Principal Investigator: Anna Chaimani

Participants: Silvia Metelli, Raphaël Porcher, Isabelle Boutron

Host Institution: METHODS Team, CRESS

The systematic identification and synthesis of all available evidence on a specific clinical question is an integral part of the medical decision-making process and the planning of future research. For most medical conditions, a plethora of healthcare interventions are available and, thus, network meta-analysis (NMA) – the only tool enabling simultaneous comparisons between many interventions – is currently among the highest levels of evidence for the development of clinical guidelines. However, current NMA methodology has important limitations for properly synthesizing different study designs (randomised, cohort, case-control, etc.), which could increase the external validity of the findings. These limitations impose restrictions in most NMAs by usually allowing the synthesis of a selective sample of randomised controlled trials only, rendering their results rarely applicable in real settings of healthcare practice. The aim of the OptiCER project is a) to develop and evaluate new synthesis methods for integrating all different sources of evidence available for addressing a common research question and b) to develop new presentation and communication tools for presenting the findings of these ‘all-evidence’ NMAs targeting the needs of different stakeholders (clinicians, regulators, guideline developers). All new statistical models and tools will be accompanied by open-access and user-friendly software. The new methods will be used for the synthesis of the COVID-19 studies but will also be freely available for application in other medical fields. In this way, clinical recommendations will be based on a global view and synthesis of any piece of evidence rather than on a partial approach.

Individual Fellow: Silvia Metelli

Supervisor: Anna Chaimani

Host Institution: METHODS Team, CRESS

Many health conditions are complex and dynamic in nature. For instance, chronic diseases often require the individuals to undergo treatments for long periods of time, thus involving a series of progressive treatment decisions to be made. Understanding how treatment effectiveness varies over time is crucial to better inform clinical decisions. So far, comparative effectiveness research has mainly taken a static perspective both in primary research and in evidence synthesis. A first attempt to move towards a dynamic approach in primary research was provided recently with just-in-time adaptive interventions (JITAIs), which are mobile technology interventions where both treatment and response occur intensively over time (see also dynamic treatment regimes); while for evidence synthesis a dynamic approach has never been considered. DyCER aims to contribute to bridge this gap in two different, yet related, ways: (i) investigating dynamic regimes and providing methods for JITAIs personalised at patient-level and (ii) developing methodology for the dynamic evolution of networks of interventions. In both cases, the project will focus on the case of complex interventions, which are interventions composed of multiple, possibly interactive, components (examples include psychological interventions for mental illness or smoking cessation support). Overall, this holds the potential to yield more effective planning of future research, and in the case of JITAIs, more personalized decision-making.

Live cumulative network meta–analysis: Systemic pharmacological treatments for chronic plaque Psoriasis

Principal Investigator: Emilie Sbidian

Doctoral Fellow: Theodoros Evrenoglou

Supervisor: Anna Chaimani

Host lab: METHODS Team, CRESS

Principal Investigator: Anna Chaimani

Host Institution: METHODS Team, CRESS

Principal Investigator: Sonal Patil