Analysis of dose proportionality testing methods in phase I clinical trials of anticancer agents
Authors: Emiliano Calvo, Haider Zafar, Andrew Goetz, Peter L. Bonate, Johan S. De Bono, Amita Patnaik, Bahram Fourezesh, Anthony W. Tolcher, Eric K. Rowinsky, Chris H. Takimoto
Journal: Cancer Research (2005)

4127  Background: In the field of cancer chemotherapy, dose escalating phase I studies are the earliest and sometimes only opportunity to study a drug’s pharmacokinetic behavior over an extended dose range. The assessment of dose proportionality (DP) is of great clinical importance for predicting the consequences of rational dose adjustments. Although a variety of methods with varying reliability have been used to analyze for DP, none have been rigorously examined in the singular setting of anticancer phase I trials. We have examined pharmacokinetic (PK) data from actual anticancer Phase I trials from our own institution and analyzed them using a panel of different methods for assessing DP from the perspective of cancer chemotherapy drug development. Methods: Twenty complete PK datasets from consecutive dose escalating clinical trials from our institution were analyzed for DP kinetics using the following methods: 1) graphical plots of AUC vs. dose level, 2) unweighted linear regression of AUC vs. dose level, and coefficient of determination, 3) weighted linear regression of AUC vs. dose level with intercept testing, 4) analysis of variance of the logarithmically transformed dose-normalized AUC, 5) non-parametric analysis of the non-transformed dose-normalized AUC using the Kruskal-Wallis statistic, 5) magnitude of deviation from DP kinetics by Power Model analysis of the form AUC = constant .(dose)β, and 6) confidence interval criteria using the Power Model testing (Smith et al, Pharm Res, 17:1278-1283; 2000). Results: Five of the 20 evaluated datasets show non-DP kinetics in at least 4 of the tests used. Graphical representation of the dose-independent parameters (e.g., clearance) vs. dose level and plots of the dose-dependent parameters (e.g., AUC, Cmax, etc.) vs. dose level with weighted linear regression and intercept testing is relatively simple and provides valuable visual information about the relationship between dose and drug kinetics. Simple unweighted linear regression and coefficient of determination is a poor representation of dose vs. PK parameter relationship. Assessment of DP using more formalized statistical tests can detect gross deviations from DP, but the power of these tests is limited. Conclusions: Graphical representations of PK parameters vs. dose level with weighted linear regression and intercept testing are valuable in all assessments of DP. Based on its low reliability, the unweighted linear regression and use of the coefficient of determination to assess DP should be avoided. More formalized tests such as the power model analysis with confidence intervals criteria and/or the ANOVA tests of logarithmically transformed dose-normalized AUC or the or Kruskal-Wallis test on non-log-transformed data can be readily applied to Phase I PK data, but their low power due to limited patients numbers treated at each dose level often limit definitive statements about DP.