A method to evaluate scientific evidence in clinical preventive medicine

Article information

J Korean Med Assoc. 2011;54(10):1006-1012
Publication date (electronic) : 2011 October 12
doi : https://doi.org/10.5124/jkma.2011.54.10.1006
1Medical Research Collaborating Center, Seoul National University College of Medicine & Seoul National University Hospital, Seoul, Korea.
2Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Corresponding author: Byung-Joo Park, bjpark@snu.ac.kr
Received 2011 September 08; Accepted 2011 September 22.


Evaluation of scientific evidence in the medical literature is based on the research methodology, which can be the fundamental tool for medical professionals to improve their practice. Since analytic studies usually provide evidence for generating hypotheses and selecting appropriate research designs, this article aims to review the methods for evaluating the study quality in randomized controlled trials (RCTs), cohort studies, and case-control studies. Critical appraisal of systematic errors including selection bias, performance bias, attrition bias, detection bias, and publication bias are the essential elements of the evaluation. Clinical trials need to have an adequate description of sequence generation and allocation concealment, blinding for exposure measurement, completeness of follow-up and intention to treat analysis, and blinding for outcome evaluation. For cohort studies, like RCTs, appropriate control of confounding variables is needed to prevent selection bias, and blinding and completeness of follow-up are also very important. Matching of the case group to the control group, blinding of interviewers, and proper definition of the cases and controls are important to prevent bias in a case-control study. Since the process of critical appraisal depends on the quality of reporting, there have been efforts to improve the reporting quality of the medical literature. However, reporting all of the elements necessary to avoid bias does not automatically guarantee an exclusion of bias or the quality of a study; instead, what is important is the logical connection of the elements of a study and the eventual lucid expression of the elements.


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Table 1

Evidence hierarchy of the research methodology

Table 1

Table 2

Methodology to avoid the bias in analytic study designs

Table 2

ITT, intention to treat.