Introduction Accurate clinical staging (CS) of gastric adenocarcinoma is important to guide treatment planning. Our objectives were to (1) assess clinical to pathologic stage migration patterns for patients with gastric adenocarcinoma, (2) identify factors associated with inaccurate CS, and (3) evaluate the association of understaging with survival. Methods The National Cancer Database was queried for patients who underwent upfront resection for stage I–III gastric adenocarcinoma. Multivariable logistic regression was used to detect factors associated with inaccurate understaging. Kaplan–Meier analyses and cox proportional hazards regression were performed to assess overall survival (OS) for patients with inaccurate CS. Results Of 14 425 analyzed patients, 5781 (40.1%) patients were inaccurately staged. Factors associated with understaging included treatment at a Comprehensive Community Cancer Program, presence of lymphovascular invasion, moderate to poor differentiation, large tumor size, and T2 disease. Based on overall CS, median OS was 51.0 months for accurately staged patients and 29.5 months for understaged patients (<0.001). Conclusion Clinical T‐category, large tumor size, and worse histologic features lead to inaccurate CS for gastric adenocarcinoma, impacting OS. Improvements to staging parameters and diagnostic modalities focusing on these factors may improve prognostication.

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e18811 Background: The Covid-19 pandemic caused unprecedented challenges in the diagnosis and evaluation of cancer. At the same time, cancer treatment was potentially impacted by significant constraints on patients and hospitals; however, the extent and differential influence on different hospital types is unknown. Our objective was to assess the patterns of treatment utilization to better characterize the impact of the first year of the Covid-19 pandemic on the US healthcare system. Methods: The National Cancer Database (NCDB) was queried for patients treated for any type of malignancy diagnosed from 2018-2020. Autoregressive models were used to forecast expected findings for 2020 based on observations from the prior two years. Descriptive univariate statistics using chi-squared tests were performed to compare observed-to-expected findings for treatment utilization and losses in provided care in 2020. Results: Overall, 1,229,654 patients underwent treatment for any newly diagnosed cancer in the NCDB in 2020, representing a 16.8% reduction compared to what was expected. Stratified by treatment modality, 146,805 fewer patients than expected underwent surgery, 80,480 fewer received radiation and 68,014 fewer received chemotherapy. Reductions in treatment were examined by hospital type. Academic hospitals experienced the greatest reduction in provided care (-105,093 patients, -19%) compared to community programs (-72,432 patients, -14%) and integrated networks (-40,827 patients, -13%). However, there were fewer hospitals in the academic cohort which exaggerated the impact on each hospital. Thus, academic hospitals lost approximately 484 patients per hospital while community hospitals lost 99 patients and integrated networks lost 110 patients per hospital. The losses in provided care were most dramatic in terms of surgical care, as academic hospitals operated on 314 fewer patients per hospital (-20%) than expected while community hospitals on average operated on 69 fewer patients (-16%) and integrated networks 71 fewer patients (-14%). Conclusions: The impact of the first year of the Covid-19 pandemic on cancer treatment was heterogenous, resulting in nearly twice the number of missed surgical patients, compared to other treatment modalities. While all hospital types were affected by the pandemic, cancer care at academic hospitals experienced disproportionate reductions, with each hospital losing more than 4 times the number of treated patients than other hospital types. Continued efforts to recover from the strain of the pandemic on the US healthcare system will need to consider the complex influence of treatment declines across hospital types and different cancer service lines.