Resources and expertise that help solve the unique challenges of rare disease research

Health Economics, Outcomes Research, & Market Access

Network Meta-Analysis

Mapi is a pioneer in network meta-analysis (NMA) methods, having co-developed the NMA guidelines and trainings. Out of 60 publications worldwide, Mapi experts are responsible for a third, and we’re at the forefront in development of new methods in NMA:

  • Understanding bias in NMAs
  • Repeated measures
  • Survival data
  • NMA treatment rankings summaries for survival
  • Reconstructing individual patient data
  • Incorporating individual patient data
  • Single-arm study designs and NMAs
  • Critical reviews of NMAs

NMA methodologies can be used to develop materials to communicate to HCPs, HTAs, and payers as support for the treatment.

Identifying Important Subgroups

As interventions become more targeted, it is increasingly important to assess the validity of comparing targeted agents to alternative treatments. Mapi has developed a process to assess the feasibility of performing NMA, which allows transparent and reproducible results that visualize the differences across studies in terms of key study and patient differentiators. This process can also be applied to assess if evidence from observational studies should be incorporated into the network of evidence, which helps draw or provide insight into the real-world effectiveness of alternative interventions. Finally, we have extended NMA models to incorporate individual patient-level data, which allows for exploring differences in patients within and between studies to better understand relevant subgroups.

Maximizing Survival and Longitudinal Data

Mapi is a leader in the analysis of survival data (time-to-event outcomes) for NMAs, which provides insight into the comparative effectiveness of new interventions for some of the most important outcomes, such as overall survival and progression-free survival. Flexible NMA models developed by Mapi for analyzing survival data can provide improved fit with the data and can be used to directly model cost-effectiveness of alternative interventions. The methods used to extract survival data from published Kaplan-Meier studies offer a more accurate and comprehensive assessment of available evidence. Similarly, integrating data from repeated measures provides more precise estimates and offers insight into the progression of outcomes over time.

Real World Evidence