Adjei, Alex A.

1043 Background: In estrogen receptor (ER) positive MBC, mutations (e.g. ESR1), identified from tumor biopsies or cfDNA, confer resistance. The concordance between mutations observed in tumor and cfDNA and the implications for response to Z-endoxifen, a potent anti-estrogen, are unknown. Methods: We previously conducted a phase I trial of Z-endoxifen in endocrine refractory, ER positive MBC. Seven dose levels were considered ranging from 20 to 160 mg/day followed by expansion cohorts (EC) of 40, 80, and 100 mg/day. Pretreatment blood samples (all pts) and fresh tumor biopsies (EC) were collected prospectively. Tumor and cfDNA were evaluated by targeted NGS. Results: 41 pts (38 evaluable) were enrolled. Prior endocrine therapy included aromatase inhibitors (37/38, 97%), fulvestrant (22/38, 58%) and tamoxifen (26/38, 68%). Substantial endoxifen exposure without DLTs at doses above 80 mg/day led to a halt in dose escalation and opening of the EC. Overall clinical benefit (stable > 6 months [7 pts.] or partial response by RECIST criteria [3 pts.]) rate was 26.3% (95%CI: 13.4-43.1%). cfDNA was obtained from 36 pts and mutations were identified in 13 (36%) including ESR1 [ Y537N or D538G] (5), PIK3CA [ H1047R or E542K] (8), TP53 [ K132R, R248Q, R267Q, or H179Y] (4), AKT ( Q79K) (1), and KRAS ( G12D) (1). In 5 pts with cf ESR1 mutations, 4 had additional cfDNA mutations including PIK3CA (3), and TP53 (1). PFS was shorter in pts with cfDNA mutations relative to those without (median: 61 vs.132 days; log-rank p = 0.021). Discordance was observed between tumor and cfDNA mutations where 3/7 PIK3CA tumor mutations were detected by cfDNA, 1/2 TP53 tumor mutations were detected by cfDNA, and 0/1 AKT tumor mutations were detected by cfDNA. Conversely, 2 pts had cfDNA mutations (either ESR1, TP53 or AKT) undetected in tumor. Conclusions: The absence of cfDNA mutations in patients with endocrine resistant, MBC treated with Z-Endoxifen was associated with significantly longer PFS. Given the discordance between tumor and cfDNA sequence data, future studies must determine which approach maximizes prognosis and prediction of benefit for estrogen-targeted therapy. Clinical trial information: NCT01327781.

2533 Background: Many cancer clinical trials (CT) lack appropriate representation of specific patients populations, limiting the generalizability of the evidence obtained. Therefore, we determined the representation of ethnic minorities in oncology CT. Methods: Enrollment data from all therapeutic trials reported as completed in clinicaltrial.gov from 2003 to 2016 were analyzed. CT in rare cancers (< 1% incidence) or with recruitment outside of the US were excluded. Enrollment fraction (EF) was defined as the number of enrollees divided by the 2013 SEER database cancer prevalence. Chi-square test was used to estimate differences in categorical data. Results: Out of 1,012 CT, 310 (31%) reported ethnicity with a total of 55689 enrollees. Distribution by race and comparison with data from 1996-2002, US cancer prevalence and US census are described in the Table. Participation in CT varied significantly across ethnic groups, non-Hispanic Whites (NHW) were more likely to be enrolled in CT (EF of 1.2%) than African Americans (EF of 0.7%, p < 0.001) and Hispanics (EF of 0.4%, p<0.001). A decrease in African Americans (AA) and Hispanics (H) enrollment was observed when compared with historical data from 1996 to 2002. Hispanics were less represented in breast and prostate cancer CT contributing only to 3% and 1.5% of the study population; African Americans were less represented in lung (5.4%) and renal cell carcinoma (3%) trials. Asians were well represented and their recruitment doubled over the past 14 years (2% vs 5.3%). Conclusions: African Americans and Hispanics were less likely to be enrolled in CT. Comparing with historical data; we observed a decrease in minorities’ recruitment in the past 14 years. This change could be attributed to the increased complexity of CT and mandatory molecular testing as many minorities lack access to institutions with genetic testing capacity. Future trials should take extra measures to recruit participants that adequately represent the U.S. cancer population. [Table: see text]

Abstract Background Treatment of non‐small‐cell lung cancer (NSCLC) has been rapidly advancing over the last decade. Academic centers are considered equipped with better expertise. NSCLC outcome trends in novel therapeutic era and impact of initial treatment at academic centers have not been reported. Methods The National Cancer Database (NCDB) was used to identify NSCLC incident cases from 2004 to 2013. Overall survival (OS) was plotted by year of diagnosis and type of initial treatment center, accounting for several factors available in NCDB. Results A total of 1 150 722 NSCLC patients were included and separated by initial treatment center type (academic: 31.5%; nonacademic: 68.5%). Median follow‐up and OS for all patients were 11.8 months (range: 0‐133.6 months) and 13.1 months (95% CI: 13.08‐13.17), respectively. Median OS improved significantly for those diagnosed in 2010‐2013 (14.8 months [95% CI: 14.7‐14.9]) as compared to 2004‐2009 (12.4 months [95% CI: 12.3‐12.5]) ( P < 0.001). Treatment at academic centers was associated with improved OS (multivariate HR for OS = 0.929 [95% CI: 0.92‐0.94], P < 0.0010). Four‐year OS for academic and nonacademic cohorts was 28.5%% and 22.1%, respectively ( P < 0.001), and the difference was more pronounced in stage I to III NSCLC. Conclusion In this largest analysis, thus far, NSCLC survival has improved over time, and type of initial treatment center significantly influences survival. Identifying and removing barriers to obtaining initial treatment of NSCLC at academic medical centers could improve OS.

Abstract Background: In stage IV non-small cell lung cancer (NSCLC), survival has significantly improved with the use of novel therapies and better supportive care. Despite such trends, it has been noted that patients (pts) frequently refuse cancer treatment. Therefore, we explored the factors associated with treatment refusal in pts with stage IV NSCLC. Methods: Utilizing the National Cancer Database (NCDB), we identified all incident cases with stage IV NSCLC from 2004 to 2014. Patients who received cancer treatment outside of the reporting facility or died before receiving treatment were excluded. Multivariable logistic regression models were used to determine associations with treatment refusal. Results: A total of 341,993 pts were identified. On average, 5.4% of pts refused radiation therapy and 10.3% refused chemotherapy despite provider recommendations. The proportion of pts refusing radiation and chemotherapy increased over the study period from 4.2% to 7.3% and 7.9% to 15%, respectively (p&lt;0.001 for both). In multivariable analysis, men were less likely to refuse radiation or chemotherapy compared to women (OR: 0.82, 95%CI: 0.76-0.83, p&lt;0.001; OR: 0.84, 95%CI: 0.81-0.86, p&lt;0.001, respectively). Factors associated with radiation therapy refusal included: Medicaid or Medicare as primary insurance (OR: 1.95, 95%CI: 1.76-2.15, p&lt;0.001; OR: 1.25, 95%CI: 1.17-1.34, p&lt;0.001, respectively) or a &gt;2 Charlson Comorbidity Index (OR: 1.97, 95%CI: 1.85-2.10, p&lt;0.001). Moreover, receiving care at an academic center (OR: 0.57, 95%CI: 0.53-0.62, p&lt;0.001) was associated with less likelihood of refusing radiation. Regarding chemotherapy, uninsured pts (OR: 2.45, 95%CI: 2.26-2.66, p&lt;0.001), pts with Medicaid as primary insurance (OR: 2.17, 95%CI: 2.03-2.32, p&lt;0.001) or with a high comorbidity index (OR: 1.76, 95%CI: 1.68-1.84, p&lt;0.001) were more likely to refuse chemotherapy. Contrary to findings from previous studies, Non-Hispanic Blacks and Hispanics were less likely to refuse chemotherapy compared to non-Hispanic whites (OR: 0.86, 95%CI: 0.82-0.91, p&lt;0.001; OR: 0.78, 95%CI: 0.72-0.89, p&lt;0.001). Patients receiving care at an academic center and residing in high income neighborhoods were less likely to refuse chemotherapy (OR: 0.76, 95%CI: 0.72-0.80, p&lt;0.001; OR: 0.76, 95%CI: 0.71-0.81, p&lt;0.001, respectively). Distance from residence to treating facility and living in a rural county did not affect treatment refusal. Conclusions: Socioeconomic factors rather than race/ethnicity appear to influence refusal of cancer treatment in pts with stage IV NSCLC in the NCDB. Assessing socioeconomic challenges should be an essential part of patients' evaluation when discussing treatment options. Citation Format: Narjust Duma, Urshila Durani, Ryan Frank, Jonas Paludo, Gustavo Westin, Yanyan Lou, Leventakos Konstantinos, Julian Molina, Ronald Go, Aaron Mansfield, Sikander Ailawadhi, Alex Adjei. Influence of sociodemographic factors on treatment decisions in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4230.

Although immune checkpoint inhibitors have resulted in durable clinical benefits in a subset of patients with advanced cancer, some patients who did not respond to initial anti–PD-1 therapy have been found to benefit from the addition of salvage chemotherapy. However, the mechanism responsible for the successful chemoimmunotherapy is not completely understood. Here we show that a subset of circulating CD8 + T cells expressing the chemokine receptor CX3CR1 are able to withstand the toxicity of chemotherapy and are increased in patients with metastatic melanoma who responded to chemoimmunotherapy (paclitaxel and carboplatin plus PD-1 blockade). These CX3CR1 + CD8 + T cells have effector memory phenotypes and the ability to efflux chemotherapy drugs via the ABCB1 transporter. In line with clinical observation, our preclinical models identified an optimal sequencing of chemoimmunotherapy that resulted in an increase of CX3CR1 + CD8 + T cells. Taken together, we found a subset of PD-1 therapy–responsive CD8 + T cells that were capable of withstanding chemotherapy and executing tumor rejection with their unique abilities of drug efflux (ABCB1), cytolytic activity (granzyme B and perforin), and migration to and retention (CX3CR1 and CD11a) at tumor sites. Future strategies to monitor and increase the frequency of CX3CR1 + CD8 + T cells may help to design effective chemoimmunotherapy to overcome cancer resistance to immune checkpoint blockade therapy.

Purpose: Many cancer clinical trials lack appropriate representation of specific patient populations, limiting their generalizability. Therefore, we determined the representation of ethnic minorities and women in cancer clinical trials. Methods: Enrollment data from all therapeutic trials reported as completed in ClinicalTrials.gov from 2003 to 2016 were analyzed. We calculated enrollment fractions (EFs) for each group, defined as the number of enrollees divided by the 2013 Surveillance, Epidemiology, and End Results (SEER) database cancer prevalence. Results: Of 1,012 clinical trials, 310 (31%) reported ethnicity with a total of 55,689 enrollees. Participation varied significantly across ethnic groups. Non-Hispanic whites were more likely to be enrolled in clinical trials (EF, 1.2%) than African Americans (EF, 0.7%; P < .001) and Hispanics (EF, 0.4%; P < .001). A decrease in African American (6% v 9.2%) and Hispanic (2.6% v 3.1%) enrollment was observed when compared with historical data from 1996 to 2002. Younger patients (age younger than 65 years) were more likely to be enrolled in clinical trials than the elderly (64% v 36%; P < .001). Low recruitment of female patients was observed in clinical trials for melanoma (35%), lung cancer (39%), and pancreatic cancer (40%). Conclusion: We observed a decrease in recruitment of minorities over the past 14 years compared with historical data. African Americans, Hispanics, and women were less likely to be enrolled in cancer clinical trials. Future trials should take extra measures to recruit participants that adequately represent the US cancer population.