A critical assessment of the National Institutes of Health Consensus Development Program against the eras which shaped it

This research study offers a critical assessment of NIH's Consensus Development Program (CDP), focusing upon its historical and valuative bases and its institutionalization in response to social and political forces. The analysis encompasses systems-level, as well as interpersonal factors in the adoption of consensus as the mechanism for resolving scientific controversies in clinical practice application. Further, the evolution of the CDP is also considered from an ecological perspective as a reasoned adaptation by NIH to pressures from its supporters and clients for translating biomedical research into medical practice. The assessment examines federal science policy and institutional designs for the inclusion of the public interest and democratic deliberation.^ The study relies on three distinct approaches to social research. Conventional historical methods were utilized in the interpretation of social and political influences across eras on the evolution of the National Institutes of Health and its response to demands for accountability and relevance through its Consensus Development Program. An embedded single-case study was utilized for an empirical examination of the CDP mechanism through five exemplar conferences. Lastly, a sociohistorical approach was taken to the CDP in order to consider its responsiveness to the values of the eras which created and shaped it. An exploration of organizational behavior with considerations for institutional reform as a response to continuing political and social pressure, it is a study of organizational birth, growth, and response to demands from its environment. The study has explanatory import in its attempt to account for the creation, timing, and form of the CDP, relative to political, institutional, and cultural pressures, and predictive import thorough its historical view which provides a basis for informed speculation on the playing out of tensions between extramural and intermural scientists and the current demands for health care reform. ^

A case-control study of bilateral compared with unilateral breast cancer

Approximately 10 to 15% of breast cancer patients develop a primary cancer in the contralateral breast. This study examined differences between women with unilateral compared with bilateral primary breast cancer. It focused on hormonal factors and family history, and evaluated the prevalences of invasive lobular histology and the replication error phenotype in the tumors. ^ Cases (n = 82) were patients at M.D. Anderson Cancer Center (MDACC) in Houston, Texas diagnosed with primary breast cancer in each breast between 1985 and 1994 inclusive. Controls (n = 82) were MDACC patients with primary cancer in a single breast diagnosed during the same interval, individually matched to cases. Data were obtained by in-person and/or telephone interview with the patient and/or proxy. Replication error phenotype was determined from archival tissue. ^ Diagnosis of breast, but not ovarian, cancer in a female first-degree relative (FFDR) was a strong risk factor for bilateral cancers. Cases had a significantly 3-fold higher excess of familial breast cancer than did controls (cases: O/E = 2.65, 95% CI = 1.85–3.69; controls: 0.86, 0.46–1.47; homogeneity: p = 0.00). Risk did not vary with menopausal status of the patient, but was greatest if a relative was diagnosed before age 45 (O/E = 38.9; 95% CI = 21.7–64.1). By implication, young first-degree relatives of patients with bilateral breast cancer are at very high risk of breast cancer themselves. Cases also had significantly fewer siblings than did controls. ^ Earlier menarche, and parity in the absence of lactation, were associated with bilateral cancers; age at menopause and parity with lactation were not. A history of alcohol consumption, particularly if heavy, carried a 3.4-fold risk (p = 0.03). The data suggested a slightly different pattern in risk factors according to menopausal status and interval between cancers. ^ Replication error phenotype was available for 59 probands. It was associated with bilateral cancers (particularly if diagnosed within one year of each other), increased age (p = 0.02) and negative nodal status. Invasive lobular histology was associated with bilateral disease but numbers were small. ^ These data suggest bilateral breast cancer arises in the context of a combination of familial and hormonal factors, and alcohol consumption. The relative importance of each factor may vary by age of the patient. ^

Case control study identifying the maternal risk factors for congenital syphilis in Texas: 1998--2001

Background. Congenital syphilis (CS) is the oldest recognized congenital infection in the world. CS infection can affect multiple organs and can even cause neonatal death. CS is largely preventable when maternal syphilis is treated in an adequate and timely manner. During the decade of the nineties, rates of CS in Texas have often exceeded the overall US rate. Few studies, with adequate sample sizes, have been conducted to determine the risk factors associated with CS while controlling for factors associated with adult (maternal) syphilis infection. Objective. To determine the current maternal risk factors for CS infection in Texas from 1998–2001. Methods. A total of 1083 women with positive serological tests for syphilis during pregnancy or at delivery were reported to, and assessed by, health department surveillance staff. Mothers delivering infants in Texas between January 1, 1998 and June 30, 2001 comprised the study population. Mothers of infants diagnosed with confirmed or presumptive CS (N = 291) were compared to mothers of infants diagnosed as non-cases (N = 792) to determine the risk factors for vertical transmission (while controlling for risk factors of horizontal transmission). Logistic regression analyses were conducted to determine the associated odds between selected maternal variables and the outcome of CS. Results. Among 291 case infants, 5 (1.7%), 12 (4.1%), 274 (94.2%) were classified as confirmed cases, syphilitic stillbirths, and presumptive cases, respectively. Lack of maternal syphilis treatment was the strongest predictor of CS: odds ratio (OR) = 199.57 (95% CI 83.45–477.25) compared to those receiving treatment before pregnancy, while women treated during their pregnancies were also at increased risk (OR = 6.67, 95% CI 4.01–11.08). Women receiving no prenatal care were more likely (OR = 2.77, 95% CI 1.60–4.79) to have CS infants than those receiving prenatal care. Single women had higher odds (OR = 1.90, 95% CI 1.10–3.26) than ever-married women. African-Americans (OR 0.91, 95% CI 0.37–2.23) and Hispanics (OR = 1.66, 95% CI 0.68–4.05) may be more likely to have a CS infant than non-Hispanic Whites. Conclusions. The burden of CS in Texas can be alleviated through the provision of quality health care services, particularly prenatal care and treatment for sexually transmitted diseases. ^

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.