Search

Summary We present a Bayes sequential economic evaluation model for health technologies in which an investigator has flexibility over the timing of a decision to stop carrying out research and to conclude that one technology is preferred to another on cost-effectiveness grounds. We implement the model by using an evaluation of the treatment of bacterial sinusitis and derive approximations of the optimal stopping rule as a function of accumulated sample size. We compare the performance of the model with existing frequentist and Bayes sequential designs and investigate the sensitivity of the stopping rule to changes in the parameters of the model. Our results suggest that accounting for the dynamic nature of experimentation, together with its economic parameters, should lead to greater efficiency in resource allocation within healthcare systems.

We observed that peripheral T cells activated in vivo or in vitro by superantigens are susceptible to cell death when their antigen receptor is cross-linked with the appropriate anti-alpha beta TCR mAb. TCR ligation by mAbs specifically drove the T cell clonal deletion in both CD4+ and CD8+ cell subsets. An IL-2/IL-2R interaction seems to be a critical step in predisposing superantigen activated cells to death; in fact, in vivo IL-2R blockade reversed T cell deletion in superantigen plus anti-alpha beta TCR mAb treated mice. TCR ligation by mAbs also produced cell death of the relevant targets in in vitro IL-2 activated T cells. Surprisingly, no T cell deletion was demonstrable in IL-2 activated cells following staphylococcal enterotoxin B--TCR interaction, ruling out the possibility that superantigen in itself can induce cell death. Thus, while superantigen activation opens the cell death program, a subsequent TCR--antigen (self) interaction appears necessary to produce clonal deletion in mature T lymphocytes.