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.     

Understanding Cumulative Risk Perception from Judgments and Choices: An Application to Flood Risks

Catastrophic events, such as floods, earthquakes, hurricanes, and tsunamis, are rare, yet the cumulative risk of each event occurring at least once over an extended time period can be substantial. In this work, we assess the perception of cumulative flood risks, how those perceptions affect the choice of insurance, and whether perceptions and choices are influenced by cumulative risk information. We find that participants' cumulative risk judgments are well represented by a bimodal distribution, with a group that severely underestimates the risk and a group that moderately overestimates it. Individuals who underestimate cumulative risks make more risk‐seeking choices compared to those who overestimate cumulative risks. Providing explicit cumulative risk information for relevant time periods, as opposed to annual probabilities, is an inexpensive and effective way to improve both the perception of cumulative risk and the choices people make to protect against that risk.     

Comparing the Prevalence and Organizational Distinctiveness of Faith-Based and Secular Development NGOs in Canada

Faith-based development organizations (FBOs) have been argued to deliver more cost-efficient development projects than their secular counterparts through exclusive access to faith networks, which provide predictable decentralized funding, the recruitment of volunteers, low employee salaries, and less overhead and indirect costs. To date, however, comparative analyses of religious and secular organizations have relied on a case-by-case approach, limiting the generalizability of findings. This study addresses this methodological gap by analyzing Registered Charity Information Return filings and organizational websites of 844 Canadian development NGOs to determine the proportion of FBOs and their organizational distinctiveness. The results show that FBOs comprise 40% of the Canadian NGO sector in terms of the number of organizations and their expenditures in developing countries, and are significantly less reliant on federal funding (p?<?.1), pay employees lower salaries (p?<?.01), but do not exhibit a significant difference in their expenditures on overhead and indirect costs. Thus, Canadian FBOs participation in faith networks shapes their organizational modus operandi but does not result in a low overhead alternative to secular NGOs.

     

Multi-valued strategy-proof social choice rules

In this paper we introduce a new definition of strategy-proofness for multi-valued social choice correspondences. We prove two Gibbard-Satterthwaite type results for strategy-proof social choice correspondences. These results show that allowing multiple outcomes as social choices will not necessarily lead to an escape from the Gibbard-Satterthwaite impossibility theorem. Received: 24 January 2001/Accepted: 19 March 2001     

Volume 30

Theory and Society -     

Generating random variates from D-distributions via substitution sampling

Laud et al. (1993) describe a method for random variate generation from D-distributions. In this paper an alternative method using substitution sampling is given. An algorithm for the random variate generation from SD-distributions is also given.     

Cognitive-behavioral-expressive interventions with aggressive and resistant youths.

Research into the nature of aggressive behavior in youths has demonstrated that these youths are often the victims of abuse, exhibit aggressive behavior in early childhood, and remain aggressive into young adulthood. The treatment approach described in this article is a modification of Monahan's [1981] model of the prediction of violent behavior and the anger-management approach of Novaco [1985], and integrates the developmental models of Piaget [1963] and Erikson [1959]. The program is a combination of cognitive, behavioral, and expressive therapies and is targeted to the reduction of dysfunctional cognitive, affective, behavioral, and problem-solving patterns of aggressive youths. As referrals of such aggressive clients are often involuntary, interventions with unwilling and resistant clients are also presented.