Abstract
e19185 Background: The importance of NGS testing to help guide oncologic therapy decisions has grown over time, presenting a unique challenge for community oncologists to properly translate the NGS test results to treatment (Tx) recommendations for patients. Kaiser Permanente Northern California (KPNC) is a large, integrated health care system providing comprehensive primary and specialty care to 4.4 million members, with over 4000 patients (pts) diagnosed with advanced cancer each year. NGS testing at KPNC is performed in a collaboration with Strata Oncology, that provides systematized comprehensive NGS testing (StrataNGS) paired with a portfolio of genomically guided clinical trials. Methods: KPNC has established workflows for upfront empiric review of all NGS results by our KPNC Genomic Oncology Committee (GOC), that includes representatives from medical oncology subspecialists, genetics, pathology, and clinical trials. KPNC GOC reviews all StrataNGS test results in our KPNC network to identify patients that might benefit from either a clinical trial, appropriate on or off-label drug options and/or genetic counseling. In addition, GOC conducts an in-depth case review per request of the treating oncologist. A study nurse pre-screens all pts whose results match to a trial for eligibility. Results: The numbers of pts tested with StrataNGS has increased over time with around 300 pts tested monthly and 4,977 NGS tests performed since Nov 2017. Median age was 65.2 (Range 18.5-96.0). About 42.4% of Pts were non-white. Approximately, 39% of Pts had an actionable mutation including 21.7% eligible for a promising in or out of network trial. 1.6% and 10.9% pts were potentially eligible for off- or on-label approved drugs, respectively. 4.9% were recommended to receive genetic counseling. The 3 most frequently sequenced cancers were: lung, colon and breast. Conclusions: KPNC is providing systematic subspecialty review and management of NGS results for pts in a community setting. Our approach has allowed for greater adoption of routine NGS testing, especially for rare cancer types with less effective standard Tx options available. This model also helps accrual to genomic-based drug trials that have been a challenge for the field. Workflows to streamline automated centralized acquisition of prior Tx history and analysis of response to therapy are in development.
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