The iterative proportional fitting algorithm for adjusted agreement in a non-inferiority diagnostic clinical trial.
El-Khorazaty, J.Ann; Koch, G.; Preisser, J.
Algorithms; Clinical Trials as Topic; Diagnostic Techniques and Procedures; Humans; Reproducibility of Results; Research Design
In this paper, we describe a method of comparing agreement between two diagnostic contingency tables after adjustment to more clinically relevant marginal distributions using the iterative proportional fitting algorithm. When the categories of a contingency table represent mild, moderate, and severe outcomes, the majority of patients often are in the mild category. Because it is often of more interest to evaluate agreement when patients are uniformly distributed among categories, we present the primary results of two clinical trials with adjustment to this structure. We also describe the relationship between the sponsor's pre-specified agreement measure for the observed contingency table and kappa for the adjusted table; and by either criterion, we then show that the agreement of the new diagnostic tool with the standard diagnostic tool is comparably non-inferior to the agreement of the standard diagnostic tool with itself.