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Clinical utilization of precision oncology decision support for genomically-guided therapy
Wednesday, May 10th, 7:30-8:30 AM - Monitor 7 - Hickey Auditorium

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Precision oncology is hindered by the lack of decision support for determining the functional and therapeutic significance of genomic alterations in tumors and relevant clinically available options. To bridge this knowledge gap, we established a Precision Oncology Decision Support (PODS) team that provides annotations at the alteration-level and subsequently determined if clinical decision-making was influenced.



Genomic alterations were annotated to determine actionability based on a variant’s known or potential functional and/or therapeutic significance, as previously described (PMID:26148707). Briefly, reports consisted of data summary with references and the alteration frequency from external (cBIO, COSMIC) and internal databases.  In 2015, reports evolved to routinely contain an alteration-level actionability call, termed the “actionable variant” call, describing the alteration’s functional and therapeutic significance, with classification into four broad categories: actionable (further subcategorized by source: literature-based, inferred, functional genomics), potentially actionable, unknown, and non-actionable. To assess clinical utility, the medical records of 539 patients annotated in 2015 through clinician-initiated requests or for treatment planning conferences, a subset of all patients annotated in 2015, were manually reviewed. A web-based survey was implemented to capture the reasons why genotype-matched therapies were not pursued.



Between 2013-2015, the PODS team processed 1,669 requests for annotation of 4,084 alterations (2,254 unique) in 356 genes, across 49 tumor types, for 1,197 patients.  2,444 annotations for 669 patients included an actionable variant call: 32.5% actionable, 9.4% potentially, 29.7% unknown, 28.4% non-actionable. 66% of patients had at least one actionable or potentially actionable alteration. 92 (27.6%) of 333 patients with actionable or potentially actionable alterations were enrolled on genomically-matched trials compared to 16 (11.8%) of 136 patients with unknown, and 2 (3%) of 66 patients with non-actionable alterations (Chi-square, p=0.00004). Actionable alterations in PTEN, PIK3CA, and ERBB2 most frequently led to enrollment on genotype-matched trials, paralleling our data that show a large number of actionable or potentially actionable annotations delivered for PIK3CA and PTEN.  To understand why physicians may not have acted on potentially actionable alterations, we introduced a web-based survey in 2015 to accompany physician-initiated requests. Of 236 surveys sent, 223 were returned (94.5% response rate). Clinicians cited a variety of reasons why patients with actionable alterations did not enroll on trials, including stable disease at the time of annotation or ineligibility. The most often cited reason for why patients did not enroll on genotype-matched trials was that the annotation did not support trial enrollment (44.1%). This response was most frequently given for alterations annotated as unknown or non-actionable, indicating physicians’ agreement with our annotation.



Over half of alterations annotated were of unknown significance or nonactionable, demonstrating the need for decision support. The growing demand for genomic testing interpretation, and greater percentage of patients with actionable/potentially actionable alterations enrolled on genotype-matched clinical trials demonstrates its utility. Future studies are needed to demonstrate impact of decision support on trial enrollment and oncologic outcomes.


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