CLINICAL TRIAL ENROLLMENT IN A MULTIDISCIPLINARY PROSTATE CANCER

Purpose: Clinical oncology trials are hampered by low accrual rates. Less than 5% of adult cancer patients are treated on a clinical trial. We aimed to evaluate clinical trial enrollment in our Multidisciplinary Prostate Cancer Clinic and to assess if a clinical trial initiative, introduced in 2006, increased our trial enrollment.Methods: Prostate cancer patients with non-metastatic disease who were seen in the clinic from 2004 to 2008 were included in the analysis. Men were categorized by whether they were seen before or after the clinical trial enrollment initiative started in 2006. The initiative included posting trial details in the clinic, educating patients about appropriate clinical trial options during the treatment recommendation discussion, and providing patients with documentation of trials offered to them. Univariate and multivariate (MVA) logistic regression analysis evaluated the impact of patient characteristics and the clinical trial initiative on clinical trial enrollment.Results: The majority of the 1,370 men were white (83%), and lived within the surrounding counties or state (69.4%). Median age was 64.2 years. Seventy-three point five percent enrolled in at least one trial and 28.5% enrolled in more than one trial. Sixty-seven percent enrolled in laboratory studies, 18% quality of life studies, 13% novel studies, and 3.7% procedural studies. On MVA, men seen in later years (p < 0.0001) were more likely to enroll in trials. The proportion of men enrolling increased from 38.9% to 84.3% (p<0.0001) after the clinical trial initiative. On MVA, older men (p < 0.0001) were less likely to enroll in clinical trials. There was a trend toward men in the high-risk group being more likely to participate in clinical trials (p = 0.056). There was a second trend for men of Hispanic, Asian, Native American and Indian decent being less likely to participate in clinical trials (p = 0.054).Conclusion: Clinical trial enrollment in the multidisciplinary clinic increased after introduction of a clinical trial initiative. Older men were less likely to enroll in trials. We speculate we achieved high enrollment rates because 1) specific trials are discussed at time of treatment recommendations, 2) we provide a letter documenting offered trials and 3) we introduce patients to the research team at the same clinic visit if they are interested in trial participation.

Multilevel analysis for a longitudinal clinical trial

This study applies the multilevel analysis technique to longitudinal data of a large clinical trial. The technique accounts for the correlation at different levels when modeling repeated blood pressure measurements taken throughout the trial. This modeling allows for closer inspection of the remaining correlation and non-homogeneity of variance in the data. Three methods of modeling the correlation were compared. ^

Hepatitis B vaccination of high risk pregnant women: A clinical trial at Parkland Memorial Hospital

Hepatitis B infection is a major public health problem of global proportions. It is estimated that 2 billion people worldwide are infected by the Hepatitis B virus (HBV) at some point, and 350 million are chronic carriers. The Centers for Disease Control and Prevention (CDC) report an incidence in the United States of 140,000–320,000 infections each year (asymptomatic and symptomatic), and estimate 1–1.25 million people are chronically infected. Hepatitis B and its chronic complications (cirrhosis of the liver, liver failure, hepatocellular carcinoma) responsible for 4,000–5,000 deaths in America each year. ^ One quarter of those who become chronic carriers develop progressive liver disease, and chronic HBV infection is thought to be responsible for 60 million cases of cirrhosis worldwide, surpassing alcohol as a cause of liver disease. Since there are few treatment options for the person chronically infected with Hepatitis B, and what is available is expensive, prevention is clearly best strategy for combating this disease. ^ Since the approval of the Hepatitis B vaccine in 1981, national and international vaccination campaigns have been undertaken for the prevention of Hepatitis B. Despite encouraging results, however, studies indicate that prevalence rates of Hepatitis B infection have not been significantly reduced in certain high risk populations because vaccination campaigns targeting those groups do not exist and opportunities for vaccination by individual physicians in clinical settings are often missed. Many of the high-risk individuals who go unvaccinated are women of childbearing age, and a significant proportion of these women become infected with the Hepatitis B virus (HBV) during pregnancy. Though these women are often seen annually or for prenatal care (because of the close spacing of their children and their high rate of fertility), the Hepatitis B vaccine series is seldom recommended by their health care provider. In 1993, ACOG issued a statement recommending Hepatitis B vaccination of pregnant women who were defined as high-risk by diagnosis of a sexually transmitted disease. ^ Hepatitis B vaccine has been extensively studied in the non-pregnant population. The overall efficacy of the vaccine in infants, children and adults is greater than 90%. In the small clinical trials to date, the vaccine seemed to be effective in those pregnant women receiving 3 doses; however, by using the usual 0, 1 and 6 month regimen, most pregnant women were unable to complete a full series during pregnancy. There is data now available supporting the use of an "accelerated" dosing schedule at 0, 1 and 4 months. This has not been evaluated in pregnant women. A clinical trial proving the efficacy of the 0, 1, 4 schedule and its feasibility in this population would add significantly to the body of research in this area, and would have implications for public health policy. Such a trial was undertaken in the Parkland Memorial Hospital Obstetrical Infectious Diseases clinic. In this study, the vaccine was very well tolerated with no major adverse events reported, 90% of fully vaccinated patients achieved immunity, and only Body Mass Index (BMI) was found to be a significant factor affecting efficacy. This thesis will report the results of the trial and compare it to previous trials, and will discuss barriers to implementation, lessons learned and implications for future trials. ^

Body mass index trajectories and predictors among 3rd to 12th graders using growth curve mixture modeling the Child and Adolescent Trial for Cardiovascular Health (CATCH) study

This dissertation examined body mass index (BMI) growth trajectories and the effects of gender, ethnicity, dietary intake, and physical activity (PA) on BMI growth trajectories among 3rd to 12th graders (9-18 years of age). Growth curve model analysis was performed using data from The Child and Adolescent Trial for Cardiovascular Health (CATCH) study. The study population included 2909 students who were followed up from grades 3-12. The main outcome was BMI at grades 3, 4, 5, 8, and 12. ^ The results revealed that BMI growth differed across two distinct developmental periods of childhood and adolescence. Rate of BMI growth was faster in middle childhood (9-11 years old or 3rd - 5th grades) than in adolescence (11-18 years old or 5th - 12th grades). Students with higher BMI at 3rd grade (baseline) had faster rates of BMI growth. Three groups of students with distinct BMI growth trajectories were identified: high, average, and low. ^ Black and Hispanic children were more likely to be in the groups with higher baseline BMI and faster rates of BMI growth over time. The effects of gender or ethnicity on BMI growth differed across the three groups. The effects of ethnicity on BMI growth were weakened as the children aged. The effects of gender on BMI growth were attenuated in the groups with a large proportion of black and Hispanic children, i.e., “high” or “average” BMI trajectory group. After controlling for gender, ethnicity, and age at baseline, in the “high BMI trajectory”, rate of yearly BMI growth in middle childhood increased 0.102 for every 500 Kcals increase (p=0.049). No significant effects of percentage of energy from total fat and saturated fat on BMI growth were found. Baseline BMI increased 0.041 for every 30 minutes increased in moderate-to-vigorous PA (MVPA) in the “low BMI trajectory”, while Baseline BMI decreased 0.345 for every 30 minutes increased in vigorous PA (VPA) in the “high BMI trajectory”. ^ Childhood overweight and obesity interventions should start at the earliest possible ages, prior to 3rd grade and continue through grade school. Interventions should focus on all children, but specifically black and Hispanic children, who are more likely to be highest at-risk. Promoting VPA earlier in childhood is important for preventing overweight and obesity among children and adolescents. Interventions should target total energy intake, rather than only percentage of energy from total fat or saturated fat. ^

The heart challenge: The effect of regular aerobic exercise on body fat distribution in third and fourth grade school children: A randomized clinical trial

The pattern of body fat distribution known as "centralized", and characterized by a predominance of subcutaneous fat on the trunk and a "pot belly", has been associated with an increased risk of chronic disease. These patterns of fat distribution, as well as the lifestyle habit variables associated with adult fatness and chronic morbidity clearly begin to develop during childhood, indicating the need for intervention and primary prevention of obesity, particularly the centralized form, during childhood or adolescence. The purpose of this study was to determine whether regular aerobic exercise could beneficially alter the distribution of body fat in 8 and 9 year old children. One hundred and eighty-eight participants were randomized into either a regular aerobic exercise treatment group or a standard physical education program control group. A variety of aerobic activities was used for intervention 5 days per week during physical education class for a period of 12 weeks. Fat distribution was measured by a number of the most commonly used indices, including ratios of body circumferences and skinfolds and indices derived from a principal components analysis. Change over time in average pulse rate was used to determine if intervention actually occurred. Approximately 10% of the students were remeasured, allowing the calculation of intra- and interexaminer measurement reliability estimates for all indices.^ This study group was comparable to the U.S. population, though the study children were slightly larger for certain measures. No effect of the exercise intervention was found. The most likely explanation for this was inadequacy of the intervention, as indicated by the lack of any change in average pulse rate with treatment. The results of the measurement reliability analysis are reported and indicate that body circumference ratios are more precise than skinfold ratios, particularly when multiple observers are used. Reliability estimates for the principal component indices were also high.^ It remains unclear whether the distribution of body fat can be altered with exercise. It is likely that this issue will remain undecided until one highly reliable, valid, and sensitive measure of fat distribution can be found. ^

Adaptive clinical trial design for targeted therapy development

The development of targeted therapy involve many challenges. Our study will address some of the key issues involved in biomarker identification and clinical trial design. In our study, we propose two biomarker selection methods, and then apply them in two different clinical trial designs for targeted therapy development. In particular, we propose a Bayesian two-step lasso procedure for biomarker selection in the proportional hazards model in Chapter 2. In the first step of this strategy, we use the Bayesian group lasso to identify the important marker groups, wherein each group contains the main effect of a single marker and its interactions with treatments. In the second step, we zoom in to select each individual marker and the interactions between markers and treatments in order to identify prognostic or predictive markers using the Bayesian adaptive lasso. In Chapter 3, we propose a Bayesian two-stage adaptive design for targeted therapy development while implementing the variable selection method given in Chapter 2. In Chapter 4, we proposed an alternate frequentist adaptive randomization strategy for situations where a large number of biomarkers need to be incorporated in the study design. We also propose a new adaptive randomization rule, which takes into account the variations associated with the point estimates of survival times. In all of our designs, we seek to identify the key markers that are either prognostic or predictive with respect to treatment. We are going to use extensive simulation to evaluate the operating characteristics of our methods.^

A systematic review of community-based participatory research interventions in pediatric and adolescent populations

Background. Community-based participatory research (CBPR) is a collaborative approach to research actively involving community members in all aspects of the research process. CBPR is not a new research method, but an approach that has gained increased attention in the field of public health over the last several years. Recognition of the inequalities in health status associated with social and environmental factors have led to calls for a renewed focus on ecological approaches to research. Ecological approaches acknowledge that the health of the community is dependent on an interaction between behavioral and environmental factors affecting the entire population. While many published studies document the benefits of CBPR in difficult-to-reach populations and describe successful implementation of this approach in adult populations, relatively few studies have been conducted in child and adolescent populations. Given that children and adolescents are particularly sensitive to the effects of their physical environments and may also be distrustful of outsiders, ecological approaches involving the community as partners, such as CBPR, may be especially useful in this population. ^ Objective. This thesis reviews published studies using a community-based participatory research approach in children and adolescents to assess the appropriateness of this approach in this population. ^ Method. Studies using CBPR in youth populations were identified using Medline and other Internet searches through both MeSH heading and text-word searches. ^ Results. A total of 16 studies were identified and analyzed for this review. Nine of the sixteen studies were experimental or quasi-experimental design, with Asthma being the most commonly studied disease. ^ Conclusions. While many studies using CBPR were not conducted with the level of scientific rigor typically found in clinical trial research, the studies reviewed each contributed to a greater understanding of the problems they investigated. Furthermore, interventional studies provided lasting benefits to communities under study above what would be found in studies using more traditional research approaches. While CBPR may not be appropriate for all research situations due to the time and resources required, we conclude that is a useful approach and should be considered when conducting community-based research for pediatric and adolescent populations.^

A systematic review of personalized therapy in patients with advanced cancer

Background: An increased understanding of the pathogenesis of cancer at the molecular level has led to the development of personalized cancer therapy based on the mutation status of the tumor. Tailoring treatments to genetic signatures has improved treatment outcomes in patients with advanced cancer. We conducted a meta-analysis to provide a quantitative summary of the response to treatment on a phase I clinical trial matched to molecular aberration in patients with advanced solid tumors. ^ Methods: Original studies that reported the results of phase I clinical trials in patients with advanced cancer treated with matched anti-cancer therapies between January 2006 and November 2011 were identified through an extensive search of Medline, Embase, Web of Science and Cochrane Library databases. Odds Ratio (OR) with 95% confidence interval (CI) was estimated for each study to assess the strength of an association between objective response rate (ORR) and mutation status. Random effects model was used to estimate the pooled OR and their 95% CI was derived. Funnel plot was used to assess publication bias. ^ Results: Thirteen studies published between January 2006 and November 2011that reported on responses to matched phase I clinical trials in patients with advanced cancer were included in the meta-analysis. Nine studies reported on the responses seen in 538 of the 835 patients with driver mutations responsive to therapy and seven studies on the responses observed in 234 of the 306 patients with mutation predictive for negative response. Random effects model was used to estimate pooled OR, which was 7.767(95% CI = 4.199 − 14.366; p-value=0.000) in patients with activating mutations that were responsive to therapy and 0.287 (95% CI = 0.119 − 0.694; p-value=0.009) in patients with mutation predictive of negative response. ^ Conclusion: It is evident from the meta-analysis that somatic mutations present in tumor tissue of patients are predictive of responses to therapy in patients with advanced cancer in phase I setting. Plethora of research and growing evidence base indicate that selection of patients based on mutation analysis of the tumor and personalizing therapy is a step forward in the war against cancer.^

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.^

A RANDOMIZED TRIAL OF BILEVEL POSITIVE AIRWAY PRESSURE DEVICE AND HIGH FLOW OXYGEN FOR PERSISTENT DYSPNEA IN

Background: Dyspnea is a common and distressing symptom among patients with advanced cancer. The role of bilevel positive airway pressure (BIPAP) and Vapotherm in the relief of dyspnea have not been well defined. We aimed to determine and to compare the efficacy of BIPAP and VapoTherm for cancer related dyspnea. Methods: In this randomized, open-label, crossover study, we randomly assigned advanced cancer patients with persistent dyspnea >=3/10 to either Vapotherm for 2 hours followed by BiPAP for 2 hours, or BiPAP followed by Vaptherm. A variable washout period was instituted between interventions. The primary end point was change in numeric rating scale before and after each intervention. We planned to enroll 50 patients in total. Results: Among the 803 patients screened over the last 8 months, 62 (26%) were eligible, and 16 (2%) were enrolled so far. Five patients completed the entire study successfully, 4 discontinued the study prematurely due to prolonged relief of dyspnea, and 7 dropped out for various reasons, including inability to tolerate BiPAP (N=3), anxiety (N=2), fatigue (N=1) and pain requiring opioids (N=1). The median baseline numeric rating score for dyspnea was 7/10 (interquartile range (IQR) 5-8), and the median baseline Borg score was 4/10 (3-7). Interim analysis revealed that BiPAP was associated with a median change in numeric rating score of -3 (N=10, IQR -6.3 to -1, p=0.007) and modified Borg score of -1 (N=10, IQR -3 to 0.3, p=0.058), while Vapotherm was associated with a median change in numeric rating score of -2 (N=9, IQR -3 to -1, p=0.011) and modified Borg score of -2.5 (N=8, IQR -5.5 to -0.1, p=0.051). Among the 5 individuals who completed the entire study, 2 preferred Vapotherm, 2 favored BiPAP, and 1 liked both. The respiratory rate decreased and the oxygen saturation improved with both interventions. No significant toxicities were observed. Conclusions: We were successfully able to enroll patients onto this clinic trial. Our preliminary results suggest that BiPAP and Vapotherm are highly efficacious in providing relief for patients with persistent refractory dyspnea. A direct comparison of the two interventions will be done upon study completion. Further research is necessary to confirm our findings.

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.

An Innovative Phase I Trial Design Allowing for the Identification of Multiple Potential Maximum Tolerated Doses with Combination Therapy of Targeted Agents

Treatment for cancer often involves combination therapies used both in medical practice and clinical trials. Korn and Simon listed three reasons for the utility of combinations: 1) biochemical synergism, 2) differential susceptibility of tumor cells to different agents, and 3) higher achievable dose intensity by exploiting non-overlapping toxicities to the host. Even if the toxicity profile of each agent of a given combination is known, the toxicity profile of the agents used in combination must be established. Thus, caution is required when designing and evaluating trials with combination therapies. Traditional clinical design is based on the consideration of a single drug. However, a trial of drugs in combination requires a dose-selection procedure that is vastly different than that needed for a single-drug trial. When two drugs are combined in a phase I trial, an important trial objective is to determine the maximum tolerated dose (MTD). The MTD is defined as the dose level below the dose at which two of six patients experience drug-related dose-limiting toxicity (DLT). In phase I trials that combine two agents, more than one MTD generally exists, although all are rarely determined. For example, there may be an MTD that includes high doses of drug A with lower doses of drug B, another one for high doses of drug B with lower doses of drug A, and yet another for intermediate doses of both drugs administered together. With classic phase I trial designs, only one MTD is identified. Our new trial design allows identification of more than one MTD efficiently, within the context of a single protocol. The two drugs combined in our phase I trial are temsirolimus and bevacizumab. Bevacizumab is a monoclonal antibody targeting the vascular endothelial growth factor (VEGF) pathway which is fundamental for tumor growth and metastasis. One mechanism of tumor resistance to antiangiogenic therapy is upregulation of hypoxia inducible factor 1α (HIF-1α) which mediates responses to hypoxic conditions. Temsirolimus has resulted in reduced levels of HIF-1α making this an ideal combination therapy. Dr. Donald Berry developed a trial design schema for evaluating low, intermediate and high dose levels of two drugs given in combination as illustrated in a recently published paper in Biometrics entitled “A Parallel Phase I/II Clinical Trial Design for Combination Therapies.” His trial design utilized cytotoxic chemotherapy. We adapted this design schema by incorporating greater numbers of dose levels for each drug. Additional dose levels are being examined because it has been the experience of phase I trials that targeted agents, when given in combination, are often effective at dosing levels lower than the FDA-approved dose of said drugs. A total of thirteen dose levels including representative high, intermediate and low dose levels of temsirolimus with representative high, intermediate, and low dose levels of bevacizumab will be evaluated. We hypothesize that our new trial design will facilitate identification of more than one MTD, if they exist, efficiently and within the context of a single protocol. Doses gleaned from this approach could potentially allow for a more personalized approach in dose selection from among the MTDs obtained that can be based upon a patient’s specific co-morbid conditions or anticipated toxicities.

Bayesian doubly optimal group sequential designs for randomized clinical trials

When conducting a randomized comparative clinical trial, ethical, scientific or economic considerations often motivate the use of interim decision rules after successive groups of patients have been treated. These decisions may pertain to the comparative efficacy or safety of the treatments under study, cost considerations, the desire to accelerate the drug evaluation process, or the likelihood of therapeutic benefit for future patients. At the time of each interim decision, an important question is whether patient enrollment should continue or be terminated; either due to a high probability that one treatment is superior to the other, or a low probability that the experimental treatment will ultimately prove to be superior. The use of frequentist group sequential decision rules has become routine in the conduct of phase III clinical trials. In this dissertation, we will present a new Bayesian decision-theoretic approach to the problem of designing a randomized group sequential clinical trial, focusing on two-arm trials with time-to-failure outcomes. Forward simulation is used to obtain optimal decision boundaries for each of a set of possible models. At each interim analysis, we use Bayesian model selection to adaptively choose the model having the largest posterior probability of being correct, and we then make the interim decision based on the boundaries that are optimal under the chosen model. We provide a simulation study to compare this method, which we call Bayesian Doubly Optimal Group Sequential (BDOGS), to corresponding frequentist designs using either O'Brien-Fleming (OF) or Pocock boundaries, as obtained from EaSt 2000. Our simulation results show that, over a wide variety of different cases, BDOGS either performs at least as well as both OF and Pocock, or on average provides a much smaller trial. ^

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. ^