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.

Improving the accuracy of radiation pneumonitis dose response models

The prognosis for lung cancer patients remains poor. Five year survival rates have been reported to be 15%. Studies have shown that dose escalation to the tumor can lead to better local control and subsequently better overall survival. However, dose to lung tumor is limited by normal tissue toxicity. The most prevalent thoracic toxicity is radiation pneumonitis. In order to determine a safe dose that can be delivered to the healthy lung, researchers have turned to mathematical models predicting the rate of radiation pneumonitis. However, these models rely on simple metrics based on the dose-volume histogram and are not yet accurate enough to be used for dose escalation trials. The purpose of this work was to improve the fit of predictive risk models for radiation pneumonitis and to show the dosimetric benefit of using the models to guide patient treatment planning. The study was divided into 3 specific aims. The first two specifics aims were focused on improving the fit of the predictive model. In Specific Aim 1 we incorporated information about the spatial location of the lung dose distribution into a predictive model. In Specific Aim 2 we incorporated ventilation-based functional information into a predictive pneumonitis model. In the third specific aim a proof of principle virtual simulation was performed where a model-determined limit was used to scale the prescription dose. The data showed that for our patient cohort, the fit of the model to the data was not improved by incorporating spatial information. Although we were not able to achieve a significant improvement in model fit using pre-treatment ventilation, we show some promising results indicating that ventilation imaging can provide useful information about lung function in lung cancer patients. The virtual simulation trial demonstrated that using a personalized lung dose limit derived from a predictive model will result in a different prescription than what was achieved with the clinically used plan; thus demonstrating the utility of a normal tissue toxicity model in personalizing the prescription dose.

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.

Reduction of setup uncertainties and tumor motion in the radiation therapy of lung tumors

Because the goal of radiation therapy is to deliver a lethal dose to the tumor, accurate information on the location of the tumor needs to be known. Margins are placed around the tumor to account for variations in the daily position of the tumor. If tumor motion and patient setup uncertainties can be reduced, margins that account for such uncertainties in tumor location in can be reduced allowing dose escalation, which in turn could potentially improve survival rates. ^ In the first part of this study, we monitor the location of fiducials implanted in the periphery of lung tumors to determine the extent of non-gated and gated fiducial motion, and to quantify patient setup uncertainties. In the second part we determine where the tumor is when different methods of image-guided patient setup and respiratory gating are employed. In the final part we develop, validate, and implement a technique in which patient setup uncertainties are reduced by aligning patients based upon fiducial locations in projection images. ^ Results from the first part indicate that respiratory gating reduces fiducial motion relative to motion during normal respiration and setup uncertainties when the patients were aligned each day using externally placed skin marks are large. The results from the second part indicate that current margins that account for setup uncertainty and tumor motion result in less than 2% of the tumor outside of the planning target volume (PTV) when the patient is aligned using skin marks. In addition, we found that if respiratory gating is going to be used, it is most effective if used in conjunction with image-guided patient setup. From the third part, we successfully developed, validated, and implemented on a patient a technique for aligning a moving target prior to treatment to reduce the uncertainties in tumor location. ^ In conclusion, setup uncertainties and tumor motion are a significant problem when treating tumors located within the thoracic region. Image-guided patient setup in conjunction with treatment delivery using respiratory gating reduces these uncertainties in tumor locations. In doing so, margins around the tumor used to generate the PTV can be reduced, which may allow for dose escalation to the tumor. ^

Bayesian adaptive designs in early phase clinical trials

There are two practical challenges in the phase I clinical trial conduct: lack of transparency to physicians, and the late onset toxicity. In my dissertation, Bayesian approaches are used to address these two problems in clinical trial designs. The proposed simple optimal designs cast the dose finding problem as a decision making process for dose escalation and deescalation. The proposed designs minimize the incorrect decision error rate to find the maximum tolerated dose (MTD). For the late onset toxicity problem, a Bayesian adaptive dose-finding design for drug combination is proposed. The dose-toxicity relationship is modeled using the Finney model. The unobserved delayed toxicity outcomes are treated as missing data and Bayesian data augment is employed to handle the resulting missing data. Extensive simulation studies have been conducted to examine the operating characteristics of the proposed designs and demonstrated the designs' good performances in various practical scenarios.^

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

Commissioning an Anthropomorphic Spine and Lung Phantom for Remote Dose Verification of Institutions Participating in RTOG 0631

The RPC developed a new phantom to ensure comparable and consistent radiation administration in spinal radiosurgery clinical trials. This study assessed the phantom’s dosimetric and anatomic utility. The ‘spine phantom’ is a water filled thorax with anatomy encountered in spinal radiosurgery: target volume, vertebral column, spinal canal, esophagus, heart, and lungs. The dose to the target volume was measured with axial and sagittal planes of radiochromic film and thermoluminescent dosimeters (TLD). The dose distributions were measured with the radiochromic film calibrated to the absolute dose measured by the TLD. Four irradiations were administered: a four angle box plan, a seven angle conformal plan, a seven angle IMRT plan, and a nine angle IMRT plan (denoted as IMRT plan #1 and plan #2, respectively). In each plan, at least 95% of the defined tumor volume received 8 Gy. For each irradiation the planned and administered dose distributions were registered via pinpricks, and compared using point dose measurements, dose profiles, isodose distributions, and gamma analyses. Based on previous experience at the RPC, a gamma analysis was considering passing if greater than 95% of pixels passed the criteria of 5% dose difference and 3 mm distance-to-agreement. Each irradiation showed acceptable agreement in the qualitative assessments and exceeded the 95% passing rate at the 5% / 3 mm criteria, except IMRT plan #1, which was determined to have been poorly localized during treatment administration. The measured and planned dose distributions demonstrated acceptable agreement at the 5% / 3 mm criteria, and the spine phantom was determined to be a useful tool for the remote assessment of an institution’s treatment planning and dose delivery regimen.

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

Dose-response characteristics of methylphenidate on locomotor behavior and on sensory evoked potentials recorded from the VTA, NAc, and PFC in freely behaving rats.

BACKGROUND: Methylphenidate (MPD) is a psychostimulant commonly prescribed for attention deficit/hyperactivity disorder. The mode of action of the brain circuitry responsible for initiating the animals' behavior in response to psychostimulants is not well understood. There is some evidence that psychostimulants activate the ventral tegmental area (VTA), nucleus accumbens (NAc), and prefrontal cortex (PFC). METHODS: The present study was designed to investigate the acute dose-response of MPD (0.6, 2.5, and 10.0 mg/kg) on locomotor behavior and sensory evoked potentials recorded from the VTA, NAc, and PFC in freely behaving rats previously implanted with permanent electrodes. For locomotor behavior, adult male Wistar-Kyoto (WKY; n = 39) rats were given saline on experimental day 1 and either saline or an acute injection of MPD (0.6, 2.5, or 10.0 mg/kg, i.p.) on experimental day 2. Locomotor activity was recorded for 2-h post injection on both days using an automated, computerized activity monitoring system. Electrophysiological recordings were also performed in the adult male WKY rats (n = 10). Five to seven days after the rats had recovered from the implantation of electrodes, each rat was placed in a sound-insulated, electrophysiological test chamber where its sensory evoked field potentials were recorded before and after saline and 0.6, 2.5, and 10.0 mg/kg MPD injection. Time interval between injections was 90 min. RESULTS: Results showed an increase in locomotion with dose-response characteristics, while a dose-response decrease in amplitude of the components of sensory evoked field responses of the VTA, NAc, and PFC neurons. For example, the P3 component of the sensory evoked field response of the VTA decreased by 19.8% +/- 7.4% from baseline after treatment of 0.6 mg/kg MPD, 37.8% +/- 5.9% after 2.5 mg/kg MPD, and 56.5% +/- 3.9% after 10 mg/kg MPD. Greater attenuation from baseline was observed in the NAc and PFC. Differences in the intensity of MPD-induced attenuation were also found among these brain areas. CONCLUSION: These results suggest that an acute treatment of MPD produces electrophysiologically detectable alterations at the neuronal level, as well as observable, behavioral responses. The present study is the first to investigate the acute dose-response effects of MPD on behavior in terms of locomotor activity and in the brain involving the sensory inputs of VTA, NAc, and PFC neurons in intact, non-anesthetized, freely behaving rats previously implanted with permanent electrodes.

Acute and chronic methylphenidate dose-response assessment on three adolescent male rat strains.

Methylphenidate (MPD), commonly known as Ritalin, is the most frequently prescribed drug to treat children and adults with attention deficit hyperactivity disorder (ADHD). Adolescence is a period of development involving numerous neuroplasticities throughout the central nervous system (CNS). Exposure to a psychostimulant such as MPD during this crucial period of neurodevelopment may cause transient or permanent changes in the CNS. Genetic variability may also influence these differences. Thus, the objective of the present study was to determine whether acute and chronic administration of MPD (0.6, 2.5, or 10.0mg/kg, i.p.) elicit effects among adolescent WKY, SHR, and SD rats and to compare whether there were strain differences. An automated, computerized, open-field activity monitoring system was used to study the dose-response characteristics of acute and repeated MPD administration throughout the 11-day experimental protocol. Results showed that all three adolescent rat groups exhibited dose-response characteristics following acute and chronic MPD administration, as well as strain differences. These strain differences depended on the MPD dose and locomotor index. Chronic treatment of MPD in these animals did not elicit behavioral sensitization, a phenomenon described in adult rats that is characterized by the progressive augmentation of the locomotor response to repeated administration of the drug. These results suggest that the animal's age at time of drug treatment and strain/genetic variability play a crucial role in the acute and chronic effect of MPD and in the development of behavioral sensitization.

Using Acceptance and Commitment Therapy during Methadone Dose Reduction: Rationale, Treatment Description, and a Case Report.

Many clients who undergo methadone maintenance (MM) treatment for heroin and other opiate dependence prefer abstinence from methadone. Attempts at methadone detoxification are often unsuccessful, however, due to distressing physical as well as psychological symptoms. Outcomes from a MM client who voluntarily participated in an Acceptance and Commitment Therapy (ACT) - based methadone detoxification program are presented. The program consisted of a 1-month stabilization and 5-month gradual methadone dose reduction period, combined with weekly individual ACT sessions. Urine samples were collected twice weekly to assess for use of illicit drugs. The participant successfully completed the program and had favorable drug use outcomes during the course of treatment, and at the one-month and one-year follow-ups. Innovative behavior therapies, such as ACT, that focus on acceptance of the inevitable distress associated with opiate withdrawal may improve methadone detoxification outcomes.

Three-dimensional electron beam dose calculations

The MDAH pencil-beam algorithm developed by Hogstrom et al (1981) has been widely used in clinics for electron beam dose calculations for radiotherapy treatment planning. The primary objective of this research was to address several deficiencies of that algorithm and to develop an enhanced version. Two enhancements have been incorporated into the pencil-beam algorithm; one models fluence rather than planar fluence, and the other models the bremsstrahlung dose using measured beam data. Comparisons of the resulting calculated dose distributions with measured dose distributions for several test phantoms have been made. From these results it is concluded (1) that the fluence-based algorithm is more accurate to use for the dose calculation in an inhomogeneous slab phantom, and (2) the fluence-based calculation provides only a limited improvement to the accuracy the calculated dose in the region just downstream of the lateral edge of an inhomogeneity. The source of the latter inaccuracy is believed primarily due to assumptions made in the pencil beam's modeling of the complex phantom or patient geometry.^ A pencil-beam redefinition model was developed for the calculation of electron beam dose distributions in three dimensions. The primary aim of this redefinition model was to solve the dosimetry problem presented by deep inhomogeneities, which was the major deficiency of the enhanced version of the MDAH pencil-beam algorithm. The pencil-beam redefinition model is based on the theory of electron transport by redefining the pencil beams at each layer of the medium. The unique approach of this model is that all the physical parameters of a given pencil beam are characterized for multiple energy bins. Comparisons of the calculated dose distributions with measured dose distributions for a homogeneous water phantom and for phantoms with deep inhomogeneities have been made. From these results it is concluded that the redefinition algorithm is superior to the conventional, fluence-based, pencil-beam algorithm, especially in predicting the dose distribution downstream of a local inhomogeneity. The accuracy of this algorithm appears sufficient for clinical use, and the algorithm is structured for future expansion of the physical model if required for site specific treatment planning problems. ^

COMPARISON OF MEASUREMENTS OF ABSORBED DOSE TO WATER USING A WATER CALORIMETER AND IONIZATION CHAMBERS FOR CLINICAL RADIOTHERAPY PHOTON AND ELECTRON BEAMS

With the development of the water calorimeter direct measurement of absorbed dose in water becomes possible. This could lead to the establishment of an absorbed dose rather than an exposure related standard for ionization chambers for high energy electrons and photons. In changing to an absorbed dose standard it is necessary to investigate the effect of different parameters, among which are the energy dependence, the air volume, wall thickness and material of the chamber. The effect of these parameters is experimentally studied and presented for several commercially available chambers and one experimental chamber, for photons up to 25 MV and electrons up to 20 MeV, using a water calorimeter as the absorbed dose standard and the most recent formalism to calculate the absorbed dose with ion chambers.^ For electron beams, the dose measured with the calorimeter was 1% lower than the dose calculated with the chambers, independent of beam energy and chamber.^ For photon beams, the absorbed dose measured with the calorimeter was 3.8% higher than the absorbed dose calculated from the chamber readings. Such differences were found to be chamber and energy independent.^ The results for the photons were found to be statistically different from the results with the electron beams. Such difference could not be attributed to a difference in the calorimeter response. ^