A simulation study of the standard design, the rolling six design, the CRM, and the modified CRM in Phase I clinical trials

The Phase I clinical trial is considered the "first in human" study in medical research to examine the toxicity of a new agent. It determines the maximum tolerable dose (MTD) of a new agent, i.e., the highest dose in which toxicity is still acceptable. Several phase I clinical trial designs have been proposed in the past 30 years. The well known standard method, so called the 3+3 design, is widely accepted by clinicians since it is the easiest to implement and it does not need a statistical calculation. Continual reassessment method (CRM), a design uses Bayesian method, has been rising in popularity in the last two decades. Several variants of the CRM design have also been suggested in numerous statistical literatures. Rolling six is a new method introduced in pediatric oncology in 2008, which claims to shorten the trial duration as compared to the 3+3 design. The goal of the present research was to simulate clinical trials and compare these phase I clinical trial designs. Patient population was created by discrete event simulation (DES) method. The characteristics of the patients were generated by several distributions with the parameters derived from a historical phase I clinical trial data review. Patients were then selected and enrolled in clinical trials, each of which uses the 3+3 design, the rolling six, or the CRM design. Five scenarios of dose-toxicity relationship were used to compare the performance of the phase I clinical trial designs. One thousand trials were simulated per phase I clinical trial design per dose-toxicity scenario. The results showed the rolling six design was not superior to the 3+3 design in terms of trial duration. The time to trial completion was comparable between the rolling six and the 3+3 design. However, they both shorten the duration as compared to the two CRM designs. Both CRMs were superior to the 3+3 design and the rolling six in accuracy of MTD estimation. The 3+3 design and rolling six tended to assign more patients to undesired lower dose levels. The toxicities were slightly greater in the CRMs.^

Study of tumor suppressor genes p53 and Rb in acute myelogenous leukemia

Loss of antiproliferative function of p53 by point mutation occurred frequently in various solid tumors. However, the genetic change of p53 by deletion or point mutation was a rare event (6%) in the cells of 49 AML patients analyzed by single-stranded conformation polymorphism and sequencing. Despite infrequent point mutation, abundant levels of p53 protein were detected in 75% of AML patients studied by immunoprecipitation with p53 specific antibodies. Furthermore, p53 protein in most cases had an altered conformation as analyzed by the reactivity to PAb240 which recognizes mutant p53; p53 protein in mitogen stimulated normal lymphocytes also had similar altered conformation. This altered conformation may be another mechanism for inactivation of p53 function in the growth stimulated environment. Some evidence indicated that posttranslational modification by phosphorylation may contribute to the conformational change of p53.^ Retinoblastoma (Rb) gene inactivation by deletion, rearrangement or mutation has also been implicated in many types of solid tumors. Our studies showed that absence or low levels of Rb protein were observed in more than 20% of AML patients at diagnosis, and the low levels of Rb correlated with shorter survival of patients. The absence of Rb protein was due to gene inactivation in some cases and to abnormal regulation of Rb expression in others. ^

Alterations in the ras oncogene and the p53 tumor suppressor gene in ultraviolet radiation-induced skin carcinogenesis

A rapid increase of the ultraviolet radiation (UVR)-related skin cancer incidence has attracted more and more public attention during the last few decades. Prevention and treatment of UVR-related skin cancer has become an important public health issue in the United States. Recent studies indicate that mutations in ras and/or p53 genes may be involved in UVR-induced skin tumor development but the precise molecular mechanism remains unclear. In this study, alterations of H-ras and p53 genes were investigated in different stages of carcinogenesis in a chronic UVR (solar simulator) exposure-induced Sencar mouse skin carcinogenesis model in order to clarify the role of the alterations of these genes during the skin carcinogenesis process and to further understand the mechanisms by which UVR causes skin cancer.^ Positive ras-p21 staining in cell membranes and cytosol were detected in 18/33 (55%) of squamous cell carcinomas (SCCs), but were not detected in UV-exposed skin, papillomas, or spindle cell tumors (SCTs). Positive staining of the malignant progression marker K13 was found in 17/33 (52%) of SCCs only. A significant positive correlation was observed between the K13 and the ras-p21 expression. Polymerase chain reaction (PCR)-based single strand conformation polymorphism (SSCP) analysis and gene sequencing analysis revealed three point mutations, one (codon 56) in UV-exposed non-tumor bearing skin and the other two (codons 21 and 13) in SCCs. No UV-specific mutation patterns were found.^ Positive p53 nuclear staining was found in 10/37 (27%) of SCCs and 12/24 (50%) of SCTs, but was not detected in normal skin or papillomas. PCR-based SSCP and sequencing analysis revealed eight point mutations in exons 5 and 6 (four in SCTs, two in SCCs, and two in UV-exposed skin) including six C-T or C-A transitions. Four of the mutations occurred at a dipyrimidine (CC) sequence. The pattern of the mutations indicated that the mutagenic lesions were induced by UVR.^ These results indicate that overexpression of ras-p21 in conjunction with aberrant expression of K13 occurred frequently in UVR-induced SCCs in Sencar mouse skin. The point mutation in the H-ras gene appeared to be a rare event in UVR skin carcinogenesis and may not be responsible for overexpression of ras-p21. UVR-induced P53 gene alteration is a frequent event in UVR-induced SCCs and later stage SCT tumors in Sencar mice skin, suggesting the p53 gene mutation plays an important role in skin tumor malignant progression. ^

Cellular dynamic simulator: an event driven molecular simulation environment for cellular physiology.

In this paper, we present the Cellular Dynamic Simulator (CDS) for simulating diffusion and chemical reactions within crowded molecular environments. CDS is based on a novel event driven algorithm specifically designed for precise calculation of the timing of collisions, reactions and other events for each individual molecule in the environment. Generic mesh based compartments allow the creation / importation of very simple or detailed cellular structures that exist in a 3D environment. Multiple levels of compartments and static obstacles can be used to create a dense environment to mimic cellular boundaries and the intracellular space. The CDS algorithm takes into account volume exclusion and molecular crowding that may impact signaling cascades in small sub-cellular compartments such as dendritic spines. With the CDS, we can simulate simple enzyme reactions; aggregation, channel transport, as well as highly complicated chemical reaction networks of both freely diffusing and membrane bound multi-protein complexes. Components of the CDS are generally defined such that the simulator can be applied to a wide range of environments in terms of scale and level of detail. Through an initialization GUI, a simple simulation environment can be created and populated within minutes yet is powerful enough to design complex 3D cellular architecture. The initialization tool allows visual confirmation of the environment construction prior to execution by the simulator. This paper describes the CDS algorithm, design implementation, and provides an overview of the types of features available and the utility of those features are highlighted in demonstrations.

Interim analysis of clinical trials: Simulation studies of fractional Brownian motion

Interim clinical trial monitoring procedures were motivated by ethical and economic considerations. Classical Brownian motion (Bm) techniques for statistical monitoring of clinical trials were widely used. Conditional power argument and α-spending function based boundary crossing probabilities are popular statistical hypothesis testing procedures under the assumption of Brownian motion. However, it is not rare that the assumptions of Brownian motion are only partially met for trial data. Therefore, I used a more generalized form of stochastic process, called fractional Brownian motion (fBm), to model the test statistics. Fractional Brownian motion does not hold Markov property and future observations depend not only on the present observations but also on the past ones. In this dissertation, we simulated a wide range of fBm data, e.g., H = 0.5 (that is, classical Bm) vs. 0.5< H <1, with treatment effects vs. without treatment effects. Then the performance of conditional power and boundary-crossing based interim analyses were compared by assuming that the data follow Bm or fBm. Our simulation study suggested that the conditional power or boundaries under fBm assumptions are generally higher than those under Bm assumptions when H > 0.5 and also matches better with the empirical results. ^

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^