Real-data-based simulative RCT (randomized controlled trial) analysis method

Abstract

The invention belongs to the field of RCT (randomized controlled trial), and relates to a real-data-based simulative RCT analysis method. The analysis method is a data analysis method for comparative effectiveness researches, is used for analyzing result data generated by different interference, and comprises the steps of database creation, randomized grouping, statistical analysis, result obtaining and the like. The analysis method is used for performing comparative effectiveness analysis on clinically generated real data, confounding factors can be effectively controlled, an analysis result is high in extensionality, requirements on the sample size are low, and a plurality of result indexes can be simultaneously analyzed; the analysis method can be used for comparing the effectiveness and security of different clinical intervention methods or strategies, and new evidences for evidence-based medicine can be provided for clinical decision making.

Description

technical field [0001] The invention belongs to the field of test data analysis methods, and relates to a simulated RCT analysis method based on real data; the method analyzes the outcome data (actual effect data) of a randomized controlled trial comparative study (Comparative Effectiveness Research, CER), providing clinical decision-making Reference evidence. Background technique [0002] Evidence-based medicine is evidence-based medicine, which aims to use the best available evidence to help clinical practice and solve clinical problems. According to the classification of evidence quality by GRADE in 2011, meta-analysis and systematic review based on high-quality randomized controlled trials (Randomized controlled trials, RCTs) and RCTs with strict design and implementation are regarded as high-quality evidence for comparison of efficacy, and it is necessary to obtain The best way to obtain evidence; CER using empirical data is a new field of analysis using clinically gen...

AI Technical Summary

Problems solved by technology

According to the classification of evidence quality by GRADE in 2011, meta-analysis and systematic review based on high-quality randomized controlled trials (Randomized controlled trials, RCTs) and RCTs with strict design and implementation are regarded as high-quality evidence for comparison of efficacy, and it is necessary to obtain The best approach to evidence; CER using empirical data is a new field of analysis using clinically generated empirical data in recent years, but the data analysis methods of the above studies are all based on the basic methods of classic epidemiology and statistics

Due to the limitations of RCT costs, ethics, and stricter inclusion of research objects, the number of RCT studies is small, the effectiveness is limited, the extrapolation is limited, and the amount of evidence of this kind is also limited.

In addition, rigorously designed and implemented observational studies are one of the ways to obtain evidence for CER, but because observational studies are not randomized into groups, the comparison of the therapeutic effects of different treatment methods becomes very complicated

In order to exclude the influence of confounding factors, the traditional method is to use a more complex multivariate analysis method to control the effect of confounding factors, but with a limited number of observational studies, it is still difficult to accurately judge the difference in the efficacy of different treatment methods

In addition, the propensity score (PS) method proposed by Rosenbaum and Rubin in 1983 can also solve the problem of unbalanced confounding factors in observational studies to a certain extent; however, due to the limitations of observational studies, The results of the study were defined as low-quality evidence by GRADE

Therefore, there are still a lot of diagnosis and treatment decision-making problems in clinical practice that urgently need evidence-based medical evidence. Especially in recent years, with the emergence of a large number of new drugs and new diagnosis and treatment technologies, the number of RCTs currently carried out is far from meeting the clinical needs. need

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