tbuckley/cabot-search huggingface dataset:
P10.03 Establishment and validation of clinical prediction model in WHO grade II glioma
Authors: X Xue, Q Gao
Journal: Neuro-Oncology (2021)

Abstract OBJECTIVE WHO grade II glioma has the characteristics of heterogeneity, and this disease progresses rapidly in some patients, in whom the malignant degree is equivalent to that of high-grade glioma. In order to accurately predict the prognosis of patients, an effective clinical prediction model based on relevant risk factors is needed which could provide a theoretical basis for optimization of clinical individualized treatment. METHODS According to the inclusion and exclusion criteria, eligible patients from January 2010 to December 2018 in our hospital were selected, and those who met the criteria were randomly assigned 4:1 to the training group and the validation group, respectively. The predictors were screened by univariate and multivariate Cox regression analysis, the prediction model was established, and the model was verified and evaluated. RESULTS A total of 258 patients with WHO grade II glioma were recruited, including 208 patients as the training group and 50 patients as the validation group. Six independent risk factors, including patient age, preoperative Karnofsky performance status (KPS) score, preoperative seizure symptoms, surgical resection range, tumor size and IDH status, were selected and included into the prediction model by univariate and multivariate Cox regression analysis, and were visualized in the form of Nomogram. The concordance index (C index) was used to evaluate the predictive ability of the model. Results showed that the C-index was 0.832 in the training group and 0.853 in the validation group, respectively, indicating good performance for the prediction model. The calibration charts were drawn in both groups respectively, which showed that the calibration lines were in good agreement with the standard lines, indicating good consistency between the two groups. CONCLUSIONS In this study, a clinical prediction model for WHO grade II glioma was established, and it was verified that the model has good predictive ability, which may be beneficial for clinical work.
P13.15 Pre-clinical trial of T601 oncolytic virus for high grade glima via intra-tumoral injection
Authors: Z He, Z Meng, P Liang, L Xing, X Zheng, G Wang
Journal: Neuro-Oncology (2021)

Abstract BACKGROUND An effective therapeutic method still hasn’t been devised for lethal high grade glioma. Thus, a method with high anti-tumoral efficiency, tumoral targeting, and acceptable side effect needs to be designed. Oncolytic virotherapy which can specifically lyse tumor cells via mass replication and deleting nucleotide metabolism related gene, like TK, required in viral replication and overexpressed in tumor cells, provides hope for patients. However, the virus only contained TK deletion is unable to show sufficient specificity of anti-tumoral response in tumor cells. Here, the adapted strain of vaccinia virus with high tumoral specificity due to TK and RR deletion and FUC1 insertion, named T601, is chosen in this project. In clinical application, intra-tumoral injection showed improved anti-tumoral efficiency and acceptable side effect. However, intra-tumoral viral injection in orthotropic glioma model is rare. In this project, various biosafety and antitumoral efficiency parameter would be tested for confirming the biosafety and reliability of intra-tumoral T601 viral injection for future clinical trials. MATERIAL AND METHODS For measuring the IC50 of T601, 10 different amounts of virus was tested in vitro via calculating cell viability with CCK-8(cell counting kit-8). For measuring the further antitumoral response of FCU1, different concentration of the 5-FC was added into the medium with IC50 viral amount. To ensure the biosafety of T601, MTD (maximum tolerance dose) was measured. Based on the MTD result, for evaluating the anti-tumoral efficiency, 106 pfu,105 pfu,104 pfu of virus was intra-tumoral injected in orthotopic GBM bearing mice. Tumor size was measured once a week through in vivo bioimaging system. RESULTS 0.022 MOI, the IC50 of T601, showed high cytotoxicity of T601. Moreover, the significantly decreased cell viability under the combined treatment of 5-FC and 0.22MOI T601 showed intact anti-tumoral function. In MTD assay, except for 107 group, no significant weight loss was found. However, in 107 pfu group, mean body weight decreased around 10% and animal fatality happened on day 9. According to the MTD result, certain amount of virus was intra-tumorally injected. In all treatment group, the tumor size was significantly shrined. At the same time, the survival rate of mice under viral treatment was significantly extended. CONCLUSION In summary, T601 exhibited efficient anti-tumoral function and acceptable side effect. T601 treatment prolonged the survival period of GBM mice with acceptable neurotoxicity, demonstrating that T601 contains necessary criterial for intra-tumoral injection. Ultimately, this project provided basic reference information of dose for future clinical trial.
Survival in the real world: A national analysis of patients treated for early-stage breast cancer.
Authors: Jeffrey Franks, Risha Gidwani, Ene Mercy Enogela, Nicole E. Caston, Courtney Williams, Monica S. Aswani, Andres Azuero, Gabrielle Betty Rocque
Journal: Journal of Clinical Oncology (2021)

75 Background: Many patient population groups are not proportionally represented in clinical trials, including patients of color, at age extremes, or with comorbidities. It is unclear how treatment outcomes may differ for these patients compared to those well represented in trials. Methods: This retrospective cohort study included women diagnosed with early-stage (I-III) breast cancer (EBC) between 2005-2015 in the CancerLinQ Discovery electronic medical record-based dataset. Patients with comorbidities or concurrent cancer were considered unrepresented in clinical trials. Non-White patients and/or those aged &lt;45 or ≥70 years were considered underrepresented. Patients who were White and aged 45-69 were considered well represented. Overall and EBC subtype-stratified Cox proportional hazards models estimated hazard ratios (HR) and 95% confidence intervals (CI) for five-year mortality by representation group. The overall model was adjusted for cancer stage, subtype, chemotherapy intensity, and year of EBC diagnosis. Stratified models were adjusted for cancer stage, individual treatment regimen (due to lack of chemotherapy intensity variation within subtype), and year of EBC diagnosis. Results: Of 11,770 patients, most were aged 45-69 (71%), White (72%), diagnosed with stage II (51%), or HR+HER2- EBC (56%). Unrepresented patients (7%) were categorized due to comorbidities (76%), concurrent cancer (22%), or both (2%). Underrepresented patients (45%) were categorized based on age (44%), race/ethnicity (39%), or both (17%). The remaining patients were well represented in trials (48%). In adjusted models, unrepresented patients had almost three times the hazard of death than well-represented patients (HR 2.71, 95% CI 2.08-3.52; Table). The hazard of death for underrepresented versus well-represented patients was similar (HR 1.19, 95% CI 0.98-1.45). Comparable results were seen in EBC subtype-specific models. Conclusions: Over half of patients in this study would be considered underrepresented or unrepresented in clinical trials due to age, comorbidity, or race/ethnicity. Patients considered unrepresented in trials experienced poorer survival compared to those well-represented. Trialists should ensure study participants reflect the real-world disease population to support evidence-based decision making for all individuals with cancer.[Table: see text]
Sentiment analysis of tweets on prior authorization.
Authors: Shivika Prasanna, Naveen Premnath, Suveen Angraal, Ramy Sedhom, Rohan Khera, Helen Parsons, Syed Hussaini, Pamela T Johnson, Emil Lou, Muhammad Shaalan Beg, Ishwaria Mohan Subbiah, Praveen Rao, Arjun Gupta
Journal: Journal of Clinical Oncology (2021)

322 Background: Natural language processing (NLP) algorithms can be leveraged to better understand prevailing themes in healthcare conversations. Sentiment analysis, an NLP technique to analyze and interpret sentiments from text, has been validated on Twitter in tracking natural disasters and disease outbreaks. To establish its role in healthcare discourse, we sought to explore the feasibility and accuracy of sentiment analysis on Twitter posts (‘’tweets’’) related to prior authorizations (PAs), a common occurrence in oncology built to curb payer-concerns about costs of cancer care, but which can obstruct timely and appropriate care and increase administrative burden and clinician frustration. Methods: We identified tweets related to PAs between 03/09/2021-04/29/2021 using pre-specified keywords [e.g., #priorauth etc.] and used Twarc, a command-line tool and Python library for archiving Twitter JavaScript Object Notation data. We performed sentiment analysis using two NLP models: (1) TextBlob (trained on movie reviews); and (2) VADER (trained on social media). These models provide results as polarity, a score between 0-1, and a sentiment as ‘’positive’’ (&gt;0), ‘’neutral’’ (exactly 0), or ‘’negative’’ (&lt;0). We (AG, NP) manually reviewed all tweets to give the ground truth (human interpretation of reality) including a notation for sarcasm since models are not trained to detect sarcasm. We calculated the precision (positive predictive value), recall (sensitivity), and the F1-Score (measure of accuracy, range 0-1, 0=failure, 1=perfect) for the models vs. the ground truth. Results: After preprocessing, 964 tweets (mean 137/ week) met our inclusion criteria for sentiment analysis. The two existing NLP models labeled 42.4%- 43.3% tweets as positive, as compared to the ground truth (5.6% tweets positive). F-1 scores of models across labels ranged from 0.18-0.54. We noted sarcasm in 2.8% of tweets. Detailed results in Table. Conclusions: We demonstrate the feasibility of performing sentiment analysis on a topic of high interest within clinical oncology and the deficiency of existing NLP models to capture sentiment within oncologic Twitter discourse. Ongoing iterations of this work further train these models through better identification of the tweeter (patient vs. health care worker) and other analytics from shared content.[Table: see text]
P03.06 Boolean logic puzzles as a neurosurgical mapping tool to preserve programming skill
Authors: M Donders-Kamphuis, K J Miller, B F W van der Kallen, M L D Broekman
Journal: Neuro-Oncology (2021)

Abstract BACKGROUND In glioma surgery, awake craniotomy with Direct Electrical Stimulation (DES) is increasingly becoming the gold standard treatment to preserve language, cognition and motor function and to optimize extent of resection. Computer programming is historically seen as an integration of cognition, language, and mathematics but an intraoperative task to monitor computer programming does not exist yet. In this study we describe a new task for intraoperative monitoring, using visual Boolean Logic Puzzles. MATERIAL AND METHODS We describe a computer programmer who underwent awake craniotomy to resect an anaplastic astrocytoma in the left superior frontal gyrus. At the request of the patient we tested programming language. We developed a new task and set of logic puzzle visual stimuli to monitor underlying cognitive function used for programming language. This test was used during preoperative functional MRI (fMRI), direct electrical stimulation (DES) and ongoing monitoring during resection. RESULTS In fMRI this task showed bilateral activation in Brodmann area 6 and 8 and for left hemisphere in Brodmann area 10. These areas are below and lateral of the tumor. Monitoring of language, motor skills and Boolean mapping was performed during DES and while resection was performed. No deficits in programming ability could be identified intra- and postoperatively. CONCLUSION Boolean Logic Puzzles may be a useful intraoperative task to preserve programming skills.
Abstract 14459: Statin Under Prescribing in African Americans With High ASCVD Risk in a Large Healthcare System
Authors: Michael P Dorsch, Corey Lester, Yuting Ding, Megan Joseph, Robert Brook
Journal: Circulation (2019)

Introduction: There is significant under prescribing with statin therapy for primary prevention in all high-risk ASCVD categories. Hypothesis: Patient characteristics, specifically race, lead to un...
Primary anti-infective prophylaxis during routine treatment of lymphoma in the United States: A large real-world cohort analysis.
Authors: Mengyang Di, Pamela R. Soulos, Scott F. Huntington
Journal: Journal of Clinical Oncology (2021)

268 Background: While infectious complications contribute to considerable morbidity and mortality in patients with cancer, most scenarios lack evidence to guide optimal anti-infective prophylaxis (AIP). We evaluated a large real-world dataset to identify baseline utilization and factors associated with AIP in patients with non-Hodgkin lymphoma (NHL) treated in the US-community setting. Methods: Using the nationwide Flatiron Health de-identified electronic health record-derived database (from ≈ 280 US cancer clinics), we selected patients treated prior to 7/1/2020 with 1) R-CHOP for DLBCL, 2) bendamustine and rituximab (BR) for CLL/SLL, or 3) ibrutinib for CLL/SLL. We limited our analysis to patients treated by providers with documented prescribing of guideline recommended anti-viral prophylaxis (ppx) during proteasome inhibitor administration to ≥1 multiple myeloma patient. Our main outcome was the documented use of primary AIP defined as anti-viral and/or pneumocystis jiroveci (PJP) ppx within +/- 14 days of treatment initiation. We also report the delayed documented AIP use from day 15 to 60. We applied separate multivariable logistic regression models to each setting to examine the associations of patient-level characteristics with primary AIP (including age, sex, race, region, insurance, ECOG, year of treatment initiation). Results: A total of 3,142 (R-CHOP for DLBCL), 2,180 (BR for CLL/SLL), and 3,590 (ibrutinib for CLL/SLL) patients were included, with median age of 69, 69, and 72 years, respectively. Primary AIP was most common during BR for CLL/SLL, with 16.8% receiving any AIP (antiviral 15.6%, PJP 7.3%). Primary AIP was used in 10.5% of DLBCL patients initiating R-CHOP (antiviral 7.6%, PJP 5.6%), with the lowest utilization of AIP during ibrutinib for CLL/SLL (any 6.4%, antiviral 5.6%, PJP 2.6%). In the delayed setting, an additional 4-6% and 2-5% received viral and PJP ppx, respectively. Across all three of our multivariable analyses, higher provider rate of anti-viral ppx during proteosome inhibitor administration in MM, residing in the Midwest (vs. Northeast), and more recent treatment initiation were associated with greater odds of AIP. Other patient characteristics (age, race, ECOG) were less consistently associated with AIP across models. Furthermore, C-statistics were &lt;0.7 in all three models (0.660-0.685), suggesting suboptimal discrimination for AIP based on patient-level characteristics alone. Conclusions: We observed low utilization of primary AIP during treatment in three common NHL settings that lack clear consensus on AIP. Variation was not well explained by measured patient characteristics, and future studies should consider provider and system attributes. Ultimately, robust evidence generation (e.g. pragmatic clinical trials) and quality improvement measures are needed to optimize ppx during routine lymphoma management.
Re-evaluating physiological indicators for all-cause mortality
Authors: Sean Clouston, Graciela Muniz Terrera
Journal: The Lancet Healthy Longevity (2021)

Geriatric research has consistently focused on the identification of appropriate benchmarks for clinical decision making and the improved detection of individuals who might be at increased risk of poor health. Over decades, researchers have relied on a small number of analytical tools, including linear models (eg, linear and logistic regression or survival modelling) to accumulate a wealth of information about appropriate biomarkers by assessing the associations between these markers and risk of death.
Therapeutic Drug Monitoring vs Standard Therapy During Infliximab Induction in Patients With Chronic Immune-Mediated Inflammatory Diseases
Authors: Trond Trætteberg Serkland, Silje Skrede, Jon Andsnes Berg
Journal: JAMA (2021)

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Breast cancer–derived GM-CSF regulates arginase 1 in myeloid cells to promote an immunosuppressive microenvironment
Authors: Xinming Su, Yalin Xu, Gregory C. Fox, Jingyu Xiang, Kristin A. Kwakwa, Jennifer L. Davis, Jad I. Belle, Wen-Chih Lee, Wing H. Wong, Francesca Fontana, Leonel F. Hernandez-Aya, Takayuki Kobayashi, Helen M. Tomasson, Junyi Su, Suzanne J. Bakewell, Sheila A. Stewart, Christopher Egbulefu, Partha Karmakar, Melisa A. Meyer, Deborah J. Veis, David G. DeNardo, Gregory M. Lanza, Samuel Achilefu, Katherine N. Weilbaecher
Journal: Journal of Clinical Investigation (2021)

Tumor-infiltrating myeloid cells contribute to the development of the immunosuppressive tumor microenvironment. Myeloid cell expression of arginase 1 (ARG1) promotes a protumor phenotype by inhibiting T cell function and depleting extracellular l-arginine, but the mechanism underlying this expression, especially in breast cancer, is poorly understood. In breast cancer clinical samples and in our mouse models, we identified tumor-derived GM-CSF as the primary regulator of myeloid cell ARG1 expression and local immune suppression through a gene-KO screen of breast tumor cell-produced factors. The induction of myeloid cell ARG1 required GM-CSF and a low pH environment. GM-CSF signaling through STAT3 and p38 MAPK and acid signaling through cAMP were required to activate myeloid cell ARG1 expression in a STAT6-independent manner. Importantly, breast tumor cell-derived GM-CSF promoted tumor progression by inhibiting host antitumor immunity, driving a significant accumulation of ARG1-expressing myeloid cells compared with lung and melanoma tumors with minimal GM-CSF expression. Blockade of tumoral GM-CSF enhanced the efficacy of tumor-specific adoptive T cell therapy and immune checkpoint blockade. Taken together, we show that breast tumor cell-derived GM-CSF contributes to the development of the immunosuppressive breast cancer microenvironment by regulating myeloid cell ARG1 expression and can be targeted to enhance breast cancer immunotherapy.
Heat‐Confined Tumor‐Docking Reversible Thermogel Potentiates Systemic Antitumor Immune Response During Near‐Infrared Photothermal Ablation in Triple‐Negative Breast Cancer
Authors: Vishnu Revuri, Santhosh Kalash Rajendrakumar, Myong‐Suk Park, Adityanarayan Mohapatra, Saji Uthaman, Jagannath Mondal, Woo Kyun Bae, In‐Kyu Park, Yong‐Kyu Lee
Journal: Advanced Healthcare Materials (2021)

Triple-negative breast cancer (TNBC) features immunologically "cold" tumor microenvironments with limited cytotoxic T lymphocyte (CTL) infiltration. Although ablation therapies have demonstrated modulation of "cold" TNBC tumors to inflamed "hot" tumors, recruitment of myeloid derived suppressor cells (MDSCs) at the tumors post ablation therapies prevents the infiltration of CTLs and challenge the antitumor potentials of T-cell therapies. Here, a thermal ablation immunotherapy strategy is developed to prevent the immune suppressive effects of MDSCs during photothermal ablation and induce a durable systemic antitumor immunity to eradicate TNBC tumors. An injectable pluronic F127/hyaluronic acid (HA)-based hydrogel embedded with manganese dioxide (BM) nanoparticles and TLR7 agonist resiquimod (R848) (BAGEL-R848), is synthesized to induce in situ laser-assisted gelation of the hydrogel and achieve desired ablation temperatures at a low laser-exposure time. Upon 808-nm laser irradiation, a significant reduction in the tumor burden is observed in BAGEL-R848-injected 4T1 tumor-bearing mice. The ablation induced immunogenic cell death and sustained release of R848 from BAGEL-R848 promotes dendritic cell maturation and reduced MDSCs localization in tumors. In addition, inflammatory M1 macrophages and CD8+IFN+ CTL are enriched in distant tumors in bilateral 4T1 tumor model, preventing metastatic tumor growth and signifying the potential of BAGEL-R848 to treat TNBC.
A targeted covalent inhibitor of p97 with proteome-wide selectivity
Authors: Zi Ye, Ke Wang, Lianguo Chen, Xiaofeng Jin, Hao Chen, Guanghui Tang, Shao Q. Yao, Zhiqiang Feng, Chong-Jing Zhang
Journal: Acta Pharmaceutica Sinica B (2021)

A resurging interest in targeted covalent inhibitors (TCIs) focus on compounds capable of irreversibly reacting with nucleophilic amino acids in a druggable target. p97 is an emerging protein target for cancer therapy, viral infections and neurodegenerative diseases. Extensive efforts were devoted to the development of p97 inhibitors. The most promising inhibitor of p97 was in phase 1 clinical trials, but failed due to the off-target-induced toxicity, suggesting the selective inhibitors of p97 are highly needed. We report herein a new type of TCIs (i.e., FL-18) that showed proteome-wide selectivity towards p97. Equipped with a Michael acceptor and a basic imidazole, FL-18 showed potent inhibition towards U87MG tumor cells, and in proteome-wide profiling, selectively modified endogenous p97 as confirmed by in situ fluorescence scanning, label-free quantitative proteomics and functional validations. FL-18 selectively modified cysteine residues located within the D2 ATP site of p97. This covalent labeling of cysteine residue in p97 was verified by LC‒MS/MS-based site-mapping and site-directed mutagenesis. Further structure-activity relationship (SAR) studies with FL-18 analogs were established. Collectively, FL-18 is the first known small-molecule TCI capable of covalent engagement of p97 with proteome-wide selectivity, thus providing a promising scaffold for cancer therapy.