A cost benefits analysis of the adoption of system of rice intensification: Evidence from smallholder rice farmers within an innovation platform in Oluch irrigation scheme, Kenya.

In the wake of climate change and dwindling natural resources, system of rice intensification has been fronted as an approach to improve rice production in several countries. Besides the benefits such as improved rice productivity, reduced water usage that have widely been observed, there is need to quantify the economic benefits of system of rice intensification accrued to farmers, thereby promoting it as an innovation to improve livelihoods of rice farmers. This aim of this paper is to quantify the economic benefits of undertaking SRI among smallholder rice farmers.

Bayesian modelling strategies for borrowing of information in randomised basket trials.

Basket trials are an innovative precision medicine clinical trial design evaluating a single targeted therapy across multiple diseases that share a common characteristic. To date, most basket trials have been conducted in early-phase oncology settings, for which several Bayesian methods permitting information sharing across subtrials have been proposed. With the increasing interest of implementing randomised basket trials, information borrowing could be exploited in two ways; considering the commensurability of either the treatment effects or the outcomes specific to each of the treatment groups between the subtrials.

Design and analysis of umbrella trials: Where do we stand?

Background: The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted in their consideration in non-oncology settings. Umbrella trials are one class of master protocol design that evaluates multiple targeted therapies in a single disease setting.

Treatment allocation strategies for umbrella trials in the presence of multiple biomarkers: A comparison of methods.

Umbrella trials are an innovative trial design where different treatments are matched with subtypes of a disease, with the matching typically based on a set of biomarkers. Consequently, when patients can be positive for more than one biomarker, they may be eligible for multiple treatment arms. In practice, different approaches could be applied to allocate patients who are positive for multiple biomarkers to treatments.