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Background: In the face of antibiotics resistance and adverse effects, emerging evidence suggests that procalcitonin guided therapy can help enhance appropriate use of antibiotics especially in patients with respiratory infections and sepsis. We seek to assess the uptake of procalcitonin among clinicians in a US hospital and assess its correlation with amount and duration of antibiotics use. We also seek to identify factors significantly associated with antibiotic use. Methodology: Retrospective cross-sectional study of patients with sepsis and COPD at a Medical Center in Texas USA. A total 48 COPD and 62 Sepsis patients were assessed. We collected demographic data such as age, weight, height, gender, and race/ethnicity. We also collected data on procalcitonin, number of antibiotics used, duration of antibiotics, and WBC levels at admission. We conducted bivariate analyses and logistic regression analyses to assess factor associated with procalcitonin, number of antibiotics used and duration of antibiotics. Results: We had 48 COPD patients and 62 sepsis patients in this study. Overall physicians ordered Procalcitonin on only 11.8% of patients. Procalcitonin was not significantly associated with antibiotics use. However, patients who had procalcitonin ordered had significantly lower WBC count than those without procalcitonin (10.1 vs. 12.9, p:0.026). Number of antibiotics was significantly associated with type of diagnosis (Sepsis 66.7% vs. COPD 50.7%, p = 0.001). In the logistic regression analysis, after adjusting for other variables patients with sepsis were significantly more likely to be on higher number antibiotics (OR 6.08, p

Abstract: Cardiotoxicity from chemotherapy regimens has been long reported. However, the understanding of cardiac side effects of biological therapies is rapidly evolving. With cancer patients achieving higher life expectancy due to the use of personalized medicine and novel targeted anticancer agents, the occurrence of cardiotoxicity is becoming more significant. Novel biological therapies include anti-HER2 antibodies, tyrosine kinase inhibitors, bruton kinase inhibitors, antivascular endothelial growth factors, proteasome inhibitors, immunomodulator drugs, and immune checkpoint inhibitors. Potential cardiovascular toxicities linked to these anticancer agents include hypertension, arrhythmias, QT prolongation, myocardial ischemia and infarction, left ventricular dysfunction, congestive heart failure, and thromboembolism. Cardiac biomarkers, electrocardiography, echocardiography and magnetic resonance imaging are common diagnostic modalities used for early detection of these complications and timely intervention. This review discusses the various types of cardiotoxicities caused by novel anticancer biologic agents, their molecular and pathophysiological mechanisms, risk factors, and diagnostic and management strategies that can be used to prevent, minimize, and treat them.

Immune thrombocytopenia, also called idiopathic thrombocytopenic purpura, is a common cause of thrombocytopenia after viral infections. Even in the second year of the coronavirus disease 2019 (COVID-19) pandemic, our body of knowledge regarding the diverse symptoms and complications of the virus continues to grow and evolve. We present a case of a 48-year-old African American male who came into the emergency department with severe left foot pain. A platelet count of 7x103/mL was incidentally found on complete blood count (CBC) during the patient's initial workup. The patient had previously been hospitalized for COVID-19 five weeks prior. Further workup did not support any etiology of his thrombocytopenia. Therefore, we gave a presumed diagnosis of idiopathic thrombocytopenic purpura secondary to COVID-19. The patient was treated with corticosteroid resulting in improvement in his platelet count.

Cardiovascular or arteriothrombotic adverse events (CV- or AT-AEs) are reported in chronic myeloid leukemia (CML) patients treated with tyrosine kinase inhibitors (TKIs). The incidence and characteristics across different TKI have not been systematically analyzed. We analyzed 531 patients treated with frontline TKIs in different prospective trials: imatinib 400 mg (n = 71) and 800 mg (n = 203), nilotinib (n = 108), dasatinib (n = 106), and ponatinib (n = 43). Characteristics and incidence of new-onset CV-AEs and AT-AEs were analyzed. Poisson regression models assessed factors associated with AE incidence. Median follow-up was 94 months (range, 2-195). Overall, 237 patients (45%) developed CV-AEs and 46 (9%) developed AT-AEs. Hypertension was the most common AE seen in 175 patients (33%; grade 3/4 in 17%). CV-AE and AT-AE incidence ratios (IRs) with 95% confidence intervals (CIs) were 8.6 (7.6-9.8) and 1.7 (1.2-2.2) per 100 person-years. Among the TKIs, ponatinib showed the highest IR (95% CI) for CV-AEs and AT-AEs at 40.7 (27.9-59.4) and 9.0 (4.1-20.1). In multivariate analysis, ponatinib therapy was associated with increased incidence rate ratio (IRR) for CV-AEs (4.62; 95% CI, 2.7-7.7; P < .0001) and AT-AEs (6.38; 95% CI, 1.8-21.8; P < .0001) compared with imatinib 400. In summary, there is an increased risk of CV-AEs (except hypertension) and AT-AEs in CML patients treated with newer TKIs, particularly with ponatinib. Patients on TKIs must be informed and closely monitored for vascular AEs. These studies were registered at www.clinicaltrials.gov as #NCT00048672, #NCT00038649, #NCT00050531, #NCT00254423, #NCT00129740, and #NCT01570868.

Introduction: The presence of hetero- (sickle trait) or homozygous (sickle disease) hemoglobin S gene is associated with increased risk of venous thromboembolism (VTE). However, sickle disease patients in particular are relatively young, lack common comorbid conditions that would qualify them for inpatient VTE prophylaxis (VTEP) and there are limited published data on trends of VTEP use in these populations. Methods: This was a retrospective analysis of all hospitalizations of sickle trait or disease adult medical patients occurring between January 2013 and December 2018 at three hospitals in Southeast Michigan, USA. Admissions for bleeding or thrombosis, requirement of intensive care stay or surgery, those occurring within 45 days of orthopedic surgery, as well as all patients already on anticoagulation or with known hypercoagulable states were excluded. Hospitalized controls were matched for race, age, sex and length of stay. Trends of VTEP use and predictive patient factors over multiple admissions were modeled using generalized estimating equations. Results: There were 803 sickle trait (525 patients; mean age 43 ± 19; 85% female) and 1020 sickle disease admissions (262 patients; mean age 34 ± 13; 57% female); all patients were Black. The percentage of hospitalizations in which subjects were offered any VTEP was similar to that of controls in both groups of interest (Figure); however, there were more encounters in which patients received greater than 50% of expected VTEP doses in the sickle trait (80% vs 51%; p Conclusions: VTEP is underused in sickle trait and disease patients. There may be a trend towards offering more VTEP in sickle disease, but not in sickle trait, where the decision is driven by comorbid conditions rather than hemoglobin genotype. Patient refusal does not appear to play a major role, but the finding of significant inter-center variability suggests provider education may result in improved use as hemoglobin genotype is currently not part of risk stratification tools that help clinicians decide on inpatient VTEP. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Background Unplanned 30-day readmissions are a frequent complication of acute leukemia therapy. However, there is limited data in acute lymphoblastic leukemia (ALL), with reported readmission rates (RaR) of 36% for pediatric ALL. Methods We retrospectively reviewed hospitalizations for ALL for adult patients >/= 18 years at our institution between January 2018 and December 2018. Unplanned readmissions were defined as any hospitalization within 30-days after discharge from the index admission, excluding all elective re-admissions for scheduled chemotherapy. Patients >/= 55 years of age receiving their initial induction therapy remained hospitalized for at least 21 days until bone marrow analysis and neutrophil count above 500/mm3. The primary objective was to identify the 30-day unplanned readmission rates, cause of readmissions, and predicted factors for readmissions. The secondary outcome included 30-day readmission mortality rate and inpatient mortality rate. Results There were a total of 841 ALL hospitalizations, 94 admissions for 63 pts (average 1.49 re-admit/pt) during frontline induction, 443 for 123 pts (average 3.6) during consolidation and 304 for 92 pts (average 3.3) with relapsed/refractory ALL (R/R ALL). The median age was 43 years for the frontline induction, 45 years for the consolidation group, and 42 years for R/R ALL patients. Baseline characteristics are listed in Table 1. The median length of index admission was 11 days for induction, 4 days during consolidation, and 8 days for R/R ALL. The 30-day unplanned RaR was 32% for induction, 28% for consolidation, and 36% for R/R ALL, with a median time to readmission of 6 days, 6 days, and 5 days, respectively. The most common causes of readmissions were infections (60%, 60% and 29% during induction, consolidation and R/R ALL respectively), including 30% neutropenic fever of unknown origin (NF), pain 20%, gastrointestinal infections 13%, neurologic causes (altered mental status, headache and LE weakness) 13%, and 10% bacteremia for induction; 19% neurologic causes, 17% NF, 15% upper respiratory infections, and11% pain during consolidation; and 9% bleeding, 8% NF, and 6% bacteremia for R/R ALL. (Figure 1) The median length of readmission was 5 days, 4 days, and 7 days for induction, consolidation, and R/R ALL patients, with a rate of ICU stay of 7%, 2%, and 18%, respectively. (Figure 2) While no significant differences were seen in the rate of ICU stay between readmissions and non-readmission for the induction and consolidation groups, R/R ALL patients had an increased incidence of ICU stay (18% vs. 11%, p=.001) and 30-day mortality (13% vs. 5% p=.010). We performed a logistical regression analysis to determine risk factors associated with readmissions. The multivariate analysis identified COPD (OR 3.30, p=.016) as an independent predictor for readmissions and male sex was associated with a decreased risk (OR 0.58, p=.016) during consolidation therapy; meanwhile, Philadelphia positive ALL (Ph+ALL) was negatively associated with RaR for R/R ALL pts (OR 0.33, p=.014). (Table 2) There was no significant association between the commonly used L.A.C.E. score and the risk of readmissions among consolidation and R/R ALL pts. However, during induction, a higher L.A.C.E score was negatively associated with the risk of readmission (OR 0.30, p=.027), likely due to a longer duration of hospital stay for high-risk patients (18 days vs. 8 days, p=.000). The 30-day mortality rate and inpatient mortality rate was 3% for unplanned induction readmissions, 0% for consolidation, and 13% for R/R ALL. One patient (3%) died after readmission during induction due to infection. The 30-day mortality rate after readmission for R/R ALL patients was 13%, with 50% of deaths due to infections and 30% due to disease progression. Conclusions Unplanned 30-day readmissions were frequent among patients with ALL, with similar rates between each sequential line of therapy, and the most common cause was infections. The 30-day mortality remains low for induction and consolidation pts, with a significantly higher risk for ICU stay and 30-day mortality for R/R ALL pts. We identified COPD, female sex, and non-Ph+ ALL as independent predictors for readmission. However, the majority of the pts were younger, with only 24-34% above 55 years of age. Implementing more frequent monitoring and increased precautions in high-risk pts could help reduce mortality in ALL. Disclosures Jain: Aprea Therapeutics: Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; ADC Therapeutics: Research Funding; Precision Bioscienes: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Research Funding; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cellectis: Research Funding; Fate Therapeutics: Research Funding; BeiGene: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Pfizer: Research Funding. Short:AstraZeneca: Consultancy; Astellas: Research Funding; Amgen: Honoraria; Takeda Oncology: Consultancy, Honoraria, Research Funding. Ravandi:Celgene: Consultancy, Honoraria; Orsenix: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Macrogenics: Research Funding; Xencor: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding. Borthakur:Abbvie: Research Funding; Curio Science LLC: Consultancy; Polaris: Research Funding; Jannsen: Research Funding; PTC Therapeutics: Consultancy; Argenx: Consultancy; PTC Therapeutics: Research Funding; GSK: Research Funding; FTC Therapeutics: Consultancy; Treadwell Therapeutics: Consultancy; BMS: Research Funding; AstraZeneca: Research Funding; Novartis: Research Funding; Incyte: Research Funding; Cyclacel: Research Funding; BioLine Rx: Consultancy; Xbiotech USA: Research Funding; BioLine Rx: Research Funding; Oncoceutics: Research Funding; BioTherix: Consultancy; Nkarta Therapeutics: Consultancy. Sasaki:Daiichi Sankyo: Consultancy; Novartis: Consultancy, Research Funding; Pfizer Japan: Consultancy; Otsuka: Honoraria. Cortes:Novartis: Consultancy, Research Funding; Merus: Research Funding; Immunogen: Research Funding; Bristol-Myers Squibb: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Amphivena Therapeutics: Research Funding; Arog: Research Funding; BiolineRx: Consultancy, Research Funding; Sun Pharma: Research Funding; Astellas: Research Funding; Telios: Research Funding; BioPath Holdings: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Takeda: Consultancy, Research Funding. Kantarjian:Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Agios: Honoraria, Research Funding; Ariad: Research Funding; Amgen: Honoraria, Research Funding; Takeda: Honoraria; AbbVie: Honoraria, Research Funding; BMS: Research Funding; Novartis: Research Funding; Astex: Research Funding; Daiichi-Sankyo: Research Funding; Immunogen: Research Funding; Pfizer: Honoraria, Research Funding; Cyclacel: Research Funding; Jazz Pharma: Research Funding. Garcia-Manero:AbbVie: Honoraria, Research Funding; Acceleron Pharmaceuticals: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Helsinn Therapeutics: Consultancy, Honoraria, Research Funding; Novartis: Research Funding; Merck: Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria, Research Funding; Jazz Pharmaceuticals: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Amphivena Therapeutics: Research Funding. Jabbour:AbbVie: Other: Advisory role, Research Funding; Pfizer: Other: Advisory role, Research Funding; BMS: Other: Advisory role, Research Funding; Amgen: Other: Advisory role, Research Funding; Genentech: Other: Advisory role, Research Funding; Takeda: Other: Advisory role, Research Funding; Adaptive Biotechnologies: Other: Advisory role, Research Funding. Kadia:Incyte: Research Funding; Celgene: Research Funding; Cellenkos: Research Funding; Genentech: Honoraria, Research Funding; JAZZ: Honoraria, Research Funding; Cyclacel: Research Funding; Novartis: Honoraria; Pulmotec: Research Funding; Abbvie: Honoraria, Research Funding; Ascentage: Research Funding; Astra Zeneca: Research Funding; Amgen: Research Funding; Pfizer: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Astellas: Research Funding.

Background Unplanned 30-day readmissions are a frequent complication of acute myeloid leukemia (AML) therapy, with rates of 30-60% from published studies, including a 30% readmission rate (RaR) for induction and 40-50% RaR during consolidation. However, the data is still limited regarding predictors for readmissions. Methods We retrospectively reviewed hospitalizations for AML for adult patients >/= 18 years at our institution between January 2018 and December 2018. Unplanned readmissions were defined as any hospitalization within 30-days after discharge from the index admission, excluding all elective re-admissions for scheduled chemotherapy. Patients >/= 60 years of age receiving their initial induction therapy remained hospitalized for at least 21 days until bone marrow analysis and neutrophil count above 500/mm3. The primary objective was to identify the 30-day unplanned readmission rates, cause of readmissions, and predicted factors for readmissions. The secondary outcome included 30-day readmission mortality rate and inpatient mortality rate. Results There were a total of 1681 AML hospitalizations, 393 admissions for 273 pts (average 1.44 re-admit/pt) during frontline induction, 364 for 179 pts (average 2.03) during consolidation and 924 for 298 pts (average 3.1) with relapsed/refractory AML (R/R AML). The median age was 68 years for the frontline induction and consolidation groups and 60 years for R/R AML patients. Baseline characteristics are listed in Table 1. The median length of index admission was 21 days for induction, 4 days during consolidation, and 7 days for R/R AML. The 30-day unplanned RaR was 27% for induction, 30% for consolidation, and 46% for R/R AML, with a median time to readmission of 7 days, 11 days, and 7 days, respectively. The most common causes of readmissions were infections (80%, 75% and 75% during induction, consolidation and R/R AML respectively), including 39% neutropenic fever of unknown origin (NF), 13% pneumonia, and 8% bacteremia for induction; 24% NF, 20% pneumonia and 11% gastrointestinal infections during consolidation; and 18% NF, 20% pneumonia and 14% bacteremia for R/R AML. (Figure 1) The median length of readmission was 6 days for frontline pts and 8 days for R/R AML. The rate of ICU stay was 9% for induction, and 22% for consolidation, and 18% for R/R AML. (Figure 2). There was a significant increase of ICU stay for readmissions during consolidation (22% vs 5%, p=0.010) and R/R AML (18% vs 10% p= We confirmed hypoalbuminemia (OR 3.42; p= 0.006), thrombocytopenia (OR 2.10; p= 0.015) and history of diabetes (OR 1.93; p= 0.020) as an independent predictor for readmissions during induction by multivariate analysis, while history of diabetes was significantly associated with increased risk of readmission for consolidation (OR 1.69; p=0.04) and neutropenia (OR 1.32, p= The 30-day mortality rate and inpatient mortality rate was 6% for unplanned induction readmissions, 11% for consolidation, and 18% for R/R AML. With the exception of induction, there was a higher incidence of 30-mortality for unplanned re-admissions during consolidation and R/R AML. The most common causes of death after readmission were infections with 57% for induction, 70% for consolidation, and 73% for R/R AML pts. Conclusions Unplanned 30-day readmissions, most commonly due to infection, were common among patients with AML, with rates increasing with each sequential line of therapy. While the 30-day mortality and ICU admissions remain low for induction pts, those receiving consolidation or with R/R AML had significantly higher rates. We identified several factors, including hypoalbuminemia, thrombocytopenia, neutropenia and diabetes, as independent predictors for readmission. Implementing more frequent monitoring or trading increased length-of-stay for RaR in high-risk pts could help reduce mortality in AML. Disclosures Pemmaraju: Plexxikon: Research Funding; Incyte Corporation: Honoraria; Stemline Therapeutics: Honoraria, Research Funding; Cellectis: Research Funding; AbbVie: Honoraria, Research Funding; MustangBio: Honoraria; Celgene: Honoraria; Pacylex Pharmaceuticals: Consultancy; Affymetrix: Other: Grant Support, Research Funding; Samus Therapeutics: Research Funding; Daiichi Sankyo: Research Funding; DAVA Oncology: Honoraria; Roche Diagnostics: Honoraria; SagerStrong Foundation: Other: Grant Support; Blueprint Medicines: Honoraria; LFB Biotechnologies: Honoraria; Novartis: Honoraria, Research Funding. DiNardo:Takeda: Honoraria; Celgene: Consultancy, Honoraria, Research Funding; MedImmune: Honoraria; ImmuneOnc: Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria, Research Funding; Syros: Honoraria; Daiichi Sankyo: Consultancy, Honoraria, Research Funding; Jazz: Honoraria; Novartis: Consultancy; Calithera: Research Funding; Notable Labs: Membership on an entity's Board of Directors or advisory committees. Daver:Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Research Funding; Servier: Research Funding; Genentech: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novimmune: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Trovagene: Research Funding; Fate Therapeutics: Research Funding; ImmunoGen: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Trillium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Syndax: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees. Borthakur:Oncoceutics: Research Funding; Nkarta Therapeutics: Consultancy; Treadwell Therapeutics: Consultancy; BioTherix: Consultancy; Novartis: Research Funding; AstraZeneca: Research Funding; Incyte: Research Funding; Abbvie: Research Funding; Jannsen: Research Funding; GSK: Research Funding; Cyclacel: Research Funding; BioLine Rx: Research Funding; Polaris: Research Funding; Xbiotech USA: Research Funding; BioLine Rx: Consultancy; FTC Therapeutics: Consultancy; PTC Therapeutics: Research Funding; PTC Therapeutics: Consultancy; Argenx: Consultancy; Curio Science LLC: Consultancy; BMS: Research Funding. Cortes:Immunogen: Research Funding; Bristol-Myers Squibb: Research Funding; BiolineRx: Consultancy, Research Funding; Arog: Research Funding; Amphivena Therapeutics: Research Funding; Astellas: Research Funding; Telios: Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Merus: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Sun Pharma: Research Funding; BioPath Holdings: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Daiichi Sankyo: Consultancy, Research Funding. Ravandi:Amgen: Consultancy, Honoraria, Research Funding; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Xencor: Consultancy, Honoraria, Research Funding; Macrogenics: Research Funding; Orsenix: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria. Kantarjian:Astex: Research Funding; Daiichi-Sankyo: Research Funding; Immunogen: Research Funding; Cyclacel: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Research Funding; Novartis: Research Funding; Agios: Honoraria, Research Funding; Ariad: Research Funding; Amgen: Honoraria, Research Funding; Takeda: Honoraria; AbbVie: Honoraria, Research Funding; BMS: Research Funding; Pfizer: Honoraria, Research Funding. Garcia-Manero:Novartis: Research Funding; Helsinn Therapeutics: Consultancy, Honoraria, Research Funding; Acceleron Pharmaceuticals: Consultancy, Honoraria; Amphivena Therapeutics: Research Funding; H3 Biomedicine: Research Funding; Jazz Pharmaceuticals: Consultancy; Astex Pharmaceuticals: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Merck: Research Funding; Onconova: Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Kadia:Ascentage: Research Funding; Astra Zeneca: Research Funding; Novartis: Honoraria; Amgen: Research Funding; Pulmotec: Research Funding; Astellas: Research Funding; Cyclacel: Research Funding; JAZZ: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; Incyte: Research Funding; Celgene: Research Funding; Cellenkos: Research Funding.

Introduction: Hyperbaric oxygen therapy (HBO) is approved for difficult-to-treat tissue injury. It also been used as a second-line treatment for refractory infection in hematologic malignancies. However, data on the efficacy of HBO in such population are limited. Here, we reviewed our single-center experience of HBO used in patients with hematologic malignancies. Methods: We identified patients undergoing HBO treatment by insurance authorization data between December 2012 and October 2019 at MD Anderson Cancer Center. Patients with a diagnosis of hematologic malignancies with or without history of stem-cell transplant were included. Clinical and demographic data were collected by retrospective chart review. Results: A total of 50 patients were included: 26 (52%) patients had Acute Myeloid Leukemia, 31 (62%) patients had received an SCT, and 34 (68%) patients had active disease, of whom 28 (56%) had relapsed/refractory disease. The most common infections were: 19 (38%) BK cystitis and 17 (34%) fungal sinusitis. Median number of HBO sessions was 5 (range 1–60), and median HBO duration was 17 days (range 0–109). All patients received initial HBO in the hospital; 25 (50%) patients were discharged from hospital at either completion of HBO or after transition to outpatient treatment. Sixteen (32%) patients were discharged to hospice, and 8 (16%) patients died during the hospitalization. Ninety-day and 1-year mortality were high at 52% and 78%, respectively. Median survival was 3.1 months. Patients with BK cystitis were less likely to respond to HBO (odds ratio 0.16, p=.004). Eight patients had response to HBO and achieved remission of infection at last follow-up. These patients had a higher proportion (50%) of underlying disease in remission, compared to 29% in rest of patients (n=42). The treatment indications in the responding group were 2 BK cystitis, 2 fungal sinusitis, 2 cellulitis, and 2 non-BK cystitis. Other patient characteristics were similar to the rest of the patients. Patients with response/infection remission had better survival with HR 0.18 (95% CI .063–.529, p=.002). Conclusion: A small subset of patients with hematologic malignancies, 16% in our study, had meaningful recovery from infection after HBO treatment. In our experience, patients whose underlying malignancy was in remission and patients with non-BK infection had better outcomes. Additional studies are needed to better identify the population who would benefit from HBO.

Studies have shown high rates of depression among men who have sex with men (MSM) in developed countries. Studies have also shown association between depression and HIV risk among MSM. However, very little research has been done on depression among African MSM. We assessed depression and HIV risk among a sample of MSM in Tanzania. We reviewed data on 205 MSM who were recruited from two Tanzanian cities using the respondent driven sampling method. Demographic and behavioral data were collected using a structured questionnaire. HIV and sexually transmitted infections data were determined from biological tests. Depression scores were assessed using the Patient Health Questionnaire (PHQ-9). For the analysis, depression scores were dichotomized as depressed (PHQ > 4) and not depressed (PHQ ≤ 4). Bivariate and multivariable Poisson regression analyses were conducted to assess factors associated with depression. The prevalence of depression in the sample was 46.3%. The mean (±SD) age of the sample was 25 (±5) years. In bivariate analysis, depression was associated with self-identifying as gay (p = .001), being HIV positive (p

Introduction Since the advent of tyrosine kinase inhibitors (TKIs) in 2001, the treatment goals in the management of chronic myeloid leukemia (CML) have evolved according to international recommendations. The 2009 European LeukemiaNet (ELN) proposed a category of "suboptimal response". The 2013 recommendations introduced a "warning response" category that saw some "suboptimals" in 2009 becoming failures in 2013. The clinical implications of this intermediate category and the difference in categorizations has not been fully explored. As new recommendations are being prepared, we seek to compare the outcomes of patients with suboptimal/warning using 2009 and 2013 guidelines. Methodology We analyzed 730 patients treated with front-line TKIs in various clinical trials and identified patients who meet the criteria for suboptimal response at 3, 6 and 12 months according to the 2009 ELN guidelines and/or warning criteria according to 2013 ELN criteria. We computed descriptive statistics for patients at each of the above criteria at the 3 time points. Kaplan-Meier product limit method, was used to estimate the median for overall survival (OS), event-free survival (EFS), failure-free survival (FFS) and transformation-free survival (TFS). Results Of the 730 CML patients evaluated, using the 2009 ELN guidelines, 2%, 3% and 5% of the patients met the 3, 6 and 12 months definition of suboptimal response, respectively. Analysis of baseline characteristics show a median age of 44.1, 42.1 and 44.4 years, respectively for the three time lines with a predominantly male and white population. Using the 2013 guidelines 4%, 10% and 17% of the patients met the 3, 6 and 12 months definition of warning, respectively. Patients were again predominantly male and white with a median age at diagnosis of 41.5, 44.1 and 47 years respectively. With regard to achieving complete cytogenetic response (CCyR), a higher percentage of patients achieved CCyR using the 2013 guidelines (55.2%, 80.8% and 98%, for warning cohorts at 3, 6 and 12 months, respectively) compared to using the 2009 guidelines (35.3%, 56.5% and 81.1%, respectively). Similarly, for best molecular response, a higher percentage of patients achieved MR4.5 using the 2013 guidelines (10.7%, 20.8% and 44.2%, for warning cohorts at 3, 6 and 12 months, respectively) compared to using the 2009 guidelines (13.3%, 4.5% and 24.2%, for suboptimal cohorts respectively). With respect to survival outcomes, patients classified as warning per the 2013 guidelines had better outcomes than those with suboptimal response using the 2009 guidelines. For example, for EFS, median survival was longer for the 2013 warning cohort compared to the 2009 suboptimal cohort (29 months vs. 18 months, by 3 months assessment). For FFS, the median survival was longer for the 2013 warning cohort compared to the 2009 suboptimal cohort (68 months vs. 11 months, by 6 months assessment). Using the 2013 guidelines median survival could not be reached for most of the survival outcomes. Conclusion Our assessment reveal that survival outcomes were better for the warning cohort using the ELN 2013 recommendations compared to the suboptimal cohort of the 2009 recommendations. This represents a stage migration by moving the subset of patients with the worse outcome away from this intermediate category and into the failure. An important, still unanswered question, is the optimal management of patients in this intermediate category or of those that migrate from one category to the next based on a change in definitions. Disclosures Kantarjian: Ariad: Research Funding; Amgen: Honoraria, Research Funding; Immunogen: Research Funding; AbbVie: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Astex: Research Funding; Cyclacel: Research Funding; Pfizer: Honoraria, Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Research Funding; BMS: Research Funding; Daiichi-Sankyo: Research Funding; Takeda: Honoraria; Novartis: Research Funding. Borthakur:Eli Lilly and Co.: Research Funding; NKarta: Consultancy; PTC Therapeutics: Consultancy; Cyclacel: Research Funding; Eisai: Research Funding; Janssen: Research Funding; Agensys: Research Funding; Oncoceutics: Research Funding; Tetralogic Pharmaceuticals: Research Funding; Bayer Healthcare AG: Research Funding; BMS: Research Funding; AbbVie: Research Funding; Merck: Research Funding; GSK: Research Funding; Incyte: Research Funding; Arvinas: Research Funding; BioTheryX: Membership on an entity's Board of Directors or advisory committees; Xbiotech USA: Research Funding; Novartis: Research Funding; AstraZeneca: Research Funding; Argenx: Membership on an entity's Board of Directors or advisory committees; Polaris: Research Funding; Cantargia AB: Research Funding; BioLine Rx: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; FTC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Oncoceutics, Inc.: Research Funding; Strategia Therapeutics: Research Funding. Verstovsek:Blueprint Medicines Corp: Research Funding; Celgene: Consultancy, Research Funding; Gilead: Research Funding; Promedior: Research Funding; CTI BioPharma Corp: Research Funding; Genetech: Research Funding; Sierra Oncology: Research Funding; Pharma Essentia: Research Funding; Roche: Research Funding; NS Pharma: Research Funding; Incyte: Research Funding; Astrazeneca: Research Funding; Ital Pharma: Research Funding; Protaganist Therapeutics: Research Funding; Constellation: Consultancy; Pragmatist: Consultancy; Novartis: Consultancy, Research Funding. Kadia:BMS: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bioline RX: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Research Funding. Pemmaraju:abbvie: Consultancy, Honoraria, Research Funding; samus: Research Funding; celgene: Consultancy, Honoraria; cellectis: Research Funding; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; novartis: Consultancy, Research Funding; plexxikon: Research Funding; Daiichi-Sankyo: Research Funding; sagerstrong: Research Funding; affymetrix: Research Funding; mustangbio: Consultancy, Research Funding; incyte: Consultancy, Research Funding. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Konopleva:Agios: Research Funding; Ablynx: Research Funding; Astra Zeneca: Research Funding; Kisoji: Consultancy, Honoraria; Reata Pharmaceuticals: Equity Ownership, Patents & Royalties; Ascentage: Research Funding; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Cellectis: Research Funding; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Eli Lilly: Research Funding; Forty-Seven: Consultancy, Honoraria; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Calithera: Research Funding. DiNardo:notable labs: Membership on an entity's Board of Directors or advisory committees; jazz: Honoraria; medimmune: Honoraria; syros: Honoraria; daiichi sankyo: Honoraria; abbvie: Consultancy, Honoraria; celgene: Consultancy, Honoraria; agios: Consultancy, Honoraria. Sasaki:Otsuka: Honoraria; Pfizer: Consultancy. Jabbour:Takeda: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Cyclacel LTD: Research Funding. Cortes:Immunogen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Sun Pharma: Research Funding; Biopath Holdings: Consultancy, Honoraria; BiolineRx: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Astellas Pharma: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Merus: Consultancy, Honoraria, Research Funding; Forma Therapeutics: Consultancy, Honoraria, Research Funding.

This study, conducted among men who have sex with men (MSM) in sub-Saharan Africa (SSA), sought to replicate the syndemic effects of psychosocial health problems on HIV risk by using data collected from a sample of 300 MSM and bisexuals from Tanzania. We also sought to test the utility of syndemic theory by replicating the effects of the number of syndemic conditions on HIV risk behavior in that population. Five psychosocial health problems (i.e., the syndemic factors), acronymized as SAVID, were examined: substance use while having condomless sexual intercourse, childhood and adolescent sexual abuse, experience of anti-gay violence, internalized homonegativity (IH), and depression. Nine of the 10 odds ratios (ORs) generated from analysis of the bivariate associations between these syndemic factors were found to be statistically significant and positive; the tenth was marginally significant and positive. These results indicate not only a high degree of coexistence of the syndemic factors but also suggest that possible interactions between these factors may have additive effects on the behavioral health outcomes of the study participants. Such additive effects were confirmed by finding a A¢Â€Âœdose-responseA¢Â€Â� relationship between HIV risk-associated sexual behavior and the number of the five syndemic factors reported by each participant. After controlling for demographic and contextual factors, we found that the SAVID syndemic variable significantly increased the odds of engaging in condomless sexual intercourse (OR, 1.48). This substantiates the central tenet of syndemic theory, which is that those participants who were exposed to a greater number of the psychosocial health problems also engaged in higher-risk sexual behavior. Multivariate regression analyses revealed not only the effect of two of the syndemic conditions (substance use during sex and IH) on HIV risk-related sexual behavior but also confirmed how one demographic variable (younger age) and one culturally structured factor (being gay but still having a meaningful sexual relationship with women) uniquely contributed to syndemic conditions among Tanzanian MSM. These results suggest that a multifaceted HIV intervention grounded in syndemic theory should be considered as an effective approach to mitigating the risk environment that potentiates the vulnerability to HIV among Tanzanian MSM.

Background: In the extremely homophobic conditions in Tanzania and other countries in sub-Saharan Africa (SSA), men who have sex with men (MSM) experience disproportionate amounts of both HIV infection and psychosocial health problems, but no research has been conducted to examine the synergistic or additive effects of these adversities on their experiences. While the predominantly deficit-based research approach has identified various HIV risks and vulnerabilities, any naturally occurring protective and resilience factors that these men naturally employ to these health-related adversities remain undetermined. Purpose: This study examined the syndemic effects of psychosocial health problems on HIV infection and HIV risk and simultaneously sought to identify any resilience or protective factors that may buffer against the syndemic production of HIV infection and risk behavior among high-risk Tanzanian MSM. These syndemic health problems were coined as SAVID (Substance abuse during condomless sex, childhood and adolescent sexual abuse, violence, internalized homonegativity and depression) Methods: Cross-sectional data on demographic characteristics and HIV prevalence and risks among Tanzanian MSM residing in Dar es Salaam and Tanga were used to examine whether there is a proportional increase in HIV infection and risk as the number of syndemic conditions increases. Logistic regression analysis was used to test for interactions between syndemic conditions and to identify any potential resilience factors as a way of establishing protection against the syndemic production of HIV infection and risk among these men. At the level of interaction between protective resilience factors (moderators)-support, age visibility- and SAVID syndemic; those that reported high social visibility among Acquaintance have lower odds of contracting HIV infection when compared to those that have lower social visibility among acquaintances Results: The results revealed significant additive associations between increasing numbers of SAVID syndemic components and higher rates of HIV infection and risk. Among a variety of identified potential resilience factors, three-functional socio-support, age at self-awareness of sexual orientation and formal social visibility among acquaintances-were found to directly associated with lower odds of contracting HIV infection. At the level of interaction between protective resilience factors (moderators: functional social support, age at awareness of sexual orientation, and formal social visibility among acquaintances) and SAVID syndemics, only those sampled MSM that reported high social visibility among acquaintances had lower odds of contracting HIV infection when compared to sampled MSM that had lower formal social visibility among acquaintances Conclusion: Harnessing naturally-occurring resilience factors through strength-based research approach and innovatively disseminate them through existing secrete social network may be a cost effective and a novel health promotion strategy suitable for MSM in extreme homophobic environment.

Tanzanian men who have sex with men (MSM) experience HIV disparity and are disproportionately vulnerable to psychosocial health problems together called SAVID (Substance abuse, childhood and adolescent sexual Abuse [CSA], anti-gay Violence, Internalized homonegativity [IH], and Depression). We applied syndemic theory to assess additive effects of the SAVID problems on HIV seropositivity among 300 MSM from two Tanzanian cities, who provided demographic, psychosocial health–problem, and HIV-status information. Prevalence rates of the problems were substance abuse during condomless sexual intercourse (37.3%), a history of CSA (35.3%), anti-gay violence (22%), high IH (52.7%), and depression (58%). Bivariate analysis showed a significantly positive “dose-response” relationship between the SAVID-problem count and HIV seropositivity: SAVID problems significantly increased the odds of HIV seropositivity (odds ratio, 1.42). This is the first study in sub-Saharan Africa to use syndemic theory to explore additive effects of coexisting psychosocial health problems on HIV seropositivity among Tanzanian MSM. Our results underscore the need for comprehensive HIV interventions targeting MSM.

Instructional videos on bowel preparation have been shown to improve bowel preparation scores during colonoscopy. YouTube™ is one of the most frequently visited website on the internet and contains videos on bowel preparation. In an era where patients are increasingly turning to social media for guidance on their health, the content of these videos merits further investigation. We assessed the content of bowel preparation videos available on YouTube™ to determine the proportion of YouTube™ videos on bowel preparation that are high-content videos and the characteristics of these videos. YouTube™ videos were assessed for the following content: (1) definition of bowel preparation, (2) importance of bowel preparation, (3) instructions on home medications, (4) name of bowel cleansing agent (BCA), (5) instructions on when to start taking BCA, (6) instructions on volume and frequency of BCA intake, (7) diet instructions, (8) instructions on fluid intake, (9) adverse events associated with BCA, and (10) rectal effluent. Each content parameter was given 1 point for a total of 10 points. Videos with ≥5 points were considered by our group to be high-content videos. Videos with ≤4 points were considered low-content videos. Forty-nine (59 %) videos were low-content videos while 34 (41 %) were high-content videos. There was no association between number of views, number of comments, thumbs up, thumbs down or engagement score, and videos deemed high-content. Multiple regression analysis revealed bowel preparation videos on YouTube™ with length >4 minutes and non-patient authorship to be associated with high-content videos.

Objectives To assess HIV and sexually transmitted infection (STI) prevalence and associated risk factors in men who have sex with men (MSM) in two cities in mainland Tanzania. Methods We conducted respondent-driven sampling of 300 MSM in Dar es Salaam and Tanga. Results In Dar es Salaam, 172 (86%) men (median age 23, IQR 21–28) consented to HIV/STI testing, and 30.2% were HIV seropositive. Only five reported a previous positive HIV test: >90% were new HIV detections. 2.5% were syphilis-exposed and none hepatitis B positive, but 21.4% had a curable STI. Over 90% of the gonorrhoea and chlamydia was rectal. In Tanga, 11.1% of MSM were HIV seropositive, 8% hepatitis B positive and 0% were syphilis-exposed, with 4.4% having a curable STI. Predictors of HIV infection were number of MSM known, city, identifying as gay and having first sex with a man. Predictors for STIs were recent unprotected receptive anal intercourse, and number of MSM seen in the last month. 30% of the sample reported that they sold sex. There was no significant association between HIV and STI infection. Conclusions HIV and STI rates were substantially lower in MSM in a provincial city than in a large metropolis and rates appear to depend on larger numbers of MSM known. Most HIV detected were new cases, and there was a high burden of asymptomatic curable rectal STIs (>1 in 5 MSM). Owing to stigma, MSM may not report homosexuality and thus not have rectal STIs treated. High need for tailored HIV testing and STI screening and treatment of MSM in Tanzania is apparent.

Mobile "doctors" are traditional herbal medical practitioners who move from one rural community in Nigeria to another diagnosing disease using a digital thermometer and stethoscope before selling their herbal drugs to the patients. Are their diagnosis correct or just a deception? This reports looks at three cases of mobile doctors ' diagnosis of patients in rural southern Nigeria.

Introduction : Efforts at immunizing children against measles was intensified in Nigeria with nation-wide measles vaccination campaigns in 2005 - 2006, 2008 and 2011 targeting children between 9 and 59 months. However, there were measles outbreaks in 2010 and 2011in Abia state Nigeria. This study seeks to find out if there is any association between measles immunization coverage and measles outbreak. Methods: This is a descriptive analysis of the 2007 to 2011 Abia state measles case-based surveillance data supplied to Abia state World Health Organization office and Abia State Ministry of Health by the disease surveillance and notification officers. Results : As the proportion of cases with febrile rash who were immunized decreased from 81% in 2007 to 42% in 2011, the laboratory confirmed cases of measles increased from two in 2007 to 53 in 2011.Of the laboratory confirmed cases of measles, five (7%) occurred in children < 9 months, 48 (64%) occurred in children 9 - 59 months and 22 (29%) occurred in children < 59 months old. Seventy five percent of all laboratory confirmed cases of measles occurred in rural areas. Conclusion : Efforts should be made to increase measles immunization in children between 9 and 59 months as most cases of measles occurred in this age group as immunization coverage dropped. In addition, further studies should be carried out to determine the cause of the disproportional incidence of measles in rural areas in Abia state bearing in mind that measles immunization coverage in urban and rural areas was not markedly different Key words: Measles, Immunization, Nigeria

Background TKIs are the mainstay of treatment for CML. Cardiovascular events may occur during the course of therapy with TKI. We present a single institution experience of cardiovascular events among CML patients receiving initial therapy with various TKIs. Methods We retrospectively assessed 584 CML patients enrolled on consecutive or parallel prospective frontline TKI clinical trials (imatinib, n=281; dasatinib, n=120; nilotinib, n=132, ponatinib n=51). Treatment-emergent adverse events (TEAE) under the MedRA heading "Cardiovascular" were analyzed. Over 1,080 unique terms are included under this MedRA heading. Poisson regression models assessed factors associated with occurrence of cardiovascular and arterio-thrombotic events. Results The median age (range) at start of treatment was 49 yrs (15 - 87); 41% were female and 79% were white. The overall median time of follow-up was 66 mos, with the longest follow-up for the imatinib (117 mos) cohort and the shortest for the ponatinib (13 mos) cohort. Co-morbid predisposing conditions were present at baseline in the majority of patients, with significant imbalance among treatment arms. Cardiovascular events occurred in 53% of all patients. Hypertension (new or worsening, 42%) was the most prevalent cardiovascular TEAE, followed by rhythm/rate disorders (11%). Arterio-thrombotic event occurred in 7% of all patients (coronary artery disease in 4%, cerebrovascular in 2%, peripheral arterial in 2%). Overall, the incidence rate (IR) of cardiovascular and arterio-thrombotic TEAEs were 13.9 and 1.1 per 100-person years respectively. Ponatinib showed the highest IR of TEAEs (85.5 and 5.1 per 100-person years respectively). In a multivariate analysis, the incidence risk ratio (IRR) of cardiovascular and arterio-thrombotic events were higher for all 2nd-3rd generation TKIs compared to imatinib. The IRR with ponatinib for cardiovascular events was 7.1 (95% CI: 4.7-10.7; p≤0.001) and for arterio-thrombotic events 6.6 (95% CI: 1.8-23.8 p=0.004); dasatinib and nilotinib showed similar IRR among them, both higher than imatinib. In addition, older age was associated with higher IRR of cardiovascular (IRR=1.01, 95% CI: 1.0-1.02; p=0.003) and arterio-thrombotic (IRR=1.04, 95% CI: 1.00-1.07; p=0.023) events adjusted for other variables. Conclusion Cardiovascular TEAE are common during the course of therapy with TKI for patients with CML, predominantly for older patients and those on 2nd and 3rd generation TKI (particularly ponatinib). These patients require close monitoring during treatment. Investigation on the mechanism for cardiovascular TEAE with TKIs is required. Disclosures Jabbour: BMS: Consultancy; Pfizer: Research Funding; ARIAD: Research Funding; ARIAD: Consultancy; Pfizer: Consultancy; Novartis: Research Funding. Wierda:Novartis: Research Funding; Abbvie: Research Funding; Acerta: Research Funding; Gilead: Research Funding; Genentech: Research Funding. Daver:Otsuka: Consultancy, Honoraria; Sunesis: Consultancy, Research Funding; Ariad: Research Funding; Kiromic: Research Funding; Pfizer: Consultancy, Research Funding; Karyopharm: Honoraria, Research Funding; BMS: Research Funding. Kadia:BMS: Research Funding; Novartis: Honoraria. Burger:Portola: Consultancy; Gilead: Research Funding; Roche: Other: Travel, Accommodations, Expenses; Janssen: Consultancy, Other: Travel, Accommodations, Expenses; Pharmacyclics, LLC, an AbbVie Company: Research Funding. DiNardo:Daiichi Sankyo: Other: advisory board, Research Funding; Novartis: Other: advisory board, Research Funding; Agios: Other: advisory board, Research Funding; Abbvie: Research Funding; Celgene: Research Funding. Ravandi:Seattle Genetics: Consultancy, Honoraria, Research Funding; BMS: Research Funding. Cortes:ARIAD: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Research Funding.

In the Veterans Affairs (VA) health care system, a formulary-based approach without beneficiary cost-share incentives is used to limit the pharmacy cost of proton pump inhibitors (PPIs). However, the effectiveness of this approach in reducing the cost of PPIs is unknown.To (a) compare cost differences between the formulary PPI (generic omeprazole) and nonformulary PPIs and (b) evaluate reasons for nonformulary PPI use in order to identify opportunities to increase formulary drug use and discourage unnecessary use of nonformulary PPIs.A list of patients with receipt of PPIs from July 1, 2008, through June 30, 2009, was obtained from the Loma Linda VA Healthcare System pharmacy. Subjects with receipt of at least 120 units (capsules or tablets) of any PPI in the study period were considered long-term users. Demographic information was collected. Pharmacy consult records were reviewed to identify reasons for nonformulary use and dosing regimen of the formulary PPI prior to the switch. Cost analysis was done based on the VA contract prices for the drugs at the time of the study.Of 58,605 unique patients seen in this VA health care system in the 12-month period from July 1, 2008, through June 30, 2009, 13,713 (23.4%) received a PPI, and of these, 10,483 (76.4%) received at least 120 PPI units and were defined as long-term users. Of the long-term users, 9,462 (90.3%) were on the formulary PPI generic omeprazole, and 1,021 were nonformulary PPI users. Use of nonformulary PPIs (esomeprazole, pantoprazole, lansoprazole, rabeprazole) accounted for 10.5% of the PPI units and 9.7% of the users but 57.3% of total PPI cost. This pattern resulted in $570,263 in excess spending (i.e., $570,263 would have been saved in the study period if the nonformulary PPI users had used the formulary drug). The most common reason for nonformulary long-term PPI use was persistent symptoms (n=901, 88.2%). Adverse reaction was cited by 111 (10.9%) of nonformulary PPI users, 33.3% (n=37) of whom reported diarrhea. Of those who switched to a nonformulary PPI due to persistent symptoms, 363 (40.3%) were on once-daily dosing prior to the switch; 379 (42.1%) were on twice-daily dosing; and 159 (17.6%) were transfers from other places in which prior dosing information was not available in the hospital pharmacy records.One-year PPI use prevalence was 23% in this VA population, and long-term use prevalence was 18%. Nonformulary PPI use accounted for 10.5% of the PPI units and 9.7% of the users but 57.3% of total PPI drug cost. Opportunities to reduce nonformulary PPI use in order to reduce overall expenditures on PPIs include verification of optimal formulary PPI use, titration to twice-daily dosing, and confirmation of adverse reaction as being attributable to PPI use.

Background: Patient report of disease- and treatment-related symptom burden in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) is scarce. Symptom burden is the combined impact of disease and treatment symptoms on daily functioning. Lack of recognition and monitoring of symptoms and symptom burden can lead to inadequate management and possible treatment non-adherence. Aims: Our aim is to develop a short, valid, reliable patient-reported outcome measure of symptoms and symptom burden experienced by AML and MDS patients and to determine the validity of a single measure for research and practice. Methods: After obtaining IRB approval, patients with AML (N=152) and MDS (N=97) were recruited to this cross-sectional study. Patients rated the 13 core symptom items (pain, fatigue, nausea, disturbed sleep, distress, shortness of breath, trouble remembering, lack of appetite, drowsiness, dry mouth, sadness, vomiting, and numbness and tingling), 6 proposed AML/MDS symptom items (muscle weakness, malaise, fever, headache, diarrhea, skin problems), and 6 interference items (general activities, mood, work, relations with others, walking, and enjoyment of life) of the MD Anderson Symptom Inventory (MDASI) on 0-to-10 scales (0 = not present or no interference; 10 = as bad as can be imagined or complete interference) twice 1-2 days apart. Clinical and demographic information was collected from medical records and analyzed using descriptive statistics. Means of the symptom and interference ratings for the AML and MDS patients were compared using T-tests. Standard psychometric techniques were used to determine the reliability, stability, and validity of the instrument in patients with AML and MDS. Results: All MDS patients were outpatients while 75 of the AML patients were inpatients and 77 were outpatients. The AML and MDS patients had been diagnosed a mean of 13.8 months (standard deviation [SD]=23.9) and 30.5 months (SD=32.4) respectively. The mean (Mn) symptom and interference ratings respectively for the AML inpatients (Mn=2.8, SD=1.6; Mn=4.0, SD=2.4) were significantly higher than for the AML outpatients (Mn=1.8, SD=1.4, p Conclusion/Summary: Lack of recognition of symptoms experienced by patients with AML and MDS can lead to inadequate management of symptoms, interfere with the ability of patients to function and enjoy life, and impact the tolerability of and adherence to treatment regimens. While the symptoms experienced by the two groups had some variation in severity, a similar group of symptoms were the most common and relevant for both groups of patients, and the same measure was appropriate for both groups. The MDASI-AML/MDS is a brief, easily-completed, and validated measure of symptom burden for patients with AML and MDS that can be used for accurate and consistent monitoring of symptoms by clinicians and researchers. Disclosures Williams: Amgen: Consultancy; Novartis: Research Funding. Cortes:Pfizer: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BerGenBio AS: Research Funding; Teva: Research Funding; Ariad: Consultancy, Research Funding; Astellas: Consultancy, Research Funding; Ambit: Consultancy, Research Funding; Arog: Research Funding; Celator: Research Funding; Jenssen: Consultancy. Mendoza:Amgen Inc.: Consultancy. Shi:Amgen Inc.: Consultancy. Cleeland:Amgen Inc.: Consultancy.

e17648 Background: Patient report of symptom burden in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) is scarce. Symptom burden is the combined impact of disease and treatment symp...

Objective: Patient report of symptom burden from acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) is scarce. Symptom burden is the combined impact of symptoms from disease and treatment on daily functioning. We are developing a measure of symptom burden in AML and MDS. The purpose of this interim analysis is to compare the symptom burden of patients with AML and MDS. Methods: Patients with AML or MDS rated the 13 core symptom items, 6 proposed AML/MDS-specific symptom items, and 6 interference items of the MD Anderson Symptom Inventory on a 0-10 scale (0 = not present or no interference; 10 = as bad as can be imagined or complete interference). Patient clinical and demographic information was collected from medical records. The symptom burden of AML/MDS was determined and compared using descriptive statistics and t-tests. Results: Mean ages of the 45 AML patients and 48 MDS patients were 62.4 (standard deviation [SD] = 11.3) and 68.5 years (SD = 9.2; p = 0.005), respectively; 61% and 60% (p = not significant), respectively, were male; 76% and 92% (p = 0.043), respectively, were white. The composite mean severity score of the core symptom items was 2.75 (SD = 1.58) and 1.84 (SD = 1.52; p = 0.006), the composite mean of the AML/MDS specific items was 2.51 (SD = 1.87) and 1.49 (1.60; p = 0.005), and the composite mean score of the interference items was 3.96 (SD = 2.72) and 2.81 (SD = 2.69; p = 0.042) for the AML and MDS patients, respectively. The means, ranks, significance of difference in ratings, and prevalence of the individual symptom and interference items for the AML and MDS patients are in Table 1. Cronbach α for all symptom items was 0.94 and for all interference items was 0.92. Conclusions: Patients with AML and MDS experience similar symptoms. However, patients with AML report significantly more severe pain, fatigue, nausea, lack of appetite, dry mouth, vomiting, fever, and headache than patients with MDS. Only prevalence of shortness of breath and diarrhea was higher in MDS patients, but there was no difference in reported mean severity of these symptoms. Except for general activity, rating of symptom interference with daily activities is similar for the two groups. Lack of recognition of symptoms experienced by patients with AML and MDS can lead to inadequate management of symptoms, interfere with patients' ability to function and enjoy life, and impact the tolerability of and adherence to treatment regimens. Validation of this measure of symptom burden for patients with AML and MDS to allow more accurate and consistent monitoring of symptoms by clinicians and in clinical research is ongoing. Table 1. Individual MDASI Item Means and Significance for AML and MDS Patients Core Symptom Items N Mean SD p-value Rank Prevalence (%) Pain MDS 48 2.00 2.760 0.009* 9 58 AML 45 3.69 3.309 3 69 Fatigue MDS 47 3.45 2.947 0.037* 1 79 AML 45 4.69 2.653 1 91 Nausea MDS 48 .50 1.368 * Significant at p < 0.05. Disclosures No relevant conflicts of interest to declare.

9637 Background: A major barrier to effective symptom management in gastrointestinal stromal tumors (GIST) is lack of recognition of the symptom burden of the disease and treatment. Symptom burden ...