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Soft-tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that arise from the oncogenic transformation of mesenchymal tissue. There are over 100 distinct STS histological and molecular subtypes with unique clinical, therapeutic, and prognostic features with variable responses to therapy regimens. Given the quality-of-life concerns and limited efficacy with current regimens, including cytotoxic chemotherapy, there is a need for novel therapies and regimens to treat advanced STS. Although immune checkpoint inhibitors have demonstrated significant improvements in survival outcomes in other cancer types, there remains ambiguous data on the impact of immunotherapy in sarcoma. Biomarkers like PD-1/PD-L1 are not always predictive of outcomes. Therefore, researching emerging novel therapies, such as CAR-T and adoptive cell therapies, is critical to understanding STS biology, STS tumor immune microenvironment immunomodulatory strategies that improve immune response, and survival outcomes. We discuss the underlying biology of the STS tumor immune microenvironment, immunomodulatory strategies that augment pre-existing immune responses, and novel approaches to develop sarcoma-specific antigen-based therapies.

Immune checkpoint inhibitors (ICIs) are associated with a unique set of immune-related adverse events (irAEs). Few studies have evaluated the risk factors and outcomes of patients who develop ICI-induced hepatitis (ICIH).We utilized an institutional database of patients with advanced cancers treated with ICI to identify patients with ICIH. irAEs were graded using the Common Terminology Criteria for Adverse Events v4. Overall survival (OS) was calculated from the date of ICI to death from any cause or the date of the last follow-up. OS with 95% confidence intervals were estimated using the Kaplan-Meier method and stratified by the occurrence of ICIH.We identified 1096 patients treated with ICI. The most common ICIs were PD1/L1 (n = 774) and CTLA-4 inhibitors (n = 195). ICIH occurred among 64 (6%) patients: severity was grade 3 in 30 and ≥ grade 3 in 24 patients (3.1% overall). Median time to ICIH was 63 days. ICIH was more frequent in women (p = 0.038), in patients treated with combination ICIs (p 0.001), and when given as first-line therapy (p = 0.018). Occurrence of ICIH was associated with significantly longer OS, median 37.0 months (95% CI 21.4, NR) compared to 11.3 months (95% CI 10, 13, p 0.001); there was no difference in OS between patients with ≥ grade 3 ICIH vs grade 1-2.Female sex, combination immunotherapy, and the first line of immunotherapy were associated with ICIH. Patients with ICIH had improved clinical survival compared to those that did not develop ICIH. There is a need for prospective further studies to confirm our findings.

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICIs). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA-seq was conducted on the formalin-fixed paraffin-embedded (FFPE) tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic}tool. The 71 patients with metastatic melanoma ranged in age from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy responsive versus non-responsive tumors. Responders showed significant enrichment of several microbes includingFusobacterium nucleatum, and non-responders showed enrichment of fungi, as well as several bacteria. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs.SignificanceWe analyzed the tumor microbiome and interactions with genes and pathways in metastatic melanoma treated with immunotherapy, and identified several microbes associated with immunotherapy response and immune-related gene expression signatures. Machine learning models that combined microbe abundances and gene expression outperformed models using either dataset alone in predicting immunotherapy responses.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10–20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, MEGA, to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of 9 cancer centers in the Oncology Research Information Exchange Network (ORIEN). This package has 3 unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2704 tumor RNA-seq samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors.SIGNIFICANCEStudying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep-learning tool, microbial graph attention (MEGA), to refine the organisms that interact with tumors.

Objectives Immune checkpoint inhibitor immunotherapy (IO) is revolutionizing cancer care but can lead to significant toxicity. This study seeks to describe potential risk factors for immune-related adverse events (irAEs) specifically among older adults. Materials and Methods This was a retrospective study at a single academic comprehensive cancer center based on chart review data abstracted by physicians. For patients aged ≥70 years, frequency, type, and grade of irAEs and their association with baseline patient demographics, comorbidities, mobility, and functional status were characterized using bivariate analysis. Based on those results, multivariable logistic regressions were constructed to model the association between these characteristics with any grade and grade 3 or higher irAEs. Results Data were analyzed for 238 patients aged ≥70 years who received IO for mostly (≥90%) advanced cancer between 2011 and 2018. Thirty-nine percent of older adults experienced an irAE and 13% experienced one that was grade 3 or higher. In the multivariable analysis, depression was associated with an increased incidence of any grade irAE, while decreased life-space mobility was associated with an increased incidence of grade ≥3 irAEs. Conclusion Most characteristics of special interest among older adults, include fall risk, weight loss, cognitive limitations, and hearing loss, were not associated with irAEs in our study. However, decreased life-space mobility and depression are potential risk factors for IO toxicity among older adults with advanced cancer. Interventions designed to evaluate and mitigate modifiable risk factors for treatment-related toxicity are needed, and the results of this study may be useful for guiding those efforts.

Background: The response rates to immune checkpoint inhibitors (ICI) remain low (13-20%) in metastatic head and neck cancer patients and better understanding of factors predictive of response to these agents is urgently needed. Here we explore the impact of smoking status, marijuana use and alcohol on treatment outcomes in recurrent-metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) treated with ICI. Methods: We performed a retrospective analysis of 201 R/M HNSCC patients treated with ICI between January 15th 2016 and April 9th 2020 at a single institution. Results: Gender: 154 male (77%), 47 female (23%). Median age 61 (IQR: 55-68). ICI drug: pembrolizumab 100 (50%), nivolumab 91 (45%), nivolumab+ipilimumab 10 (5%). Line of therapy: first: 98 (49%), second and beyond: 103 (51%). Tumor site: oropharynx 84 (42%), oral cavity 45 (22%), larynx 26 (13%), other sites 46 (23%). p16 tumor status: negative 132 (66%), positive 69 (34%). Smoking status: former 111 (55%), never 54 (27%), current 36 (18%), median pack-year 18 (IQR: 0-37). Alcohol use: yes 110 (55%), no 91 (54%). Marijuana use: yes 47 (23%), no 154 (77%). Overall response rate: 36 (18%). Median OS: 12 months (95% CI: 9.4-14.8). Tobacco: former (HR: 0.75, 95% CI: 0.50, 1.11), current (HR: 0.58, 95% CI: 0.33, 1.02). Marijuana: yes (HR: 0.93, 95% CI: 0.58, 1.49). Alcohol: yes (HR: 1.04, 95% CI: 0.72, 1.49). Conclusion: In our cohort, smoking status, marijuana use and alcohol consumption did not have a statistically significant impact on OS in patients with R/M HNSCC treated with ICI. Trial registration: retrospectively registered.

OBJECTIVES: Despite growing evidence that checkpoint inhibitor immunotherapy (IO) toxicity is associated with improved treatment response, the relationship between immune-related adverse events (irAEs) and overall survival (OS) among older adults [age ≥ 70 years (y)] remains unknown. The study goal was to determine differences in OS based on age and ≥ grade 3 (G3) irAEs. MATERIALS AND METHODS: This was a retrospective cohort study of 673 patients with advanced cancer. Patients who received ≥1 dose of IO at our institution from 2011–2018 were eligible. The primary outcome was OS from the start of first line of IO treatment, compared between four patient groups stratified by age and ≥G3 irAEs with adjustment for patient characteristics using a Cox proportional hazards model. RESULTS AND CONCLUSION: Among all 673 patients, 35.4% were ≥70y, 39.8% had melanoma, and 45.6% received single-agent nivolumab. Incidence and types of ≥G3 irAEs did not differ by age. Median OS was significantly longer for all patients with ≥G3 irAEs (unadjusted 21.7 vs. 11.9 months, P=0.007). There was no difference in OS among patients ≥70y with ≥G3 irAEs (HR 0.94, 95% CI 0.61–1.47, P=0.79) in the multivariable analysis. Patients

Introduction: Adrenocortical cancer (ACC) is a rare and aggressive disease with a median survival of 14–17 months and 5-year survival of around 20% for advanced disease. Emerging evidence of sub-gr...

BACKGROUND: Checkpoint inhibitor pneumonitis (CIP) is an immune related adverse event that may complicate treatment with immune checkpoint inhibitors (ICI) and can cause significant morbidity. We sought to identify predictors for the development of CIP, and whether the use of inhaled corticosteroids (ICS) at time of ICI may be protective. METHODS: Patients with advanced cancer treated with ICI from 2011 and 2018 were included in this study. CIP attribution to ICI was determined by treating physician at time of diagnosis. Predictors were assessed by univariate and multivariable Cox proportional hazard models. RESULTS: We identified 837 pts treated with ICI, of whom 30 (3.6%) developed grade 2 or higher CIP. 82 patients (9.8%) were receiving ICS at time of ICI and had increased risk of developing CIP with hazard ration (HR) of 4.22 (95% CI: 1.93-9.21, p

Background The microbiome has been shown to affect the response to Immune Checkpoint Inhibitors (ICIs) in a small number of cancers and in preclinical models. Here, we sought to broadly survey cancers to identify those in which the microbiome may play a prognostic role using retrospective analyses of patients with advanced cancer treated with ICIs. Methods We conducted a retrospective analysis of 690 patients who received ICI therapy for advanced cancer. We used a literature review to define a causal model for the relationship between medications, the microbiome, and ICI response to guide the abstraction of electronic health records. Medications with precedent for changes to the microbiome included antibiotics, corticosteroids, proton pump inhibitors, histamine receptor blockers, non-steroid anti-inflammatories and statins. We tested the effect of medication timing on overall survival (OS) and evaluated the robustness of medication effects in each cancer. Finally, we compared the size of the effect observed for different classes of antibiotics to taxa that have been correlated to ICI response using a literature review of culture-based antibiotic susceptibilities. Results Of the medications assessed, only antibiotics and corticosteroids significantly associated with shorter OS. The hazard ratios (HRs) for antibiotics and corticosteroids were highest near the start of ICI treatment but remained significant when given prior to ICI. Antibiotics and corticosteroids remained significantly associated with OS even when controlling for multiple factors such as Eastern Cooperative Oncology Group performance status, Charlson Comorbidity Index score, and stage. When grouping antibiotics by class, β-lactams showed the strongest association with OS across all tested cancers. Conclusions The timing and strength of the correlations with antibiotics and corticosteroids after controlling for confounding factors are consistent with the microbiome involvement with the response to ICIs across several cancers.

This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Short Talks from Proffered Abstracts section (PR004) of the Conference Proceedings. Citation Format: Daniel Spakowicz, Rebecca Hoyd, Caroline E. Wheeler, Nyelia Williams, Amna Bibi, Marium Husain, Srichandhana Rajamouli, Shankar Suman, Joseph Amann, Madison Grogan, Pooja Vibhakar, Dwight H. Owen, David P. Carbone, Ashley Rosko, Christin E. Burd, Carolyn J. Presley. Older adult-specific microbes correlate with treatment response and markers of T-cell senescence in NSCLC [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr A021.

The gut microbiome changes with age and affects many aspects of human health, including response to cancer treatments. Cancer survival rates have improved with new treatment options, including immune checkpoint blockade (ICB); however, the objective response rate remains low. Manipulation of the microbiome is a promising approach to improving cancer outcomes, but the effect of age is understudied. Here, we sought to understand whether (1) specific microbes are associated with treatment response in older adults with non-small cell lung cancer (NSCLC) and (2) whether these microbes are the same as for younger adults. Next, we explored the causal effects of the microbiome on ICB response in mouse models and the relationship with blood-based markers of T-cell senescence. We conducted a prospective cohort study of adults ≥60 years with a new diagnosis of NSCLC who received any treatment modality. Stool was collected, and metagenomic whole-genome shotgun sequencing was performed. Blood T-cells were isolated, the RNA purified and then assessed for markers of senescence by nanostring. Response to treatment was determined by RECIST v1.1 criteria. Generalized linear regression was used to relate baseline microbiome abundances to treatment response and non-parametric correlations associated with CDKN2A (p16) expression to microbe abundances. To assess the causal role of the gut microbiome in ICB response, we gavaged gut microbiome samples from responders and non-responders into C57BL/6 mice to create human-microbiome avatar models. The mice were then injected with MC38 cancer cells and treated with anti-PD1 or isotype control antibodies, and tumor volume was measured over time. Biospecimens and best response data at three months were captured from 23 patients, of which five had a complete response, eight had a partial response, eight had stable disease, and two had progressive disease. Over 50 microbes were associated with a response after p-value adjustment. Responder stool was enriched for microbes associated with youth and ICB response (Bifidobacterium adolescentis, p = 2.64e-20). However, microbial taxa associated with response differed from those reported in younger populations (Firmicutes sp. CAG 145, p = 1.58e-20, Oscillibacter sp. 57-20, p = 7.96e-24). Stool from non-responders (NRs) was enriched in taxa previously linked to treatment-related toxicities and shorter progression-free survival (Streptococcus lutetiensis, p = 4.55E-24) but also contained microbes previously linked to response in younger adults (e.g., Roseburia sp. CAG 309, p = 5.16e-15). The T cell senescence marker, p16, correlated with the most enriched taxon in non-responders NRs (Streptococcus thermophilus, r = 0.45, p = 0.02), suggesting a connection between immune aging and the microbiome. Preliminary fecal transplant studies in mice showed improved ICB response in mice engrafted with stool from responders versus non-responders. Together, these data identify potential differences in the gut microbiomes of young and older adult NSCLC patients who respond to ICB. Citation Format: Daniel Spakowicz, Rebecca Hoyd, Caroline E. Wheeler, Nyelia Williams, Amna Bibi, Marium Husain, Srichandhana Rajamouli, Shankar Suman, Joseph Amann, Madison Grogan, Pooja Vibhakar, Dwight H. Owen, David P. Carbone, Ashley Rosko, Christin E. Burd, Carolyn J. Presley. Older adult-specific microbes correlate with treatment response and markers of T-cell senescence in NSCLC [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr PR004.

BackgroundImmune checkpoint inhibitor-associated acute kidney injury (ICPi-AKI) has emerged as an important toxicity among patients with cancer.MethodsWe collected data on 429 patients with ICPi-AKI and 429 control patients who received ICPis contemporaneously but who did not develop ICPi-AKI from 30 sites in 10 countries. Multivariable logistic regression was used to identify predictors of ICPi-AKI and its recovery. A multivariable Cox model was used to estimate the effect of ICPi rechallenge versus no rechallenge on survival following ICPi-AKI.ResultsICPi-AKI occurred at a median of 16 weeks (IQR 8–32) following ICPi initiation. Lower baseline estimated glomerular filtration rate, proton pump inhibitor (PPI) use, and extrarenal immune-related adverse events (irAEs) were each associated with a higher risk of ICPi-AKI. Acute tubulointerstitial nephritis was the most common lesion on kidney biopsy (125/151 biopsied patients [82.7%]). Renal recovery occurred in 276 patients (64.3%) at a median of 7 weeks (IQR 3–10) following ICPi-AKI. Treatment with corticosteroids within 14 days following ICPi-AKI diagnosis was associated with higher odds of renal recovery (adjusted OR 2.64; 95% CI 1.58 to 4.41). Among patients treated with corticosteroids, early initiation of corticosteroids (within 3 days of ICPi-AKI) was associated with a higher odds of renal recovery compared with later initiation (more than 3 days following ICPi-AKI) (adjusted OR 2.09; 95% CI 1.16 to 3.79). Of 121 patients rechallenged, 20 (16.5%) developed recurrent ICPi-AKI. There was no difference in survival among patients rechallenged versus those not rechallenged following ICPi-AKI.ConclusionsPatients who developed ICPi-AKI were more likely to have impaired renal function at baseline, use a PPI, and have extrarenal irAEs. Two-thirds of patients had renal recovery following ICPi-AKI. Treatment with corticosteroids was associated with improved renal recovery.

Background A low absolute lymphocyte/monocyte ratio (LMR) in the peripheral blood is associated with poor prognosis in various cancers; however, its role as a predictive biomarker has not been well defined in the era of treatment with immune checkpoint inhibitors (ICI). Methods We queried a database of advanced cancer patients treated with at least one dose of ICI from 2011 to 2017 to study the association of LMR with overall survival (OS). We calculated LMR at baseline and a median of 21 days after the first cycle of ICI (on-treatment LMR), and defined low if

Background The neutrophil to lymphocyte ratio (NLR) is known to be prognostic for patients with advanced cancers treated with immune checkpoint inhibitors (ICI), but has generally been evaluated as a single threshold value at baseline. We evaluated NLR at baseline and within first month during treatment in patients who received ICI for advanced cancer to evaluate the prognostic value of baseline and of changes from baseline to on-treatment NLR. Methods A retrospective review of patients with advanced cancer treated with ICI from 2011 to 2017 at the Ohio State University was performed. NLR was calculated at the initiation of ICI and repeated at median of 21 days. Overall survival (OS) was calculated from the initiation of ICI to date of death or censored at last follow-up. Significance of Cox proportional hazards models were evaluated by log-rank test. Calculations were performed using the survival and survminer packages in R, and SPSS. Results 509 patients were identified and included in the analysis. Patients with baseline and on-treatment NLR

e13623 Background: Climate change is one of the largest threats to human health and greenhouse gas (GHG) emissions are a substantial component of climate change. In the U.S., the healthcare industry accounts for an estimated 8.5% of GHG emissions, equating to the loss of 470,000 disability-adjusted life-years annually. Cancer care encapsulates a significant portion of hospital resources and climate change has disproportionate effects on cancer patients. Therefore, it is imperative and urgent that cancer centers actively engage in reducing healthcare related GHG emissions. In this systematic analysis and comprehensive review, we reviewed publicly accessible sustainability plans of National Cancer Institute (NCI)-designated Cancer Centers and their affiliated organizations to understand the involvement Cancer Centers have in their organization's sustainability efforts. Methods: We reviewed 64 NCI designated Cancer Centers, using the first 20 results of a Google search with terms: “Hospital X AND (climate action plan OR climate change OR sustainability plan OR carbon neutral)” and hospital homepages to identify publicly accessible sustainability plans for each organization. We reviewed the plans, performed a Google search/Cancer Center homepage search and messaged sustainability plan developers to identify involvement of the hospital and Cancer Center. We identified which hospitals assigned sustainability personnel. We performed a student’s t-test to assess for a correlation between incidence of lung cancer in a state and presence of a sustainability plan for that state’s Cancer Center. Data was collected by one reviewer, independently validated by a separate reviewer and differences were resolved by a joint data review. Results: Amongst the 65 Cancer Centers and organizations reviewed, 55 (36 university, 12 hospital, 7 joint) had publicly available sustainability plans. Of which, 31% (11/36) of university plans explicitly mentioned an affiliated hospital as part of the sustainability plan. Two Cancer Centers (3%) had independent sustainability plans and 7 (11%) centers mentioned sustainability on their homepage. 77% (23/30) of hospitals with sustainability plans identified sustainability personnel. We did not find an association between the existence of Cancer Center sustainability plan and that state’s lung cancer incidence rates (p = 0.932). Conclusions: In this review and analysis of NCI-designated Cancer Center sustainability plans, we found that while most centers’ affiliated organizations have publicly accessible sustainability plans, the majority (86%) of centers do not independently report on their sustainability efforts. These findings highlight a pressing need to increase engagement between Cancer Centers and their organizations regarding sustainability plans, and a need for greater transparency in publicizing sustainability plans.

11578 Background: Despite immunotherapy’s promise in oncology, its use for sarcoma remains challenging. There are no sarcoma-specific biomarkers for immune checkpoint inhibitors (ICI). Previously, we reported our institutional experience highlighting ICI activity in 29 patients with sarcoma. In this updated study, we further explore responses to ICI based on ICI regimen and other covariates to identify significant clinical factors in sarcoma outcomes. Methods: Patients in the Ohio State University Sarcoma clinics were enrolled in the Sarcoma Retrospective ICI database from January 1, 2015 through November 1, 2021. Data included treatment regimen (single agent ICI or ICI+combination) along with covariates: stage, age, gender, histology, change in neutrophil-to-lymphocyte ratio (NLR), number of cycles of ICI and immune-related adverse events (irAE). ICI+combination was further categorized into ICI+chemotherapy, ICI+radiation, ICI+surgery or ICI+multiple (more than 2 modalities). Statistical analysis included log rank tests and proportional hazard regression. The primary objective was to evaluate overall survival (OS) and progression-free survival (PFS). Results: One hundred and thirty-five patients met inclusion criteria. We demonstrated improved OS in patients treated with ICI+combination (p = 0.014, median 64 weeks), but no effect on PFS (p = 0.471, median 31 weeks). Whether patients had received single agent or combination ICI, those who received more than 3 cycles of ICI had an improved OS and PFS (p < 0.05 for both). Patients who received single-agent ICI and whose change in NLR was less than 5 had an improved OS (p = 0.002); this was not seen in patients who received ICI+combination therapy (p = 0.441). Patients who had a documented irAE of dermatitis had improved OS but only in the ICI+combination cohort (p = 0.021). There were no differences in OS based on age, gender, histology or sub-categories of ICI+combination. This was not the case for PFS; patients who received any ICI regimen and were younger than 70 had a worse PFS (p = 0.036). Patients who developed an irAE, specifically colitis (p = 0.009), hepatitis (p = 0.048) and dermatitis (p = 0.003) had an improved PFS. There were no differences in PFS based on ICI regimen (or sub-categories of ICI+combination), gender, histology, change in NLR or grade of irAE. Our ICI cohort results are consistent with historical data from our previous study. Further, irAEs are similar to historical data. Conclusions: This retrospective study demonstrates that ICI+combination therapy can improve OS in sarcoma. This is consistent with our prior results of ICI in sarcoma. Benefits in OS/PFS were seen in patients who received more than 3 cycles of ICI and developed certain irAE. These results can direct the optimal duration of ICI therapy. Those with decreased change in NLR also had improved OS, demonstrating a potential prognostic biomarker. Further studies are needed to validate our findings.

Additional file 1: Figure S1. Causal diagram with references. Figure S2. Number of medications prescribed across all cancers and the frequency of multiple medications. Figure S3. Number of antibiotics, separated by class, prescribed across all cancers and the frequency of multiple antibiotics. Figure S4. Number of corticosteroids, separated by class, prescribed across all cancers and the frequency of multiple antibiotics.

Additional file 2: Table S1. References for the antibiotic susceptibilities of bacterial taxa found to be enriched in responders or non-responders to ICI therapy

11541 Background: Sarcoma is a heterogeneous group of malignant tumors that consist of distinct histological and molecular subtypes, each with unique features. Despite immunotherapy’s promise in many cancers, immunotherapeutic approaches for sarcoma have had variable response rates. Evaluating the tumor microbiome is a promising new approach that aims to improve our understanding of the immunogenicity of sarcoma subtypes, leading to improved treatment options and better clinical outcomes. Methods: We utilized The Cancer Genome Atlas (TCGA) and Genome Tissue Expression (GTEx) database to obtain RNA sequencing (RNAseq) data to identify microbes in sarcoma samples (all subtypes available). Due to the large number of sarcoma subtypes, we focused on three groups: dedifferentiated liposarcoma (DDLPS), leiomyosarcoma (LMS) and “other,” representing all other sarcoma subtypes. We utilized ExoTIC, “Exogenous sequences in Tumors and Immune cells,” a tool recently developed by Dr. Daniel Spakowicz and Dr. Xaiokui Mo. ExoTIC takes raw RNAseq reads and carefully aligns to both human and non-human reference genomes to identify low-abundance microbes. Models of association were analyzed based on each of the three groups as well as all the samples: “All” group. We performed Cox proportional hazards regression to identify the microbes associated with overall survival (OS). Results: We evaluated 97 LMS, 56 DDLPS and 100 “other” RNAseq samples (Table). ExoTIC identified 1304 microbes, of which 431 were statistically associated with OS in the “All” group. Of these, 50 microbes were statistically associated only with DDLPS, 54 only with LMS (e.g., Candida dubliniensis, Mycobacterium avium, Streptococcus sp. Z15), and 46 with “other.” The presence of no organism was associated with improved survival. Median hazard ratios were largest in DDLPS (2.3), followed by “other” (2.1) and LMS (1.9). Only 18 microbes were found in the DDLPS, LMS and “All” groups, including Bacillus sp., Streptococcus lutetiensis, Clostridium tetani, and Pseudomonas sp. LTJR-52. Each was negatively correlated with survival with a median hazard ratio of 2.5. Conclusions: We found a specific relationship between microbial presence and histological sarcoma subtype (DDLPS, LMS), which also statistically correlated with OS. Assessing individual characteristics of a sarcoma histological subtype with its particular microenvironment (e.g., microbes) can lead to personalized treatment insights and improvements in outcomes. Our future research will consist of validating and correlation of the microbial profile of sarcoma subtypes with clinical outcomes retrospectively and prospectively. [Table: see text]

e14525 Background: Immune checkpoint inhibitors (ICIs) have improved the survival of patients with multiple cancer types, however ICI treatment is associated with a unique set of immune-related adverse events (irAEs) that can affect any organ. Few studies have evaluated the risk factors and outcomes of ICI induced hepatitis (ICIH). Methods: We utilized an institutional database of patients with advanced cancers treated with ICI between 2011 and 2017 at The OSU Comprehensive Cancer Center to identify patients with ICIH. Any patient who received at least one dose of ICI alone or in combination with other systemic therapies either as part of clinical trial or standard of care were included. Clinical data were extracted through chart abstraction. irAEs were graded using the Common Terminology Criteria for Adverse Events v5. Overall survival (OS) was calculated from the date of ICI initiation to death from any cause or the date of the last follow-up. OS with 95% confidence intervals were estimated using the Kaplan–Meier method. OS was also evaluated by occurrence of ICIH using the log-rank test. Results: We identified 1,096 patients treated with at least one dose of ICI. Most common cancers included lung (n=224, 20%) and melanoma (n=342, 31%). The most common ICIs were PD1/L1 (n=774, 71%) and CTLA-4 inhibitors (n=195, 18%). ICIH of any grade occurred in 64 (6%) patients. Overall, 46 (71%) were male and median age was 60 years. Severity of hepatitis was grade 1-2 in 30 patients (47%) (Table 1). The incidence of ≥grade 3 ICIH in the entire cohort was 3.1%. Median time to ICIH diagnosis was 63 days. ICIH occurred alone in 24 patients, and co-occurred with other irAEs in 40 patients. The most common co-occurring irAEs were pneumonitis (n=7); colitis (n=15), thyroid abnormality (n=14); and dermatitis (n=15). ICIH was more common in women (p=0.038), in patients treated with combination ICIs (p

Sickle cell disease (SCD) is a monogenetic disease but has a wide range of phenotypic expressions. Some of these differences in phenotype can be explained by genetic polymorphisms in the human globin gene. These polymorphisms can result in different responses to typical treatment, sometimes leading to inadequate therapeutics. Research is revealing more polymorphisms, and therefore, new targets for intervention to improve outcomes in SCD. This area of pharmacogenomics is continuing to develop. We provide a brief review of the current literature on pharmacogenomics in SCD and possible targets for intervention.

7039 Background: Checkpoint inhibitor immunotherapy (IO) is widely used to treat advanced cancer in pts. with medical comorbidities (MC), but the effect of MC on outcomes is poorly understood. Methods: We performed a single institution retrospective cohort study of pts. who received IO from 2011-2018. Immune-related adverse events (irAEs) were graded by Common Terminology for Adverse Events criteria, v4.0. MC were abstracted by query of ICD-10 codes corresponding to diagnoses in the Charlson Comorbidity Index (CCI) at any time prior to IO start. Modified CCI scores excluding points for cancer were calculated for each pt. Bivariate analysis with chi-squared statistics was used to describe characteristics and MC of pts. with vs. without irAEs. Overall survival (OS) was estimated by the Kaplan-Meier method (from start of first-line IO) and compared using the log-rank test. The association of CCI score and individual MC with irAEs and OS was tested with regression models adjusted for pt. characteristics. Results: Among 671 pts. with advanced cancer (39.6% melanoma; 21.8% non-small cell lung) treated with IO, median age 65 (IQR 55-74) years, the most common MC were COPD (24%) and diabetes (20%). 33.8% of pts. had CCI score ≥2. Neither CCI score nor any specific MC were associated with any grade or ≥G3 irAEs (P > 0.05). Increasing CCI score was significantly associated with decreased OS (P = 0.002). CHF (13.9 vs. 8.1 months, P = 0.008) and previous MI (14.2 vs. 10.1 months, P = 0.009) were associated with decreased median OS but did not remain significant in the regression model. Among pts. without cardiovascular disease (CVD), pts. with ≥G3 irAEs had longer OS than pts. with no ≥G3 irAEs (P < 0.001). This OS benefit for ≥G3 irAEs was not seen in pts. with CVD (P = 0.94). See table for adjusted HR. Conclusions: Risk for irAEs does not appear to be impacted by MC. Pts. with MC have shorter OS, but no specific MC are associated with OS after adjustment for pt. characteristics. OS is significantly increased among pts. without CVD who experience ≥G3 irAEs. CVD may be an important predictor of OS in pts. with irAEs and should be evaluated in patients receiving IO. [Table: see text]

3047 Background: Immunosuppressive factors within the tumor microenvironment (TME) pose a barrier to response to treatment with immune checkpoint inhibitors (ICI). Monocytes alter the TME to promote cancer progression through local immune suppression and angiogenesis. Peripheral blood lymphocyte-to-monocyte ratio (LMR) may reflect the interaction between host immunity, represented by lymphocytes, and the tumor microenvironment, represented by monocytes. A low LMR in the peripheral blood may serve as a surrogate biomarker and has been associated with poor prognosis in various cancers; however, its role has not been well defined in the era of treatment with ICI. Methods: We retrospectively evaluated 1034 patients with advanced cancer treated with ICI from 2011 to 2017. We calculated LMR as ratio of absolute lymphocyte/monocyte counts at baseline and median of 21 days after first cycle of ICI (on-treatment LMR) and considered low if < 2. Overall survival (OS) was calculated from the initiation of ICI to date of death or censored at last follow-up. Median OS with 95% confidence intervals (CI) was estimated using the Kaplan-Meier method. Log rank test was used for group comparison. Results: 536 pts (52%) with LMR < 2 at baseline had shorted median OS compared to 498 (48%) with LMR≥2 (median OS 8.4 months vs 17.8 months, p < 0.001). Of 1034 pts with baseline LMR, 837 had follow up LMR evaluable. In patients with baseline and on-treatment LMR, those with baseline LMR < 2, who had on treatment LMR ≥2, had OS of 16.8 months (95% CI 10.3-23.5) compared to median OS 8.0 months (95% CI 6-9.4) for patients with on treatment LMR < 2 after first cycle of ICI, p < 0.001. Patients with baseline LMR≥2, who had on treatment LMR ≥ 2, had median OS of 23 months (95% CI 19.7-28.9), but median OS was 9.4 months (95% CI 7.1-11.1) for patients with on-treatment LMR < 2 after first cycle of ICI, p < 0.001. Conclusions: We observed a statistically significant association between not only baseline LMR but also change in LMR from baseline after first cycle of ICI and overall survival in cancer patients treated with ICI. The role of LMR at baseline and on-treatment LMR should be evaluated in further studies incorporating known additional prognostic factors for ICI therapy. [Table: see text]

3140 Background: The identification of risk factors for immune-related adverse events (irAEs) is an important area of research. Among irAEs, pneumonitis carries one of the highest morbidities. There is a lack of strong predictors for pneumonitis in patients (pts) treated with ICI. We sought to identify predictors for the development of pneumonitis, and whether the use of inhaled corticosteroids (ICS) at time of ICI could be protective. Methods: Pts with advanced cancer treated with ICI from 2011 and 2018 were included in this retrospective study. Pneumonitis attribution to ICI was determined by treating physician at time of diagnosis. Time to pneumonitis was defined as days from the start of ICI to pneumonitis diagnosis. Pts who never had pneumonitis were censored at the time of last follow up or death. Predictors of pneumonitis were assessed by univariate Cox proportional hazard models at a significance threshold of alpha = 0.05. Results: A total of 837 pts were identified, and 30 (3.6%) pts developed any grade pneumonitis (12 grade 2, 14 grade 3, 1 grade 4, 3 grade 5) after receiving ICI (Table). Pts with age ≥65 years (y) had increased risk of developing pneumonitis over pts with age < 65y (HR 2.1, 95 CI: 1.02-4.4, p=0.041). 82 (9.7%) of the total cohort were on inhaled corticosteroid (ICS) at time of ICI, and 9 (11%) developed pneumonitis. Rather than being protective, pts on ICS had higher risk of pneumonitis (HR 4.2, 95 CI: 1.9-9.2, p=0.001). Pts with lung cancer had an increased risk for pneumonitis compared to pts with other cancers (HR 3.2, 95 CI: 1.5-6.4, p =0.003). Other risk factors included performance status, smoking history, line of therapy, or prior treatment including radiation were not statistically significant. Conclusions: Rather than a protective effect of ICS, our analysis found a higher risk of pneumonitis in pts treated with ICS. We confirmed an increased risk of pneumonitis for lung cancer pts compared to pts with other cancers, and higher risk of pneumonitis in pts age >65y. We hypothesize that the increased inflammatory status in chronic lung inflammation may predispose pts to pneumonitis that was not ameliorated by ICS. Future study is needed in prospective cohorts to further clarify the underlying inflammatory mechanism. [Table: see text]

3048 Background: Indications for immune checkpoint inhibitor (ICI) in cancer care are expanding rapidly. There is increasing need for accurate decision tool to better guide treatment. We have constructed a new prognostic scoring system, neutrophil-lymphocyte score (NRS), based on the nonlinear dynamic change of neutrophil to lymphocyte ratio (NLR) in relation to survival over the first cycle of ICI treatment. We compared this novel system to existing indices such as NLR, lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR), Advanced Lung Cancer Inflammation Index (ALI), and Systemic Immune-inflammation Index (SII). Methods: This is a retrospective analysis of 837 patients at Ohio State University from 2011-18. Neutrophil (ANC), lymphocyte (ALC), platelet (plt), monocyte (AMC), albumin (alb), and body mass index (BMI) were collected at baseline. Repeat labs were collected at cycle 2. NLR = ANC/ALC, ALI = BMI x alb / NLR, LMR = ALC/AMC, SII = platelet x NLR, PLR = plt/ALC. NLR Ratio = baseline NLR / repeat NLR. Based on the association between NLR and the overall survival, we assigned 1 point (p) for baseline NLR < 0.7, 6p for 0.7 to < 2, 5p for 2 to < 3, 4 p for 3 to < 4, 3 for 4 to 5, 2p for 5 to < 9, and 1p for ≥9. We also assigned 1p for NLR ratio < 0.6, 2p for 0.6 to < 0.8, 3p for 0.8 to < 1.2, 5p for 1.25 to < 1.4, 3p for 1.4 to < 1.6, and 2p for ≥1.6. NLS = sum of these 2 scores . NLS_A = NLS*alb. Time-dependent receiver operator characteristic (ROC) curves with integrated time-dependent area under the curve (TD AUC) values were used to evaluate the predictive accuracy of each index for survival. Results: For baseline and repeat values, all indices were statistically significant (P < 0.001) in predicting survival. Baseline integrated TD AUC were: ALI 0.704, NLR 0.692, SII 0.663, LMR 0.645, and PLR 0.612. All of the repeat indices at cycle 2 had higher prognostic value than their baseline counterparts. Integrated TD AUC for indices at cycle 2 were: ALI 0.740 (with baseline BMI), NLR 0.729, SII 0.694, LMR 0.671, and PLR 0.652. NLS_A was a composite score based on the dynamic change of NLR from cycle 1 to 2 and the treatment alb with integrated TD-AUC at 0.754. Conclusions: Indices constructed from ANC, ALC, AMC, Plt, alb, and BMI can be obtained inexpensively and provide great prognostic value for pts on ICI. We have constructed a novel scoring system (NLS_A) and demonstrated its improvement over the current prognostic indices. Studies with a larger cohort are needed to further improve and validate this system.

e24047 Background: Surveys suggest up to 87% of patients with cancer use complementary and integrative (CIM) therapies such as herbal medicine, acupuncture, massage and mind-body practices. These therapies may assist with symptoms of pain, nausea and anxiety. However, several studies have demonstrated that many clinicians do not inquire about CIM use, which may be due to lack of education and/or limited evidence-based data. We sought to explore the perspectives of clinicians at an academic comprehensive cancer center on the use of CIM therapies. Methods: Physicians and advanced practice providers (APPs) who practice medical oncology, hematology, radiation oncology, surgical oncology and neuro-oncology in a Midwest tertiary comprehensive cancer center were asked to participate in a 9-question online survey which inquired about their personal knowledge and recommendation for 21 different CIM therapies (not all are offered at the cancer center). Responses were summarized using descriptive statistics. Results: The response rate for this survey was 24.5% (n = 49). Responders were from the following specialties: hematology (n = 17; 35%); solid tumor (n = 18; 37%); both hematology and solid tumor (n = 8; 16%), surgical oncology (n = 3; 6%); gynecologic oncology (n = 2; 4%) and radiation oncology (n = 1; 2%). Sixty-seven percent were attending physicians and hematology/oncology fellows (n = 33), and 33% were APPs (n = 16). Median age range was 30-39 years (range 20-59). The most recommended CIM therapy for cancer treatment-related effects was massage (80%), followed by deep breathing (55%). The least recommended CIM therapies were traditional Chinese medicine (TCM) and Ayurvedic medicine (2%), followed by vitamins/minerals and homeopathy (both 6%). Participants requested more education on CBD/CBD oil (59%) and herbs/botanicals (49%). Up to 14% of respondents already had education on five integrative therapies. Conclusions: Hematology/oncology clinicians do not routinely recommend most CIM therapies, except for massage therapy. Efforts should be made to educate clinicians regarding CIM therapies used by patients with cancer as well resources that appraise the efficacy, safety, and potential drug interactions of these therapies. Education could encourage informed decision-making and improved patient-clinician communication and satisfaction.

e23547 Background: Given the rare nature of sarcoma cancers and the sometimes severe treatment-related effects of chemotherapy, many patients with sarcoma face quality of life issues during treatment. Unplanned hospital admission and emergency room (ER) visits can occur from uncontrolled symptoms and ultimately delay treatment regimens and negatively impact quality of life. The PROMIS Global Health v1.2 (PROMIS-10) surveys are validated tools to assess patients’ physical and mental well-being at the time of the survey. We sought to evaluate the correlation between PROMIS-10 scores and adverse outcomes of interest, including unplanned admissions/ED visits and patient mortality. Methods: All patients currently seen in the Sarcoma Clinics at Ohio State University routinely complete the PROMIS-10 survey at each clinic visit. For this pilot study, we collected the raw and normalized t-scores for PROMIS-10 surveys for all patients consented to The Ohio State University Sarcoma Registry (OSU-14242) from 6/1/2018 to 11/20/2019. We also collected data on unplanned hospital admission/ED visits and mortality data for each patient. Results: A total of 864 surveys for 112 patients were collected for the study period. The median number of surveys answered per patient was 6. Mean global physical t-scores (43.7 ± 8.5) and mental t-scores (47.9 ± 9.2) were lower than reference scores for the general US population (p < 0.001). 109 of 112 patients experienced an unplanned admission or ED visit during the study, with a total of 270 such encounters during the study period. PROMIS-10 scores were slightly but significantly lower for patients experiencing an admission or ED visit within 30 days of taking the survey (physical: 41.9 vs 44.1, p = 0.006; mental: 46.4 vs 48.2, p = 0.035). A total of 26 patients died during the study period; surveys completed prior to death were consistent with a greater level of physical and mental distress, with the median physical t-score = 34.9 (range: 23.5 – 50.8) and mental t-score = 43.5 (range: 33.8 – 67.6). Conclusions: We showed that we are able to obtain worthwhile data to objectively evaluate patients’ physical and mental well-being through survey data during cancer treatment. We are currently performing additional confirmatory analysis of the predictive value of the PROMIS-10 survey for adverse events and for treatment-related complications.

46 Background: Neutrophil to lymphocyte ratio (NLR) is known to be prognostic for patients with various types of cancer, including those who are treated with immune checkpoint inhibitors (ICI). We evaluated NLR at baseline and during early phase of treatment for patients with advanced non-small cell lung cancer (NSCLC) who received ICI to evaluate its prognostic value in first line ICI therapy and its relationship to programmed death-ligand 1 (PD-L1) expression. Methods: We retrospectively evaluated patients with advanced NSCLC who received ICI as first line therapy from 2016 to 2018. NLR was calculated as ratio of absolute neutrophil/lymphocyte counts and was consider elevated if ≥5. PD-L1 expression by immunohistochemistry was performed as standard of care with 22C3 antibody. Kaplan Meier analysis was used for survival. Wilcoxon-Mann-Whitney test was used to evaluate PD-L1 expression between groups. All Calculation was performed using SAS V9.4. Results: A total of 78 patients were included in this study; 28 received pembrolizumab monotherapy, 45 received pembrolizumab, carboplatin, and pemetrexed, and 5 received other pembrolizumab combinations. Patients with baseline NLR < 5 before initiating ICI had median estimated OS of 46.1 months (79.4% patient still alive and 95% CI not reached) compare to median OS of 10.7 months (95% CI lower limit 6.4 and upper limit not reached) for patients with NLR ≥5, P < 0.001. Similar association between NLR and OS can be seen when NLR were repeated immediate before the cycle 2 with P = 0.001. We observed an association between baseline NLR and PD-L1 expression. The median PD-L1 tumor proportion score (TPS) was 60% (Interquartile Range 1-80) for patients with baseline NLR < 5 vs 20% (IQR 0-60) for patients with NLR ≥5, P = 0.037. Conclusions: We confirmed the prognostic value of NLR for patients with advanced NSCLC at baseline and during early treatment in patients with NSCLC receiving first line ICI treatment. We also found an association between elevated NLR and lower PD-L1 expression. Future study with larger cohort is still needed to further delineate these relationships.

The existence of cancer disparities is well known. Focus on alleviating such disparities centers on diagnosis, treatment, and mortality. This review surveyed current knowledge of health disparities that exist in the acute survivorship period (immediately following diagnosis and treatment) and their contributors, particularly for African-American breast cancer survivors (AA-BCS). Utilizing the ASCO four components of survivorship care, we explore disparities in surveillance and effects of cancer and therapies that AA-BCS face within the acute survivorship period (the years immediately following diagnosis). A literature review of PUBMED, Scopus, and Cochrane databases was conducted to identify articles related to AA-BCS acute survivorship. The search yielded 97 articles. Of the 97 articles, 38 articles met inclusion criteria. AA-BCS experience disparate survivorship care, which negatively impacts quality of life and health outcomes. Challenges exist in surveillance, interventions for late effects (e.g., quality-of-life outcomes, cardiotoxicity, and cognitive changes), preventing recurrence with promotion of healthy living, and coordinating care among the healthcare team. This overview identified current knowledge on the challenges in survivorship among AA-BCS. Barriers to optimal survivorship care inhibit progress in eliminating breast cancer disparities. Research addressing best practices for survivorship care is needed for this population. Implementation of culturally tailored care may reduce breast cancer disparities among AA-BCS.

e18201 Background: Neutrophil to Lymphocyte Ratio (NLR) is prognostic for cancer patients treated with immune checkpoint inhibitors (ICI). We showed the change in NLR early during treatment to be a stronger, curvilinear predictor, i.e. patients with an intermediate change in NLR performed better than those with large decreases or increases. This led us to re-examine whether NLR is an optimal predictor of overall survival (OS). Methods: A retrospective review of 467 patients with advanced cancer who received ICIs from 2011 to 2017 at the Ohio State University was performed with IRB approval. NLR was collected at the initiation of ICI and on-treatment (median 21, IQR 8 days) and calculated as ratio of absolute neutrophil to lymphocyte counts. Variable selection machine-learning algorithms included fast and frugal decision trees and random forest, performed in R. Results: The machine-learning algorithm fast and frugal decision trees identified the ratio of NLR on treatment to baseline NLR, the NLR on treatment, the change in NLR and the cubic change in NLR to be the most informative predictors of survival at 12 months. A random forest algorithm identified the same four variables as the most important for prediction accuracy. Age, sex and cancer type were the least informative predictors in the model, suggesting the on-treatment NLR variables are of value across wide range of demographics. Conclusions: NLR measured during treatment, and its derivative values of the ratio to baseline, change from baseline, and the cubic change from baseline, hold more predictive value than NLR measured at baseline. Common control variables such as age, and sex showed little effect on the model, suggesting on-treatment NLR is useful across wide demographic space. [Table: see text]

6580 Background: There is growing evidence that checkpoint inhibitor immunotherapy (IO) toxicity is associated with improved treatment response. There is a paucity of evidence examining the relationship between toxicity and overall survival (OS) in older adults. Methods: We performed a single institution retrospective cohort study of adults who received IO for advanced cancer from 2011-2017. Baseline clinical characteristics were abstracted from the electronic health record. Immune-related toxicities were graded by physicians based on Common Terminology for Adverse Events criteria, v4.0. Bivariate analysis with chi-squared statistics was used to describe baseline characteristics of patients ≥70 years (y) vs.

94 Background: The response to Immunotherapy (IO) is known to be affected by concomitant medications including corticosteroids and antibiotics. We evaluated the medication history of patients undergoing IO to explore other medications that affect overall survival and to estimate the relative impact of each medication when given in combination. Methods: A retrospective review of patients with advanced cancer who received IO from 2011 to 2017 at the Ohio State University was performed with IRB approval. Data were extracted from the medical record, including medication history 180 days around the start of IO therapy. Data were collected in a REDCap database. Overall Survival (OS) was calculated from the initiation of IO. Cox Proportional-Hazards models were used and evaluated by log-rank test at alpha = 0.05. All calculations were performed using the survival and survminer packages in R. Results: Patients who received antibiotics or corticosteroids had decreased OS (p = 0.019 and p = 0.043, respectively) across several cancer types. Medications that were not significantly associated with OS included statins (p = 0.38), proton pump inhibitors (p = 0.94), H2 blockers (p = 0.27) and NSAIDS (p = 0.46). A total of 159 patients had complete data for all medications suitable for modeling relative effects. 149 (94%) of patients received antibiotics within 180 days of IO and 19 (12%) received both corticosteroids and antibiotics. The combination of corticosteroids and antibiotics had lower median OS than antibiotics alone or neither medication (p < 0.0018). A Cox Proportional Hazards model of antibiotics and corticosteroids, controlling for age, BMI and ECOG performance status, showed antibiotics, age and BMI to be significant predictors. Conclusions: Antibiotics and corticosteroids near the start of IO reduced overall survival, and the combination reduced the median overall survival further. However, a combined model that controlled for age, BMI and ECOG showed antibiotics, age and BMI to have a significant effect on OS. Though preliminary, these results suggest that antibiotics and corticosteroids may be affecting OS in the context of IO through overlapping pathways.

Background: The objective of our study was to assess women’s awareness and knowledge of risk factors and symptoms associated with endometrial cancer. Methods: A convenience sample of women waiting at clinics (general internal medicine, gynecology, and diabetes) was asked to complete a questionnaire focused on risk factors, symptoms, and concerns about endometrial cancer. Results: A total of 161 women participated in this survey study (June 2010-January 2011). The majority of women (67.3%) did not know or did not perceive themselves to be at risk for endometrial cancer, and nearly two-thirds (62.7%) did not worry about developing endometrial cancer. Participants (n=45) with a selfreported history of diabetes mellitus (DM) were more likely to report not knowing symptoms of endometrial cancer (46.7% vs. 25.9%; p