Ailawadhi, Sikander

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.

Abstract Multiple myeloma (MM) is twice as common in African Americans (AA) compared to European Americans (EA). The reported familial clustering and the elevated MM risk among first-degree relatives of cases implicate genetic susceptibility. Previous genome-wide association studies (GWAS) in EA have identified 16 novel risk loci. In this study, we tested the generalizability of the established risk alleles to AA and conducted a meta-GWAS analysis using two sets of AA to identify additional novel common MM risk variants. In the first study, we genotyped 1,305 incident AA MM cases from the African American Multiple Myeloma Study (AAMMS) using the Illumina HumanCore GWAS array and compared them to 7,078 AA controls from the African Ancestry Prostate Cancer Consortium (AAPC) and African Ancestry Breast Cancer Consortium (AABC) using the Illumina 1M-Duo. In the second study, 95 additional AAMMS cases and 435 AA MM cases from the University of Arkansas for Medical Sciences (UAMS) were genotyped using the Illumina MegaBead Chip and compared to 2,390 AA controls from the Multiethnic Cohort. The Haplotype Reference Consortium (HRC) was used to impute the overlapping typed SNPS from each GWAS case and control set together. Per-allele risk associations were tested for 8,715,278 overlapping genotyped and imputed variants with &gt;1% frequency and &gt;0.8 imputation score using unconditional logistic regression in both sets, and the combined effects were estimated using a fixed-effect meta-analysis. Of the 16 reported risk loci discovered in EA, directional consistency was present for 15 variants; eight of these replicated at nominal significance p&lt;0.05, with the most statistically significant variant being rs4487645 at 7p15.3 (OR=1.38, p=3.56×10-6). AA individuals with polygenic risk scores from these 16 variants (PRS) in the top 10% stratum had a 1.44-fold increased MM risk compared to those with a PRS in the 25th -75th percentiles. Additionally, we identified three suggestive novel loci located at 12q12, 9p24.3 and 9p13.1 at p&lt;1×10-6, with ORs ranging from 1.25-1.55, but none reached genome-wide significance. The variant at 9p24.3 is located in an intron in the KANK1 gene and a correlated SNP in EAs (r2=0.5) is strongly associated with gene expression in neoplastic plasma cells (unpublished, Weinhold and Morgan). Our study replicated most of the reported risk loci discovered among EA, demonstrated that a PRS constructed using the 16 reported risk alleles was associated with MM risk, and provides suggestive evidence for additional loci associated with MM risk in AAs. Citation Format: Zhaohui Du, Chi Song, Kristin Rand, Niels Weinhold, David Van Den Berg, Amie Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward S. Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William Blot, John David Carpten, Antoinette Stroup, Andrew Olshan, Wei Zhang, African Ancestry Breast & Prostate Consortium, Stephen Chanock, Jayesh Mehta, Graham A. Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Loic LeMarchand, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association studies of multiple myeloma among African Americans [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 223.

SummaryCD38 is expressed on Waldenström macroglobulinaemia (WM) cells, but its role as a therapeutic target remains undefined. With recent approval of the anti‐CD38 monoclonal antibody, daratumumab (Dara), we hypothesized that blocking CD38 would be lethal to WM cells.In vitroDara treatment of WM cells (including ibrutinib‐resistant lines) elicited antibody‐dependent cellular cytotoxicity (ADCC), complement‐dependent cytotoxicity (CDC), antibody‐dependent cell phagocytosis (ADCP) and direct apoptosis.In vivo, Dara treatment was well tolerated and delayed tumour growth in RPCI‐WM1‐xenografted mice. CD38 is reported to augment B‐cell receptor (BCR) signalling; we noted that Dara significantly attenuated phosphorylated SYK, LYN, BTK, PLCγ2, ERK1/2, AKT, mTOR, and S6 levels, and this effect was augmented by cotreatment with ibrutinib. Indeed, WM cells, including ibrutinib‐resistant WM cell lines treated with the ibrutinib + Dara combination, showed significantly more cell death through ADCC, CDC, ADCP and apoptosis relative to single‐agent Dara or ibrutinib. In summary, we are the first to report thein vitroandin vivoanti‐WM activity of Dara. Furthermore, we show a close connection between BCR and CD38 signalling, which can be co‐targeted with ibrutinib + Dara to induce marked WM cell death, irrespective of acquired resistance to ibrutinib.

Background: Palliative care has been increasingly recognized as an important part of cancer care but remains underutilized in patients with solid cancers. There is a current gap in knowledge regarding why palliative care is underutilized nationwide. Objective: To identify the factors associated with palliative care use among deceased patients with solid cancer tumors. Methods: Using the 2016 National Cancer Data Base, we identified deceased patients (2004-2013) with breast, colon, lung, melanoma, and prostate cancer. Data were described as percentages. Associations between palliative care use and patient, facility, and geographic characteristics were evaluated through multivariate logistic regression. Results: A total of 1 840 111 patients were analyzed; 9.6% received palliative care. Palliative care use was higher in the following patient groups: survival >24 months (17% vs 2%), male (54% vs 46%), higher Charlson-Deyo comorbidity score (16% vs 8%), treatment at designated cancer programs (74% vs 71%), lung cancer (76% vs 28%), higher grade cancer (53% vs 24%), and stage IV cancer (59% vs 13%). Patients who lived in communities with a greater percentage of high school degrees had higher odds of receiving palliative care; Central and Pacific regions of the United States had lower odds of palliative care use than the East Coast. Patients with colon, melanoma, or prostate cancer had lower odds of palliative care than patients with breast cancer, whereas those with lung cancer had higher odds. Conclusions: Palliative care use in solid cancer tumors is variable, with a preference for patients with lung cancer, younger age, known insurance status, and higher educational level.