BAYESIAN PHASE I DOSE FINDING IN CANCER TRIALS

This dissertation explores phase I dose-finding designs in cancer trials from three perspectives: the alternative Bayesian dose-escalation rules, a design based on a time-to-dose-limiting toxicity (DLT) model, and a design based on a discrete-time multi-state (DTMS) model. We list alternative Bayesian dose-escalation rules and perform a simulation study for the intra-rule and inter-rule comparisons based on two statistical models to identify the most appropriate rule under certain scenarios. We provide evidence that all the Bayesian rules outperform the traditional ``3+3'' design in the allocation of patients and selection of the maximum tolerated dose. The design based on a time-to-DLT model uses patients' DLT information over multiple treatment cycles in estimating the probability of DLT at the end of treatment cycle 1. Dose-escalation decisions are made whenever a cycle-1 DLT occurs, or two months after the previous check point. Compared to the design based on a logistic regression model, the new design shows more safety benefits for trials in which more late-onset toxicities are expected. As a trade-off, the new design requires more patients on average. The design based on a discrete-time multi-state (DTMS) model has three important attributes: (1) Toxicities are categorized over a distribution of severity levels, (2) Early toxicity may inform dose escalation, and (3) No suspension is required between accrual cohorts. The proposed model accounts for the difference in the importance of the toxicity severity levels and for transitions between toxicity levels. We compare the operating characteristics of the proposed design with those from a similar design based on a fully-evaluated model that directly models the maximum observed toxicity level within the patients' entire assessment window. We describe settings in which, under comparable power, the proposed design shortens the trial. The proposed design offers more benefit compared to the alternative design as patient accrual becomes slower.

A nonparametric method of comparing the partial areas under two correlated receiver operating characteristic curves

A non-parametric method was developed and tested to compare the partial areas under two correlated Receiver Operating Characteristic curves. Based on the theory of generalized U-statistics the mathematical formulas have been derived for computing ROC area, and the variance and covariance between the portions of two ROC curves. A practical SAS application also has been developed to facilitate the calculations. The accuracy of the non-parametric method was evaluated by comparing it to other methods. By applying our method to the data from a published ROC analysis of CT image, our results are very close to theirs. A hypothetical example was used to demonstrate the effects of two crossed ROC curves. The two ROC areas are the same. However each portion of the area between two ROC curves were found to be significantly different by the partial ROC curve analysis. For computation of ROC curves with large scales, such as a logistic regression model, we applied our method to the breast cancer study with Medicare claims data. It yielded the same ROC area computation as the SAS Logistic procedure. Our method also provides an alternative to the global summary of ROC area comparison by directly comparing the true-positive rates for two regression models and by determining the range of false-positive values where the models differ. ^

Cyclin D1 mediates epithelial proliferation and links {\it ras\/} activation to the cell cycle

The studies presented in this thesis focus on two aspects of the involvement of cyclin D1 in epithelial proliferation. Since cyclin D1 has been identified as a target for genetic alterations and deregulation in a variety of human cancers, we studied cyclin D1 expression in two experimental models of epithelial carcinogenesis. These studies provided evidence that cyclin D1 was a potential target of the activating mutation of the Ha-ras gene characteristic of the experimental protocol. In addition, evidence from two independent in vitro models suggested that cyclin D1 was indeed part of the primary cellular response to activated ras, and at least partly responsible for the increase in proliferation observed in ras-transformed cells.^ Cyclin D1 has also been described as a key regulator of the passage through the G1 phase of the cell cycle. Cyclin D1 is induced in response to mitogens in a variety of cell lines, and cells engineered to overexpress cyclin D1 show accelerated G1 transit. In order to study the involvement of cyclin D1 in epithelial cell growth and differentiation, we generated transgenic mice that constitutively overexpress cyclin D1 in stratified epithelia. These mice developed thymic hyperplasia and skin hyperproliferation, providing in vivo evidence of the potential of cyclin D1 to regulate growth of epithelial cells. ^