Key result
Systemic trial bias limits real-world generalizability, warranting integration of trial and real-world data.
Why the study?
Systemic bias in modern randomized trials may distort results and limit their applicability to real clinical practice.
Answers are grounded in this paper and cite their sources.
Highlights the need to pool clinical trial results with real-world practice data to overcome systemic bias and population incomparability.
Objective. To analyze the causes of systemic bias in modern randomized trials potentially distorting the results in relation to real clinical practice. Material and methods. The Rob2 tool presented in the Cochrane Handbook for Systematic Reviews of Interventions guidelines was used to assess the risk. Among 2.555 studies, we enrolled 25 ones into this review. For examples of each type of systemic bias, we selected one article related to each of the five topics: oncology, cardiology, endocrinology, COVID-19, biological drugs for various diseases (therapy, infectious diseases). Results. We established the main critical area of clinical trials where systemic bias leads to incomparability of populations of clinical trial subjects and patients in real practice. Conclusion. Only pooling the results of clinical trials and real practice will allow a significant assessment of data.
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Lantsova et al. (2024) conducted a review in Various diseases (oncology, cardiology, endocrinology, COVID-19, biological drugs) (n=25). Systemic bias in randomized clinical trials was evaluated on Causes of systemic bias in modern randomized trials. Systemic bias in clinical trials leads to incomparability between trial populations and real-world patients, necessitating the pooling of trial and real-world data.
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