Citations

9543 Background: Lung cancer is the leading cause of cancer related death in the United States in all racial groups. However, the overall death rate from lung cancer is different among white, black and Asian. Although differences in socioeconomic status and treatments received might be the contributing factors, the biology, particularly genomic alteration of cancer might also have an important impact. To date, the differences of genomic alterations among all racial patients are poorly understood. Methods: The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE, version 7.0) database was analyzed. A total of 8908 patients with lung adenocarcinoma (LUAD) were identified. Among them, 5652 patients who had comprehensive sequencing results (gene panel ≥ 275) were selected for further analysis. Patients with unknown race, undefined and Pacific Island (only 3 patients) were excluded. Finally, 5360 patients were included in the study. The prevalence and distribution of genomic alteration cross all racial groups were analyzed. Results: Overall 5951 samples from 5360 patients were collected (85.7% white, 7.9% Asian, 4.7% black, 0.2% Native American and 1.4% other). Most patients have only one sample. The median mutation counts in white, black, Asian, Native American and others are 7, 6, 5, 5, 7 respectively (Kruskal–Wallis test, P< 0.001). Asian have significantly higher rates of insertion and deletions than other races (14.8% of Asian versus 9.8% of white, 10.7% of black, 10.4% of Native American, 11.1% of other; Pearson’s chi-square test, < 0.001). TP53, EGFR, KRAS and STK11 are the most frequent alterations in white, black and other. EGFR, TP53, KRAS and APC are the most frequent alterations in Asian. STK11 mutations are rare in both Asian and Native American. Native Americans have more alterations of LRP1B, ARID2 and ATM, although the patients’ number remains small. ATM and KEAP1 mutations are also common in white and black. EGFR is the highest discrepancy gene in racial distribution. 78.9% Asian, 47.7% black, 36.4% of native American had EGFR alteration in comparison to 29.6% in white (Fisher's exact test, P < 0.001). KRAS is the second highest discrepancy gene in racial distribution. 11.6% Asian, 26.3% black, 27.3% of Native American had KRAS alteration in comparison to 36.1% in white (Fisher's exact test, P< 0.001). Conclusions: Our study demonstrated the potential diversity of genomic alterations across all racial groups with potential impact on therapeutic decisions.

9058 Background: Lung Cancer is the leading cause of cancer related deaths in the USA. NSCLC comprises about 85% of lung cancer cases. Although timeliness of care in patients with NSCLC is considered an important aspect of quality care, there are conflicting data about its impact on clinical outcomes. The primary objective of this study is to determine if there is an association between TTI and survival in patients with NSCLC. Methods: In this retrospective study, we reviewed data from our multi-site Mayo Clinic Cancer Center registry and identified patients with newly diagnosed NSCLC from 2000 to 2016. TTI was calculated from time of diagnosis to time of first treatment (surgery, radiation therapy or systemic therapy). Analyses were performed by SAS software 9.4. Log-Rank test was used to compare survival. Cox regression multivariate model was used to evaluate the prognostic value of variables to survival. Results: 10010 patients (53% males and 47%) were reviewed. Median age at diagnosis was 70. Median TTI was 12 days for stage I, and 20 days for stage II, III and IV. We compared outcomes of patients with TTI > 20 days to TTI ≤20 days. Outcomes were stratified based on age, gender, grade, and stage. Median Overall Survival (OS) was significantly better for patients with TTI ≤20 days compared to TTI > 20 days (39.1 vs 28.6 months P-value < 0.0001). Further stratification, based on stage, showed significantly better OS for stage I and II patients with TTI ≤20 days compared to TTI > 20 days (103.4 vs. 63.9 months P-value < 0.0001 and 72.3 vs. 46.8 months P-value 0.0014 respectively). OS for stage III patients with TTI ≤20 days was not significantly different from patients with TTI > 20 days (30.6 vs. 28.5 months P-value 0.118). Interestingly, stage IV patients had worse OS if TTI ≤20 days compared to TTI > 20 days (8.3 vs. 12.8 months P-value < 0.0001). Conclusions: Our study showed an association between TTI and survival of patients with NSCLC. Shorter TTI was associated with better survival in stage I and II patients and worse survival in stage IV patients. Our study further highlights the controversy surrounding the topic of impact of timeliness of care on survival in patients with cancer, specifically NSCLC across different stages.

Abstract ABSTRACT Background: In 2014, the American Society of Hematology (ASH) established a practice improvement module (PIM) incorporating quality metrics for management of diffuse large B cell lymphoma (DLBCL). Such PIMs have allowed physicians to monitor the quality of care in their practice. We implemented a DLBCL quality improvement initiative (QII) at our institution in January, 2015. In an appraisal of this initiative, we reviewed the ASH PIM metrics and included several others to assess adherence to guidelines for treatment of DLBCL and to examine the need for institutional improvement. Methods: Patients who were newly diagnosed with DLBCL and received treatment at our institution from January 2006 through December 2017 were identified. Electronic medical records were reviewed for documentation of ASH PIM quality measures (e.g., key pathologic features of DLBCL, lymphoma staging, screening for hepatitis B virus (HBV) infection in patients receiving rituximab-based chemotherapy, etc). We also reviewed the proportion of patients who had assessment of prognosis by revised International Prognostic Index (r-IPI) score, testing for hepatitis C (HCV), HIV viral infections, chemotherapy education, and the addition of rituximab in the treatment regimen of CD20+ DLBCL. Results: Following implementation of the QII, our institution saw improvement in most quality metrics. Particularly significant were improvements in reporting of key molecular features (45.45% to 91.6%, P < 0.0001), screening for HBV (41.82% to 91.67%, P < 0.001) and HIV infections (33.94% to 87.5%, P < 0.0001). All patients post-QII had a PET-CT scan for staging of DLBCL and there was a significantly lower use of bone marrow biopsy (61.2% to 33.33%, P = 0.011). Conclusion: Implementation of a quality initiative and employing standardized metrics can aid in improving institutional quality of care for patients with newly diagnosed DLBCL, and allows opportunity to build and ensure better adherence to evolving national and professional patient care guidelines. Figure. Figure. Disclosures No relevant conflicts of interest to declare.

Abstract Background: DLBCL is the most common adult NHL and despite significant advancements, outcomes in ethnic minorities remain suboptimal. Factors responsible for these disparities in ethnic minorities, especially variability in clinical and pathological features with evaluation of patient-level data have not been studied. Methods: A multi-institutional database of DLBCL patients seen at Mayo Clinic in Florida, University of Miami and University of Southern California between 1996-2016 was developed. Patient demographics, clinical disease characteristics and details of DLBCL immunophenotype [CD10, MUM1, BCL6 (Han's classification), Ki 67, MYC, BCL2) were reviewed. Comparisons between Hispanic and Non-Hispanic patients were made by Chi-square, Fischer's exact and Signed rank tests, where applicable. Patients with missing data on a certain feature were not included in the statistical analysis of that specific characteristic. Results: A total of 966 DLBCL patients with 69 Hispanics and 752 non-Hispanics were identified. These included 52% males (N=36) and 48% females (N=33) in Hispanics versus 58% males (N=436) and 42% females (N=316) in Non-Hispanics (p=0.35). Median age at diagnosis was significantly lower at 61 years (range 27-89) in Hispanics versus 66 in non-Hispanics (p=0.014). Extranodal disease was seen significantly more commonly in Hispanics (74%) than in non-Hispanics (60%) (p=0.037). There was no significant difference in disease stage at presentation between the two cohorts (p=0.189) although the proportion of patients with stage III and IV disease was higher among Hispanics (80.4%) as compared to non-Hispanics (68.5%). Similarly there was no significant difference in presence of primary CNS DLBCL at diagnosis between the two groups (p=0.74). GCB phenotype per the Hans' classification was seen in 59% (N=29) in both, Hispanics and Non-Hispanics (N=241) (p=0.99). Similarly, the median ki67 index of 80% was seen in both cohorts (p=0.48). MYC was positive in 59% in Hispanics versus only 37.5% in non-Hispanics (p=0.024). BCL2 expression by itself and also combined BCL2 and MYC double expression were not significantly different between the two groups (p=0.58 and p=0.11, respectively). Median overall survival (OS) was 22.5 months in Hispanics compared 54.9 months in Non-Hispanics (p<0.0001) (Figure 1). Conclusion: Survival outcome disparities in racial and ethnic minorities have been previously reported from population-based analyses. Lack of patient-level clinical data makes these analyses hypothesis generating, but not conclusive. We confirmed some prior findings including younger age at diagnosis for Hispanics with DLBCL. We also reported greater incidence of extranodal as well as stage III or IV disease at the time of presentation among Hispanics which may contribute to poor outcomes in this population. From DLBCL pathology standpoint, we found increased expression of MYC among Hispanics but no other significant immunohistochemical differences including double expression or non-GCB phenotype. The inferior OS despite uniform treatment practices at large Cancer Centers suggest multifactorial influences on patient outcomes which may at least in part include some of the differences we report here. Disclosures Ailawadhi: Pharmacyclics: Research Funding; Janssen: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy.