Bayesian Methods in Human Drug and Biological Products Development in CDER and CBER.

The Center for Drug Evaluation and Research (CDER) and the Center for Biologics Evaluation and Research (CBER) of the U.S. Food and Drug Administration (FDA) have been leaders in protecting and promoting the U.S. public health by helping to ensure that safe and effective drugs and biological products are available in the United States for those who need them. The null hypothesis significance testing approach, along with other considerations, is typically used to demonstrate the effectiveness of a drug or biological product. The Bayesian framework presents an alternative approach to demonstrate the effectiveness of a treatment. This article discusses the Bayesian framework for drug and biological product development, highlights key settings in which Bayesian approaches may be appropriate, and provides recent examples of the use of Bayesian approaches within CDER and CBER.

Comparison of confidence interval methods for an intra-class correlation coefficient (ICC).

BACKGROUND: The intraclass correlation coefficient (ICC) is widely used in biomedical research to assess the reproducibility of measurements between raters, labs, technicians, or devices. For example, in an inter-rater reliability study, a high ICC value means that noise variability (between-raters and within-raters) is small relative to variability from patient to patient. A confidence interval or Bayesian credible interval for the ICC is a commonly reported summary. Such intervals can be constructed employing either frequentist or Bayesian methodologies. METHODS: This study examines the performance of three different methods for constructing an interval in a two-way, crossed, random effects model without interaction: the Generalized Confidence Interval method (GCI), the Modified Large Sample method (MLS), and a Bayesian method based on a noninformative prior distribution (NIB). Guidance is provided on interval construction method selection based on study design, sample size, and normality of the data. We compare the coverage probabilities and widths of the different interval methods. RESULTS: We show that, for the two-way, crossed, random effects model without interaction, care is needed in interval method selection because the interval estimates do not always have properties that the user expects. While different methods generally perform well when there are a large number of levels of each factor, large differences between the methods emerge when the number of one or more factors is limited. In addition, all methods are shown to lack robustness to certain hard-to-detect violations of normality when the sample size is limited. CONCLUSIONS: Decision rules and software programs for interval construction are provided for practical implementation in the two-way, crossed, random effects model without interaction. All interval methods perform similarly when the data are normal and there are sufficient numbers of levels of each factor. The MLS and GCI methods outperform the NIB when one of the factors has a limited number of levels and the data are normally distributed or nearly normally distributed. None of the methods work well if the number of levels of a factor are limited and data are markedly non-normal. The software programs are implemented in the popular R language.

Depression, cortisol, and suppressed cell-mediated immunity in metastatic breast cancer.

Cancer treatment is known to have significant immuno-suppressive/dysregulatory effects. Psychological distress and depression, which often accompany cancer diagnosis and treatment, can also suppress or dysregulate endocrine and immune function. Cell-mediated immunity (CMI) is critical for protection against a host of pathogens to which cancer patients may be particularly susceptible. CMI is also important for defense against some tumors. This study explored relationships among depressive symptoms, cortisol secretion, and CMI responses in 72 women with metastatic breast cancer. Depressive symptoms were assessed with the Center for Epidemiologic Studies-Depression Scale (CES-D). Saliva was sampled throughout the day over a 3-day period to obtain a physiologic index of diurnal cortisol concentrations and rhythmicity, which is associated with breast cancer survival time. CMI for specific antigens was measured following intradermal administration of seven commonly encountered antigens (tuberculin, tetanus, diphtheria, Streptococcus, Candida, Trichophyton, and Proteus). Analyses adjusting for relevant medical and treatment variables indicated that women reporting more depressive symptoms showed suppressed immunity as measured by lower average induration size. Women with higher mean diurnal cortisol concentrations also showed suppressed immunity as indicated by a decreased number of antigens to which positive reactions were measured. This study highlights the relationships among depression, stress, and immune function in the context of advanced breast cancer.