Conducting evidence reviews using systematic or targeted approaches is one of the core competences of our Evidence Synthesis team. We use state-of-the art methodology in line with the most rigorous evidence requirements. The research conducted within our organisation is published in peer-reviewed journals and conferences, and used to support reimbursement submissions. We also have extensive experience in conducting direct and indirect comparisons as well as Bayesian network meta-analysis (which combines direct and indirect comparisons) and MAIC (matching-adjusted indirect comparison) in order to support both internal decision making and HTA submissions.
Evidence-based research is the foundation of healthcare decision-making. Excellence in evidence synthesis planning and methodology is the key to success as you demonstrate the comparative effectiveness and safety of your product. Synthesizing such evidence can help key policy makers visualize and interpret a broader picture of the evidence available for a given therapeutic area in light of the various different interventions that may be indicated. We are confident that we can help you make sense of this data because our department was founded on and is grounded in robust quantitative methodology. We understand the intricacies of synthesizing multiple sources of information and can help you navigate the associated uncertainty to support you in answering your research questions. We assemble integrated and inter-disciplinary project teams that will generate strategic clinical insights to provide you with a clear competitive edge and strong element to launch excellence.
Our services in evidence synthesis include:
- Indirect treatment comparisons
- Network meta-analyses (NMAs)
- Meta-regressions
- Fractional polynomial NMAs
- Matching adjusted indirect comparison (MAIC)
- Simulated treatment comparison (STC)
Our evidence synthesis team has conducted studies in various disease areas including oncology, infectious diseases, major depressive disorders, inflammatory and respiratory diseases.
Several projects were conducted in collaboration with academic experts and were used as part of submissions to NICE, EUnetHTA and CADTH.
Focus on one type of project: The Amaris HEMA team has extensive experience in conducting direct and indirect comparisons as well as Bayesian network meta-analysis (which combines direct and indirect comparisons) in order to support your launch excellence in line with the most rigorous of HTA guidelines, including NICE, iQWiG, the HAS, ICER, and CDR.
Here is how we would typically conduct such a project, assuming the systematic literature review of efficacy and safety has already been performed.
Step 1. Feasibility assessment and validating key assumptions
- Homogeneity
- Transitivity
- Consistency
Step 2. Study protocol development following the key guidelines and recommendations, depending on your overarching objectives
Step 3. Integral data quality checking and cleaning
Step 4. Data analysis (base case, sensitivity, and scenario analyses) using both a frequentist and Bayesian framework
Step 5. Reporting of results
Step 6. Interpretation and validation from a clinical perspective
We believe that the following elements are our key success factors when performing evidence synthesis:
- Multidisciplinary project teams working together to solve your research questions (clinicians, statisticians, epidemiologists, economists) to make sure that your end goal is taken into account properly (e.g. seeking health economist input early on if the NMA is to feed into a model later on)
- Our rapid response unit ensures a fast turnover of data analyses following internal SOPs
- Our organizational structure is designed to ensure the highest quality of deliverables across our offices
- We leverage our inner-group synergies to offer innovative solutions to you (i.e. incorporation of RWE data in NMAs)
- Thought leadership: Our team of experts has extensive experience in NMA methodology, from dealing with non-proportional hazard ratios to integrating RWE into your NMAs
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