A product of independent beta probabilities dose escalation design for dual-agent phase I trials.

Dual-agent trials are now increasingly common in oncology research, and many proposed dose-escalation designs are available in the statistical literature. Despite this, the translation from statistical design to practical application is slow, as has been highlighted in single-agent phase I trials, where a 3 + 3 rule-based design is often still used. To expedite this process, new dose-escalation designs need to be not only scientifically beneficial but also easy to understand and implement by clinicians. In this paper, we propose a curve-free (nonparametric) design for a dual-agent trial in which the model parameters are the probabilities of toxicity at each of the dose combinations. We show that it is relatively trivial for a clinician's prior beliefs or historical information to be incorporated in the model and updating is fast and computationally simple through the use of conjugate Bayesian inference. Monotonicity is ensured by considering only a set of monotonic contours for the distribution of the maximum tolerated contour, which defines the dose-escalation decision process. Varied experimentation around the contour is achievable, and multiple dose combinations can be recommended to take forward to phase II. Code for R, Stata and Excel are available for implementation.We would like to acknowledge funding from the UK Medical Research Council (grant code U1052.00.014) for this work. We would also like to thank the reviewers for providing some excellent suggestions to help improve the manuscript.This is the final published version. It first appeared at http://onlinelibrary.wiley.com/doi/10.1002/sim.6434/abstract

Do single-arm trials have a role in drug development plans incorporating randomised trials?

Often, single-arm trials are used in phase II to gather the first evidence of an oncological drug's efficacy, with drug activity determined through tumour response using the RECIST criterion. Provided the null hypothesis of 'insufficient drug activity' is rejected, the next step could be a randomised two-arm trial. However, single-arm trials may provide a biased treatment effect because of patient selection, and thus, this development plan may not be an efficient use of resources. Therefore, we compare the performance of development plans consisting of single-arm trials followed by randomised two-arm trials with stand-alone single-stage or group sequential randomised two-arm trials. Through this, we are able to investigate the utility of single-arm trials and determine the most efficient drug development plans, setting our work in the context of a published single-arm non-small-cell lung cancer trial. Reference priors, reflecting the opinions of 'sceptical' and 'enthusiastic' investigators, are used to quantify and guide the suitability of single-arm trials in this setting. We observe that the explored development plans incorporating single-arm trials are often non-optimal. Moreover, even the most pessimistic reference priors have a considerable probability in favour of alternative plans. Analysis suggests expected sample size savings of up to 25% could have been made, and the issues associated with single-arm trials avoided, for the non-small-cell lung cancer treatment through direct progression to a group sequential randomised two-arm trial. Careful consideration should thus be given to the use of single-arm trials in oncological drug development when a randomised trial will follow.Michael J. Grayling is supported by the Wellcome Trust [grant number 099770/Z/12/Z]. Adrian P. Mander is supported by the Medical Research Council [grant number G0800860].This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/pst.172

Ecoengineering with Ecohydrology: Successes and failures in estuarine restoration

© 2016 Elsevier Ltd. Ecological Engineering (or Ecoengineering) is increasingly used in estuaries to re-create and restore ecosystems degraded by human activities, including reduced water flow or land poldered for agricultural use. Here we focus on ecosystem recolonization by the biota and their functioning and we separate Type A Ecoengineering where the physico-chemical structure is modified on the basis that ecological structure and functioning will then follow, and Type B Ecoengineering where the biota are engineered directly such as through restocking or replanting. Modifying the physical system to create and restore natural processes and habitats relies on successfully applying Ecohydrology, where suitable physical conditions, especially hydrography and sedimentology, are created to recover estuarine ecology by natural or human-mediated colonisation of primary producers and consumers, or habitat creation. This successional process then allows wading birds and fish to reoccupy the rehabilitated areas, thus restoring the natural food web and recreating nursery areas for aquatic biota. We describe Ecohydrology principles applied during Ecoengineering restoration projects in Europe, Australia, Asia, South Africa and North America. These show some successful and sustainable approaches but also others that were less than successful and not sustainable despite the best of intentions (and which may even have harmed the ecology). Some schemes may be 'good for the ecologists', as conservationists consider it successful that at least some habitat was created, albeit in the short-term, but arguably did little for the overall ecology of the area in space or time. We indicate the trade-offs between the short- and long-term value of restored and created ecosystems, the success at developing natural structure and functioning in disturbed estuaries, the role of this in estuarine and wetland management, and the costs and benefits of Ecoengineering to the socio-ecological system. These global case studies provide important lessons for both the science and management of estuaries, including that successful estuarine restoration is a complex and often difficult process, and that Ecoengineering with Ecohydrology aims to control and/or simulate natural ecosystem processes