Implementation of comparative effectiveness research in personalized medicine applications in oncology: current and future perspectives

Abstract

Personalized medicine (PM) or precision medicine has been defined as an innovative approach that takes into account individual differences in people's genes, environments, and lifestyles in prevention and treatment of disease. In PM, genomic information may contribute to the molecular understanding of disease, to optimize preventive health care strategies, and to fit the best drug therapies to the patient's individual characteristics. Evidence development in the era of genomic medicine is extremely challenging due to a number of factors. These include the rapid technological innovation in molecular diagnostics and targeted drug discoveries, and hence the large number of mutations and multiple ways these may influence treatment decisions. Although the evidence base for PM is evolving rapidly, the main question to be explored in this article is whether existing evidence is also fit for comparative effectiveness research (CER). As a starting point, this paper therefore reflects on the evidence required for CER and the evidence gaps preventing decisions on market access and coverage. The paper then discusses challenges and potential barriers for applying a CER paradigm to PM, identifies common methodologies for designing clinical trials in PM, discusses various approaches for analyzing clinical trials to infer from population to individual level, and presents an example of a clinical trial in PM (The RxPONDER TRIAL) demonstrating good practice. The paper concludes with a future perspective, including modeling approaches for evidence synthesis.

The Future of Precision Medicine: Potential Impacts for Health Technology Assessment

“…A preliminary consideration for this study was to define the types of technologies and services that precision medicine encompasses. Ten papers from the review provided a definition for precision medicine, as did each of the consulted experts, resulting in a wide range of interpretations [ 10 – 12 ]. Most agreed that precision medicine encompasses more than just pharmacogenetic and pharmacogenomic tests, and the term is now used interchangeably with stratified medicine .…”

“…Most agreed that precision medicine encompasses more than just pharmacogenetic and pharmacogenomic tests, and the term is now used interchangeably with stratified medicine . It is also replacing the term personalised medicine , as it also covers technologies that offer unique treatment pathways for individual patients [ 10 , 11 ].…”

A systematic review and checklist presenting the main challenges for health economic modeling in personalized medicine: towards implementing patient-level models

“…The resulting data gaps characterize the increasingly common work setting in which evaluations of health care interventions need to be performed, initiating the need for accumulating other types of data, e.g. observational (big) data, or expert elicitation techniques [10,11]. Furthermore, new challenges occur with respect to analyzing trial data at the individual level and identifying and handling multiple subgroups [11].…”

“…observational (big) data, or expert elicitation techniques [10,11]. Furthermore, new challenges occur with respect to analyzing trial data at the individual level and identifying and handling multiple subgroups [11]. Therefore, health economic evaluation in the context of PM increasingly relies on modeling approaches and new methods, such as dynamic simulation modeling and the use of machine learning or other statistical approaches [12].…”

“…Markov modeling, is being questioned [14,18], as this modeling approach may not be able to fully capture the complex treatment processes associated with PM [19][20][21][22]. Consequently, the use of more advanced modeling methods, such as discrete event simulation, agent based modeling, and system dynamics, might be more appropriate in this personalized context [11,[23][24][25].…”