Observational studies provide an important source of information when randomized controlled
trials (RCTs) cannot or should not be undertaken, provided that the data are analyzed and
interpreted with special attention to bias. Evidence-based medicine (EBM) stresses the
examination of evidence from clinical research and describes it as a shift in medical paradigm,
in contrast to intuition, unsystematic clinical experience, and pathophysiologic rationale. While
the importance of randomized trials has been created by the concept of the hierarchy of
evidence in guiding therapy, much of the medical research is observational. The reporting of
observational research is often not detailed and clear enough with insufficient quality and poor
reporting, which hampers the assessment of strengths and weaknesses of the study and the
generalizability of the mixed results. Thus, in recent years, progress and innovations in health
care are measured by systematic reviews and meta-analyses. A systematic review is defined
as, “the application of scientific strategies that limit bias by the systematic assembly, clinical
appraisal, and synthesis of all relevant studies on a specific topic.” Meta-analysis usually is the
final step in a systematic review.
Systematic reviews and meta-analyses are labor intensive, requiring expertise in both the subject
matter and review methodology, and also must follow the rules of EBM which suggests that
a formal set of rules must complement medical training and common sense for clinicians to
integrate the results of clinical research effectively. While expertise in the review methods is
important, the expertise in the subject matter and technical components is also crucial.
Even though, systematic reviews and meta-analyses, specifically of RCTs, have exploded, the
quality of the systematic reviews is highly variable and consequently, the opinions reached
of the same studies are quite divergent. Numerous deficiencies have been described in
methodologic assessment of the quality of the individual articles. Consequently, observational
studies can provide an important complementary source of information, provided that the
data are analyzed and interpreted in the context of confounding bias to which they are prone.
Appropriate systematic reviews of observational studies, in conjunction with RCTs, may provide
the basis for elimination of a dangerous discrepancy between the experts and the evidence.
Steps in conducting systematic reviews of observational studies include planning, conducting,
reporting, and disseminating the results. MOOSE, or Meta-analysis of Observational Studies in
Epidemiology, a proposal for reporting contains specifications including background, search
strategy, methods, results, discussion, and conclusion. Use of the MOOSE checklist should improve
the usefulness of meta-analysis for authors, reviewers, editors, readers, and decision-makers.
This manuscript describes systematic reviews and meta-analyses of observational studies. Authors
frequently utilize RCTs and observational studies in one systematic review; thus, they should also
follow the reporting standards of the Quality of Reporting of Meta-analysis (QUOROM) statement,
which also provides a checklist. A combined approach of QUOROM and MOOSE will improve
reporting of systematic reviews and lead to progress and innovations in health care.
Key words: Observational studies, evidence-based medicine, systematic reviews, metaanalysis, randomized trials, case-control studies, cross-sectional studies, cohort studies,
confounding bias, QUOROM, MOOSE
The Square Curve Paradigm for Research in Alternative, Complementary, and Holistic Medicine: A Cost-Effective, Easy, and Scientifically Valid Design for Evidence-Based Medicine and Quality Improvement