OP64 Review Of Economic Evaluations Of Next-Generation Precision Oncology

Abstract

Introduction:

Proponents of precision oncology report that genomic testing has the potential to reduce health system costs and improve patient health. Yet, testing also involves significant expenditures that challenge the sustainability of adopting technologies into routine practice. Our study explores the availability and scope of economic evaluations of precision oncology informed by next-generation sequencing (NGS).

Methods:

We searched Medline (PubMed), Embase (Ovid), and Web of Science databases for English-language full-text peer reviewed articles published between 2000 and 2016. We focused our search on articles that estimated the benefit of precision oncology in relation to its costs. We excluded studies that did not undertake full economic evaluations or did not focus on NGS. We reviewed all included studies and summarized key methodological and empirical study characteristics.

Results:

Fifty-five economic evaluations met our inclusion criteria. The first study was published in 2005 and the number of published studies increased steadily, from three studies between 2005 and 2007 to twenty-six between 2014 and 2016. Most studies evaluated multiplex panels (86 percent). Testing was frequently used to diagnose patients (24 percent) or predict prognosis (67 percent), rather than identify targeted therapies (7 percent). Methods varied considerably and cost-effectiveness differed according to test type, test strategy, and cancer type. Deterministic and probabilistic analyses were typically used to characterize uncertainty (91% percent and 75% percent).

Conclusions:

While the availability of economic evidence examining precision oncology increased over time, methods used often did not align with current guidelines. Future evaluations should undertake extensive sensitivity analysis to address all sources of uncertainty associated with rapidly changing NGS technologies. Further, additional research is needed evaluating the cost-effectiveness of more comprehensive next-generation technologies prior to implementing these on a wider scale.