Citations

6594 Background: Patient reported financial hardship (FH) in cancer care is a growing challenge for patients, their caregivers and healthcare providers. As treatment costs escalate, it is imperative to develop effective strategies to proactively recognize and mitigate FH within oncology practice. Using automated processes to screen and refer patients to appropriate resources is a potential option. At Mayo Clinic, screening for FH involves using a single financial strain question ‘ How hard is it for you to pay for the very basics like food, housing, medical care, and heating?’ completed by all cancer patients annually as part of the Social Determinants of Health (SDOH) assessment. In this study, we describe the prevalence and predictors for FH (denoted by the answer ‘hard and very hard’) in our patient population. Methods: Patients receiving cancer care at the three Mayo Clinic sites (Minnesota, Arizona, and Florida) who completed the FH screen at least once were included in this study. Demographics (age, gender, race/ ethnicity, insurance, employment status, marital status, and zip code) and disease state data for included patients was extracted from the EMR and Mayo Clinic Cancer Registry. Disease state was categorized by type of cancer (hematological or solid malignancy) and cancer stage. Zip code was used to derive median income, rural/urban residence and distance from the cancer center. Multivariable logistic regression models were utilized to examine factors associated with FH. Results: The final study cohort included 31,969 patients with median age 66 years (IQR 57,73), 51% females, and 76% married. Race/ethnicity composition was 93% White, 3% Black, and 4% Hispanic. 52% of patients had Medicare and 43% had commercial insurance. Other notable factors included 48% retired, 41% working/ students, 76% married, and 72% urban residents. Median time from cancer diagnosis was 1.1 year (IQR 0.1, 3.8) and median income was $64,406 (IQR 53,067, 82,038). 31% of patients had hematological malignancies, 20% of the cancers for which staging information was available were metastatic. FH was reported by 4% (n = 1194) of the patients. A significantly higher likelihood of endorsing FH (p < 0.001 for all) was noted in Hispanic (OR 1.64), Black (OR 1.84), American Indian/Alaskan native (OR 2.02), below median income (OR 1.48), rural (OR 1.17), self-pay (OR 2.77), Medicaid (OR 2.29), Medicare (OR 1.43), unemployed/disabled (OR 2.39), single (OR 2.07), or divorced (OR 2.43) patients. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Conclusions: Our study successfully leveraged the EMR to identify key sociodemographic groups more likely to report FH. An electronic trigger to flag such patients at high-risk of FH and proactively address FH is currently being developed.

Introduction: Serum folate (SF), vitamin B12 (B12), and iron deficiency (def) are common causes of nutritional anemias (NA). These deficiencies are usually multifactorial, with nutritional and non-nutritional causes playing a role. SF, B12, and iron levels are usually ordered in the setting of anemia, and malnutrition with or without neurologic symptoms. Clinical evidence suggests that these def have a strong dietary component and socioeconomic status (SES). The relationship of NA and area-based SES in the US has not been studied. We aimed to determine the relationship of SES with the prevalence of NA. Methods: We performed a cross-sectional analysis of adult patients with SF, B12 and iron levels at Mayo Clinic Arizona and Florida between 2010 and 2018. Race was classified using the NIH criteria. Normal laboratory values were determined according to our lab reference and the US NHANES III. SF levels (mcg/Lt) were defined as deficient &lt;4, normal ≥4.0, and excess ≥20. B12 levels (ng/L) as deficient &lt;150, borderline 150-400, normal &gt;400-900, and excess ≥900. Iron def was determined by ferritin levels (mcg/L) as low &lt;24, normal 24-336, elevated &gt;336 for men, low &lt;11, normal 11-307, elevated &gt;307 for women. Area-Level SES indicators: Median Household income (MHI), unemployment rate (UR), median gross rent month (MGRM), % uninsured, median house value (MHV), % high school; were geocoded by zip code using the 2014 American Community Survey. Demographics and clinical variables were compared between groups by chi-square test for frequency data or Kruskal Wallis rank-sum test for continuous variables. Results: 202,046 samples from 128,084 patients were analyzed. In the sample-level analysis, there were statistically significant associations between SES and SF def; all SES indicators except UR for B12 def; and no differences for iron def, except % uninsured (Table 1). There was no statistically significant interaction between race and SES for SF def and iron def. Race was a statistically significant modifier between B12 def and MHI (p&lt;0.001), % uninsured (p=0.002), and MHV (p=0.007). Asian and Other race had an increase in odds of B12 def with increasing MHI (Asian OR=1.11 , Other OR=1.18); white race had a decrease in odds of B12 def with increasing MHI (OR=0.95 for a $10,000 increase in MHI). Conclusions: We show significant relationships between SES and NA in the US. Differences were observed between SF def and all the SES indicators without race interactions. There were significant interactions between B12 def, race and SES for pts of White, Asian and Other race. There were no differences between SES and race for iron def. These relationships confirm that NA are related to area-level SES and other social determinants of health. Research regarding the causes of these disparities on a population level are needed. Disclosures No relevant conflicts of interest to declare.

Background: The COVID pandemic has resulted in significant changes many aspects of daily living. To understand the impact that COVID-19 has had on the myeloproliferative neoplasm (MPN) patient population, we conducted an internet based survey. Methods: Survey: This survey was hosted Mayo Clinic's secured REDCap system for online surveys with a link to the survey alongside a brief description posted via the www.mpnqol.com website, as well as other MPN organizational partners. Survey responses were completely anonymous. Questions included MPN-Total symptom score (TSS), NCCN distress thermometer (NCCN-DT), questions regarding impact on medical care, and questions from CDC COVID-19 community survey question bank regarding the impact of social distancing as well as changes in health behaviors. Distress thermometer, MPN-TSS, and/or questions related to the impact of COVID-19 on MPN treatment were analyzed by: MPN diagnosis, among those with ET, PV, or MF diagnoses; medication status; stay at home order; community spread; and country. Associations were tested using Kruskal-Wallis or Wilcoxon rank sum tests (for continuous variables) or Fisher Exact tests (for categorical variables). Analysis: Results: Patient Demographics (Table 1): 1560 people responded to the survey, 1217 were eligible for analysis. Median age was 62 (range: 21-93), and 298 (24.6%) respondents were male. There were respondents from USA, Australia, Canada, Netherlands, Ireland, and UK. 233 patients (19.2%) have myelofibrosis, 419 (34.6%) polycythemia vera and 543 (44.8%) essential thrombocythemia. At the time of the COVID outbreak, 1026 (84.3%) were on MPN directed medical therapy, including ruxolitinib (15.3%), interferon (14.7%), hydroxyurea (42.7%) and ASA (47.7%). 165 (13.6%) respondents received COVID testing, of which 5 had positive tests. Impact on MPN Care (Table 2): We sought to understand how patient's clinical care changed. Over half respondents who spoke to their MPN doctor had a telemedicine visit after COVID19 (57.1%). 422 (36.5%) patients spaced out visits, of which 99 (22.7%) felt there were consequences. A change in therapy due to COVID-1 occurred in only 5.4% of patients. MPN Symptom Burden and QoL: Data captured on the NCCN-DT had a median of 4 (0-10). MPN-SAF-TSS composite score was collected in 1150 respondents, median score was 26 (0-90). These scores are higher than those previously reported. Pandemic Impact on Lifestyle (Table 1): 595 (49.5%) of patients report living in a community where there is significant COVID-19 spread. 946 (78.9%) reported that COVID-19 has impacted their day to day life. 198 (17.2%) of patients agreed, or strongly agreed that COVID had a significant impact on their finances. 799 (67.8%) had a stay at home order. Of those who quarantined (112), the median duration was 30d (1-120). The majority of people increased hand-washing, and cleaning habits. 954 (81.7%) respondents reported wearing masks in public. 908 (76.8%) reported increased stress from social distancing. The majority of respondents report using healthy coping habits, such as reaching out to friends/loved ones, breathing and relaxation, as well as healthy diet. Less than 15% of patients report unhealthy coping strategies, such as use of opioids, benzodiazepines, alcohol, or cannabis Factors associated with response: There were no differences in responses based on type of MPN. If a patient was on medication, they were more likely to have spoken to their provider (p&lt;0.001). If there was a stay at home order in place, there was a higher MPN-TSS score (p&lt;0.001). If the respondent lived in an area of high community spread, they had a higher NCCN-DT score (p&lt;0.001). Patients in the USA had a higher NCCN-DT score (p=0.001), were more likely to stretch out the duration of time between visits (p&lt;0.001) and less likely to have a telemedicine visit (p&lt;0.001). Although fewer respondents in the USA thought COVID-19 was a serious disease (p=0.02), a higher percentage of respondents wore masks (p &lt;0.001). Conclusions: In our survey of MPN patients, there were many changes noted in clinical care. The use of telemedicine was common, and at least a third had significant changes in their care. Most experienced increased stress, however, employed healthy coping strategies. Only a minority of patients had a COVID test, and only 5 were positive, further data will be needed to understand the impact of COVID infection. Figure 1 Disclosures Harrison: Roche: Honoraria; Incyte Corporation: Speakers Bureau; Celgene: Honoraria, Research Funding, Speakers Bureau; Sierra Oncology: Honoraria; Promedior: Honoraria; Shire: Honoraria, Speakers Bureau; AOP Orphan Pharmaceuticals: Honoraria; Novartis: Honoraria, Research Funding, Speakers Bureau; Janssen: Speakers Bureau; Gilead Sciences: Honoraria, Speakers Bureau; CTI Biopharma Corp: Honoraria, Speakers Bureau. Pemmaraju:Affymetrix: Other: Grant Support, Research Funding; Plexxikon: Research Funding; Incyte Corporation: Honoraria; Roche Diagnostics: Honoraria; Blueprint Medicines: Honoraria; Novartis: Honoraria, Research Funding; SagerStrong Foundation: Other: Grant Support; DAVA Oncology: Honoraria; Samus Therapeutics: Research Funding; Cellectis: Research Funding; Daiichi Sankyo: Research Funding; Celgene: Honoraria; AbbVie: Honoraria, Research Funding; Stemline Therapeutics: Honoraria, Research Funding; MustangBio: Honoraria; LFB Biotechnologies: Honoraria; Pacylex Pharmaceuticals: Consultancy. Vannucchi:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees; Blueprint: Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gupta:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol MyersSquibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Research Funding; Pfizer: Consultancy. Mascarenhas:Celgene, Prelude, Galecto, Promedior, Geron, Constellation, and Incyte: Consultancy; Incyte, Kartos, Roche, Promedior, Merck, Merus, Arog, CTI Biopharma, Janssen, and PharmaEssentia: Other: Research funding (institution). Shimoda:Kyowa Hakko Kirin Co., Ltd.: Research Funding; Pfizer Inc.: Research Funding; Otsuka Pharmaceutical: Research Funding; Celgene: Honoraria; Perseus Proteomics: Research Funding; PharmaEssentia Japan: Research Funding; AbbVie Inc.: Research Funding; Astellas Pharma: Research Funding; Merck & Co.: Research Funding; CHUGAI PHARMACEUTICAL CO., LTD.: Research Funding; Bristol-Myers Squibb: Honoraria; Takeda Pharmaceutical Company: Honoraria; Novartis: Honoraria, Research Funding; Shire plc: Honoraria; Asahi Kasei Medical: Research Funding; Japanese Society of Hematology: Research Funding; The Shinnihon Foundation of Advanced Medical Treatment Research: Research Funding. Kiladjian:AOP Orphan: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Komatsu:AbbVie: Other: member of safety assessment committee in M13-834 clinical trial.; Otsuka Pharmaceutical Co., Ltd., Shire Japan KK, Novartis Pharma KK, PharmaEssentia Japan KK, Fuso Pharmaceutical Industries, Ltd., Fujifilm Wako Pure Chemical Corporation, Chugai Pharmaceutical Co., Ltd., Kyowa Hakko Kirin Co., Ltd., Takeda Pharmaceutica: Research Funding; Meiji Seika Pharma Co., Ltd.: Patents & Royalties: PCT/JP2020/008434, Research Funding; PPMX: Consultancy, Research Funding; Otsuka Pharmaceutical Co., Ltd., PharmaEssentia Japan KK, AbbVie GK, Celgene KK, Novartis Pharma KK, Shire Japan KK, Japan Tobacco Inc: Consultancy; Takeda Pharmaceutical Co., Ltd, Novartis Pharma KK, Shire Japan KK: Speakers Bureau. Abello:Takeda: Honoraria, Research Funding; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Research Funding; Dr. Reddy's: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding. Gomez-Almaguer:Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Scherber:Incyte Corporation: Current Employment, Current equity holder in publicly-traded company. Mauro:Novartis: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding; Sun Pharma/SPARC: Research Funding; Takeda: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding; Pfizer: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding. Mesa:Samus Therapeutics: Research Funding; Novartis: Consultancy; Genentech: Research Funding; Incyte: Research Funding; Bristol Myers Squibb: Research Funding; AbbVie: Research Funding; CTI BioPharma: Research Funding; Sierra Oncology: Consultancy; LaJolla Pharmaceutical Company: Consultancy; Promedior: Research Funding.

Background Patients with myeloproliferative neoplasms (MPNs) are faced with severe disease-related fatigue among a range of other constitutional and spleen-related symptoms. The MPN-Symptom Assessment Form (SAF) is recommended for use to characterize symptom burden (Scherber R, et al. Blood 2011). Within the SAF, a profile of 18 symptom items are evaluated ranging in severity from 0 (absent) to 10 (worst imaginable). The SAF is often summarized to the MPN-SAF Total Symptom Score (TSS) for analysis purposes - a single computed sum of the 10 most clinically meaningful symptom scores, including fatigue (Emanuel R, et al. J Clin Oncol 2012). Though the SAF includes a fatigue item, initial deployments of the MPN-SAF TSS incorporated a 0-10 scaled fatigue item taken from the Brief Fatigue Inventory (BFI; Mendoza T, et al. Cancer 1999). A subsequent version of the MPN-SAF TSS for use within myelofibrosis clinical trials (called the MFSAF v4; Gwaltney C, et al. Leuk Res 2017) employed a harmonized fatigue item. This analysis employing data from two studies was carried out to assess the use of the SAF fatigue item within the MPN-SAF TSS for consistency with the MFSAF v4. Methods Both BFI and SAF fatigue items were included in an initial online survey evaluating disease burden among patients with MPNs. Participants were assigned to survey variants as a function of their age. Survey variants included those to receive 1 instance of either the BFI or SAF fatigue item, instances of both BFI and SAF, or 2 instances of the same fatigue item. Surveying was aimed to assess the worst symptom experience in the patient's last 24 hours. Additionally, an independent survey assessing the impact of COVID-19 among MPN patients was deployed using the SAF fatigue item for the MPN-SAF TSS. This modified version was then used to test internal validity. Pearson correlation (r) and t-tests were used to assess association, Bland-Altman methods were used to evaluate systematic agreement between BFI and SAF fatigue scores, and Cronbach's alpha was used to measure internal consistency. Results There were 229 participants assigned both BFI and SAF fatigue items within the same survey. Among them, 51% (n=117) received the BFI item first and 49% (n=112) the SAF item first. No difference was seen between first and second fatigue scores (mean difference [first-second] = 0.00; 95%CI -0.18, 0.17). BFI and SAF fatigue scores were highly correlated (r=0.88, p&lt;0.001) and showed 88.7% agreement in categorizing severe versus non-severe fatigue (score ≥ 7 versus &lt; 7). Overall concordance in severity category was 73.4% (category [score range]: absent [0]; mild [1-3]; moderate [4-6]; severe [7-10]). Constructing the MPN-SAF TSS using the BFI and SAF fatigue components separately, the original and modified MPN-SAF TSS were nearly identical (r=0.997, p&lt;0.001), and had equivalent internal consistency (both Cronbach's alpha=0.88). The Bland-Altman plot further indicates the 2 fatigue measures have high agreement with no evidence of directional bias and negligible overall bias (Figure 1: regression slope = -0.04, p=0.25; mean difference=0.22; 95%CI 0.05, 0.39). Within the COVID-19 survey (n=1217), the modified version of the MPN-SAF TSS was consistent with known correlates among disease characteristics (Emanuel R, et al. J Clin Oncol 2012). For example, more severe MPN-SAF TSS scores were highly correlated with low quality-of-life (n=1156, r = -0.50, p&lt;0.001), and associated with those reporting spleen enlargement (n=301) versus not (n=617) (p&lt;0.001; mean difference=7.7; 95%CI 5.4, 10.1). Conclusion The BFI and SAF fatigue items are highly consistent in raw score, severity category, and in contribution to the MPN-SAF TSS. There was no order effect seen in which fatigue item was asked first. The independent COVID-19 survey using the modified MPN-SAF TSS was validated and shows high internal consistent. In the ongoing development to capture the symptom experience, this analysis shows disease-related fatigue is equivalently measured using the SAF fatigue survey item in harmonization with the MFSAF v4. Disclosures Mesa: Bristol Myers Squibb: Research Funding; CTI BioPharma: Research Funding; Promedior: Research Funding; AbbVie: Research Funding; Samus Therapeutics: Research Funding; Genentech: Research Funding; Incyte: Research Funding; LaJolla Pharmaceutical Company: Consultancy; Novartis: Consultancy; Sierra Oncology: Consultancy.

Abstract Hashimoto encephalopathy, also known as steroid-responsive encephalopathy associated with autoimmune thyroiditis, has been defined by sub-acute onset encephalopathy, with elevated thyroid antibodies, and immunotherapy responsiveness, in the absence of specific neural autoantibodies. We aimed to retrospectively review 144 cases referred with suspected Hashimoto encephalopathy over a 13-year period, and to determine the clinical utility of thyroid antibodies in the course of evaluation of those patients. One hundred and forty-four patients (all thyroid antibody positive) were included; 72% were women. Median age of symptom onset was 44.5 years (range, 10–87). After evaluation of Mayo Clinic, 39 patients (27%) were diagnosed with an autoimmune CNS disorder [autoimmune encephalopathy (36), dementia (2) or epilepsy (1)]. Three of those 39 patients had neural-IgGs detected (high glutamic acid decarboxylase-65, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor-receptor and neural-restricted unclassified antibody), and 36 were seronegative. Diagnoses among the remaining 105 patients (73%) were functional neurological disorder (n = 20), neurodegenerative disorder (n = 18), subjective cognitive complaints (n = 14), chronic pain syndrome (n = 12), primary psychiatric (n = 11), sleep disorder (n = 10), genetic/developmental (n = 8), non-autoimmune seizure disorders (n = 2) and other (n = 10). More patients with autoimmune CNS disorders presented with sub-acute symptom onset (P &lt; 0.001), seizures (P = 0.008), stroke-like episodes (P = 0.007), aphasia (P = 0.04) and ataxia (P = 0.02), and had a prior autoimmune history (P = 0.04). Abnormal brain MRI (P = 0.003), abnormal EEG (P = 0.007) and CSF inflammatory findings (P = 0.002) were also more frequent in the autoimmune CNS patients. Patients with an alternative diagnosis had more depressive symptoms (P = 0.008), anxiety (P = 0.003) and chronic pain (P = 0.002). Thyoperoxidase antibody titre was not different between the groups (median, 312.7 versus 259.4 IU/ml; P = 0.44; normal range, &lt;9 IU/ml). None of the non-autoimmune group and all but three of the CNS autoimmune group (two with insidious dementia presentation, one with seizures only) fulfilled the autoimmune encephalopathy criteria proposed by Graus et al. (A clinical approach to diagnosis of autoimmune encephalitis. Lancet Neurol 2016; 15: 391–404.) (sensitivity, 92%; specificity, 100%). Among patients who received an immunotherapy trial at our institution and had objective post-treatment evaluations, the 16 responders with autoimmune CNS disorders more frequently had inflammatory CSF, compared to 12 non-responders, all eventually given an alternative diagnosis (P = 0.02). In total, 73% of the patients referred with suspected Hashimoto encephalopathy had an alternative non-immune-mediated diagnosis, and more than half had no evidence of a primary neurological disorder. Thyroid antibody prevalence is high in the general population, and does not support a diagnosis of autoimmune encephalopathy in the absence of objective neurological and CNS-specific immunological abnormalities. Thyroid antibody testing is of little value in the contemporary evaluation and diagnosis of autoimmune encephalopathies.

Idiopathic pulmonary fibrosis (IPF) is a chronic inflammatory disorder which leads to progressive fibrosis and lung failure within 2-5 years1,2. Approximately 30% of IPF patients develop Chronic Kidney Disease (CKD) with renal dysfunction and fibrosis3. The treatment options for IPF are still limited and the disease is an unmet clinical need. The only animal model for IPF is represented by mice treated with bleomycin, a compound used for chemotherapy which has lung toxicity as its major adverse effect, that develop progressive fibrosis. Recent data indicate that bleomycin triggers lung fibrosis by increasing the release of the pro-inflammatory cytokine TGF-β by the resident megakaryocytes (MK)4. Using these observations as foundation, we investigated whetherGata1lowmice, a model for myelofibrosis induced by a TGF-β/P-selectin (P-sel) circuitry established by the abnormal MK5, includes fibrosis in lungs and kidney and whether these traits are rescued by genetic ablation (P-selnullmutation) and antibody neutralization (by RB40.34) of P-sel. MK were observed in lungs from wild-type (WT, n=9),Gata1low(n=22),P-selnull(n=4) andP-selnullGata1low(n=10) littermates. In frequency, MK were significantly lower inGata1low andP-selnullGata1lowthan in WT andP-selnulllittermates (median=1.3-1.5 vs 3-3.7/0.144mm2, p&lt;0.003) and mostly immature. In addition, lungs and kidney fromGata1low mice, but not those from the other experimental groups, contained great levels of TGF- β (Fig.1). Interstitial pneumonia was observed in lungs from WT (n=12, age=3-13 months, males=8, females=4),P-selnull(n=9, age=3-16 months, males=4, females=5),Gata1low(n=29, age=2-24 months, males=16, females=13) andGata1lowP-selnull(n=18, age=3-16 months, males=7, females=11) mice while nephritis was observed only in kidneys fromGata1low mice. Controlling for the effects of sex, there are statistically significant differences in severity of inflammation in kidney (p=0.001) but not in lungs (p=0.86) betweenGata1low and WT mice. These results indicate that lung inflammation is a baseline condition of the CD1 background used for the study while kidney inflammation is a trait exclusive toGata1low mutants independently from their gender. Great levels of fibrosis were observed in lungs and kidney fromGata1low mice but not in those from WT littermates. There are statistically significant differences in lung (p=0.01) and kidney (p&lt;0.001) fibrosis between the two groups; these differences remained after adjusting for age or sex. By contrast, there is insufficient evidence to conclude there exists a relationship between age and fibrosis grade in the other experimental groups. Age was found to be a statistically significant effect modifier on the relationship between genotype and fibrosis in lung (p=0.024) and kidney (0.004). In addition, although there is insufficient evidence for a relationship between sex and fibrosis grade in lung (p=0.62), there is a statistically significant effect of gender in kidney fibrosis inGata1low mice (p&lt;0.001). These results indicate that fibrosis in lung and nephritis and fibrosis in kidney are novel traits ofGata1low mice developed independently from the underlying state of inflammation and which are rescued by ablation ofP-sel. To further clarify the role of P-sel in lung and kidney fibrosis, 14Gata1lowmice (7 males, 7 females) were treated with either vehicle (8 mice) or RB40.34 (30 μg/mouse/day per 3 days/week by tail vein injection as described6). Mice were sacrificed on day 5 (males) and 12 (females) and histopathology, inflammation, fibrosis and TGF-β content in lungs and kidney analyzed. Treatment with RB40.34 restored the morphology and reduced inflammation, fibrosis and TGF-β content in the lungs and in kidney with respect to vehicle (Fig.1). In conclusion, Gata1low mice are a novel animal model for IPF with CKD. The phenotype is associated with highTGF-βcontent in lung and kidney and is rescued by targeting P-sel, suggesting that treatment with antibodies against P-sel may cure IPF in man. REF: 1Richeldi et al.Lancet389: 1941, 2017; 2Hutchinson et al.EurRespirJ46, 795, 2015; 3Ikezoeet al.Respiration94: 346, 2017; 4Zhouet al.CellDeathDis10:648, 2019: 5Spangrudeet al.StemCells34: 67, 2016; 6Emburyet al.Blood104: 3378, 2004. Disclosures Migliaccio: Novartis:Research Funding.

Introduction Essential thrombocythemia (ET) and polycythemia vera (PV) patients suffer from various symptoms that worsen quality of life (QOL), yet serial data on symptom changes resulting from therapy are sparse in the literature. Patient questionnaires from 2 large multicenter trials (MPN-RC 111, 112) were used to assess change in symptom burden and QOL over 12 months and impact of baseline symptom burden on subsequent change in ET / PV patients on hydroxyurea (HU) or pegylated interferon alfa-2a (PEG). Methods Trials MPN-RC 111 was a single-arm, open-label, phase II trial evaluating response to PEG in high-risk ET / PV patients with HU resistance/intolerance or splanchnic vein thrombosis (SVT; NCT01259817). MPN-RC 112 was a randomized, open-label, phase III trial comparing response to PEG versus HU in cytoreductive therapy naïve high-risk ET / PV patients diagnosed &lt; 5 years ago (NCT01258856). Measures Patients reported disease-related symptoms via the validated Myeloproliferative Neoplasms Symptom Assessment Form (MPN-SAF), QOL via the European Organisation for the Research and Treatment of Cancer Core QOL Questionnaire (EORTC QLQ-C30), and (if applicable) PEG-related symptoms (flu-like symptoms, injection site irritation, blurry vision, vision change, flushing) at baseline, 3, 6, 9, and 12 months. Analysis Mixed models assessed mean changes from baseline in the MPN-SAF Total Symptom Score (TSS), MPN-SAF items, QOL, and PEG-related symptoms in MPN-RC 111, 112 PEG, and 112 HU patients. Mixed models also assessed the impact of baseline symptom burden (high [TSS ≥ 20] versus low) on subsequent change in PEG (MPN-RC 111 and 112) and HU patients. Results Patients Of the 135 enrolled MPN-RC 111 patients, 20 with SVT and 1 with no questionnaires were excluded. Of the remaining 114, 64 (56%) / 50 (44%) had ET / PV. Patients were 51% / 48% female. Median age was 65 / 64 years, and median time since diagnosis was 38 / 55 months. 31% / 22% had prior thrombosis, and 19% / 56% had splenomegaly. Of the 168 enrolled MPN-RC 112 patients (82 PEG, 86 HU), 2 with no questionnaires were excluded. Of the remaining 166, 79 (48%) / 87 (52%) had ET / PV. Patients were 50% / 33% female. Median age was 60 / 62 years, and median time since diagnosis was 3 / 3 months. 25% / 29% had prior thrombosis, and 11% / 37% had splenomegaly. Symptoms Questionnaire completion rates ranged from 90 - 99%, 87 - 100%, and 75 - 96% for on-treatment MPN-RC 111, 112 PEG, and 112 HU patients. At baseline, TSS (0 [absent] - 100 [worst imaginable]) and QOL (0 [very poor] - 100 [excellent]) means (SDs) were 19.5 (18.4) and 71.6 (20.1) for MPN-RC 111, 17.0 (13.6) and 67.9 (24.3) for MPN-RC 112 PEG, and 14.6 (11.4) and 73.8 (18.8) for MPN-RC 112 HU patients. On average, MPN-RC 111 patients had significant improvement of TSS, fatigue, abdominal pain, abdominal discomfort, dizziness, numbness, night sweats, and fever; MPN-RC 112 PEG patients had significant worsening of fever; and MPN-RC 112 HU patients had significant worsening of inactivity (no mean changes indicating improvement were observed). PEG patients had significant worsening of PEG-related symptoms. The greatest improvements occurred in the 46 (40%), 27 (33%), and 23 (28%) MPN-RC 111, 112 PEG, and 112 HU patients with high baseline symptom burden. On average, PEG patients with high baseline symptom burden had significant improvement of TSS, fatigue, early satiety, abdominal pain, abdominal discomfort, inactivity, headache, concentration, dizziness, numbness, insomnia, cough, night sweats, itching, bone pain, fever, weight loss, and QOL, while those with low baseline symptom burden had significant worsening of TSS, early satiety, headache, itching, and bone pain. On average, HU patients with high baseline symptom burden had significant improvement of TSS, early satiety, abdominal discomfort, headache, dizziness, numbness, insomnia, itching, and weight loss, while those with low baseline symptom burden had significant worsening of TSS, early satiety, abdominal discomfort, inactivity, concentration, and sexual desire/function (Figures 1 and 2). Conclusions Although no statistical comparisons were made across trials, overall improvements were seen in MPN-RC 111 but not 112. Patients with high baseline symptom burden experienced the greatest improvements in symptom burden and QOL during treatment with PEG or HU, which may explain the improvements seen in the more advanced patients in MPN-RC 111 compared to 112. Disclosures Mascarenhas: Celgene, Prelude, Galecto, Promedior, Geron, Constellation, and Incyte: Consultancy; Incyte, Kartos, Roche, Promedior, Merck, Merus, Arog, CTI Biopharma, Janssen, and PharmaEssentia: Other: Research funding (institution). Yacoub:Dynavax: Current equity holder in publicly-traded company; Ardelyx: Current equity holder in publicly-traded company; Cara Therapeutics: Current equity holder in publicly-traded company; Hylapharm: Current equity holder in private company; Incyte: Speakers Bureau; Agios: Honoraria, Speakers Bureau; Novartis: Speakers Bureau; Roche: Other: Support of parent study and funding of editorial support. Hoffman:Protagonist: Consultancy; Forbius: Consultancy; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Dompe: Research Funding. Silver:PharmaEssentia: Speakers Bureau. Mesa:Bristol Myers Squibb: Research Funding; Incyte: Research Funding; AbbVie: Research Funding; Samus Therapeutics: Research Funding; Genentech: Research Funding; CTI BioPharma: Research Funding; Promedior: Research Funding; Sierra Oncology: Consultancy; LaJolla Pharmaceutical Company: Consultancy; Novartis: Consultancy.

Background The COVID-19 pandemic continues to challenge effective treatment delivery to hematologically-compromised patients, including those with myeloproliferative neoplasms (MPNs). MPNs are characterized by clonal proliferation of hematopoietic cell lines in bone marrow. As such, increasing reports of COVID-19 related thrombotic events highlight how MPN patients are at an increased risk in navigating potential complications during this pandemic. Mitigation strategies to lesson MPN patient exposure to COVID-19 are vital. Though, such efforts come at an inherent cost to effective healthcare delivery. Restriction of regular in-clinic treatments and reported shortages of MPN pharmacotherapies present these patients with diminishing continued care. To understand how MPN patient care has been impacted by COVID-19, an internet-based questionnaire was deployed surveying a variety of disease and pandemic related items (reported elsewhere; Palmer J et al, ASH 2020 submitted). A single free-text response item instructed respondents to: "Please tell us anything else (bad or good) about how the COVID-19 outbreak has impacted your MPN care." This qualitative analysis evaluated first-hand comments directly from patients in order to form a richer understanding of how those with MPNs have been managing disease-related care amidst this pandemic. Methods This COVID-19 survey was hosted via Mayo Clinic's secured REDCap system for online surveys and posted on MPN organizational partner websites. Surveys were completely anonymous. The free-text responses describing impacts to MPN care were each independently reviewed by 2 individuals for overall sentiment (positive, negative, both, or neutral [no impact]) and categorized for themes. The 2 reviewers were assessed for agreement. Conflicting reviews were evaluated then adjudicated by an algorithm for cases meeting selected conditions or by lead author review for all remaining cases. Descriptive statistics are reported. Results Of the 1217 consenting adult patients participating in the overall COVID-19 study, 824 provided free-text responses. Of these, respondent MPN diagnoses included, essential thrombocythemia (n=324, 39%), polycythemia vera (n=251, 30%), myelofibrosis (n=153, 19%), and other/undisclosed (96, 12%); 69% (n=567) were female; median age was 63 (range 21-93); 38% (n=313) were from the US, 38% (n=313) UK, and 24% (n=198) other/unknown. There was 89% (n=734) sentiment agreement between reviewers. Free-text responses about the impact of COVID-19 on MPN care were 49% (n=400) negative, 21% (n=177) positive, 8% (n=65) both positive and negative, and 22% (n=182) neutral/no impact. Table 1 shows a selection of MPN patient free-text responses reflecting common negative and positive sentiment themes. Negative impact (n=400): The most common negative impact involved delays or cancellations of visits or perceived inaccessibility to regular providers (n=261, 65%). Primarily this sentiment was driven by lack of clinic availability and restrictions at treatment centers or by providers. However, some respondents reported delaying or canceling visits themselves due to fear of COVID-19 exposure. Perceived health consequences from this delay were also expressed. There were 129 (32%) respondents with concern regarding changes or access to medications, including explicit drug supply shortages. Some patients resorted to self-adjusting medications and reusing single-use supplies. General anxiety, stress, and isolation were also reported (n=98, 25%). Positive impact (n=177): Availability of telemedicine comprised the majority of positive impacts of the pandemic (n=95, 54%), with many noting the reduced travel time to visits. Routine local testing coupled with follow-up telemedicine was favorable. Despite general positivity towards telemedicine, some reported preferences for in-person visits; commenting that telemedicine was impersonal, difficult to schedule or receive virtual communication, and expressed concern for lack of spleen examinations during virtual visits. Conclusion Positive and negative aspects were reported including MPN-specific issues. Healthcare systems should use such data to emerge from the COVID-19 pandemic and retain the positive impacts such as telemedicine, while developing education materials and other resources to address the reported negative impacts where possible. Disclosures Mesa: CTI BioPharma: Research Funding; Promedior: Research Funding; Novartis: Consultancy; Sierra Oncology: Consultancy; Samus Therapeutics: Research Funding; Genentech: Research Funding; AbbVie: Research Funding; Incyte: Research Funding; LaJolla Pharmaceutical Company: Consultancy; Bristol Myers Squibb: Research Funding.

AbstractObjectiveTo determine the presence of racial/ethnic differences in patients with anemia and serum folate deficiency.MethodsWe performed a retrospective analysis of data from patient samples collected from January 2010 to October 2018. Reference laboratory ranges were determined by Mayo Clinic Reference Laboratories. Race and ethnicity were classified according to National Institutes of Health categories.ResultsThe analysis comprised 197 974 samples. Hemoglobin, hematocrit, and SF results were available for 173 337, 173 056, and 129 760 samples, respectively. Of the samples, 46 505 (26.8%) showed anemia, with a higher prevalence among American Indian/Alaskan Natives (AI/AN) 42.9% and African Americans (AA) 47.2% (P < .001). SF deficiency was present in 897 (0.7%), with a higher prevalence among AI/AN (9, [1.4%]) and AA (78, [1.2%]) and a lower prevalence in non‐Hispanic whites (NHW) (758, [0.7%]), Hispanics (40, [0.6%]), and Asians (8, [0.3%]). In multivariable analysis, the prevalence of anemia was higher in all non‐NHW racial/ethnic groups: AA (OR, 3.67, [95%CI: 3.47‐3.88, P < .001]), AI/AN (OR, 3.25, [95%CI: 2.71‐3.90, P < .001]), Asians (OR, 1.62, [95%CI: 1.47‐1.77, P < .001]), and Hispanics (OR, 1.41, [95%CI: 1.32‐1.50, P < .001]). SF deficiency was more common in AA (OR, 1.48, [95%CI: 1.17‐1.88, P.001]) and less common in Asians (OR, 0.35, [95%CI: 0.17‐0.70, P = .003]), compared with NHW.ConclusionsWe showed significant racial/ethnic differences in anemia and SF deficiency. Differences were observed especially among NHW, AA, and Asians. We believe that these differences may be explained by social determinants of health. More research is needed regarding the causes of these differences and their clinical implications at a population level.

Objective We surveyed the American Headache Society (AHS) New Investigators and Trainees Section (NITS), and International Headache Academy (IHA) attendees to better understand what they perceive as the most pressing issues for themselves as new investigators and trainees in the field of headache medicine. Background The NITS and IHA are intended as platforms for mentorship, leadership training, and professional development in the field of headache medicine. Identifying and addressing pressing issues among new investigators and trainees based on their perceived needs is critical to encouraging their development and success as headache medicine clinicians and researchers. Methods Paper surveys were administered at the NITS meeting at the November 2018 Scottsdale Headache Symposium and the January 2019 IHA. Additionally an online version was sent to the NIT listserv in November of 2018. The survey queried demographic information (gender, race, age, profession, training status, and years in practice) and asked participants to identify their top 3 most pressing issues/questions among a list of options. Results Fifty‐three responses were submitted (53/255; total response rate 20.7%). Among the surveys, 18 in‐person responses were from the NITS meeting (18/20; response rate 90.0%), 23 in‐person responses were from the IHA (23/45; response rate 51.1%), and 12 responses were from the online survey (12/190; response rate 6.3%). No duplicate responses were submitted based on comparison of demographics. One respondent identified as a researcher exclusively and was excluded from further analyses; the rest identified as clinicians at various levels of medical training. Fifteen respondents were not members of the NITS (28.8%); the most common reason for nonmembership was lack of awareness of the section (92.8%). Overall the most pressing issues/questions included (% of respondents who ranked issue/question among top 3): Career planning (51.9%), Logistics of running a headache clinic (40.4%), and Opportunities for involvement (38.5%). Most pressing issues/questions differed depending on level of training. Working with industry was the most pressing issue/question identified by early career physicians (55.0%). Career planning was the most pressing issue/question among fellows (72.2%) and residents (64.3%). Conclusion Many of the most pressing issues identified by respondents are topics that are not formally addressed in medical and research training.