LAUSR

e18649 Background: Molecular biomarker testing is integral to NSCLC cancer care, but adoption and testing practices in the community are varied and often suboptimal. Testing practices, such as standard testing protocols and results turnaround time (TAT), impact timely treatment decisions. We examined adoption and testing practices for guideline recommended NSCLC biomarkers among National Cancer Institute Community Research Program (NCORP) sites. The study was conducted in collaboration with Wake Forest NCORP Research Base. Methods: An online survey was administered to onsite labs affiliated with NCORP sites April 2019 – June 2020. We assessed testing practices for 7 NCCN recommended biomarkers, including 3 with category 1 recommendation (EGFR, ALK, PD-L1) and 4 with category 2 recommendations (BRAF, ROS1, MET, RET). Guideline concordant result TAT was defined as return of EGFR and ALK results in ≤ 10 days (Lindeman 2018) (see Table for other outcomes). We used proportions, including two-sided Fischer exact tests, to compare outcomes by site characteristics (safety net, practice size). Results: The survey response rate was 69% (58/85). All responding labs offered testing for category 1 biomarkers (EGFR, ALK and PD-L1); only 10% conducted these tests in-house (Table). The majority of labs also tested for category 2 biomarkers (67%). TAT varied, with most labs returning results in ≤ 10 days for EGFR and ALK (69%, but only a minority meet this TAT for all biomarkers. Larger practice size (> 1400 new cancer cases a year) was associated with in-house testing of EGFR, ALK, PD-L1 (p=0.03) and having standard testing protocols (p<0.001). Safety net affiliation did not significantly impact practices. Conclusions: We found universal adoption of NCCN category 1 biomarkers among the labs affiliated with NCORP sites, with the majority meeting guideline concordant results TAT. There is opportunity for improvement in adoption of category 2 biomarkers and result TAT, for example, by using standard testing protocols. Reassuringly, no difference in testing practices was detected by safety net affiliation.[Table: see text]