Patient Characteristics and Outcomes of Gastrointestinal Stromal Tumor Patients Undergoing Imatinib Plasma Level Testing

Although gastrointestinal stromal tumor (GIST) is effectively treated with imatinib, there are a number of clinical challenges in the optimal treatment of these patients. The plasma steady-state trough level of imatinib has been proposed to correlate with clinical outcome. Plasma imatinib level may be affected by a number of patient characteristics. Additionally, the ideal plasma trough concentration of imatinib is likely to vary based on the KIT genotype (genotype determines imatinib binding affinity) of the individual patient. Patients’ genotype or plasma imatinib level may influence the type and duration of response that is appreciable by clinical evaluation. The objectives of this study were to determine effects of genotype on the type of response appreciable by current imaging criteria, to determine the distribution of plasma imatinib levels in patients with GIST, to determine factors that correlate with plasma imatinib level, to determine the incremental effects of imatinib dose escalation; and to explore the median plasma levels and outcomes of patients with various KIT mutations. We therefore obtained KIT mutation information and analyzed CT response for size and density measurement of GISTs at baseline and within the first four moths of imatinib treatment. In 126 patients with metastatic/unresectable disease, the KIT genotype of patients’ tumor was significantly associated with unique response characteristics measurable by CT. Furthermore, hepatic and peritoneal metastases differed in their response characteristics. A subgroup of patients with KIT exon 9 mutation, who received higher doses of imatinib and experienced higher trough imatinib levels, experienced improved progression-free survival similar to that of KIT exon 11 patients. Therefore, we have found that imatinib plasma levels were higher in patients with elevated Aspartate amino transferase, were women, were older, or were being treated concomitantly with CYP450 substrate drugs. As expected, CYP450 inducers correlated with a lower plasma imatinib levels in GIST patients. Renal metabolism of imatinib accounts for <10%, so it was not included in the analysis but may affect covariates. Interestingly, there was a trend for low imatinib levels and inferior progression-free survival in patients who had undergone complete gastrectomy. Patients with KIT exon 9 mutation in our cohort received higher imatinib doses, experienced higher trough imatinib levels, and experienced a PFS similar to that of KIT exon 11 patients. In conclusion, imatinib plasma levels are influenced by a number of patient characteristics. The optimal imatinib plasma level for individual patients is not known but is an area of intense investigation. Our study confirms patients with KIT exon 9 mutations benefit from high-dose imatinib and higher trough imatinib levels.

Optimal, minimax, and Bayesian two-stage designs in two-dose phase II clinical trials

Background: For most cytotoxic and biologic anti-cancer agents, the response rate of the drug is commonly assumed to be non-decreasing with an increasing dose. However, an increasing dose does not always result in an appreciable increase in the response rate. This may especially be true at high doses for a biologic agent. Therefore, in a phase II trial the investigators may be interested in testing the anti-tumor activity of a drug at more than one (often two) doses, instead of only at the maximum tolerated dose (MTD). This way, when the lower dose appears equally effective, this dose can be recommended for further confirmatory testing in a phase III trial under potential long-term toxicity and cost considerations. A common approach to designing such a phase II trial has been to use an independent (e.g., Simon's two-stage) design at each dose ignoring the prior knowledge about the ordering of the response probabilities at the different doses. However, failure to account for this ordering constraint in estimating the response probabilities may result in an inefficient design. In this dissertation, we developed extensions of Simon's optimal and minimax two-stage designs, including both frequentist and Bayesian methods, for two doses that assume ordered response rates between doses. ^ Methods: Optimal and minimax two-stage designs are proposed for phase II clinical trials in settings where the true response rates at two dose levels are ordered. We borrow strength between doses using isotonic regression and control the joint and/or marginal error probabilities. Bayesian two-stage designs are also proposed under a stochastic ordering constraint. ^ Results: Compared to Simon's designs, when controlling the power and type I error at the same levels, the proposed frequentist and Bayesian designs reduce the maximum and expected sample sizes. Most of the proposed designs also increase the probability of early termination when the true response rates are poor. ^ Conclusion: Proposed frequentist and Bayesian designs are superior to Simon's designs in terms of operating characteristics (expected sample size and probability of early termination, when the response rates are poor) Thus, the proposed designs lead to more cost-efficient and ethical trials, and may consequently improve and expedite the drug discovery process. The proposed designs may be extended to designs of multiple group trials and drug combination trials.^