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.

FDG-PET Intra-tratamiento como valor pronóstico en el tratamiento del linfoma Hodgkin

Introducción: La utilización de regímenes de tratamiento más individualizados requiere de mejores sistemas de estratificación temprana en Linfoma Hodgkin (LH). El estudio Tomografía por Emisión de Positrones utilizando 2-[18F] fluoro-2-deoxi-Dglucosa (FDG-PET) intra-tratamiento podría jugar un rol muy importante en esta evaluación. Objetivo: Determinar el valor pronóstico del FDG-PET intra-tratamiento en pacientes con LH para predecir sobrevida libre de progresión y sobrevida global. Material y método: El estudio fue llevado a cabo en el Servicio de Hematología del Hospital Central de Mendoza incluyendo pacientes con diagnóstico de LH confirmados por histología. De acuerdo al estadio y sitio de presentación, los pacientes recibieron quimioterapia sola o la combinación de radioterapia y quimioterapia, con el uso del esquema ABVD (adriamicina, bleomicina, vinblastina y dacarbazina) como protocolo estándar. Los estudios FDG-PET fueron practicados como parte de la evaluación intra-tratamiento y a la finalización. Resultados: En total fueron evaluados 8 pacientes, Sexo: F/M: 4/4, Edad: 18-58 años (Mediana: 29 años), Estadios: IIB:1, IIIA:2, IIIB:1, IVA:1, IVB:3, regiones nodales: 2-10 (Mediana:4), compromiso extranodal: 4/8, síntomas B: 5/8, enfermedad bulky 2/8 . Subtipos: Escleronodular: 6/8, Celularidad mixta: 1/8, Depleción linfocítica: 1/8. IPS: 1: 3/8 2: 3/8 3: 1/8 4: 0/8 ≥ 5: 1/8. Tratamientos: ABVD x 6: 6/8, ABVD x 6 + Radioterapia: 2/8. PET intermedio: 8/8 negativos (6/8 PET 3, 2/8 PET 2). PET final: 7/8 PET negativo, 1/8 PET positivo. Recaída: 1/8 (10° mes). Seguimiento: 11-37 meses (mediana de 24 meses). Discusión y Conclusiones: Al momento actual el FDG-PET intra-tratamiento demostró tener un importante valor predictivo negativo dado que todos los pacientes, menos uno, se encuentran en remisión completa sin progresión de enfermedad. Resta aún determinar el rol que esta herramienta pueda tener en el futuro en la terapia adaptada al riesgo de pacientes con LH.

Daily MODIS composites of thin-ice thickness and ice-surface temperatures for the Southern Weddell Sea

Based upon high-resolution thermal-infrared Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite imagery in combination with ERA-Interim atmospheric reanalysis data, we derived long-term polynya parameters such as polynya area, thin-ice thickness distribution and ice-production rates from daily cloud-cover corrected thin-ice thickness composites. Our study is based on a thirteen year investigation period (2002-2014) for the austral winter (1 April to 30 September) in the Antarctic Southern Weddell Sea. The focus lies on coastal polynyas which are important hot spots for new-ice formation, bottom-water formation and heat/moisture release into the atmosphere. MODIS has the capability to resolve even very narrow coastal polynyas. Its major disadvantage is the sensor limitation due to cloud cover. We make use of a newly developed and adapted spatial feature reconstruction scheme to account for cloud-covered areas. We find the sea-ice areas in front of Ronne and Brunt Ice Shelf to be the most active with an annual average polynya area of 3018 ± 1298 and 3516 ± 1420 km2 as well as an accumulated volume ice production of 31 ± 13 and 31 ± 12 km**3, respectively. For the remaining four regions, estimates amount to 421 ± 294 km**2 and 4 ± 3 km**3 (Antarctic Peninsula), 1148 ± 432 km**2 and 12 ± 5 km**3 (Iceberg A23A), 901 ± 703 km**2 and 10 ± 8 km**3 (Filchner Ice Shelf) as well as 499 ± 277 km**2 and 5 ± 2 km**3 (Coats Land). Our findings are discussed in comparison to recent studies based on coupled sea-ice/ocean models and passive-microwave satellite imagery, each investigating different parts of the Southern Weddell Sea.