Nursing care challenges: homosexual psychiatric patients.

1. Stereotypes of homosexual behavior may negatively affect the nursing care for homosexual patients. Nurses must closely examine their attitudes toward homosexuals. To be able to provide quality care to homosexual patients, nurses must feel comfortable and fully aware of their own attitudes toward sexuality and homosexuality. 2. Nurses stand in a unique position to foster acceptance of homosexuality by assuming the advocacy role and addressing the stereotypes regarding homosexuality for both individual clients and the community. 3. Nurses need to provide an atmosphere of acceptance for homosexual patients by creating an environment where sexuality can be discussed in nonthreatening ways.     

Leveraging historical data into oncology development programs: Two case studies of phase 2 Bayesian augmented control trial designs

Leveraging historical data into the design and analysis of phase 2 randomized controlled trials can improve efficiency of drug development programs. Such approaches can reduce sample size without loss of power. Potential issues arise when the current control arm is inconsistent with historical data, which may lead to biased estimates of treatment efficacy, loss of power, or inflated type 1 error. Consideration as to how to borrow historical information is important, and in particular, adjustment for prognostic factors should be considered. This paper will illustrate two motivating case studies of oncology Bayesian augmented control (BAC) trials. In the first example, a glioblastoma study, an informative prior was used for the control arm hazard rate. Sample size savings were 15% to 20% by using a BAC design. In the second example, a pancreatic cancer study, a hierarchical model borrowing method was used, which enabled the extent of borrowing to be determined by consistency of observed study data with historical studies. Supporting Bayesian analyses also adjusted for prognostic factors. Incorporating historical data via Bayesian trial design can provide sample size savings, reduce study duration, and enable a more scientific approach to development of novel therapies by avoiding excess recruitment to a control arm. Various sensitivity analyses are necessary to interpret results. Current industry efforts for data transparency have meaningful implications for access to patient‐level historical data, which, while not critical, is helpful to adjust for potential imbalances in prognostic factors.     

A review and evaluation of the housing unit method of population estimation

"The housing unit (HU) method is used by public and private agencies throughout the United States to make local population estimates. This article describes many of the different types of data and techniques that can be used in applying the HU method, and it discusses the strengths and weaknesses of each. Empirical evidence from four different states is provided, comparing the accuracy of HU population estimates with the accuracy of other commonly used estimation techniques. Several conclusions are drawn regarding the usefulness of the HU method for local population estimation."