Systematic Review Protocol to Evaluate the Effectiveness and Cost Effectiveness of Personalised Surveillance after Colorectal Adenomatous Polypectomy

Lifetime risk of developing colorectal cancer (CRC) is 5% and five-year survival at early-stage is 92%. CRC risk following index colonoscopy should establish post-screening surveillance benefit, which may be greater in high-risk patients. This review evaluated published cost-effectiveness estimates of post-polypectomy surveillance to assess the potential for personalised recommendations by risk sub-group. Current data suggested colonoscopy identifies those at low-risk of CRC, who may not benefit from intensive surveillance, which risks unnecessary harms and inefficient use of colonoscopy resources. Meta-analyses of incidence of advanced-neoplasia post-polypectomy for low-risk was comparable to those without adenoma; both rates were under the lifetime risk of 5%. Therefore, greater personalisation through de-intensified strategies for low-risk individuals could be beneficial and could employ non-invasive testing such as faecal immunochemical tests (FIT) combined with primary prevention or chemoprevention, thereby reserving colonoscopy for targeted use in personalised risk-stratified surveillance.
This systematic review aims to:
1. Assess if there is evidence supporting a program of personalised surveillance in patients with colorectal adenoma according to risk sub-group.
2. Compare the effectiveness of surveillance colonoscopy with alternative prevention strategies.
3. Assess trade-off between costs, benefits and adverse effects which must be considered in a decision to adopt or reject personalised surveillance.

A green perspective on Structured parallel programming

Structured parallel programming, and in particular programming models using the algorithmic skeleton or parallel design pattern concepts, are increasingly considered to be the only viable means of supporting effective development of scalable and efficient parallel programs. Structured parallel programming models have been assessed in a number of works in the context of performance. In this paper we consider how the use of structured parallel programming models allows knowledge of the parallel patterns present to be harnessed to address both performance and energy consumption. We consider different features of structured parallel programming that may be leveraged to impact the performance/energy trade-off and we discuss a preliminary set of experiments validating our claims.