From Systematic Reviews to Clinical Recommendations for Evidence-Based Health Care: Validation of Revised Assessment of Multiple Systematic Reviews (R-AMSTAR) for Grading of Clinical Relevance

Research synthesis seeks to gather, examine and evaluate systematically research reports that converge toward answering a carefully crafted research question, which states the problem patient population, the intervention under consideration, and the clinical outcome of interest. The product of the process of systematically reviewing the research literature pertinent to the research question thusly stated is the “systematic review”. The objective and transparent approach of the systematic review aims to minimize bias. Most systematic reviews yield quantitative analyses of measurable data (e.g., acceptable sampling analysis, meta-analysis). Systematic reviews may also be qualitative, while adhering to accepted standards for gathering, evaluating, and reporting evidence. Systematic reviews provide highly rated recommendations for evidence-based health care; but, systematic reviews are not equally reliable and successful in minimizing bias. Several instruments are available to evaluate the quality of systematic reviews. The 'assessment of multiple systematic reviews' (AMSTAR) was derived from factor analysis of the most relevant items among them. AMSTAR consists of eleven items with good face and content validity for measuring the methodological quality of systematic reviews, has been widely accepted and utilized, and has gained in reliability, reproducibility. AMSTAR does not produce quantifiable assessments of systematic review quality and clinical relevance. In this study, we have revised the AMSTAR instrument, detracting nothing from its content and construct validity, and utilizing the very criteria employed in the development of the original tool, with the aim of yielding an instrument that can quantify the quality of systematic reviews. We present validation data of the revised AMSTAR (R-AMSTAR), and discuss its implications and application in evidence-based health care.