Bayesian Adaptive Designs for Early Phase Clinical Trials

My dissertation focuses mainly on Bayesian adaptive designs for phase I and phase II clinical trials. It includes three specific topics: (1) proposing a novel two-dimensional dose-finding algorithm for biological agents, (2) developing Bayesian adaptive screening designs to provide more efficient and ethical clinical trials, and (3) incorporating missing late-onset responses to make an early stopping decision. Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as an example, we propose a phase I/II trial design to identify the biologically optimal dose combination (BODC), which is defined as the dose combination of the two agents with the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the dose-efficacy relationship. During the trial, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination. We propose a novel dose-finding algorithm to encourage sufficient exploration of untried dose combinations in the two-dimensional space. Extensive simulation studies show that the proposed design has desirable operating characteristics in identifying the BODC under various patterns of dose-toxicity and dose-efficacy relationships. Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Simulation studies show that the proposed design substantially outperforms the conventional multi-arm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while at the same time allocating substantially more patients to efficacious treatments. The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while at the same time providing higher power to identify the best treatment at the end of the trial. Phase II trial studies usually are single-arm trials which are conducted to test the efficacy of experimental agents and decide whether agents are promising to be sent to phase III trials. Interim monitoring is employed to stop the trial early for futility to avoid assigning unacceptable number of patients to inferior treatments. We propose a Bayesian single-arm phase II design with continuous monitoring for estimating the response rate of the experimental drug. To address the issue of late-onset responses, we use a piece-wise exponential model to estimate the hazard function of time to response data and handle the missing responses using the multiple imputation approach. We evaluate the operating characteristics of the proposed method through extensive simulation studies. We show that the proposed method reduces the total length of the trial duration and yields desirable operating characteristics for different physician-specified lower bounds of response rate with different true response rates.

Retrospective assesment of the levonorgestrel intrauterine device to treat complex atypical hyperplasia and early endometrioid endometrial cancer

Objective: The primary objective of this project was to describe the efficacy of the Levonorgestrel Intrauterine Device (LIUD) for treatment of Complex Endometrial Cancer (CAH) and Grade 1 Endometrial Cancer (G1EEC) in terms of rate of Complete Response (CR) and Partial Response (PR) after 6 months of therapy. Finally, we assessed if any clinical or pathologic features were associated with response to the LIUD. ^ Methods: This study was a retrospective case series designed to report the response rate of patients with CAH or G1EEC treated with LIUD therapy. In addition, this study has a laboratory component to assess molecular predictors of response to LIUD therapy. Retrospective data already collected from patients diagnosed with CAH or EEC grade 1 and treated with LIUD therapy at MD Anderson Cancer Center (MDACC) were used for this study. Patients from all ethnic and race groups were included. A Complete Response (CR) was defined in patients diagnosed with CAH if pathologic report at 6 months demonstrated either no evidence of hyperplasia or no atypia in the setting of simple or complex hyperplasia. Partial Response (PR) was recorded if disease downgraded to only CAH from G1EEC. No Response (NR) was recorded if pathologic report demonstrates no change (Stable Disease, SD) or progression to cancer (Progressive Disease, PD). We calculated the proportion of patients with complete response to LIUD therapy with 95% confidence interval. We compared the response rates (CR/PR vs NR) by obesity status (Obese if BMI > 40 kg/m2 vs non-obese if BMI <= 40 kg/m2) as well as other clinical and pathologic factors, such as age, uterine size (median size), and presence of exogenous progesterone effect. ^ Results: There were 39 patients diagnosed with either CAH or G1EEC treated with the LIUD. Of 39 patients, 12 did not have pathological results of biopsy at 6months time period. Of 27 evaluable patients, 17 were diagnosed with CAH and 10 with G1EEC. Overall response rate (RR) was 78% (95% CI = 62-94%) at 6 months, 18 patients had CR (4 in G1EEC; 14 in CAH), 3 patients had PR (3 in G1EEC), 3 had SD (1 in CAH; 2 in G1EEC), 3 had PD (2 in CAH; 1 in G1EEC). After histology stratification, RR at 6 months was 82.35% (14/17; 95%CI = 67.4-97.3%) in CAH and 70% (7/10; 95% CI = 41-98.4%) in G1EEC. ^ There was no difference in response (R) and no response (NR) based on BMI (p=0.56). He observed a trend showing association between age with response (p=0.1). There was no association between uterine size and response to therapy (p=0.17). We recorded strong association between exogenous progesterone effect and response. ^ Conclusion: LIUD therapy for the treatment of CAH and G1EEC may be effective and safe. Presence of exogenous progesterone effect may predict the response to LIUD therapy at earlier time points. There is need of further studies with larger sample size to explore the relationship of response with other clinical and pathologic factors^