OBJECTIVES

: The study aims to assess current testing procedures for NGS and hotspot single gene tests in terms of impact on hospital organization, patient and disease management. The analysis focuses on advanced non-small-cell lung cancer (NSCLC) and unresectable metastatic colon-rectal cancer (mCRC), for patients treated in Italian hospitals. A set of decisional and operational recommendations on clinical practice, defined by an expert panel, is provided.

METHODS

: The study is based on a decision model, designed to compare NGS with single gene tests, along the whole testing process.

The model assesses the impact of testing alternatives on hospital organization and outcomes, in terms of: activities to be performed, professionals and resources absorbed, time to treatment, access rate to personalized medicine, testing invasiveness.

The assessment of current gene testing path has been conducted in Italian advanced Oncological Hospitals. The data and information collected on current clinical practice, organization, resources and economics were integrated with published data.

Results are articulated into a present scenario, based on current diagnostic practice and associated gene testing and a future scenario defined as the set of genes that an expert panel would recommend to test in order to deploy the best test strategy in the perspective of the Italian NHS.

RESULTS

: The study provides strategic recommendations on NGS use to maximize its associated benefits.

The study measures also the potential impact of NGS adoption for patients, hospitals and NHS in terms of: time to treatment, costs, number of biopsy and associated adverse events.

NGS might enable oncologist to profile the patients and define the most suitable treatment path. Such benefits still need to be further investigated.

CONCLUSIONS

: The strategic use of NGS as an alternative to single gene tests, allows hospitals and the NHS to capture significant organization, clinical and economic benefits in the management of advanced NSCLC and unresectable mCRC.