Evidence synthesis

Our team has vast experience in combining existing sources of information to generate new conclusions, insights and directions for future research. With academic rigour, we perform systematic reviews that are highly valuable for strategy development, recommendation development, and the visualization of an evidence base for medical innovation.

With our expertise in targeted literature reviews, we answer complex research questions by identifying the key evidence in the literature. Targeted literature reviews can be a powerful tool to determine key stakeholders, identify market access opportunities, and provide tailored advice from the health-economic perspective.

Asc Academics frequently carries out the burden of disease studies, in order to measure the impact a disease or health problem has on a population in a specific context or setting. A burden of disease study may include measurements of the incidence, prevalence, morbidity, mortality, associated quality- or disability-adjusted life years (QALY’s or DALY’s), costs, and other indicators of a disease or health problem.

Meta-analyses can be a powerful tool to inform decision-makers, payers and patients about the clinical effectiveness and safety of an intervention. By pooling together the findings from two or more studies, we can help you synthesize data in the context of growing scientific literature and increasing demand for meta-analyses by regulatory agencies.

Asc Academics has expertise in performing network meta-analyses, which allows for the comparison of multiple treatments using both direct comparisons of interventions within randomized controlled trials, and indirect comparisons across trials based on a common comparator. With this kind of analysis, we can provide comparisons when no head-to-head studies are available or possible.

Matching-adjusted indirect comparisons (MAICs) is a novel technique which has been increasingly adopted across several therapeutic areas and accepted by HTA bodies. With MAICs, we provide indirect treatment comparisons that are able to adjust for observed trial differences and reduce bias by matching patient-level data.

Our consultants are skilled in performing survival analyses using R software. Survival analysis is a commonly used tool in oncology and is necessary for HTA submissions. With survival analyses, we estimate mean survival times to identify the benefits of a given technology in terms of its health gains and financial savings.