Rate of change in investigational treatment options: An analysis of reports from a large precision oncology decision support effort

Alejandro Araya 1, Jia Zeng 2, Amber Johnson 2, Md Abu Shufean 3, Jordi Rodon 2, Funda Meric-Bernstam 2, Elmer V Bernstam 4

Affiliations

PMID: 32889387
DOI: 10.1016/j.ijmedinf.2020.104261

Abstract

Purpose: Genomic analysis of individual patients is now affordable, and therapies targeting specific molecular aberrations are being tested in clinical trials. Genomically-informed therapy is relevant to many clinical domains, but is particularly applicable to cancer treatment. However, even specialized clinicians need help to interpret genomic data, to navigate the complicated space of clinical trials, and to keep up with the rapidly expanding biomedical literature. To quantitate the cognitive load on treating clinicians, we attempt to quantitate the rate of change in potential treatment options for patients considering genomically-relevant and genomically-selected therapy for cancer.

Materials and methods: To this end, we analyzed patient-specific reports generated by a precision oncology decision support team (PODS) at a large academic cancer center. Two types of potential treatment options were analyzed: FDA-approved genomically-relevant and genomically-selected therapies and therapies available via clinical trials. We focused on two clinically-actionable alterations: ERBB2 (Her2/neu; amplified vs. non-amplified) and BRAF mutation (V600 vs. non-V600). To determine changes in available treatment options, we grouped patients into similar groups by disease site (ERBB2: breast, gastric and "other"; BRAF: melanoma, non-melanoma).

Results: A total of 2927 reports for 2366 unique patients were generated 8/2016-12/2018. Reports included 9902 gene variants and 150 disease classifications. BRAF mutation and ERBB2 amplification were annotated with therapeutic options in 270 reports (225 unique patients). The median survival time of a therapeutic option was nine months.

Conclusion: When compared to "traditional" clinical practice guideline recommendations, treatment options for personalized cancer therapy change seven times more rapidly; partly due to change in knowledge and partly due to logistics such as clinical trial availability.

Keywords: Medical decision making; clinical trials; oncology; precision medicine.