A Comparative Study on Evaluation Methods of Sample Representativeness for Clinical Research
Objective To compare the existing evaluation methods of sample's representativeness and provide reference for selection of sample representativeness evaluation methods in clinical research.Methods Simulate the target population of lung cancer patients and select samples with different sample sizes and different degrees of deviation based on the distribution of traits of lung cancer patients in China and the actual situation of sample screening in domestic clinical studies.Calculate sample representativeness using the existing evaluation methods of sample's representativeness,and calculate estimation deviation(bias).By constructing the correlation model between the measured value of each method and bias,analyze the accuracy and stability of each method.Results The overall structural variance rate RV1、RV2、C-statistic based on propensity score、SGCR and K-S distance could well measure the degrees of deviation of different samples.Under different sample sizes,the R2 of RV2 and RV1 are greater than 0.90,and R2 of C-Statistic、SGCR and K-S distance were greater than 0.80.Conclusion The overall structural variance rate is more accurate and stable because the traits weight is taken into account.In particular,RV2 can better measure the representativeness of samples with different degrees of deviation and accurately reflect the estimation deviation.However,when it is difficult to obtain the feature importance information,the reliability of the representative measurement of SGCR as well as C-statistic and K-S distance used the propensity score-based method are acceptable.
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