Outcome-based adaptive randomization for binary data in clinical trials---Compare and contrast

Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^

Performance evaluation in Bayesian adaptive randomization

Bayesian adaptive randomization (BAR) is an attractive approach to allocate more patients to the putatively superior arm based on the interim data while maintains good statistical properties attributed to randomization. Under this approach, patients are adaptively assigned to a treatment group based on the probability that the treatment is better. The basic randomization scheme can be modified by introducing a tuning parameter, replacing the posterior estimated response probability, setting a boundary to randomization probabilities. Under randomization settings comprised of the above modifications, operating characteristics, including type I error, power, sample size, imbalance of sample size, interim success rate, and overall success rate, were evaluated through simulation. All randomization settings have low and comparable type I errors. Increasing tuning parameter decreases power, but increases imbalance of sample size and interim success rate. Compared with settings using the posterior probability, settings using the estimated response rates have higher power and overall success rate, but less imbalance of sample size and lower interim success rate. Bounded settings have higher power but less imbalance of sample size than unbounded settings. All settings have better performance in the Bayesian design than in the frequentist design. This simulation study provided practical guidance on the choice of how to implement the adaptive design. ^

Apply response adaptive randomization to group sequential with early stopping

Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.^

Volumetric and anatomical MRI for hypoxic-ischemic encephalopathy: relationship to hypothermia therapy and neurosensory impairments.

OBJECTIVE: To relate volumetric magnetic resonance imaging (MRI) findings to hypothermia therapy and neurosensory impairments. STUDY DESIGN: Newborns > or =36 weeks' gestation with hypoxic-ischemic encephalopathy who participated in the National Institute of Child Health and Human Development hypothermia randomized trial at our center were eligible. We determined the relationship between hypothermia treatment and usual care (control) to absolute and relative cerebral tissue volumes. Furthermore, we correlated brain volumes with death or neurosensory impairments at 18 to 22 months. RESULT: Both treatment groups were comparable before randomization. Total brain tissue volumes did not differ in relation to treatment assignment. However, relative volumes of subcortical white matter were significantly larger in hypothermia-treated than control infants. Furthermore, relative total brain volumes correlated significantly with death or neurosensory impairments. Relative volumes of the cortical gray and subcortical white matter also correlated significantly with Bayley Scales psychomotor development index. CONCLUSION: Selected volumetric MRI findings correlated with hypothermia therapy and neurosensory impairments. Larger studies using MRI brain volumes as a secondary outcome measure are needed.

Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

For-profit business safety interventions: A systematic, descriptive review of the literature

The purpose of this research was to determine if principles from organizational theory could be used as a framework to compare and contrast safety interventions developed by for-profit industry for the time period 1986–1996. A literature search of electronic databases and manual search of journals and local university libraries' book stacks was conducted for safety interventions developed by for-profit businesses. To maintain a constant regulatory environment, the business sectors of nuclear power, aviation and non-profits were excluded. Safety intervention evaluations were screened for scientific merit. Leavitt's model from organization theory was updated to include safety climate and renamed the Updated Leavitt's Model. In all, 8000 safety citations were retrieved, 525 met the inclusion criteria, 255 met the organizational safety intervention criteria, and 50 met the scientific merit criteria. Most came from non-public health journals. These 50 were categorized by the Updated Leavitt's Model according to where within the organizational structure the intervention took place. Evidence tables were constructed for descriptive comparison. The interventions clustered in the areas of social structure, safety climate, the interaction between social structure and participants, and the interaction between technology and participants. No interventions were found in the interactions between social structure and technology, goals and technology, or participants and goals. Despite the scientific merit criteria, many still had significant study design weaknesses. Five interventions tested for statistical significance but none of the interventions commented on the power of their study. Empiric studies based on safety climate theorems had the most rigorous designs. There was an attempt in these studies to address randomization amongst subjects to avoid bias. This work highlights the utility of using the Updated Leavitt's Model, a model from organizational theory, as a framework when comparing safety interventions. This work also highlights the need for better study design of future trials of safety interventions. ^

Yoga off the mat: How far and to whom do the benefits extend?

At least 15 million American adults have participated in yoga at least once in their lifetime (Saper, Eisenberg, Davis, Culpepper, & Phillips, 2004). The field of yoga research is relatively new in the United States, and the majority of studies have concentrated on yoga's effect on measures of physiology (cardiovascular disease, diabetes, obesity) or psychological measures of stress and anxiety. This review attempted to identify studies that had been conducted measuring a different set of outcome measures, specifically violence, trauma, eating, and other behavioral disorders. In 9 of 10 studies reviewed, researchers observed statistically significant effects of yoga interventions. Effects were most evident within multifaceted studies that combined intensive yoga practice with group discussion and training. Only one group (Mitchell, Mazzeo, Rausch, & Cooke, 2007) failed to observe any significant differences between yoga practice groups and control groups. Effects were seen in both sexes, although a majority of the studies were aimed specifically at women. All studies were limited by small sample size and lack of follow-up data. Future research should seek to increase sample size, to diversify recruitment to allow for the randomization of treatment and control groups, and to allow for long-term follow-up.^

Factors contributing to the attrition of women in the African-American Nutrition for Life study

Background. There is currently a push to increase the number of minorities in cancer clinical trials in an effort to reduce cancer health disparities. Overcoming barriers to clinical trial research for minorities is necessary if we are to achieve the goals of Healthy People 2010. To understand the unexpectedly high rate of attrition in the A NULIFE study, the research team examined the perceived barriers to participation among minority women. The purpose of this study was to determine if either personal or study-related factors influenced healthy pre-menopausal women aged 25-45 years to terminate their participation in the A NULIFE Study. We hypothesized that personal factors were the driving forces for attrition rates in the prevention trial.^ Methods. The target population consisted of eligible women who consented to the A NULIFE study but withdrew prior to being randomized (N= 46), as well as eligible women who completed the informed consent process for the A NULIFE study and withdrew after randomization (N= 42). Examination of attrition rates in this study occurred at a time point when 10 out of 12 participant groups had completed the A NULIFE study. Data involving the 2 groups that were actively engaged in study activities were not used in this analysis. A survey instrument was designed to query the personal and study-related factors that were believed to have contributed to the decision to terminate participation in the A NULIFE study.^ Results. Overall, the highest ranked personal reason that influenced withdrawal from the study was being “too busy” with other obligations. The second highest ranked factor for withdrawal was work obligations. Whereas, more than half of all participants agreed that they were well-informed about the study and considered the study personnel to be approachable, 54% of participants would have been inclined to remain in the study if it were located at a local community center.^ Conclusions. Time commitment was likely a major factor for withdrawal from the A NULIFE study. Future investigators should implement trials within participant communities where possible. Also, focus group settings may provide detailed insight into factors that contribute to the attrition of minorities in cancer clinical trials.^

Increasing awareness of colorectal cancer screening through targeted exam room based video messages

Colorectal cancer (CRC) is the third largest cause of cancer death in the United States. While the disease burden is high, there are proven methods to screen for CRC and detect it at a stage that is amenable to cure. Patients with low health literacy have difficulty navigating the health care system and are at increased risk to not receive preventive care services such as colorectal cancer screening (CRCS). To address this need, an exam-room based video was developed to be played for patients in the privacy of the exam room, while they are waiting to be seen by their medical provider. In roughly 2 minutes, the video informs the patient about CRC and CRCS and how they can successfully complete CRCS. One of the key barriers to completing CRCS is the need to increase patients' knowledge and improve attitudes surrounding CRCS. This study examines the impact of the video on patients' knowledge and attitudes about CRC and CRCS in a medically underserved patient population in Houston, Texas. ^ Sixty-one patients presenting for routine medical care were enrolled in the study. Depending on their randomization, the patients either received routine information about CRC and CRCS or they watched the video. We found that the patients who did watch the video did have improvements in their knowledge and improved attitudes about CRC and CRCS. Future studies will be needed to examine whether the video improves the patients' completion of CRCS.^

Bisphosphonates for metastatic bone disease in lung cancer

Bisphosphonates have proven effectiveness in preventing skeletal-related events (SREs) in advanced breast cancer, prostate cancer and multiple myeloma. The purpose of this study was to assess efficacy of bisphosphonates in preventing SREs, in controlling pain, and in increasing life expectancy in lung cancer patients with bone metastases.^ We performed an electronic search in MEDLINE, EMBASE, Web of Science, and Cochrane library databases up to April 4, 2010. Hand searching and searching in clinicaltrials.gov were also performed. Two independent reviewers selected all clinical trials that included lung cancer patients with bone metastases treated with bisphosphonates. We excluded articles that involved cancers other than lung, patients without bone metastasis and treatment other than bisphosphonates. Outcome questions answered were efficacy measured as overall pain control, overall improvement in survival and reduction in skeletal-related events or SREs (fracture, cord compression, radiation or surgery to the bone, hypercalcemia of malignancy). The quality of each study was evaluated using the Cochrane Back Review group questionnaire to assess risk of bias (0-worst to 11-best). Data extraction and quality assessments were independently performed by two assessors. Meta-analyses were performed where more than one study with similar outcomes were found.^ We identified eight trials that met our inclusion criteria. Three studies evaluated zoledronic acid, three pamidronate, three clodronate and two ibandronate. Two were placebocontrol trials while two had multi-group comparisons (radiotherapy, radionucleotides, and chemotherapy) and two had different bisphosphonate as active controls. Quality scores ranged from 1-4 out of 11 suggesting high risk of bias. Studies failed to report adequate explanation of randomization procedures, concealment of randomization and blinding. Metaanalysis showed that patients treated with zoledronic acid alone had lower rates of developing SREs compared to placebo at 21 months (RR=0.80, 95% CI=0.66-0.97, p=0.02). Meta-analyses also showed increased pain control when a bisphosphonate was added to the existing treatment modality like chemotherapy or radiation (RR=1.17, 95% CI=1.03-1.34, p=0.02). However, pain control was not statistically significantly different among various bisphosphonates when other treatment modalities were not present. Despite improvement in SRE and pain control, bisphosphonates failed to show improvement in overall survival (Difference in means=109.1 days, 95% CI= -51.52 – 269.71, p=0.183).^ Adding biphosphonates to standard care improved pain control and reduced SREs. Biphosphonates did not improve overall survival. Further larger studies with higher quality are required to stengthen the evidence.^ Keywords/MeSH terms Bisphosphonates/diphosphonates: generic, chemical and trade names.^

On Bayesian seamless phase I-II designs

Early phase clinical trial designs have long been the focus of interest for clinicians and statisticians working in oncology field. There are several standard phse I and phase II designs that have been widely-implemented in medical practice. For phase I design, the most commonly used methods are 3+3 and CRM. A newly-developed Bayesian model-based mTPI design has now been used by an increasing number of hospitals and pharmaceutical companies. The advantages and disadvantages of these three top phase I designs have been discussed in my work here and their performances were compared using simulated data. It was shown that mTPI design exhibited superior performance in most scenarios in comparison with 3+3 and CRM designs. ^ The next major part of my work is proposing an innovative seamless phase I/II design that allows clinicians to conduct phase I and phase II clinical trials simultaneously. Bayesian framework was implemented throughout the whole design. The phase I portion of the design adopts mTPI method, with the addition of futility rule which monitors the efficacy performance of the tested drugs. Dose graduation rules were proposed in this design to allow doses move forward from phase I portion of the study to phase II portion without interrupting the ongoing phase I dose-finding schema. Once a dose graduated to phase II, adaptive randomization was used to randomly allocated patients into different treatment arms, with the intention of more patients being assigned to receive more promising dose(s). Again simulations were performed to compare the performance of this innovative phase I/II design with a recently published phase I/II design, together with the conventional phase I and phase II designs. The simulation results indicated that the seamless phase I/II design outperform the other two competing methods in most scenarios, with superior trial power and the fact that it requires smaller sample size. It also significantly reduces the overall study time. ^ Similar to other early phase clinical trial designs, the proposed seamless phase I/II design requires that the efficacy and safety outcomes being able to be observed in a short time frame. This limitation can be overcome by using validated surrogate marker for the efficacy and safety endpoints.^

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.^

Instrumental variable method for the causal relationship between soluble receptor for advanced glycation end-products (sRAGE) and risk of pancreatic cancer

This thesis project is motivated by the potential problem of using observational data to draw inferences about a causal relationship in observational epidemiology research when controlled randomization is not applicable. Instrumental variable (IV) method is one of the statistical tools to overcome this problem. Mendelian randomization study uses genetic variants as IVs in genetic association study. In this thesis, the IV method, as well as standard logistic and linear regression models, is used to investigate the causal association between risk of pancreatic cancer and the circulating levels of soluble receptor for advanced glycation end-products (sRAGE). Higher levels of serum sRAGE were found to be associated with a lower risk of pancreatic cancer in a previous observational study (255 cases and 485 controls). However, such a novel association may be biased by unknown confounding factors. In a case-control study, we aimed to use the IV approach to confirm or refute this observation in a subset of study subjects for whom the genotyping data were available (178 cases and 177 controls). Two-stage IV method using generalized method of moments-structural mean models (GMM-SMM) was conducted and the relative risk (RR) was calculated. In the first stage analysis, we found that the single nucleotide polymorphism (SNP) rs2070600 of the receptor for advanced glycation end-products (AGER) gene meets all three general assumptions for a genetic IV in examining the causal association between sRAGE and risk of pancreatic cancer. The variant allele of SNP rs2070600 of the AGER gene was associated with lower levels of sRAGE, and it was neither associated with risk of pancreatic cancer, nor with the confounding factors. It was a potential strong IV (F statistic = 29.2). However, in the second stage analysis, the GMM-SMM model failed to converge due to non- concaveness probably because of the small sample size. Therefore, the IV analysis could not support the causality of the association between serum sRAGE levels and risk of pancreatic cancer. Nevertheless, these analyses suggest that rs2070600 was a potentially good genetic IV for testing the causality between the risk of pancreatic cancer and sRAGE levels. A larger sample size is required to conduct a credible IV analysis.^