment of acute decompensated heart failure is a contemporary example of the use of nonrandomized research to address a research question that is unanswered by prospective, randomized studies. We review the details of a recent metaanalysis and observational evaluation of mortality associated with nesiritide and discuss the issues that are important in critical evaluation of nonrandomized study designs.
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The majority of articles advised against the use of scales but 12 articles recommended their use.
“The majority of articles advised against the use of scales but 12 articles recommended their use [29, 30, 48–50, 52, 53, 56, 66, 77, 86, 91].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [66]
One common recommendation was to explore heterogeneity in sensitivity analyses, comparing studies stratified by design or clinical features.
“One common recommendation was to explore heterogeneity in sensitivity analyses, comparing studies stratified by design or clinical features [12, 16, 29, 34, 39, 51, 55, 56, 66, 77, 85, 100, 102].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [66]
Authors recommended not to pool if heterogeneity is too high, and use statistical measures of heterogeneity to choose between random-effects and fixed-effect models.
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From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [66]
Many considered heterogeneity important for the decision whether to pool the data.
“Many considered heterogeneity important for the decision whether to pool the data [34, 36, 47, 55, 56, 66, 101, 103].”
From Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations (2018) · cites this paper as [66]
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- Authors
- Winegardner, M. L., Reaume, K. T., Dabaja, G. S., & Kalus, J. S.
- Affiliations
- Henry Ford Health (US)
- Eugene Applebaum College of Pharmacy and Health Sciences (US)
- Corresponding author
- Kalus, James S.
- Venue
- Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy
- Publisher
- Wiley
- Published
- 2007-01
- Volume
- 27
- Issue
- 1
- Pages
- 143-151
- ISSN
- 0277-0008 (ISSN-L)
- 1875-9114
- OpenAlex
- W2000416034
- Cited by
- 2
- References
- 44
- Citations by year
- 2018: 1
- FWCI
- 0.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Pharmacotherapy The Journal of Human Pharmacology and Drug Therapy (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Failure Treatment and Management
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- nesiritide, acute decompensated heart failure, mortality, non-randomized studies, meta-analysis bias, confounding, observational studies, clinical heterogeneity, evidence-based care
- MeSH terms
- Clinical Trials as Topic, Heart Failure, Humans, Prospective Studies, Research Design, Retrospective Studies, Meta-Analysis as Topic, Bias, Confounding Factors, Epidemiologic, Natriuretic Peptide, Brain, Natriuretic Agents
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