Scenario drafting for early technology assessment of next generation sequencing in clinical oncology

Abstract

Background

Next Generation Sequencing (NGS) is expected to lift molecular diagnostics in clinical oncology to the next level. It enables simultaneous identification of mutations in a patient tumor, after which targeted therapy may be assigned. This approach could improve patient survival and/or assist in controlling healthcare costs by offering expensive treatment to only those likely to benefit. However, NGS has yet to make its way into the clinic. Health Technology Assessment can support the adoption and implementation of a novel technology, but at this early stage many of the required variables are still unknown.

Methods

Scenario drafting and expert elicitation via a questionnaire were used to identify factors that may act as a barrier or facilitate adoption of NGS-based molecular diagnostics. Attention was paid to predominantly elicit quantitative answers, allowing their use in future modelling of cost-effectiveness.

Results

Adequately informing patients and physicians, the latters' opinion on clinical utility and underlying evidence as well as presenting sequencing results within a relevant timeframe may act as pivotal facilitators. Reimbursement for NGS-based testing and accompanying therapies (both general and in case of off-label prescription) was found to be a potential barrier. Competition on the market and demonstrating clinical utility may also be challenging. Importantly, numerous quantitative values for variables related to each of these potential barriers/facilitators, such as such as desired panel characteristics, willingness to pay or the expected number of targets identified per person, were also elicited.

Conclusions

We have identified several factors that may either pose a barrier or facilitate the adoption of NGS in the clinic. We believe acting upon these findings, for instance by organizing educational events, advocating new ways of evidence generation and steering towards the most cost-effective solution, will accelerate the route from bench-to-bedside. Moreover, due to the methodology of expert elicitation, this study provides parameters that can be incorporated in future cost-effectiveness modeling to steer the development of NGS gene panels towards the most optimal direction.

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