The effects of binge drinking on military readiness: The inability to deploy

The negative outcomes from alcohol misuse have been chronicled for decades in epidemiological studies. Recent research has focused on patterns of drinking. Binge and heavy drinking have been associated with multiple negative outcomes, to include surrogate outcomes designed to measure decrements to military readiness. This study is perhaps the first to examine whether binge or heavy drinking patterns are associated with the U.S. military’s overall inability to deploy rate or the individual reasons unable to deploy. ^ The prevalence of binge and heavy drinking and the inability to deploy rates were assessed from responses to the 2005 Department of Defense Survey of Health Related Behaviors Among Military Personnel. A secondary analysis of extant data resulted in a final sample size of 13,619 respondents who represented 847,253 active-duty military personnel. Multivariate models were fitted to examine the association between patterns of drinking and individual reasons for the inability to deploy. ^ Logistic regression showed no association of binge or heavy drinking to greater inability to deploy. Interestingly, individual reasons for the inability to deploy did show an association to include: Training, Dental Issue, No HIV Test, and Family Situation. There was no association noted for the individual reasons: Injury, Illness, Leave/Temporary Duty, or Other. Binge and heavy drinkers appear to be more susceptible to the psychosocial determinants than physical determinants as reasons for the inability to deploy. ^

Deployed military women: A second look at gender-specific infections

This descriptive, cross-sectional study addressed the relationship between variables of deployed military women and prevalence of gender-specific infections. The analysis of secondary data will look at the last deployment experience of 880 randomly selected U.S. military women who completed a mailed questionnaire (Deployed Female Health Practice Questionnaire (FHPQ)) in June 1998. The questionnaire contained 191 items with 80 data elements and one page for the subject's written comments. The broad categories of the questionnaire included: health practices, health promotion, disease prevention and treatment, reproduction, lifestyle management, military characteristics and demographics. The research questions are: (1) What is the prevalence of sexually transmitted diseases (STD), urinary tract infections (UTI) and vaginal infections (VI) related to demographic data, military characteristics, behavioral risk factors and health practices of military women during their last deployment? and (2) What are the differences between STD, UTI and VI related to the demographic data, military characteristics, behavioral risk factors and health practices of military women during their last deployment. The results showed that (1) STDs were found to be significantly associated with age and rank but not location of deployment or military branch; (2) UTI were found to be significantly associated with intrauterine device (IUD) use, prior UTI and type of items used for menses management, but not education or age; and (3) VI were significantly associated with age, rank and deployment location but not ethnicity or education. Although quantitative research exploring hygiene needs of deployed women continues, qualitative studies may uncover further “hidden” issues of importance. It cannot be said that the military has not made proactive changes for women, however, continued efforts to hone these changes are still encouraged. Mandatory debriefings of “seasoned” deployed women soldiers and their experiences would benefit leadership and newly deployed female soldiers with valuable “lessons learned.” Tailored hygiene education material, prevention education classes, easy access website with self-care algorithms, pre-deployment physicals, revision of military protocols for health care providers related to screening, diagnosing and treatment of gender-specific infections and process changes in military supply network of hygiene items for women are offered as recommendations. ^

The association between mental health and cigarette smoking in active duty military members

Previous research has shown an association between mental health status and cigarette smoking. This study examined four specific mental health predictors and the outcome variable any smoking, defined as smoking one or more cigarettes in the past 30 days. The population included active duty military members serving in the United States Army, Air Force, Navy and Marine Corps. The data was collected during the 2005 Department of Defense Survey of Health Related Behaviors Among Active Duty Military Personnel, a component of the Defense Lifestyle Assessment Program. The sample size included 13,603 subjects. This cross sectional prevalence study consisted of descriptive statistics, univariate analysis, and multivariate logistic regression analysis of the four mental health predictors and the any smoking outcome variable. Multivariate adjustment showed an association between the four mental health predictors and any smoking. This association is consistent with previous literature and can help guide public health officials in the development of smoking prevention and cessation programs.^

A new combined endpoint using U-statistic in analysis in clinical trials

Common endpoints can be divided into two categories. One is dichotomous endpoints which take only fixed values (most of the time two values). The other is continuous endpoints which can be any real number between two specified values. Choices of primary endpoints are critical in clinical trials. If we only use dichotomous endpoints, the power could be underestimated. If only continuous endpoints are chosen, we may not obtain expected sample size due to occurrence of some significant clinical events. Combined endpoints are used in clinical trials to give additional power. However, current combined endpoints or composite endpoints in cardiovascular disease clinical trials or most clinical trials are endpoints that combine either dichotomous endpoints (total mortality + total hospitalization), or continuous endpoints (risk score). Our present work applied U-statistic to combine one dichotomous endpoint and one continuous endpoint, which has three different assessments and to calculate the sample size and test the hypothesis to see if there is any treatment effect. It is especially useful when some patients cannot provide the most precise measurement due to medical contraindication or some personal reasons. Results show that this method has greater power then the analysis using continuous endpoints alone. ^

Ascertainment, meta-analysis and reporting of adverse reactions in clinical trials of antibiotics

The ascertainment and analysis of adverse reactions to investigational agents presents a significant challenge because of the infrequency of these events, their subjective nature and the low priority of safety evaluations in many clinical trials. A one year review of antibiotic trials published in medical journals demonstrates the lack of standards in identifying and reporting these potentially fatal conditions. This review also illustrates the low probability of observing and detecting rare events in typical clinical trials which include fewer than 300 subjects. Uniform standards for ascertainment and reporting are suggested which include operational definitions of study subjects. Meta-analysis of selected antibiotic trials using multivariate regression analysis indicates that meaningful conclusions may be drawn from data from multiple studies which are pooled in a scientifically rigorous manner. ^

Behavioral facets of cancer chemoprevention trials

Few studies have explored factors related to participation in cancer chemoprevention trials. The purpose of this dissertation was to conduct investigations in this emerging field by studying aspects of participation at three phases of cancer chemoprevention trials: at enrollment, during a placebo run-in period, and post-trial. In all three studies, subjects had a history of cancer and were at high risk of recurrence or second primary tumors.^ The first study explored correlates of enrollment in a head and neck cancer chemoprevention trial by comparing participants and eligible nonparticipants. Of 148 subjects who met the trial's preliminary eligibility criteria, 40% enrolled. In multivariate analysis, enrollment was positively associated with being male (OR 2.36) and being employed (OR 2.73). The most commonly cited reason for declining participation among nonparticipants was transportation.^ The second study examined outcomes of an eight-week placebo run-in period in a head and neck cancer chemoprevention trial. Of 391 subjects, 91.3% were randomized after the run-in. Adherence to drug capsules ranged from 0% to 120.3% (mean $\pm$ SD, 95.8% $\pm$ 15.1). In multivariate analysis, the main variable predicting run-in outcome was race; white subjects were 3.45 times more likely to be randomized than non-white subjects. Subjects with Karnofsky scores of 100 were 2.13 times more likely to be randomized than were subjects with lower scores.^ The third study used post-trial questionnaires to assess subjects' (n = 64) perceptions of participation in a cancer chemoprevention trial. The most highly rated trial benefit was the perception of potential colon cancer prevention, and the most troublesome barrier was erroneous billing for study visits. Perceived benefits were positively associated with interest in participating in future trials of the same (p = 0.05) and longer (p = 0.02) duration, and difficulty with trial pills and procedures was inversely related to interest in future placebo-controlled trials (p = 0.01).^ These are among the first behavioral studies to be completed in the rapidly growing field of cancer chemoprevention. Much work has yet to be done, however, to advance our understanding of the complex issues relating to chemoprevention trial participation. ^

PRETERM BIRTH AND OCCUPATIONAL PHYSICAL ACTIVITY: A CASE-CONTROL STUDY OF THE RELATIONSHIP BETWEEN LENGTH OF GESTATION AND THE PHYSICAL DEMAND OF U.S. ARMY MILITARY OCCUPATIONAL SPECIALTIES (UNITED STATES)

A case-control study has been conducted examining the relationship between preterm birth and occupational physical activity among U.S. Army enlisted gravidas from 1981 to 1984. The study includes 604 cases (37 or less weeks gestation) and 6,070 controls (greater than 37 weeks gestation) treated at U.S. Army medical treatment facilities worldwide. Occupational physical activity was measured using existing physical demand ratings of military occupational specialties.^ A statistically significant trend of preterm birth with increasing physical demand level was found (p = 0.0056). The relative risk point estimates for the two highest physical demand categories were statistically significant, RR's = 1.69 (p = 0.02) and 1.75 (p = 0.01), respectively. Six of eleven additional variables were also statistically significant predictors of preterm birth: age (less than 20), race (non-white), marital status (single, never married), paygrade (E1 - E3), length of military service (less than 2 years), and aptitude score (less than 100).^ Multivariate analyses using the logistic model resulted in three statistically significant risk factors for preterm birth: occupational physical demand; lower paygrade; and non-white race. Controlling for race and paygrade, the two highest physical demand categories were again statistically significant with relative risk point estimates of 1.56 and 1.70, respectively. The population attributable risk for military occupational physical demand was 26%, adjusted for paygrade and race; 17.5% of the preterm births were attributable to the two highest physical demand categories. ^

Bayesian adaptive designs for drug combinations in early phase clinical trials

Treating patients with combined agents is a growing trend in cancer clinical trials. Evaluating the synergism of multiple drugs is often the primary motivation for such drug-combination studies. Focusing on the drug combination study in the early phase clinical trials, our research is composed of three parts: (1) We conduct a comprehensive comparison of four dose-finding designs in the two-dimensional toxicity probability space and propose using the Bayesian model averaging method to overcome the arbitrariness of the model specification and enhance the robustness of the design; (2) Motivated by a recent drug-combination trial at MD Anderson Cancer Center with a continuous-dose standard of care agent and a discrete-dose investigational agent, we propose a two-stage Bayesian adaptive dose-finding design based on an extended continual reassessment method; (3) By combining phase I and phase II clinical trials, we propose an extension of a single agent dose-finding design. We model the time-to-event toxicity and efficacy to direct dose finding in two-dimensional drug-combination studies. We conduct extensive simulation studies to examine the operating characteristics of the aforementioned designs and demonstrate the designs' good performances in various practical scenarios.^

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.

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^

A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

Risk and resiliency: The untold story of youth in military families

Background: Risky sexual behaviors have been shown to increase the risk of unintended pregnancy and sexually transmitted infections (STIs) among youth. Youth in military families may be especially at risk for engaging in risky sexual behaviors because they are exposed to factors that are unique to the military culture, such as multiple relocations and parental deployment. However, data on sexual behaviors among military-dependent youth are limited and few studies have examined how these factors influence the sexual behaviors among youth. Purpose: The purpose of this dissertation was to estimate the prevalence of risky sexual behaviors among military-dependent youth and to describe how military factors may influence their sexual behaviors. Methods: Youth, aged 15–19 years, who attended a military health facility in the southern United States between June 2011 and September 2011 were recruited to complete a short, paper-based survey (N= 208, males and females) and to participate in an in-depth interview (N = 25, females). For quantitative data, prevalence estimates were computed and chi-square analyses were conducted. Logistic regression analyses were also conducted, adjusting for age, gender, and parents' duty status. For qualitative data, thematic coding of transcribed interviews was performed. Common and unique themes were examined across participants' experiences. Results: Over half of the youth was sexually experienced (53.7%). Parental deployment and number of relocations were significantly associated with having had sex in the past 3 months; however no significant associations were found between these military factors and other sexual behaviors. Although some youth felt that being a military-dependent had negatively impacted their sexual decisions, most believed the military experience had little influence on their sexual decisions. Most youth in military families also perceived having higher parental expectations to avoid risky behaviors, in general, than youth in civilian families. Conclusions: The majority of military-dependent youth are sexually experienced; however, individual and parental factors may have a greater role in sexual initiation among youth than military stressors do. The findings highlight the need for implementation of evidence-based strategies to prevent teen pregnancy and STIs at military installations. Future studies with larger sample sizes are needed to further explore how youth may cope with these military factors and the impact of parental factors on the sexual behaviors of youth.^

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 comparison of adherence with minocycline treatment in Parkinson's disease and rheumatoid arthritis clinical trials

Background: Little is known about the effects on patient adherence when the same study drug is administered in the same dose in two populations with two different diseases in two different clinical trials. The Minocycline in Rheumatoid Arthritis (MIRA) trial and the NIH Exploratory Trials in Parkinson's disease (NET-PD) Futility Study I provide a unique opportunity to do the above and to compare methods measuring adherence. This study may increase understanding of the influence of disease and adverse events on patient adherence and will provide insights to investigators selecting adherence assessment methods in clinical trials of minocycline and other drugs in future.^ Methods: Minocycline adherence by pill count and the effect of adverse events was compared in the MIRA and NET-PD FS1 trials using multivariable linear regression. Within the MIRA trial, agreement between assay and pill count was compared. The association of adverse events with assay adherence was examined using multivariable logistic regression.^ Results: Adherence derived from pill count in the MIRA and NET-PD FS1 trials did not differ significantly. Adverse events potentially related to minocycline did not appear useful to predict minocycline adherence. In the MIRA trial, adherence measured by pill count appears higher than adherence measured by assay. Agreement between pill count and assay was poor (kappa statistic = 0.25).^ Limitations: Trial and disease are completely confounded and hence the independent effect of disease on adherence to minocycline treatment cannot be studied.^ Conclusion: Simple pill count may be preferred over assay in the minocycline clinical trials to measure adherence. Assays may be less sensitive in a clinical setting where appointments are not scheduled in relation to medication administration time, given assays depend on many pharmacokinetic and instrument-related factors. However, pill count can be manipulated by the patient. Another study suggested that self-report method is more sensitive than pill count method in differentiating adherence from non-adherence. An effect of medication-related adverse events on adherence could not be detected.^