Citations

Introduction: Clue cells result from aberrant vaginal microflora and are associated with an increased vaginal pH, which can allow colonization of uropathogens in the vaginal introitus, increasing the risk for urinary tract infections (UTI). We sought to determine whether clue cells on vaginal wet preparation in the emergency department (ED) are associated with emergency physician diagnoses of UTIs and positive urine cultures. Methods: We conducted a retrospective analysis examining a dataset of women (≥18 years of age) who received both a genital wet preparation and urine testing in the ED. Both chi-square and multivariable regression analysis were performed. Results: We analyzed 14,952 encounters. On both univariable and multivariable analyses, emergency physicians diagnosed significantly fewer clue cell-positive women with a UTI (10.9% diagnosed with UTI vs 13.1% without UTI) (P <.001). Women with clue cells on vaginal wet preparation were not more likely to have a positive urine culture or have a urine culture growing Escherichia coli. Pregnant women with clue cells on vaginal wet preparation were not more likely to have a UTI or have a positive urine culture. Conclusion: Emergency physicians diagnosed significantly fewer women with UTIs when they found clue cells on vaginal wet preparation. Clue cells on vaginal wet preparation were not associated with an increased likelihood of a positive urine culture or having E. coli growing in the urine.

e19078 Background: Patients with myeloproliferative neoplasms (MPN), including polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF), experience chronic disease-related symptoms. Surveying these patients while incorporating the MPN-Symptom Assessment Form (SAF) gains valuable insight. Independent surveys evaluating symptoms among MPN patients have seen disproportionate participation among females compared to males (upwards of 4:1). Though the general MPN patient population is roughly gender balanced, epidemiological studies show the occurrence of MPN types differ between men and women (MPN [%male]: PV [65%], ET [33%], MF [50%]. Mehta, et al. Leuk & Lymph 2014). In-clinic evaluations and international MPN surveys of disease-related symptoms suggest women report higher symptom burden on average compared to men, despite MPN type [Emanuel, et al. JCO 2012. Geyer, et al. Haematol 2017]. Further, a recent study across cancer trials showed women had a 34% increased risk of reporting severe symptoms [Unger, et al. JCO 2022]. This study aimed to evaluate gender imbalance in survey participation among MPN patient surveys and investigate its potential to overestimate symptom burden if gender is ignored. Methods: Five anonymous web-based surveys were used to assess the impact of disproportionate gender participation. The MPN-10 assessing the 10 most clinically meaningful SAF items was present in these surveys and generated the Total Symptom Score (TSS). Survey responses with no self-reported gender or ≥5 missing MPN-10 symptoms were excluded. Raking weights based on expected MPN population were applied at the survey- and MPN type-level. Relative bias of mean TSS was calculated to evaluate over- and underestimation due to this participation imbalance. Relative bias <5% is commonly acceptable. Results: There were 4962 survey participants total and 74% were female (Table). Epidemiologically expected gender frequency by MPN type was not seen (MPN [%male]: PV [31%], ET [15%], MF [37%]). The gender participation imbalance accounted for a 3.1% overestimation of overall TSS. This also resulted in a 6.8% underestimation of the mean difference in TSS between genders, across MPNs. Conclusions: Overall bias due to gender participation imbalance was relatively low. However, analyses considering gender differences were more impacted. Anonymous surveys should seek to reduce participation bias during the survey design phase. More research is needed to evaluate gender and other participation biases in surveys across cancer domains.[Table: see text]

1564 Background: Enrollment in clinical trials has declined during the COVID-19 pandemic. Simultaneously, breast cancer patients have reported heightened anxiety. We assessed whether breast cancer patients’ anxiety about the pandemic affects their willingness to participate in trials. Methods: English or Spanish-speaking US residents with breast cancer were eligible to complete the online REDCap survey 8/6/21 – 9/30/21. Respondents rated their anxiety about the pandemic on an 11-point scale from 0 (no anxiety) to 10 (worst anxiety possible). Anxiety scores were categorized as no/mild (0-3), moderate (4-6) or severe (7-10). Knowledge about trials was assessed with 11 true/false items and attitudes toward trials with the Attitudes Toward Cancer Trials Scales - Cancer Treatment Subscale (ATCTS-CTS). Respondents rated their willingness to participate in a breast cancer clinical trial before and during the pandemic on 5-point scales from 0 (not at all willing) to 4 (definitely willing). Trial participants were considered “definitely willing.” Change in willingness to participate in trials during the pandemic compared to prior was defined as a binary outcome, "less willing" vs "no less willing." Means were compared via t-test and mean difference was tested via paired t-test. Multivariable logistic regression was used to model the association of anxiety and other factors with being less willing to participate in trials during compared to prior to the pandemic. Results: Among 385 respondents, median age was 52 (range 25-85), 271 (70%) were non-Hispanic White and 202 (53%) had metastatic disease. 154 (40%) received care at academic centers and 37 (10%) were current trial participants. Most rated their anxiety as moderate (43%) or severe (38%). Mean willingness to participate in a trial was lower during compared to prior to the pandemic (2.97 vs 3.10; p < 0.0001). Fifty (13%) respondents were less willing to participate in a trial during the pandemic compared to prior. After controlling for covariates, those with severe anxiety had 5.07 times odds of being less willing to participate during the pandemic compared to prior than those with no/mild anxiety (p = 0.01). For every 1-point increase in ATCTS-CTS score (indicating better attitude toward trials) there was a 3% decrease in the odds of being less willing to participate during the pandemic (p = 0.006). For every 1-point increase in the clinical trials knowledge score (indicating more knowledge) there was a 15% decrease in the odds of being less willing to participate during the pandemic (p = 0.02). Conclusions: Pandemic-related anxiety is common in breast cancer patients and is associated with being less willing to participate in trials during the pandemic compared to prior. Education about trials, including safety modifications implemented during the pandemic, may mitigate anxiety and improve willingness to participate.

Abstract Background Orthopaedic surgery has the lowest proportion of women surgeons in practice of any specialty in the United States. Preliminary studies suggest that patients who are treated by physicians of the same race, ethnicity, cultural background, or gender feel more comfortable with their care and may have better outcomes. Therefore, understanding the discrepancies in the diversity of the orthopaedic surgeon workforce is crucial to addressing system-wide healthcare inequities. Questions/purposes (1) Does a difference exist in gender representation among practicing orthopaedic surgeons across geographic distributions and years in practice? (2) Does a difference exist in gender representation among practicing orthopaedic surgeons with regard to rural-urban setting, group practice size, and years in practice? Methods Orthopaedic surgeons serving Medicare patients in 2017 were identified in the Medicare Physician and Other Supplier Public Use File and Physician Compare national databases. This dataset encompasses more than 64% of practicing orthopaedic surgeons, providing a low proportion of missing data compared with other survey techniques. Group practice size, location, and Rural-urban Commuting Area scores were compared across physician gender and years in practice. Linear and logistic regressions modeled gender and outcomes relationships adjusted by years in practice. Least-square means estimates for outcomes were calculated by gender at the median years in practice (19 years) via regression models. Results According to the combined Medicare databases used, 5% (1019 of 19,221) of orthopaedic surgeons serving Medicare patients were women; this proportion increased with decreasing years in practice (R2 0.97; p < 0.001). Compared by region, the West region demonstrated the highest proportion of women orthopaedic surgeons overall (7% [259 of 3811]). The Midwest and South regions were below the national mean for proportions of women orthopaedic surgeons, both overall (5% [305 of 6666] and 5% [209 of 4146], respectively) and in the first 5 years of practice (9% [54 of 574] and 9% [74 of 817], respectively). Women worked in larger group practices than men (median [interquartile range] 118 physicians [20 to 636] versus median 56 [12 to 338]; p < 0.001, respectively). Both genders were more likely to practice in an urban setting, and when controlling for years in practice, there was no difference between men and women orthopaedic surgeons practicing in rural or urban settings (respectively, R2 = 0.0004 and 0.07; p = 0.89 and 0.09). Conclusion Among orthopaedic surgeons, there is only one woman for every 20 men caring for Medicare patients in the United States. Although gender representation is increasing longitudinally for women, it trails behind other surgical subspecialties substantially. Longitudinal mentoring programs, among other evidenced initiatives, should focus on the more pronounced underrepresentation identified in Midwestern/Southern regions and smaller group practices. Gender-based equity, inclusion, and diversity efforts should focus on recruitment strategies, and further research is needed to study how inclusion and diversity efforts among orthopaedic surgeons improves patient-centered care. Level of Evidence Level III, therapeutic study.

Abstract Context Enhanced Recovery After Surgery (ERAS) is a multimodal protocol aimed to improve quality of postoperative recovery, minimize complications, and optimize overall self-regulation. Preoperative gabapentin decreases postoperative pain but can be associated with prolonged postoperative somnolence and respiratory depression risk. Although it is known that gabapentin affects the postoperative course, it is unclear if the timing of preoperative administration affects this finding. Objectives This study aims to assess the optimal preoperative timing for gabapentin administration in patients undergoing gynecologic surgery to minimize postoperative somnolence risk. Methods A retrospective cohort study evaluated patients who underwent major gynecologic surgery and received preoperative gabapentin. Patients were grouped based on timing from gabapentin administration to surgical incision (<4 h group vs. ≥4 h group). Preoperative, intraoperative, and postoperative data were abstracted and compared. Univariate associations between the timing of gabapentin administration and the patient and surgical characteristics and outcomes were tested utilizing two-sample equal-variance t-tests, linear model ANOVA, or Fisher’s exact tests. Associations between the timing of gabapentin administration and the time until the Richmond Agitation Sedation Scale (RASS) score of 0 were modeled utilizing linear regression, adjusted for age, initial postoperative anesthesia care unit (PACU), RASS score, and postoperative narcotics. Results Each group contained 127 patients. Demographics were similar except for age (<4 h group mean=44.2 years; ≥4 h group mean=40.5 years; p=0.021), chronic pain (<4 h group=17.6%; ≥4 h group=43.3%; p<0.001), and surgical indication (<4 h group=pelvic pain [29.1%]; ≥4 h group=pelvic pain [51.2%]; p=0.007). The <4 h group had a similar postoperative narcotic administration (<4 h group mean morphine milligram equivalents [MME]=3.667; ≥4 h group mean MME=4.833; p=0.185). The minutes from surgical closure until the patient received a RASS score of 0 and initial PACU pain score (Visual Analogue Scale [VAS]) were similar. The initial PACU oxygen administration volume, hours from surgical closure until the patient transitioned to room air, and initial PACU respiratory rate were similar. The PACU duration, admission secondary to somnolence, and initial PACU Glasgow Coma Scale (GCS) score showed no difference. Postoperative nausea/vomiting was decreased in the ≥4 h group (<4 h group=24.4%; ≥4 h group=13.4%; p-value=0.036), and urinary retention (<4 h group=14.2%; ≥4 h group=5.5%; p-value=0.033) was decreased in the ≥4 h group. Conclusions The timing of gabapentin administration less than or more than 4 h preoperatively in patients ≥18 years does not significantly affect postoperative somnolence or respiratory depression. Further, it does not have a significant effect on GCS scores or VAS scores.

Abstract Background Although uncommon, nontuberculous mycobacterial infections (NTMI) of the upper extremity cause significant morbidity based on their natural history, delay in diagnosis, prolonged duration of antimicrobial therapy often combined with surgical debridement, and functional loss. Herein we describe our experience with such infections. Methods Records for adult patients from two academic, tertiary facilities with culture-proven NTMI involving the upper extremity were retrospectively reviewed. Demographic information, co-morbidities, laboratory and microbiological evaluation, management, and outcomes were extracted. Patients were analyzed based on pathogen identified and immune suppression. Results 77 patients were identified. The mean age was 59 years and 65% of patients were male. 48% reported a preceding injury, with the hand being most frequently involved (58%). 41% were considered immune compromised; 19% of them were organ transplant recipients. Mean symptom duration prior to presentation was 203 days. Mean time to culture identification was 33 days, and 25 different species of NTM were identified (subcategorized as rapid or slow growers). 77% had solitary lesions, with cutaneous/subcutaneous location as the most common site. All patients underwent surgical debridement with four undergoing amputation to control infection. 69% received combination antimicrobial therapy for a mean duration of 184 days. Immunosuppressed patients were treated with antimicrobial therapy for a longer duration (mean 243 vs 155 days). One-third of patients experienced complications and/or recurrence regardless of organism type. Conclusion NTMI of the upper extremity is often misdiagnosed leading to significant delays in appropriate management. Knowledge of its protean manifestations and early consideration in the differential diagnosis of chronic, painful swelling of the hand or wrist, nodular or inflammatory lesions, or septic arthritis is crucial. A low threshold for surgical or biopsy with specimens sent for histopathology as well as microbiologic analysis is warranted. A combined approach with surgical debridement and prolonged combination antimicrobial therapy is necessary for optimal outcomes; however, adverse reactions from such therapy are commonly encountered. Disclosures All Authors: No reported disclosures

Abstract TGFβ plays a pivotal role in the pathobiology of myelofibrosis (MF) by not only promoting bone marrow fibrosis (BMF) but also by enhancing the dormancy of normal but not MF hematopoietic stem cells (HSCs). TGFβ has also previously been reported to inhibit normal megakaryocyte (MK) production (Bruno et al Blood 1998). TGFβ1 promotes the synthesis of collagen by normal human mesenchymal stromal cells (MSCs). Treatment of MSCs with AVID200, a potent TGFβ1/3 protein trap, significantly decreased MSC proliferation, phosphorylation of SMAD2, and collagen expression. Robust expression of pSMAD2 was observed in the absence of exogenous TGFβ in normal donor or MF-MKs, Addition of AVID200 to MKs decreased pSMAD2 without affecting total SMAD2/3 and led to increased numbers of MKs. Treatment of MF MNCs with AVID200 also led to increased numbers of progenitor cells with wild type JAK2 and a reduction of mutated colonies. A phase 1b trial of AVID200 (NCT03895112) was performed and completed in INT-2/high risk MF patients resistant/intolerant to ruxolitinib (rux); baseline platelet count of ≥ 25 x 10 9/L, and grade 2/3 BMF. Subjects received AVID200 intravenously on Day 1 of a 21 day cycle. Response was assessed by IWG/ELN criteria after 6 cycles of AVID200. Subjects attaining at least a CI or SD with a decrease in BMF by ≥1 grade, continued AVID200. We previously presented the results of the dose escalation study (Mascarenhas ASH 2020) demonstrating that AVID200 was well tolerated without dose limiting toxicities at 3 tested dose levels (Lots A and B) in dose cohorts of 180 mg (A), 550 mg (A)/70 mg (B), and 180 mg (B). Here we report updated safety and efficacy results of the phase 1b dose expansion stage at the two highest doses tested (70 mg (B) and 180 mg (B). Twenty-two subjects were enrolled (1 withdrew before receiving treatment) and 9 were treated with AVID200 in the dose escalation phase and 12 in the dose expansion phase [Table1]. Median time after rux discontinuation was 7.4 months (0.5-59.9). The most common mutations observed at baseline in this cohort included JAK2V617F (71%), TET2 (29%) ASXL1 (24%) and CALR (19%). (Fig 1) No DLTs were observed and Grade 3/4 AEs were observed in 16 (76.2%) subjects. Grade 3/4 non-hematologic AEs were observed in 8 (38.1%) subjects and included one subject in each case (epistaxis, mucositis, extraocular muscle paresis, fatigue, rash, duodenal hemorrhage, gastric hemorrhage, urinary tract infection, and syncope). Grade 3/4 hematologic AEs were anemia (6; 28.3%) and thrombocytopenia (2; 14.3%) [Table 2]. No fatal events were observed. The median number of cycles received was 5 (range 2 - 13) and 7 (33%) patients received more than 6 cycles. For dose levels 2-3 at cycle 7, a CI was attained in one subject at dose level 2 [anemia, spleen and TSS], 5 subjects had SD, 3 subjects had PD and two subjects with 10% and 15% blasts at screening developed MPN-BP while on study based on central review. Reasons for discontinuation by local PI included PD (n=8), lack of response (n=5), study completed (n=2), other (n=2), patient decision (n=1). Median % change in palpable spleen length was +10% (range -70% to +150%) and TSS change was -50% (-100% to +185.7%) The median platelet count at baseline was 114 x 10 9/L (range: 28-695) and 215 x 10 9/L (range: 66-263) after cycle 6 in 7 evaluable subjects (Fig 2A). Notably, 17 subjects had an increase in platelets from baseline during treatment and two subjects normalized their platelet counts. Maximum changes in platelets from baseline across all cycles was +63.8% [range -15.7%, +505.5%] (Fig 2B). Paired bone marrow biopsy pathology samples for 12 subjects were available for central review and showed no significant changes in BMF score or MK histo topography at end of treatment compared to baseline. All patients had elevated plasma levels of TGF β1, but not TGFβ2/β3 levels as detected by ELISA, which were dramatically reduced 21 days after the last dose of AVID200. AVID200 a TGFβ1/3 protein trap is well tolerated and clinical responses at cycle 7 of therapy in this advanced MF patient population were limited as judged by IWG/MRT response criteria. However, AVID200 therapy resulted in significant reduction in serum TGFβ levels and improvements in platelet counts indicating that TGF β1 plays a pivotal role in MF leading to thrombocytopenia which can be reversed with AVID200 therapy. We conclude that AVID200 may best be employed in combination therapy approaches in thrombocytopenic MF patients. Figure 1 Figure 1. Disclosures Mascarenhas: Constellation: Consultancy, Membership on an entity's Board of Directors or advisory committees; Promedior: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Geron: Consultancy, Research Funding; Forbius: Research Funding; Genentech/Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; PharmaEssentia: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Galecto: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Prelude: Consultancy; Kartos: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; CTI Biopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Geron: Consultancy; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merus: Research Funding. Palmer: PharmaEssentia: Research Funding; Sierra Oncology: Consultancy, Research Funding; Incyte: Research Funding; CTI BioPharma: Consultancy, Research Funding; Protagonist: Consultancy, Research Funding. Kuykendall: Celgene/BMS: Honoraria; Pharmaessentia: Honoraria; Novartis: Honoraria, Speakers Bureau; Protagonist: Consultancy, Research Funding; Incyte: Consultancy; Abbvie: Honoraria; Blueprint: Honoraria. Mesa: Genentech: Research Funding; Promedior: Research Funding; Samus: Research Funding; Gilead: Research Funding; CTI: Research Funding; Abbvie: Research Funding; Sierra Oncology: Consultancy, Research Funding; Celgene: Research Funding; Novartis: Consultancy; Pharma: Consultancy; CTI: Research Funding; Constellation Pharmaceuticals: Consultancy, Research Funding; AOP: Consultancy; La Jolla Pharma: Consultancy; Incyte Corporation: Consultancy, Research Funding. Rampal: Stemline: Consultancy, Research Funding; Memorial Sloan Kettering: Current Employment; BMS/Celgene: Consultancy; Abbvie: Consultancy; CTI: Consultancy; Novartis: Consultancy; Disc Medicine: Consultancy; Blueprint: Consultancy; Pharmaessentia: Consultancy; Incyte: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy; Constellation: Research Funding; Kartos: Consultancy; Sierra Oncology: Consultancy. Gerds: PharmaEssentia Corporation: Consultancy; Sierra Oncology: Consultancy; CTI BioPharma: Research Funding; Constellation: Consultancy; Celgene/Bristol Myers Squibb: Consultancy; AbbVie: Consultancy; Novartis: Consultancy. Yacoub: Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CTI Biopharma: Membership on an entity's Board of Directors or advisory committees; ACCELERON PHARMA: Membership on an entity's Board of Directors or advisory committees; Agios: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Dynavex: Current equity holder in publicly-traded company; Cara: Current equity holder in publicly-traded company; Ardelyx: Current equity holder in publicly-traded company; Seattle Genetics: Honoraria, Speakers Bureau; Incyte: Consultancy, Honoraria, Speakers Bureau; Hylapharm: Current equity holder in publicly-traded company. Talpaz: Imago: Consultancy; Constellation: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Other: Grant/research support ; Celgene: Consultancy. Komrokji: Acceleron: Consultancy; Taiho Oncology: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; BMSCelgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; PharmaEssentia: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy; Jazz: Consultancy, Speakers Bureau. Kremyanskaya: Astellas: Research Funding; Astex: Research Funding; Chimerix: Research Funding; Bristol Myers Squibb: Research Funding; Constellation: Research Funding; Protagonist Therapeutics: Consultancy, Research Funding; Incyte: Research Funding. Salama: Mayo Clinic: Current Employment, Other: Mayo Clinic had the contractual work for the central pathology review for this study and I was one of the reviewing pathologists; Constellation Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Hoffman: Kartos Therapeutics, Inc.: Research Funding; Protagonist Therapeutics, Inc.: Consultancy; Novartis: Other: Data Safety Monitoring Board, Research Funding; AbbVie Inc.: Other: Data Safety Monitoring Board, Research Funding. OffLabel Disclosure: AVID200 is a TGFb trap and is in clinical testing for fibrotic diseases. It does not have an approved indication at this time.

Abstract MAJIC is a phase II trial of Ruxolitinib (RUX) vs Best Available Therapy (BAT) in polycythemia vera (PV) patients with resistance/intolerance to Hydroxycarbamide (HC). This analysis involved a primary comparison between the RUX and BAT arms for quality of life (QOL) durability over 60 months, with secondary comparisons of best QOL response within first year in complete hematologic responders (CR) vs a group of partial or no response (NR/PR). This is a unique analysis due to cross-over nature of prior studies. Patients were stratified by treatment arm with either RUX or BAT. QOL was assessed over 0-60 months using the Myeloproliferative Neoplasms Symptom Assessment Form (MPN-SAF). MPN-SAF Total Symptom Score (TSS) was computed as the average of all completed items multiplied by 10 (scale 0-100, higher score represents higher symptom burden). Estimates of change from baseline and between arm differences in change by timepoint were made using a linear mixed model with compound symmetry covariance structure, which included covariates for categorical time point, treatment arm, and the interaction between time point and treatment arm. The difference between arms in proportion of patients with best post-baseline TSS response of 50% or greater was testing using a Chi-square test. In this study, 147 of the 190 trial patients had started treatment and completed at least their baseline assessment and were included in the analysis with 39 patients completing through 60 months. Groups were comprised of 76 patients in the RUX group (31 females, 45 males, mean age 64.2 [SD 11.4]) and 71 patients in the BAT group (29 females, 42 males, mean age 64.6 [SD 11.5]). Symptom scores at baseline were similar between arms, with MPN-SAF weight loss the only statistically significant difference (BAT 0.7 [SD 1.71] vs RUX 1.7 [SD 2.83], p=0.02). Significant, durable improvements in TSS were noted in RUX patients with symptom improvements lasting a mean of 52 months. BAT patients experienced a worsening of their symptom burden with improvements back to baseline notable at 56 months (Figure 1). MPN-SAF TSS there were significant differences between treatment arms in change from baseline to months 2-32, 44, and 48 (all p&lt;0.05). In all months the trend was in the direction of larger improvement in the RUX arm, with the point estimate for difference ranging from 2.1 (at month 56) to 11.3 (at month 4) with most prominent changes occurring between months 2 and 32. Of the 80 patients with MPN-SAF TSS scores at baseline and at least one post-baseline timepoint, 13/41 (31.7%) BAT and 24/39 (61.5%) RUX patients had TSS reduction of 50% or greater in at least one time point, which was statistically significant (p=0.008). In regard to specific symptoms, there was a statistically significant between arm difference seen in over 5 timepoints for fatigue, early satiety, night-sweats, itching, bone pain, and weight loss. Comparing MPN-SAF TSS in Complete Response (CR n=51) vs Non-Responder/Partial Responders (NR/PR) (n=96) there was no difference at baseline in any of the measures at any time point. A possible limitation of this study is the potential for bias in which the patients who were lost to follow up could be different then the patients who remained in the study through all 60 months which would affect generalization, particularly at time points at the later years. The novel findings of this investigation demonstrate that Ruxolitinib ameliorates the PV symptom burden in patients resistant or intolerant to HC in a robust durable manner over at least four years, while patients receiving BAT have worsening of their symptom burden over this same time period. Figure 1 Figure 1. Disclosures Mead: Novartis: Consultancy, Honoraria, Speakers Bureau; Celgene/BMS: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria. Yap: Celgene: Honoraria; Faron Pharmaceuticals: Honoraria. Scherber: Incyte Corporation: Current Employment, Current holder of stock options in a privately-held company. Knapper: Novartis: Consultancy, Research Funding, Speakers Bureau; Astellas: Ended employment in the past 24 months, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; Jazz: Consultancy, Speakers Bureau. Drummond: Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CTI: Membership on an entity's Board of Directors or advisory committees. McMullin: Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: clinical trial support, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AOP Orphan: Research Funding, Speakers Bureau. Mesa: CTI: Research Funding; AOP: Consultancy; Celgene: Research Funding; Novartis: Consultancy; Gilead: Research Funding; Pharma: Consultancy; Promedior: Research Funding; Constellation Pharmaceuticals: Consultancy, Research Funding; CTI: Research Funding; Samus: Research Funding; Sierra Oncology: Consultancy, Research Funding; Genentech: Research Funding; Incyte Corporation: Consultancy, Research Funding; Abbvie: Research Funding; La Jolla Pharma: Consultancy. Harrison: CTI BioPharma: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead Sciences: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Shire: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Geron: 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; Constellation Pharmaceuticals: Research Funding; Galacteo: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: 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; Incyte Corporation: Speakers Bureau; Sierra Oncology: Honoraria; Promedior: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AOP Orphan Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Keros: 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, Research Funding, Speakers Bureau.

Abstract Background: Self-reported financial hardship (FH) amongst cancer patients is increasingly becoming a challenge for patients, caregivers, and healthcare providers. FH not only leads to financial struggles, significant lifestyle changes, and emotional distress, but also contributes to treatment noncompliance, affecting clinical outcomes. As treatment costs rise, it is crucial to develop efficient methods to proactively identify and alleviate FH in hematology practice. One potential approach is utilizing automated processes to identify those at highest risk of FH. 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?' which all cancer patients answer annually as part of the institution's Social Determinants of Health (SDOH) assessment. Answers are on a five-point scale including not hard at all, not very hard, somewhat hard, hard, and very hard. In this study, we assess the prevalence and predictors for FH (denoted by a response of "Very hard" "Hard" or "Somewhat hard") amongst the Mayo Clinic hematologic malignancy patient population. Our study objective was to determine if this automated process could identify those at risk for FH. Methods: Patients who received care for hematologic malignancies (lymphoma, leukemia, plasma disorders, myelodysplastic/myeloproliferative disorders, and other heme malignancies) at any of the Mayo Clinic cancer centers (Minnesota, Arizona, and Florida) and who had completed the SDOH screen at least once were included in this study. The electronic medical record (EMR) and Mayo Clinic Cancer Registry were utilized to extract demographic and disease variables. Patient's home zip code was used to determine rural/urban residence, distance from cancer center, and the Area Deprivation Index (ADI), a measure of socioeconomic disadvantage based on home zip code (ranging from 1-100, with 100 representing the most disadvantaged). Multivariable logistic regression modeling was used to examine predictor variables for FH in this patient population. Results: The final cohort included 10,024 patients from 2018 to 2020. Median age was 64.6 years (IQR 58.1,73.7), 58% were male, and 79% married. Race/ethnicity composition was 94% White (n=9,268), 2.5% Black (n=246), 0.4% American Indian/Alaskan Native (44), and 4% Hispanic (n=360). Fifty-six percent of patients had Medicare and 41% had commercial insurance. Fifty percent were retired, 40% were working/students, and 72% were urban residents. Mean ADI was 41.2. Fifty-six percent of patients had lymphomas, 23.5% had plasma cell disorders, 8.5% had leukemias, 6.8% had other hematological malignancies, and 5.5% had myelodysplastic/myeloproliferative neoplasms. FH was reported by 12.8% (n=1286) of the patients. Table 1 shows the results of the multivariable model. A significantly higher likelihood of endorsing FH was noted in Hispanic vs non-Hispanics, Black and American Indian/Alaskan Native groups vs whites, Disabled/Unemployed vs working, Medicaid, Medicare, and Self-Pay groups vs commercial insurance, higher ADI (5 th quintile vs 1 st), and myelodysplastic/myeloproliferative disorder and other hematologic malignancy vs lymphoma patients. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Conclusion: Our study used automated data extraction from the EMR to efficiently identify predictors of FH in hematologic cancer patients. Employing a dichotomized and automated "flag" for FH, particularly if incorporated in the EMR, could ease the identification of SDOH issues, facilitate timely connection to appropriate resources, and help provide better patient-centered care. Figure 1 Figure 1. Disclosures Ailawadhi: Sanofi: Consultancy; Cellectar: Research Funding; Karyopharm: Consultancy; Ascentage: Research Funding; Genentech: Consultancy; Janssen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Beigene: Consultancy; GSK: Consultancy, Research Funding; AbbVie: Consultancy; Medimmune: Research Funding; Pharmacyclics: Consultancy, Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Xencor: Research Funding. Fonseca: OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy; BMS: Consultancy; Mayo Clinic in Arizona: Current Employment; Aduro: Consultancy; AbbVie: Consultancy; GSK: Consultancy; Merck: Consultancy; Juno: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Novartis: Consultancy; Bayer: Consultancy; Celgene: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy. Griffin: Exact Sciences: Research Funding.

Abstract The myeloproliferative neoplasms (MPN) polycythaemia vera (PV) and essential thrombocythaemia (ET) are associated with significant symptom burden with impaired quality of life (QoL). In the MAJIC study patients refractory/intolerant to hydroxycarbamide (HC), were randomised to treatment with ruxolitinib (Rux) or best available therapy (BAT). In this unique and comprehensive analysis we explore quality of life (QoL) outcomes in the MAJIC study using the MPN10 Self-Assessment Form (SAF) in particular using this unique dataset to explore for the first time differences between JAK2 ET vs PV, and JAK2 ET vs CALR ET at baseline and 12 months of therapy with Rux or BAT. Methods 306 patients were randomised, (190, PV and 116 ET arm) and followed for 5 years, no cross over was permitted. MPN10 SAF was assessed at baseline, 2, 4, 8 and 12 months in both arms. Equal variance two sample t-tests were used to test differences between diagnosis groups (JAK2 ET vs PV & JAK2 ET vs CALR ET) in baseline scores and 12-month change from baseline scores, here negative change from baseline indicates improvement. QoL data was also collected using MD Anderson Symptoms Inventory (MDASI) and 5 level EQ5D at the same time points as the MPN10 SAF. Results JAK2 ET vs PV 110 participants with JAK2 mutation were included in the analysis for JAK2 ET vs PV. 81 (74%) had PV and 29 (26%) had JAK2 ET; 44 patients (54.3%) with PV and 18 (62.1%) patients with ET were randomised to Rux, and 37 (45.6%) patients with PV and 11 (37.9%) with ET to BAT. Baseline mean total symptom score (TSS) was similar (JAK2 ET: 18.9. SD 18.4 and PV: 23.7, SD 17.81 (p=0.27). Mean for pruritus was 1.9 (SD 2.47) in JAK2 ET and 3.5 (SD 2.99) in PV (p=0.03). Other baseline scores were comparable: mean scores for fatigue was 3.3 (SD 3.07) for JAK2 ET vs 4.7 (SD 2.68) for PV, for early satiety was 2.6 (SD 2.78) for JAK2 ET vs 2.1 (SD 2.40) for PV, for abdominal discomfort 3.0 (SD 3.34) for JAK2 ET vs 2.0 (SD 2.78) for PV, for inactivity was 2.4 (SD 2.86) for JAK2 ET vs 3.2 (SD 2.72) for PV; for concentration problems was 2.2 (SD 2.51) for JAK2 ET vs 2.9 (SD 3.11) for PV, for night sweats was 1.6 (SD 2.20) for JAK2 ET vs 2.1 (SD 2.66) for PV, for bone pain was 1.8 (SD 2.97) for JAK2 ET vs 2.0 (SD 2.86) for PV, for fever was 0.5 (SD 1.46) for JAK2 ET vs 0.5 (SD 1.70) for PV and for weight loss was 0.3 (SD 0.73) for JAK2 ET vs 1.0 (SD 2.15) for PV (p&gt;0.05 for all). Concerning change at 12 months, mean (SD) change in TSS was -0.5 (SD 10.86) for JAK2 ET (n=21) vs -0.8 (SD 13.32) for PV (n=66) (P=0.93). Mean for individual symptom scores at 12 months were also not significantly different between the two phenotypic disease group (P&gt;0.05 for all parameters). (Fig 1, top panels). CALR vs JAK2 ET Exploring symptoms for CALR vs JAK2 ET: 45 patients were included; 9/16 (56.3%) CALR and 18/29 (62.1%) JAK2 patients were assigned to Rux (p=0.70). 10/16 (62.5%) CALR ET and 19/29 (65.5%) JAK2 ET. Baseline mean total symptom score (TSS) was similar (JAK2 ET: 18.9, SD 18.4 and CALR ET: 18.8, SD 16.99 (p=0. 0.98). All other baseline scores were comparable in this intolerant/ refractory population (p&gt;0.05 for all. Concerning change at 12 months, mean (SD) change in TSS was -0.5 (SD 10.86) for JAK2 ET vs -2.8 (SD 9.96) for CALR ET (P=0.56). Mean for individual symptom scores at 12 months were also not significantly different between the two phenotypic disease group (P&gt;0.05 for all parameters); the mean change in night sweats approached but did not reach significance similar (JAK2 ET: 0.2 (SD 1.89) and CALR ET: 1.8 (SD 3.07) (p=0. 0.06). (Fig 1, lower panels). Preliminary analysis of the MDASI and EQ5D-5L data at baseline and at 12 months shows similar results and will be presented. Conclusion This first analysis of its kind compared the symptom burden and other parameters of QoL of patients with PV and ET, resistant/intolerant to HC shows that with the exception of pruritus at baseline there were no substantial differences between JAK2 ET or PV. Equally changes in symptom burden across 12 months did not substantially differ between JAK2 ET or PV. A second analysis of JAK2 vs CALR ET also failed to show substantial differences. This data should be expanded in a larger cohort but supports a symptom continuum of JAK2 ET and PV and also JAK2 vs CALR ET. Figure 1 Figure 1. Disclosures Mead: Abbvie: Consultancy, Honoraria; Celgene/BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Speakers Bureau. Yap: Faron Pharmaceuticals: Honoraria; Celgene: Honoraria. Knapper: Novartis: Consultancy, Research Funding, Speakers Bureau; Astellas: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau. Drummond: CTI: Membership on an entity's Board of Directors or advisory committees; BMS: 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. Mesa: Pharma: Consultancy; CTI: Research Funding; Abbvie: Research Funding; Genentech: Research Funding; Gilead: Research Funding; AOP: Consultancy; Incyte Corporation: Consultancy, Research Funding; Sierra Oncology: Consultancy, Research Funding; Novartis: Consultancy; La Jolla Pharma: Consultancy; Samus: Research Funding; Promedior: Research Funding; Constellation Pharmaceuticals: Consultancy, Research Funding; Celgene: Research Funding; CTI: Research Funding. Scherber: Incyte Corporation: Current Employment, Current holder of stock options in a privately-held company. McMullin: Celgene: 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; AOP Orphan: Research Funding, Speakers Bureau; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: clinical trial support, Research Funding. Harrison: CTI BioPharma: 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; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Promedior: 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; Gilead Sciences: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Keros: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AOP Orphan Pharmaceuticals: 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: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Shire: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sierra Oncology: Honoraria; Constellation Pharmaceuticals: Research Funding; Incyte Corporation: Speakers Bureau; Geron: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Galacteo: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.