Concordance rate of a four-quadrant plot for repeated measurements

Abstract

Abstract Background To assure the equivalence between new clinical measurement methods and the standard methods, the four-quadrant plot and the plot’s concordance rate is used in clinical practice, along with Bland-Altman analysis. The conventional concordance rate does not consider the correlation among the data on individual subjects, which may affect its proper evaluation. Methods We propose a new concordance rate for the four-quadrant plot based on multivariate normal distribution to take into account the covariance within each individual subject. The proposed concordance rate is formulated as the conditional probability of the agreement. It contains a parameter to set the minimum concordant number between two measurement methods, which is regarded as agreement. This parameter allows flexibility in the interpretation of the results. Results Through numerical simulations, the AUC value of the proposed method was 0.967, while that of the conventional concordance rate was 0.938. In the application to a real example, the AUC value of the proposed method was 0.999 and that of the conventional concordance rate was 0.964. Conclusion From the results of numerical simulations and a real example, the proposed concordance rate showed better accuracy and higher diagnosability than the conventional approaches.

Keywords

• Clinical trial
• Method comparison
• Monte Carlo simulation
• Trending agreement