Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

Reviews

Abstract

Michelle DeMars reviews The Indispensable Academic Librarian: Teaching and Collaborating for Change; Norma Durian reviews The Library Outreach Casebook; Trina Boykin Nolen reviews Licensing Digital Content: A Practical Guide for Librarians, Third Edition.     

Spatial Variations in Church Burnings: The Social Ecology of Victimized Communities in the South*

Abstract In recent years, church burnings in the South have attracted a great deal of attention. Many commentators have charged that they are a product of strained race relations throughout the South, and particularly of severe racial tensions in Southern rural areas. In this study we evaluate these claims. We begin by mapping the spatial coordinates of recorded church burnings from 1990 to 1997, and find that church arsons indeed are concentrated in the South. Church burnings, however, are a more urban phenomenon than popular media accounts would suggest. Our analysis then explores the influence of contextual factors (population and locale, racial composition and inequality, so‐cioeconomic conditions, local religious ecology, and patterns of reported crime) on church burnings in counties located in the study region. Logistic regression models confirm that church arsons are most likely to occur in small metropolitan statistical areas (MSAs) and non‐MSA counties containing a city of at least 10,000 residents. Church burnings also are especially likely in counties with a higher percentage of black residents, a larger number of churches relative to the rest of the state, and a higher arson rate. We conclude by discussing the implications of these findings for future research and public policy.     

Challenges to professionalism and union voting intentions: The case of pharmacists

Using data from a national survey of pharmacists who are members of the American Pharmaceutical Association, we examine the union voting intentions of employee pharmacists. We find that union instrumentality regarding professionalism is a primary predictor of union voting intent among these employees. In addition, this predictor mediates the relationship between the level of professionalism at a pharmacist’s current employment situation and his or her expected union vote. Also important to union voting intent are respondent beliefs about union instrumentality regarding pecuniary issues, prior union experience, as well as overall job satisfaction. Implications for employers, unions, and researchers are drawn. We thank Mary Graham, Jann Skelton, Paul Swiercz, Terry Thomason, and participants at the Seventh Bar-gaining Group Conference at Michigan State University for their comments on earlier versions of this paper. This research was made possible by a grant from the American Pharmaceutical Association.     

A NOTE ON EVANESCENT PROCESSES

This note examines the connection between μ-invariant measures for the transition function of a continuous-time Markov chain and those of its q-matrix, Q. The major result establishes a necessary and aufficient condition for a convergent μ-invariant measure for Q to be μ-inhant for the minimal transition function, P, under the assumption that P is honest. This corrects Theorem 6 of Vere-Jones (1969) and the first part of Corollary 1 of Pollett (1986), both of which assert that the above conclusion holds in the absence of this condition. The error was pointed out by E.A. van Doom (1991) and the counterexample which be presented provides the basis for the present arguments. In determining where the error occurred in the original proof, we are able to identify a simple sufficient condition for μ-invariance.     

TEACHING PROFESSIONAL WRITING TO FAMILY THERAPISTS: THREE APPROACHES

The authors present three educational approaches designed to demystify the writing process and to support better writing skills among family therapists. One framework is an academic course in professional writing, another is a writing seminar for family therapy and physician trainees within a medical school setting, and the third is a 2-hour continuing education writing workshop for family therapists. Each is replicable within a variety of settings.     

Measuring agreement between two statistics with applications to age standardization

Summary.  We detail a general method for measuring agreement between two statistics. An application is two ratios of directly standardized rates which differ only by the choice of the standard. If the statistics have a high value for the coefficient of agreement then the expected squared difference between the statistics is small relative to the variance of the average of the two statistics, and inferences vary little by changing statistics. The estimation of a coefficient of agreement between two statistics is not straightforward because there is only one pair of observed values, each statistic calculated from the data. We introduce estimators of the coefficient of agreement for two statistics and discuss their use, especially as applied to functions of standardized rates.     

Bayesian analysis of mixture modelling using the multivariate t distribution

A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data.