The Johns Hopkins Molecular Tumor Board Precision Oncology elective for Medical Oncology fellows.

Authors

null

Kristen Marrone

Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD

Kristen Marrone , Jessica Tao , Jenna VanLiere Canzoniero , Paola Ghanem , Emily Nizialek , Kymberleigh Pagel , Rachel Karchin , Ross C. Donehower , Valsamo Anagnostou

Organizations

Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, Memorial Sloan Kettering Cancer Center, New York, NY, Johns Hopkins, Baltimore, MD, Johns Hopkins Hospital, Baltimore, MD, Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, Johns Hopkins University, Baltimore, MD

Research Funding

No funding received
None

Background: The accelerated impact of next generation sequencing (NGS) in clinical decision making requires the integration of cancer genomics and precision oncology focused training into medical oncology education. The Johns Hopkins Molecular Tumor Board (JH MTB) is a multi-disciplinary effort focused on integration of NGS findings with critical evidence interpretation to generate personalized recommendations tailored to the genetic footprint of individual patients. Methods: The JH MTB and the Medical Oncology Fellowship Program have developed a 3-month precision oncology elective for fellows in their research years. Commencing fall of 2020, the goals of this elective are to enhance the understanding of NGS platforms and findings, advance the interpretation and characterization of molecular assay outputs by use of mutation annotators and knowledgebases and ultimately master the art of matching NGS findings with available therapies. Fellow integration into the MTB focuses on mentored case-based learning in mutation characterization and ranking by levels of evidence for actionability, with culmination in form of verbal presentations and written summary reports of final MTB recommendations. A mixed methods questionnaire was administered to evaluate progress since elective initiation. Results: Three learners who have participated as of February 2021 were included. Of the two who had completed the MTB elective, each have presented at least 10 cases, with at least 1 scholarly publication planned. All indicated strong agreement that MTB elective had increased their comfort with interpreting clinical NGS reports as well as the use of knowledgebases and variant annotators. Exposure to experts in the field of molecular precision oncology, identification of resources necessary to interpret clinical NGS reports, development of ability to critically assess various NGS platforms, and gained familiarity with computational analyses relevant to clinical decision making were noted as strengths of the MTB elective. Areas of improvement included ongoing initiatives that involve streamlining variant annotation and transcription of information for written reports. Conclusions: A longitudinal elective in the JHU MTB has been found to be preliminarily effective in promoting knowledge mastery and creating academic opportunities related to the clinical application of precision medicine. Future directions will include leveraging of the MTB infrastructure for research projects, learner integration into computational laboratory meetings, and expansion of the MTB curriculum to include different levels of learners from multiple medical education programs. Continued elective participation will be key to understanding how best to facilitate adaptive expertise in assigning clinical relevance to genomic findings, ultimately improving precision medicine delivery in patient care and trial development.

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Abstract Details

Meeting

2021 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Professional Development and Education Advances

Track

Medical Education and Professional Development

Sub Track

Education Research

Citation

J Clin Oncol 39, 2021 (suppl 15; abstr 11035)

DOI

10.1200/JCO.2021.39.15_suppl.11035

Abstract #

11035

Poster Bd #

Online Only

Abstract Disclosures

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