CLINICAL TRIAL ENROLLMENT IN A MULTIDISCIPLINARY PROSTATE CANCER

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

Public service use by residents of Jackson Hinds Gardens before and after enrollment

Homelessness is associated with high use of public services such as health care and criminal justice services. Intervention designs to reverse homelessness have broadly fallen into two categories: either standard care which employs requisitely addressing the causes of homelessness, or housing first, which emphasizes provision of permanent housing without requisitely addressing the causes of homelessness. Multiple cities have recently commenced housing first interventions. Locally, Houston’s first housing first development is the Jackson Hinds Gardens project. The purpose of this study is to analyze the public service use of residents of housing first in Houston. Residents of Jackson Hinds Gardens who have been enrolled for at least 6 months were evaluated for public service use for an equal amount of time preceding and during their residence at Jackson Hinds. Resident interactions with county health services and criminal justice entities were determined by electronic database searches; these data were supplemented by life experience interview data. Service usage values pre- and post-enrollment at Jackson Hinds Gardens were compared by paired t-test analyses. We found that ER and inpatient usage decreased following enrollment in Jackson Hinds, although these reductions were not significant. In contrast, outpatient care and number of medications significantly increased following enrollment. These analyses inform on the effects of housing first in another major city, as well as informing the ethical considerations regarding housing first versus standard care. ^

When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students

In 1998, Texas initiated a bold new statewide university admission policy aimed at increasing college access for traditionally underserved students in the state. House Bill 588 (known as the Texas Top 10 Percent Plan (TTPP)) guaranteed automatic admission to the college or university of their choice for all top performing students in Texas public high schools. Fourteen years after the plan’s implementation, we see great strides and complexities in understanding student outcomes as a result of the percent plan. However, the legal controversy over the percent plan both in Texas and other states incorporating similar yet distinctly motivated alternative admissions plans continues to play out from institutional decision boards to the highest court in the nation. This study seeks to add to that discussion by exploring two questions. Descriptively, what are the admission and enrollment patterns within racial/ethnic groups of percent plan eligible students, over time, for Texas elite, emergent elite, and remaining public institutions? Given that all eligible percent plan students may enter the institution of choice in Texas, does which type of institution a TTPP student chooses relate to their race/ethnicity? The descriptive story told by the admission and enrollment distributions of equally eligible TTPP students is a complex but compelling one. Fundamentally, it identifies that statistically different application and enrollment patterns exist for Hispanic and especially African American TTPP beneficiaries relative to their White and Asian American counterparts.

Commentary on "When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students"

Invited commentary on "When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students" by Catherine Horn and Stella Flores.

A simulation study of the effects of small center enrollment in multi -center clinical trials

Multi-center clinical trials are very common in the development of new drugs and devices. One concern in such trials, is the effect of individual investigational sites enrolling small numbers of patients on the overall result. Can the presence of small centers cause an ineffective treatment to appear effective when treatment-by-center interaction is not statistically significant?^ In this research, simulations are used to study the effect that centers enrolling few patients may have on the analysis of clinical trial data. A multi-center clinical trial with 20 sites is simulated to investigate the effect of a new treatment in comparison to a placebo treatment. Twelve of these 20 investigational sites are considered small, each enrolling less than four patients per treatment group. Three clinical trials are simulated with sample sizes of 100, 170 and 300. The simulated data is generated with various characteristics, one in which treatment should be considered effective and another where treatment is not effective. Qualitative interactions are also produced within the small sites to further investigate the effect of small centers under various conditions.^ Standard analysis of variance methods and the "sometimes-pool" testing procedure are applied to the simulated data. One model investigates treatment and center effect and treatment-by-center interaction. Another model investigates treatment effect alone. These analyses are used to determine the power to detect treatment-by-center interactions, and the probability of type I error.^ We find it is difficult to detect treatment-by-center interactions when only a few investigational sites enrolling a limited number of patients participate in the interaction. However, we find no increased risk of type I error in these situations. In a pooled analysis, when the treatment is not effective, the probability of finding a significant treatment effect in the absence of significant treatment-by-center interaction is well within standard limits of type I error. ^