Quantifying the value of the molecular tumor board: Discordance recommendation rate and drug cost avoidance

Authors

Mary K. Walters, Advocate Aurora HealthFollow
Andrew T. Ackerman, Advocate Aurora HealthFollow
James L. Weese, Advocate Aurora HealthFollow
Antony Ruggeri, Advocate Aurora HealthFollow
Michael P. Mullane, Advocate Aurora HealthFollow
Alicia Hunt, Advocate Aurora HealthFollow
Amanda Wilson, Advocate Aurora HealthFollow
Brenda L. Ramczyk, Advocate Aurora HealthFollow
Michael A. Thompson, Advocate Aurora HealthFollow

Recommended Citation

Walters MK, Ackerman AT, Weese JL, et al. Quantifying the Value of the Molecular Tumor Board: Discordance Recommendation Rate and Drug Cost Avoidance. JCO Precis Oncol. 2022;6:e2200132. doi:10.1200/PO.22.00132

Affiliations

Aurora Cancer Care, ACL Laboratories

Abstract

Purpose: Molecular tumor boards (MTBs) provide interventions that assist the patient's primary oncologist's interpretation and application of precision oncology and avoid clinical and financial toxicities of prescribing inappropriate targeted therapy. In this article, we describe a novel method for illustrating MTBs value and recommendation discordance rate and report associated drug cost avoidance data.

Methods: From January 1, 2021, to December 31, 2021, patients assessed by our program's MTB were retrospectively evaluated. Recommendation discordance was defined as any disagreement between MTB therapeutic recommendations and those provided in the next-generation sequencing vendor's report.

Results: In 2021, our program processed 1,119 next-generation sequencing orders via external vendors for 1,029 unique patients with a variety of solid tumor and hematologic malignancies. During this period, 962 patients were reviewed through our MTB process. MTB recommendation discordance rate was high (229 of 502; 45.6%) and varied across test vendors. Rationales for discordance included the following: low level of evidence (88% of patients), alternative standard of care available (60%), and tolerability concerns (42%), among others. Discordance was highest for Vendor C (30%), followed by Vendor A (24%) and Vendor B (8%). The most common drug classes not supported were mTOR, PARP, MEK, and PIK3CA inhibitors when recommended by vendors in off-label settings. MTB interventions accounted for $3,209,070 in US dollars in potential drug cost avoidance.

Conclusion: Therapeutic recommendation discordance rates can provide quantitative insight into the benefit of MTB. Discordance-associated drug cost avoidance further demonstrates MTB's financial value. These measures may be used as part of the justification for this service line within a cancer care program.

Document Type

Article

PubMed ID

36265115