Abstract
We began this monograph by citing an Evidence Report Publication (No. 07-E012) of the Agency for Healthcare Research and Quality (AHRQ). AHRQ plays a leadership role in the evolution of the field, from fundamental methodological issues to the design, establishment, verification, and dissemination of Registries. AHRQ defines Registries as: “… (a) patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes… registries (are) created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or costeffectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care….(and) are classified according to how their (patient) populations are defined…” (Gliklich and Dreyer 2010).
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Notes
- 1.
“…for example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure…” (Gliklich and Dreyer 2010).
- 2.
For example, the purpose of registries may include “…internal, external, or historical comparison groups in order to strengthen the understanding of whether the observed effects are indeed real and in fact different from what would have occurred under other circumstances…” (Gliklich and Dreyer 2010).
- 3.
AHRQ, for example, refers to evidence reports; whereas the American Dental Association, for instance, uses the term evidence reviews.
- 4.
The interested reader is advised to get on the mailing list of the Cochrane journal club (http://www.cochranejournalclub.com).
- 5.
Some degree of selection bias is unavoidable because of the very nature of our peer-review system. For example, a certain degree of publication bias cannot be avoided simply because, as a general rule, papers that are statistically significant, whether they demonstrate clinical relevance or not, tend to be prefentially published in the scientific literature, compared to reports that demonstrate clinical relevance but fail to reach statistical significance. The problem of publication bias is inherent to our present system of scientific literature, and is an unavoidable issue of the research synthesis process. The effect of the preferential acceptance of articles reporting significant results on research is critical: bias in favor of studies showing significant results alter the reliability of systematic reviews by reducing the included number of papers with opposing results. Since the validity of this type of publications depends on the representativeness and soundness of the source material, underrepresented evidence will have a disproportionally decreased influence on the outcome. That will be particularly grave when, as is the case for instance in osteoimmunology, research synthesis is utilized to obtain the best available evidence for treatment of pathologies in order to perform either evidence-based clinical decisions, or comparative effectiveness analysis (cf., Chiappelli et al. 2010a, b).
- 6.
It is important to note that inter-rater reliability obtains a correlation coefficient between two raters, and a high correlation implies that the two raters “agreed” on which item to score high or low (i.e., strong positive Pearson correlation coefficient). By contrast, Cohen’s kappa coefficient is a statistical measure of agreement, which assesses whether or not the probability of the raters agreeing is larger than chance alone. That is to say, the Pearson intra-rater reliability coefficient is distinct from Cohen’s kappa coefficient, although both values establish the degree of agreement between two raters, they are two distinct sides of the same coin.
- 7.
The Institute of Medicine Committee on Comparative Effectiveness Research Prioritization defined (2009) comparative effectiveness research and analysis as “the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care. The purpose of CER is to assist consumers, clinicians, purchasers, and policy makers to make informed decisions that will improve health care at both the individual and population levels.”
- 8.
For example, the interested reader is referred to a recent AHRQ report: Creating a Framework for “Best Evidence” Approaches in Systematic Reviews, Review Protocol. September 2010. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/clinic/tp/bestevtp.htm.
- 9.
Fundamentally, and as defined by the National Institutes of Health (NIH), translational research is used to translate the findings in basic research efficiently into clinical practice.
- 10.
The clinically relevant complex mixed systematic reviews (CRCMSRs) combine (i.e., “mix”) the traditional systematic review approach outlined above with the systematic reviews performed on a set of systematic reviews (i.e., CRCSRs). That mixing of two heterogeneous bodies of research in a single research synthesis process engenders significant analytical challenges and interpretative difficulties, which are still under development by my research group and others.
- 11.
These limitations emphasize the need for assessment of the level of the evidence and of the quality of the evidence, followed by an acceptable sampling step, as described above (vide supra).
- 12.
The CONSORT statement has recently been revised as CONSORT-2010 (vide infra).
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Chiappelli, F. (2011). Translational Evidence-Based Interventions in Osteoimmunology. In: Osteoimmunopathology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9495-0_3
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