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.

The angiotensin-converting enzyme insertion/deletion polymorphism and its associations with carotid artery wall thickness and coronary heart disease: The atherosclerosis risk in communities study

Coronary heart disease (CHD) is the leading cause of death in the United States. Recently, renin-angiotensin system (RAS) was found associated with atherosclerosis formation, with angiotensin II inducing vascular smooth muscle cell growth and migration, platelet activation and aggregation, and stimulation of plasminogen activator inhibitor-1. Angiotensin II is converted from angiotensin I by angiotensin I-converting enzyme (ACE) and this enzyme is mainly genetically determined. The ACE gene has been assigned to chromosome 17q23 and an insertion/deletion (I/D)polymorphism has been characterized by the presence/absence of a 287 bp fragment in intron 16 of the gene. The two alleles form three genotypes, namely, DD, ID and II and the DD genotype has been linked to higher plasma ACE levels and cell ACE activity.^ In this study, the association between the ACE I/D polymorphism and carotid artery wall thickness measured by B-mode ultrasound was investigated in a biracial sample, and the association between the gene and incident CHD was investigated in whites and if the gene-CHD association in whites, if any, was due to the gene effect on atherosclerosis. The study participants are from the prospective Atherosclerosis Risk in Communities (ARIC) Study, including adults aged 45 to 65 years. The present dissertation used a matched case-control design for studying the associations of the ACE gene with carotid artery atherosclerosis and an unmatched case-control design for the association of the gene with CHD. A significant recessive effect of the D allele on carotid artery thickness was found in blacks (OR = 3.06, 95% C.I: 1.11-8.47, DD vs. ID and II) adjusting for age, gender, cigarette smoking, LDL-cholesterol and diabetes. No similar associations were found in whites. The ACE I/D polymorphism is significantly associated with coronary heart disease in whites, and while stratifying data by carotid artery wall thickness, the significant associations were only observed in thin-walled subgroups. Assuming a recessive effect of the D allele, odds ratio was 2.84 (95% C.I:1.17-6.90, DD vs. ID and II) and it was 2.30 (95% C.I:1.22-4.35, DD vs. ID vs. II) assuming a codominant effect of the D allele. No significant associations were observed while comparing thick-walled CHD cases with thin-walled controls. Following conclusions could be drawn: (1) The ACE I/D polymorphism is unlikely to confer appreciable increase in the risk of carotid atherosclerosis in US whites, but may increases the risk of carotid atherosclerosis in blacks. (2) ACE I/D polymorphism is a genetic risk factor for incident CHD in US whites and this effect is separate from the chronic process of atherosclerosis development. Finally, the associations observed here are not causal, since the I/D polymorphism is in an intron, where no ACE proteins are encoded. ^

Exploring the role of viral infection in type 2 diabetes

Viral infection is known to play a role in type I diabetes, but there is a paucity of information on the role of viruses in type 2 diabetes. This research examined the seroprevalence of selected viruses in a group of predominantly Mexican-American patients with End Stage Renal Disease (ESRD). Using a case control design, patients with type 2 diabetes were compared with a group of non-diabetic controls. ^ One hundred and thirteen patients, 83 with type 2 diabetes and 30 controls without diabetes, underwent hemodialysis at the same chronic dialysis facility in San Antonio, Texas. AD subjects were tested for IgG, IgM, and neutralizing antibodies against Coxsackie B viruses (CBV), and IgG and IgM antibodies against cytomegalovirus (CMV) and parvovirus B19 (PVB19). Hepatitis B virus antigen (HBVAg), Hepatitis B virus antibody (HBVAb), Hepatitis C virus antibody (HCVAb), and Rubella (IgG) were also measured. A subset of 91 patients, 66 with diabetes and 25 controls, were tested bimonthly for six months. There was a significant difference (P = 0.04) in the seroprevalence of IgG antibodies to CMV between patients with type 2 diabetes (98%) and non-diabetic controls (87%) in the initial sample (OR = 6.2, 95% CI:1.1–36.0). A greater seroprevalence of CMV IgG antibodies was observed over the six month period among patients with type 2 diabetes (M) compared to controls (84%). This difference was also statistically (P < 0.03), with a greater odds ratio (OR = 12.4, 95% CI: 1.3–116.9), but with larger confidence interval related to the small number of subjects. However, when adjusted for age by logistic regression analysis there was no difference between the groups (OR = 1). ^ After one sample, there was a greater seroprevalence of HCVAb in the group without diabetes (28%), compared to those with type 2 diabetes (10%) (P = 0.04). This difference was no longer significant when adjusted for patient age. The prevalence of antibodies to PVB19, HBSAg, HBV, and Rubella was not significantly different in patients with type 2 diabetes and controls. There were significantly more vascular complications (P < 0.02) among patients with diabetes. ^ These results indicate that the significant associations observed in this population between viral infection with CMV, HCV, and type 2 diabetes are confounded by age. Accelerated atherosclerosis has been associated with age, diabetes, as well as CMV. Latent infection may be a factor that links these processes. ^

An innovative approach to impacting student academic achievement and attitudes: Pilot study of the HEADS UP Virtual Molecular Biology Lab

Objective. To evaluate the HEADS UP Virtual Molecular Biology Lab, a computer-based simulated laboratory designed to teach advanced high school biology students how to create a mouse model. ^ Design. A randomized clinical control design of forty-four students from two science magnet high schools in Mercedes, Texas was utilized to assess knowledge and skills of molecular laboratory procedures, attitudes towards science and computers as a learning tool, and usability of the program. ^ Measurements. Data was collected using five paper-and-pencil formatted questionnaires and an internal "lab notebook." ^ Results. The Virtual Lab was found to significantly increase student knowledge over time (p<0.005) and with each use (p<0.001) as well as positively increase attitudes towards computers (p<0.001) and skills (p<0.005). No significant differences were seen in science attitude scores.^ Conclusion. These results provide evidence that the HEADS UP Virtual Molecular Biology Lab is a potentially effective educational tool for high school molecular biology education.^

Alpha C protein of group B Streptococcus as a potential vaccine candidate

Group B Streptococcus (GBS) is a leading cause of life-threatening infection in neonates and young infants, pregnant women, and non-pregnant adults with underlying medical conditions. Immunization has theoretical potential to prevent significant morbidity and mortality from GBS disease. Alpha C protein (α C), found in 70% of non-type III capsule polysaccharide group B Streptococcus, elicits antibodies protective against α C-expressing strains in experimental animals and is an appealing carrier for a GBS conjugate vaccine. We determined whether natural exposure to α C elicits antibodies in women and if high maternal α C-specific serum antibody at delivery is associated with protection against neonatal disease. An ELISA was designed to measure α C-specific IgM and IgG in human sera. A case-control design (1:3 ratio) was used to match α C-expressing GBS colonized and non-colonized women by age and compare quantified serum α C-specific IgM and IgG. Sera also were analyzed from bacteremic neonates and their mothers and from women with invasive GBS disease. Antibody concentrations were compared using t-tests on log-transformed data. Geometric mean concentrations of α C-specific IgM and IgG were similar in sera from 58 α C strain colonized and 174 age-matched non-colonized women (IgG 245 and 313 ng/ml; IgM 257 and 229 ng/ml, respectively). Delivery sera from mothers of 42 neonates with GBS α C sepsis had similar concentrations of α C-specific IgM (245 ng/ml) and IgG (371 ng/ml), but acute sera from 13 women with invasive α C-expressing GBS infection had significantly higher concentrations (IgM 383 and IgG 476 ng/ml [p=0.036 and 0.038, respectively]). Convalescent sera from 5 of these women 16-49 days later had high α C-specific IgM and IgG concentrations (1355 and 4173 ng/ml, respectively). In vitro killing of α C-expressing GBS correlated with total α C-specific antibody concentration. Invasive disease but not colonization elicits α C-specific IgM and IgG in adults. Whether α C-specific IgG induced by vaccine would protect against disease in neonates merits further investigation. ^

The role of workplace absence as an organizational mechanism in predicting employee alcohol and drug disorders

Background. EAP programs for airline pilots in companies with a well developed recovery management program are known to reduce pilot absenteeism following treatment. Given the costs and safety consequences to society, it is important to identify pilots who may be experiencing an AOD disorder to get them into treatment. ^ Hypotheses. This study investigated the predictive power of workplace absenteeism in identifying alcohol or drug disorders (AOD). The first hypothesis was that higher absenteeism in a 12-month period is associated with higher risk that an employee is experiencing AOD. The second hypothesis was that AOD treatment would reduce subsequent absence rates and the costs of replacing pilots on missed flights. ^ Methods. A case control design using eight years (time period) of monthly archival absence data (53,000 pay records) was conducted with a sample of (N = 76) employees having an AOD diagnosis (cases) matched 1:4 with (N = 304) non-diagnosed employees (controls) of the same profession and company (male commercial airline pilots). Cases and controls were matched on the variables age, rank and date of hire. Absence rate was defined as sick time hours used over the sum of the minimum guarantee pay hours annualized using the months the pilot worked for the year. Conditional logistic regression was used to determine if absence predicts employees experiencing an AOD disorder, starting 3 years prior to the cases receiving the AOD diagnosis. A repeated measures ANOVA, t tests and rate ratios (with 95% confidence intervals) were conducted to determine differences between cases and controls in absence usage for 3 years pre and 5 years post treatment. Mean replacement costs were calculated for sick leave usage 3 years pre and 5 years post treatment to estimate the cost of sick leave from the perspective of the company. ^ Results. Sick leave, as measured by absence rate, predicted the risk of being diagnosed with an AOD disorder (OR 1.10, 95% CI = 1.06, 1.15) during the 12 months prior to receiving the diagnosis. Mean absence rates for diagnosed employees increased over the three years before treatment, particularly in the year before treatment, whereas the controls’ did not (three years, x = 6.80 vs. 5.52; two years, x = 7.81 vs. 6.30, and one year, x = 11.00cases vs. 5.51controls. In the first year post treatment compared to the year prior to treatment, rate ratios indicated a significant (60%) post treatment reduction in absence rates (OR = 0.40, CI = 0.28, 0.57). Absence rates for cases remained lower than controls for the first three years after completion of treatment. Upon discharge from the FAA and company’s three year AOD monitoring program, case’s absence rates increased slightly during the fourth year (controls, x = 0.09, SD = 0.14, cases, x = 0.12, SD = 0.21). However, the following year, their mean absence rates were again below those of the controls (controls, x = 0.08, SD = 0.12, cases, x¯ = 0.06, SD = 0.07). Significant reductions in costs associated with replacing pilots calling in sick, were found to be 60% less, between the year of diagnosis for the cases and the first year after returning to work. A reduction in replacement costs continued over the next two years for the treated employees. ^ Conclusions. This research demonstrates the potential for workplace absences as an active organizational surveillance mechanism to assist managers and supervisors in identifying employees who may be experiencing or at risk of experiencing an alcohol/drug disorder. Currently, many workplaces use only performance problems and ignore the employee’s absence record. A referral to an EAP or alcohol/drug evaluation based on the employee’s absence/sick leave record as incorporated into company policy can provide another useful indicator that may also carry less stigma, thus reducing barriers to seeking help. This research also confirms two conclusions heretofore based only on cross-sectional studies: (1) higher absence rates are associated with employees experiencing an AOD disorder; (2) treatment is associated with lower costs for replacing absent pilots. Due to the uniqueness of the employee population studied (commercial airline pilots) and the organizational documentation of absence, the generalizability of this study to other professions and occupations should be considered limited. ^ Transition to Practice. The odds ratios for the relationship between absence rates and an AOD diagnosis are precise; the OR for year of diagnosis indicates the likelihood of being diagnosed increases 10% for every hour change in sick leave taken. In practice, however, a pilot uses approximately 20 hours of sick leave for one trip, because the replacement will have to be paid the guaranteed minimum of 20 hour. Thus, the rate based on hourly changes is precise but not practical. ^ To provide the organization with practical recommendations the yearly mean absence rates were used. A pilot flies on average, 90 hours a month, 1080 annually. Cases used almost twice the mean rate of sick time the year prior to diagnosis (T-1) compared to controls (cases, x = .11, controls, x = .06). Cases are expected to use on average 119 hours annually (total annual hours*mean annual absence rate), while controls will use 60 hours. The cases’ 60 hours could translate to 3 trips of 20 hours each. Management could use a standard of 80 hours or more of sick time claimed in a year as the threshold for unacceptable absence, a 25% increase over the controls (a cost to the company of approximately of $4000). At the 80-hour mark, the Chief Pilot would be able to call the pilot in for a routine check as to the nature of the pilot’s excessive absence. This management action would be based on a company standard, rather than a behavioral or performance issue. Using absence data in this fashion would make it an active surveillance mechanism. ^

Epidemiology of allergic gastroenteritis in socio-culture perspective of rural Egypt

Diarrhea is a major public health problem in developing countries among infants and young children. Not all episodes of diarrhea are confirmed as infectious, suggesting alternate mechanisms. One such is immunoglobulin E (IgE) mediated or allergic diarrhea that can be seen in food allergy. In order to determine the relation between allergic gastroenteritis and feeding practice, a cohort of 152 infants were followed from birth to one year age in a rural community of Egypt between October, 1987 to April, 1988 were analyzed. In multivariate analysis of the data, statistically conclusive higher risk had been observed with presence of factors, like consumption of milk pudding (RR = 7.4, CI = 1.5-36.2 and p = 0.01), infant's age 3-6 months (RR = 7.7, CI = 1.3-45.9 and p = 0.02), infants whose mothers were vaccinated antenatally (RR = 3.1, CI = 1.3-7.0 and p = 1.3-7.0, p = 0.0) and wet-nursed infants (RR = 2.7, CI = 1.1-6.5 and p = 0.02). In contrast, infants who were completely breast-fed (RR = 0.13, CI = 0.02-0.6 and p = 0.01), and infants family owning a television set (RR = 0.29, CI = 0.1-0.6 and p = 0.0) were less likely to develop allergic gastroenteritis. The role of IgE on development of persistent diarrhea was also examined in a nested case-control design. Multivariate analysis revealed a significant association between detection of fecal IgE and development of persistent diarrhea compared to acute diarrhea (OR = 3.32, CI = 1.0-10.9 and p = 0.04) and health or non diarrhea (OR = 4.8, CI = 1.07-21.7 and p = 0.03) controls. ^

Predictors of HIV-1 slow progression among vertically infected children in Botswana

HIV-1 infected children display a highly variable rate of progression to AIDS. Data about reasons underlying the variable progression to AIDS among vertically-infected children is sparse, and the few studies that have examined this important question have almost exclusively been done in the developed world. This is despite the fact that Sub-Saharan Africa is home to over 90% of all HIV infected children around the world.^ The main objective of this study was to examine predictors of HIV-1 slow progression among vertically infected children in Botswana, using a case control design. Cases (slow progressors) and controls (rapid progressors) were drawn from medical records of HIV-1 infected children being followed up for routine care and treatment at the BBCCCOE between February 2003 and February 2011. Univariate and Multivariate Logistic Regression Analyses were performed to identify independent predictors of slow disease progression and control for confounding respectively. ^ The study population comprised of 152 cases and 201 controls with ages ranging from 6 months to 16 years at baseline. Low baseline HIV-1 RNA viral load was the strongest independent predictor of slow progression (adjusted OR = 5.52, 95% CI = 2.75-11.07; P <0.001). Other independent predictors of slow disease progression identified were: lack of history of PMTCT with single dose Nevirapine plus Zidovudine (adjusted OR = 4.45, 95% CI = 1.45-13.69; P = 0.009) and maternal vital status (alive) (adjusted OR = 2.46, 95% CI = 1.51-4.01; P < 0.00 ).^ The results of this study may help clinicians and policy-makers in resource-limited settings to identify, at baseline, which children are at highest risk of rapid progression to AIDS and thus prioritize them for immediate intervention with HAART and other measures that would mitigate disease progression. At the same time HAART may be delayed among children who are at lower risk of disease progression. This would enable the highly affected, yet impoverished, Sub-Saharan African countries to use their scarce resources more efficiently which may in turn ensure that their National Antiretroviral Therapy Programs become more sustainable. Delaying HAART among the low-risk children would also lower the occurrence of adverse drug reactions associated with antiretroviral drugs exposure.^ Keywords. Slow Progressors, Rapid Progressors, HIV-1, Predictors, Children, Vertical Transmission, Sub-Saharan Africa^

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.^