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ABL1 Kinase Domain (ABL1-KD) mutations are a common resistance mechanism to tyrosine-kinase inhibitors (TKIs) in Chronic Myeloid Leukemia (CML) and Philadelphia Positive Acute Lymphoblastic Leukemia (ALL). Different ABL1-KD mutations induce different degrees of resistance to different TKIs. The early detection of these resistant mutations helps to adjust patient's treatment. Here we present an Ultra-Deep Sequencing approach to detect and quantify acquired ABL1-KD mutations in genomic DNA (gDNA), aiming to define a robust test to detect such alterations in TKIs exposed Philadelphia-Positive Leukemia Patients with a resolution below 1E-4. Firstly, we defined an ABL1 specific next-generation sequencing (NGS) panel designed to cover all coding regions of ABL1 exons 4-10. The 9 amplicons were designed to cover full exons where possible to detect co-occurring mutations (Figure 1A). A panel was then applied to 3 biological replicates of 3 Healthy control donors (9 NGS data points each with 220ng of gDNA). The average coverage per amplicon in all samples was at least 500,000x. The NGS data was then analyzed applying the NGS-MRD algorithm described elsewhere (Onecha, E et al. Haematologica 2019) to 25 known ABL1-KD hotspots. After applying our error correcting algorithm, we obtained an average of 135,000 (22,000-503,000) refined reads for the 25 hotspots. The limit of detection (LOD) was calculated for every position in the DNA as the mean noise (Variant Read Frequency; VRF) per position in the controls ± 3SD (standard deviation); the limit of quantification (LOQ) being defined as mean ± 10SD. For all the hotspots analyzed, the LOD was below 1E-4 and the LOQ below 3E-4 (Figure 1B), except for p.F311L (c.931T>C; LOD=2.7E-3). The high level of noise in this position, constant in the different control samples sequenced in different sequencing runs, is most likely related to the high number of homopolymers in the region. Ten Philadelphia-Positive Leukemia patients were then screened after TKI treatment (8 CML and 2 ALL). The median BCR-ABL1 defined by quantitative PCR (ratio BCR-ABL1 vs ABL1) in these follow-up samples was 0.6% (0.034% - 95%). All patients were screened in triplicates (220ng gDNA each) and the data-points ± 1SD from the mean were considered outliers (NGS false positives) and excluded from further analysis. Five patients presented a signal above the LOD for p.T315I (c.944C>T). This position is covered by 2 different amplicons in our panel. By bioinformatically demultiplexing the signal, the detection of those five mutations in both amplicons was confirmed (Amp_4; LOD=3E-5, Amp_5; LOD=4E-5). Moreover, aiming to validate this new approach, we applied to paired RNA samples an in-house BCR-ABL1/ABL1 nested PCR + NGS approach designed to quantify those alterations in cDNA. This approach confirmed the presence of 4 out of 5 gDNA detected mutations, with a Pearson correlation of 0.92 (Pval Here we show an Ultra-Deep NGS based test which allows the early detection of TKI resistant emerging clones in genomic DNA samples with a resolution of 1E-4. Despite the facts that in Phi-positive leukemia patients' other techniques such as the nested PCR are available, for most of heme- dyscrasias it is not easy to detect acquired mutations below 1% VRF. Our test can reduce this limit by at least 2 logarithms. The clinical impact of this approach is illustrated by the two LLA patients included, both under dasatinib therapy when the p.T315I mutations were detected. Those 2 patients were changed to ponatinib, reducing BCR-ABL1 levels. An extension of the cohort and the validation of our test at clinical level will be presented at the meeting. Figure Disclosures Heredia: Altum sequencing: Current Employment. Carrillo:Altum sequencing: Current Employment. Rufian:Altum sequencing: Current Employment. Wang:Hosea Precision Medical Technology Co., Ltd: Current Employment. Ribera:Pfizer, Amgen: Research Funding; Pfizer, Amgen, Ariad, Novartis: Consultancy, Speakers Bureau. Martinez-López:Janssen, BMS, Sanofi, Novartis, Incyte, F. Hoffmann-La Roche and Amgen: Honoraria, Other: Advisory boards; Hosea and Altum: Membership on an entity's Board of Directors or advisory committees; Janssen, Novartis, BMS, Incyte: Consultancy.

Introduction. MPN-COVID is a European LeukemiaNet cohort study, launched in March 2020 in patients with myeloproliferative neoplasms (MPN) with COVID-19. The first cohort of 175 cases was analyzed at the end of first wave (July 2020) and results provided estimates and risk factors of overall mortality (Barbui T. Leukemia, 2021), thrombosis incidence (Barbui T. Blood Cancer J, 2021), and post-COVID outcomes (Barbui T. Blood Cancer J, 2021). In the second wave of pandemic (June 2020 to June 2021), case-fatality risk in the general population has been found variable across different countries, and no information is available in MPN patients with COVID-19 diagnosed during the second wave in comparison with those of the first wave. Methods. In an electronic case report form, we registered a total of 479 cases of ET (n=161, 34%), PV (n=135, 28%), pre-PMF (n=49, 10%) and overt MF (n=134, 28%), from 39 European hematology units (Italy, Spain, Germany, France, UK, Poland, Croatia). Of these, 304 were diagnosed COVID-19 during the second wave. Results. Patients in the second wave were significantly different from those in the first wave, including parameters such as age (median: 63 vs. 71 years, p Conclusions. This is the largest series of MPN patients who incurred COVID-19 from June 2020 onward, namely during the "second COVID-19 wave". Compared to the first wave, the second one recorded a lower overall COVID-19 severity, but Ruxolitinib discontinuation still remained a risk factor for a dismal outcome. Greater vulnerability of ET than PV in developing venous thrombosis was confirmed also during the second wave. This finding suggests that ET warrants a specific antithrombotic prophylaxis in addition to heparin. Figure 1 Figure 1. Disclosures Barbui: AOP Orphan: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. Iurlo: Novartis: Speakers Bureau; Incyte: Speakers Bureau; Pfizer: Speakers Bureau; Bristol Myers Squibb: Speakers Bureau. Sobas: Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Fox: Novartis: Honoraria; Sierra: Honoraria. Palandri: AOP: Membership on an entity's Board of Directors or advisory committees; CTI: Consultancy; Sierra Oncology: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Benevolo: Novartis: 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; Takeda: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Amgen: Speakers Bureau. Harrison: Gilead Sciences: 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; Sierra Oncology: Honoraria; Galacteo: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Promedior: 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, 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; Incyte Corporation: Speakers Bureau; BMS: 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; Janssen: 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; Geron: 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; Constellation Pharmaceuticals: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Bonifacio: Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: 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; Amgen: Membership on an entity's Board of Directors or advisory committees. Kiladjian: Taiho Oncology, Inc.: Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; PharmaEssentia: Other: Personal fees; AOP Orphan: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees. Patriarca: Incyte: Honoraria; Takeda: Honoraria; Argenix: Honoraria; Novartis: Honoraria; Amgen: Honoraria; Pfizer: Honoraria. Griesshammer: Janssen: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Shire: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; AOP Orphan: Consultancy, Honoraria; CTI: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria. Garcia Gutierrez: Pfizer: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Osorio: Janssen, Abbvie, Roche: Consultancy. Koschmieder: CTI: Membership on an entity's Board of Directors or advisory committees, Other; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support); Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding; Baxalta: Membership on an entity's Board of Directors or advisory committees, Other; Abbvie: Other: Travel support; Alexion: Other: Travel support; Karthos: Other: Travel support; Sanofi: Membership on an entity's Board of Directors or advisory committees, Other: Travel support; Image Biosciences: Other: Travel support; AOP Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support), Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support); Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support); Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support), Research Funding; Geron: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support), Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding; Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support); Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: (e.g. travel support); Shire: Honoraria, Other. Vannucchi: Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees.

Background: Ruxolitinib is the standard of care for myelofibrosis (MF). However not all patients respond to ruxolitinib and other lose response while on treatment or require discontinuation due to adverse events. Therefore, several clinical trials with ruxolitinib in combination with other drugs are being conducted. We previously showed the synergistic effect of the combination ruxolitinib/nilotinib/prednisone in ex vivo models of peripheral blood mononuclear cells from MF patients and cell lines. Aims: This phase Ib/II study, non-randomized, open-label, evaluates safety and tolerability of ruxolitinib in combination with nilotinib and prednisone in patients with naïve or ruxolitinib-resistant MF. Methods:Between November 2017 and June 2020, 21 patients were included in RUNIC (EudraCT Number:2016-005214-21) at 6 Spanish sites. Six patients were considered screening failures. A total of 15 patients received at least one dose of ruxolitinib and were included in the intention-to-treat (ITT) or the per-protocol (PP) populations. The study design is summarized in figure 1. Out of 15 evaluable patients whose median age was 66.5 years (53.4-70.8). Six patients (40%) had a diagnosis of primary MF, 4 patients (26.7%) post-polycythemia vera MF, and 4 patients (26.7%) post-essential thrombocythemia MF. Most patients had International Prognostic Scoring System (IPSS) intermediate-1 or -2 disease (5 [33.3%] and 4 [26.7%], respectively), and 9 patients (60%) had JAK2 V617F mutation. Most of the patients (n=13; 86.7%) had received ruxolitinib as previous anti-neoplastic therapy for MF. Results:Eight patients completed 7 cycles (53.3%), and six patients 12 cycles (40%) and nine patients withdrawn because of disease progression, lack of efficacy, or no clinical benefit (n=5), withdrawal of consent (n=2), adverse event (AE) (pulmonary thromboembolism, n=1), and investigator's medical judgment (n=1). All patients experienced at least one AE during the study (the most common were hyperglycemia, asthenia and thrombocytopenia, and 14 patients registered at least one treatment-related AE (the most common were hyperglycemia (22.2%), thrombocytopenia (13.3%), and anemia (8.9%)). Five treatment-related serious adverse events (SAEs) were reported in 2 patients (13.3%), all of them related to nilotinib: one patient had pericardial effusion and bilateral pleural effusion, the other had congestive heart failure, pleural effusion, and pulmonary hypertension. No deaths were registered throughout the study.There were 2 patients with at least one adverse event meeting criteria for dose-limiting toxicity: grade 4 anemia and lumbar pain. Only eight patients were evaluated for spleen lengths at screening and cycle 7 (Figure 2B). Of these, 6 experienced a palpable spleen reduction, 4 of them with a 100% reduction. In contrast, one patient remained with the same spleen length, and one patient experienced a 25% increase.Six patients had both symptom evaluation at screening and cycle 7 (Figure 2D). Four experienced a total symptom score reduction, one patient remained with the same total symptom score, and two patients reported an increase.Six patients had spleen length measures recorded both at screening and at cycle 12. From those, 4 showed a spleen length reduction, 3 of them with a 100% reduction. Conclusions: Ruxolitinib in combination with nilotinib and prednisone showed relevant clinical activity in patients with naïve or ruxolitinib-resistant MF. The tolerability of this combination was acceptable, and the hyperglycemia was the treatment-related AE most frequent. The main cause of trial withdrawn was disease progression, lack of efficacy, or no clinical benefit. Based on these results, this triple combination should be explored in phase II/III clinical trials. Figure 1 Figure 1. Disclosures Ayala: Incyte Corporation: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas: Honoraria; Celgene: Honoraria. Garcia Gutierrez: BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Osorio: Janssen, Abbvie, Roche: Consultancy. Sanchez: Janssen, Jazz Pharmaceuticals, Gilead, Novartis, Amgen: Consultancy. Martínez-López: Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy; Roche, Novartis, Incyte, Astellas, BMS: Research Funding.

Introduction Hyperinflammatory response induced by the SARS-CoV19 (CV) coronavirus is the main cause of morbidity and mortality. Numerous studies have pointed-out the main role of monocyte activation. In addition neutrophils alterations appear to differ pathophysiologically from the changes that occur in Influenza Virus (IV) infection. Due to the overlap of symptoms between these two entities, the search of analytical markers that help in early diagnostic orientation is considered of crucial importance. Changes in cell function, phenotype, and morphology in circulating leukocytes can be translated into numerical data obtained from an automated analyzer. The objective of our study is to generate an Artificial Intelligence Model from conventional hematological blood count parameters which be able to discriminate between CV and IV infection, in a fast and efficient maner. Methods This is a retrospective single-center study, performed between January-April 2020. The patients (n = 816) were divided into two groups: Patients who came for suspected COVID and had a positive RT-PCR (n = 408) and patients with a diagnosis of influenza confirmed by RT-PCR (n = 408). The database was divided into two random subgroups (n = 654) to train the model and another (n = 162) to validate it. The first hemogram on admission to the Emergency Department of these patients was performed on a Beckman-Coulter® DXH-900 equipment. Total white blood cells, absolute neutrophils, absolute lymphocytes, absolute monocytes, monocyte distribution wide (MDW) and Cell Morphological Data (CMDs) based on the impedance, conductivity and light scattering of these leukocyte subpopulations have been used to construct the model. Five algorithms have been evaluated using the R studio Software and the Caret (Classification and Regression Training) package: Linear Discriminant Analysis (LDA), K-Nearest Neighbor (kNN), Neural Networks (NN), Support Vector Machines (SVM) and Recursive partitioning (Rpart). Results The evaluation of the different models was based on the comparison of the efficacy obtained through a cross validation (10x). It was decided to choose the SVM model by presenting a median of the area under the ROC curve of 0,841. No data preprocessing was performed, and the parameters chosen for the model were: sigma = 0,014, C = 1 and Number of Support Vectors = 458. Parameters with greater importance (>80%) in the model, were CMDs based on Neutrophil Light Scattering (SDLNE, SDLAN, SDMNE and MNLNE). The analysis of results was performed using a confusion matrix, where the model predicts the diagnosis of each patient in the validation subgroup (Table 2). A ROC curve with an area of 0,892 was obtained, with a sensitivity and specificity of 80% and 85%, respectively (Fig 1). Conclusions The creation of prediction algorithms from hemogram parameters allow to discriminate between COVID 19 infection and influenza A and B with a high specificity and sensitivity in a fast way. This could be a great advance for the early diagnostic orientation and guide clinical decisions as soon as possible with the consequent clinical benefit. Disclosures No relevant conflicts of interest to declare.

Introduction: Myeloid malignancies are clonal disorders of hematopoietic stem cells and include acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN). Common biological markers have been described in the molecular pathogenesis, including gene mutations in splicing factors, epigenetic modifiers, transcription factors, signal pathways and tumor suppressors. These mechanisms have been associated with MDS and MPN progression to AML. Objectives: The main objective of this study is to identify differences in the mutational landscape of myeloid malignancies and describe mutation frequencies of genes and functional pathways in each neoplasm, as well as determine their clinical impact. Methods: This study involved a retrospective analysis of 430 patients with AML (209), MDS (106) and Philadelphia negative MPN (86) diagnosed in the Hospital Universitario 12 de Octubre (Spain). They were analyzed by a next generation sequencing (NGS)- panel for myeloid malignancies. The panel include 32 genes: CALR, ASXL1, EZH2, PHF6, DNMT3A 2, TET2, IDH1, IDH2, KDM6A, KMT2A, SF1, SF3A1, SF3B1, SRSF2, U2AF1, ZRSR2, PRPF40B, EPOR, FLT3, JAK2, KIT, SH2B3, MPL, CBL, HRAS, NRAS, KRAS, ETV6, RUNX1, VHL, TP53, PTEN. In addition, there were included 29 patients diagnosed with benign pathology that were referred to rule out MPN or congenital polyglobulia. Results: In the analyzed cohort we obtained a larger number of mutations in the more aggressive malignancies, AML and MDS. Mutations in epigenetic modifiers and signal pathways were the most frequent detected (31% and 24% respectively). The epigenetic modifiers were notably affected in AML (78%) and MDS (60.4%), whereas signal pathways were mutated more frequently in MPN (70.9%). Transcription factors, tumor suppressors and splicing factors mutations were more detected in AML and MDS (40%, 32%, 44% and 22%, 13%, 32% respectively). The mutation landscape obtained by genes was: Signal pathways: FLT3, NRAS, KIT, KRAS y SH2B3 were specially detected in AML (25%, 11%, 6%, 5% and 4% respectively). JAK2, CALR and MPL in MPN (38%, 15% and 6% respectively). Transcription factors: RUNX1, ETV6, PHF6, CEBPA and WT1 mutations were regularly observed in AML (21%, 6%, 6%, 6% and 5% respectively), and GATA1 in SMD (3.8%). Tumor suppressors: TP53 was particularly affected in AML (21%) and MDS (11%). Epigenetic modifiers: TET2 was notably mutated in MDS (32%), whereas ASXL1, DNMT3A, IDH2, IDH1 and EZH2 were in AML (21%, 21%, 17% 16% and 8% respectively). Splicing factors: SF3B1 was more frequently detected in MDS (18%) than AML (7%), whereas ZRSR2 presented a similar frequency in both pathologies (around 8%). U2AF1 was most commonly mutated in MPN (9%). SRSF2 was specially mutated in AML (23%). SF3A1 was altered in around 1%, similar in all three malignancies. With regard to survival studies, the presence of mutations in splicing factors (primarily in U2AF1) and its absence in signal pathways conferred an adverse outcome for overall survival (OS) in MPN. In MDS, gene mutations in tumor suppressors (especially TP53), U2AF1 splicing factor and EZH2 epigenetic modifier were associated with poor outcome. In our series of AML, gene mutations in tumor suppressors and TP53 were related to unfavorable prognosis in OS. Conclusion: The largest number of mutations and affected genes observed in AML suggest that leukemic transformation of MDS and MPN is conditioned by acquisition of new mutations. We observed different frequencies of mutations between AML, MDS and MPN that could guide the diagnostic and identify new targets of treatment. Further, some mutations have demonstrated differential prognostic impact. An extension of this study and the design of an algorithm with mutation data to elucidate a more accurate molecular prognosis will be presented at the meeting. This work has been financed thanks to the grant PI16/01225, PI 19/01518 and PI19/00730 from the Instituto de Salud Carlos III (Ministerio de Economia, Industria y Competititvidad) and cofinanced by the European Development Fund. Figure 1. Mutations detected (%) in AML, MDS and MPN classified by function. Table 1. Median overall survival of patients with MPN, MDS and AML according to gene state (mutated or not). Figure Disclosures No relevant conflicts of interest to declare.

Background. Increasing age is a risk factor for vascular events but also for bleeding in immune thrombocytopenia (ITP). In elderly, meta-analysis of clinical trials of romiplostim (ROM) and eltrombopag (ELT) show that thrombopoietin receptor agonists (TPO-RA) are effective and safe with the exception of increased thromboembolic risk (Olney et al, 2011; Michel et al 2015). Objective. To analyze how age influences the selection of TPO-RA, bleeding and thrombotic risk, comorbidities, and therapeutic management of ITP patients in a real-world setting. Methods. We conducted a multicenter retrospective study that included 121 adult patients with primary ITP from 19 secondary and tertiary Spanish hospitals who had initiated long-term therapy with ROM or ELT between January 2012 and December 2014. Information was collected from medical records (November 2016 to January 2018) to assess variables related to patient characteristics and outcomes of elderly (> 65 years; n=54) compared with younger individuals (n=67). Results. Patients included initiated TPO-RA (ROM, n=54; ELT, n=67) and maintained this therapy for a median time to collection of data of 35.2 months (1 to 67.3 months). The median age at diagnosis of elderly and younger cohorts was respectively 75 years (66-96 years), and 48 years (19-65 years). Older age was associated with a previous history of vascular events (VE) (P=0.049), with more patients receiving antithrombotic therapy (P=0.001), and with a non-significant trend towards increased risk of current VE under TPO-RA therapy (Table). During treatment, 15 patients experienced 17 VE (9 arterial, 8 venous); no association was found between risk for VE in patients under TPO-RA and past history of thromboembolic or ischemic events (P=0.727). Patients that were offered TPO-RA at younger ages presented at diagnosis with significantly lower platelet counts, and increased cumulative bleeding score (Page et al, 2007) (P=0.003, and P=0.034) than elderly ones. Younger patients also had significantly higher visceral bleeding rates at the onset of TPO-RA therapy (P=0.042) and had increased requirement for hospital care (emergency treatment or hospital admission) both six months before and after the start of TPO-RA (P=0.016, and P=0.002, respectively). Older age was associated with comorbidities such as hypertension and diabetes (P65 versus ≤65 years, however a more conservative management in terms of discontinuation of therapies was confirmed. Therefore, the rate of tapering off TPO-RA was significantly lower in those >65 years (P=0.028), although the proportion of patients that achieved therapy free response (TFR) (platelet count >50x109/l for at least 6 months) upon discontinuation was similar in both groups (Table). Conclusion. The management of older patients with chronic ITP is still challenging, and widespread effort is made to avoid potential complications such as those related to splenectomy. Our study reflects that the introduction of TPO-RAs has caused a change in the outcomes of these patients. The increased awareness of the unfavorable conditions that are present in this population induces a preferential use of TPO-RAs in elderly patients with a lower bleeding history than in younger patients. Although these drugs associate with a potential risk of increased thrombotic risk, our data indicate that past thrombotic history does not predispose to the development of VE; rather neoplasia in elderly patients, and splenectomy at younger ages are factors that increase the likelihood to suffer from these events. The compromise towards effective therapies in these fragile patients associates with low discontinuation of TPO-RA to test for TFR, although once tapered off, sustained platelet responses are similar to those in younger patients. Disclosures Mingot-Castellano: Novonordisk: Consultancy; Sobi: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Bayer: Consultancy; CSL Behring: Consultancy; Roche: Consultancy; Novartis: Consultancy. Jarque:Abbie: Consultancy, Speakers Bureau; Alexion: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; CellTrion: Consultancy; Gilead: Consultancy, Speakers Bureau; Grifols: Consultancy; Janssen: Consultancy, Speakers Bureau; MSD: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; Servier: Speakers Bureau; Shionogi: Consultancy, Speakers Bureau; Shire: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau. Campos:Novartis: Speakers Bureau; Amgen: Speakers Bureau. Lopez Fernandez:Amgen: Consultancy, Speakers Bureau. Valcarcel:MSD: Consultancy, Honoraria, Speakers Bureau; Astellas: Consultancy, Honoraria, Speakers Bureau; JAZZ: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau. Casado:Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau. Álvarez Roman:Takeda: Research Funding; Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Bayer: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; CSL Behring: Consultancy, Speakers Bureau; NovoNordisk: Consultancy, Speakers Bureau; Sobi: Consultancy, Speakers Bureau.

Background and aims: Significant efforts have been made in international guidelines since 2009 to establish recommendations for the initial work-up of patients with suspected immune thrombocytopenia (ITP), and to define who should be treated and how. A previous retrospective study of 101 ITP patients identified important areas of inappropriateness in the diagnostic and therapeutic management of ITP (Lozano et al, 2016), which could negatively impact patient outcomes. This study was aimed to further analyze the level of implementation of current recommendations in the standard practice of adult ITP patients in an independent validation cohort, and compare it to the pre-guideline period. Methods: We collected retrospectively the clinical data of 146 primary adult ITP patients who initiated treatment with thrombopoietin receptor agonists (TPO-RA) between January 2012 and December 2014. Data on patient characteristics were obtained from medical records from November 2016 to January 2018 in a multicenter study from 19 secondary and tertiary Spanish hospitals. To evaluate the laboratory diagnosis and the appropriateness of treatment according to guidelines, two cohorts of patients were considered: "pre-group" and "post-group" depending on the date of diagnosis (before or after January 2010). Results: Patients in pre-group (n=71) and post-group (n=75) had a median follow-up from diagnosis of 13.6 years (7.5-54.2 years), and 4.6 years (2.2-7.6 years), respectively. The level of compliance of general diagnostic tests was analyzed and compared. Peripheral blood smear, an examination recommended by all recent guidelines, was performed in 84% of patients in the post-group, and in only 64% of those in the pre-group (P=0.007). Bone marrow assessment at diagnosis of the disorder was ordinarily performed in around half of the patients regardless of the period (54% and 47% in the pre- and post- groups, respectively; P=0.408). Remarkably, in 49% of the patients in the pre-group, bone marrow evaluation was primarily performed due to the department policy, whereas that reason decreased to 25% in the post-group (P=0.027). Moreover, in 21% and 9% of patients in the pre-group and post-group that underwent a bone marrow assessment at diagnosis, the peripheral blood film had not been previously examined (P=0.192). In our cohort, differences in the treatment patterns were analyzed. Prednisone was used as first line-therapy in 89% and 84% of pre- and post- groups, respectively (P=0.406). There was a significant decrease in the duration of first-line therapy with prednisone from start until withdrawal in the post-group compared with the pre-group (median 77 vs. 122 days, respectively; P=0.004). Following first-line treatment, more patients in the pre-group were exposed to further prednisone (45% vs. 25%, P=0.003), and also the number of second or subsequent lines of therapies with this corticosteroid were significantly higher (61 courses of prednisone retreatment in 32 patients vs. 22 courses in 19 patients in the pre- and post- groups, respectively; P=0.008). As expected, a higher proportion of patients in the pre-group underwent splenectomy, and also received more immunosuppressant and immunomodulatory drugs than those in the post-group prior to TPO-RA therapy (P Conclusions: Although some studies have analyzed the compliance with the proposals of guidelines, to date it remains unclear whether the implementation of the recommendations of these consensus-based documents has significantly changed the management of ITP patients compared to the pre-guideline era. Overall, our study evidences that the post-guideline management of ITP in the hospitals included in this multicenter study shows substantial gaps for the diagnosis and treatment of these patients. These deviations include failure to perform universal peripheral blood film examination, ordinary bone marrow assessment in half of the patients at diagnosis, and corticosteroid abuse in terms of duration and number of lines of therapies being prescribed. However, those shortcomings have experienced a considerable reduction compared to the previous decade, likely as a result not only of the availability of new therapies, but also from the translation into the physician's practice of the proposals of guidelines. Table Disclosures Mingot-Castellano: Roche: Consultancy; Takeda: Consultancy; Sobi: Consultancy; CSL Behring: Consultancy; Amgen: Consultancy; Novartis: Consultancy; Bayer: Consultancy; Novonordisk: Consultancy. Jarque:Takeda: Consultancy, Speakers Bureau; Shire: Consultancy, Speakers Bureau; Shionogi: Consultancy, Speakers Bureau; Servier: Speakers Bureau; Roche: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; MSD: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Grifols: Consultancy; Gilead: Consultancy, Speakers Bureau; CellTrion: Consultancy; Celgene: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Abbie: Consultancy, Speakers Bureau; Alexion: Consultancy, Speakers Bureau. Campos:Novartis: Speakers Bureau; Amgen: Speakers Bureau. Lopez Fernandez:Amgen: Consultancy, Speakers Bureau. Casado:Novartis: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau. Álvarez Roman:Roche: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Bayer: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Takeda: Research Funding; NovoNordisk: Consultancy, Speakers Bureau; CSL Behring: Consultancy, Speakers Bureau; Sobi: Consultancy, Speakers Bureau.

Background: Kinase domain (KD) mutations is a common resistance mechanism, secondary to the tyrosine-kinase inhibitors (ITKs) treatment in the case of chronic myeloid leukemia (CML) and Philadelphia (Ph)-positive acute lymphoblastic leukemia (ALL) patients. Sanger sequencing is the gold standard technique and already the currently recommended method for BCR-ABL1 KD mutation detection. However, Sanger sequencing has limited sensitivity and cannot firmly identify populations with variant allele frequencies (VAF) < 15-20%. Next-generation sequencing (NGS) allow us the screening of mutations in the whole KD with variants with a VAF greater than 1%. The aim of this study is to evaluate the clinical and prognostic implications of CML and Ph-positive ALL patients who have been studied for mutations in BCR-ABL1 by NGS. Methods: Seventy CML and Ph-pos ALL patients have been studied for BCR-ABL1 mutations between years 2015-2017. The study reason was warning or failure according to European Leukemia Net recommendations in the case of CML patients, and diagnostic or relapse in the case of ALL patients. Clinical characteristics of the patients are depicted on Table 1. Categorical variables are described as frequency, and quantitative variables as medians. Contingency tables were used to analyze associations between categorical variables (χ2). Median test was used to compare medians of continuous variables between groups. Overall survival (OS) was estimated using the Kaplan-Meier method and compared between patients using the log-rank test. Results: We have found 37 patients with mutations (51%), the most frequent being p.T315I, p.L248V and p.L387M. 28 out of 59 were found in CML (47%) vs 9 out of 13 (69%) in ALL. Of the 37 patients with mutations, double mutations have been found 10 times (27%). In the 72 analyses performed, 62 mutations were found in total, 41 of them were variants of uncertain significance (VUS) and 21 were well-known mutation. The median levels of BCR-ABL1 (IS) at the time of analysis were 3.00 (0.01-196.18) %. Regarding CML patients, we have found 12 and 16 cases with pathogenic mutations and VUS, respectively. The mean survival for CML and ALL were 75.2 months (CI 95%, 65.7-84.6) and 24.7 months (13.3-36.2), respectively. There are significant differences between the overall survival curves for patients with CML who have mutations in BCR-ABL1 compared to those who have VUS or do not (p-value = 0.024, n=59), suggesting a second role of the VUS variants in the resistance of the patients to the TKI. These two groups have no significant differences in ALL patients (p-value= 0.32, n=13). Overall survival at 10 years from the date of diagnosis is 74% for CML patients with mutations and 90% for CML patients without mutations. Data dropped significantly for ALL patients, but the number of cases is too low. Conclusions: - Mutations have been identified in 47% of CML patients studied in the case of failure or warning and 69% of the patients of ALL at diagnosis or relapse moments. - The identification of pathogenic variants has poor prognosis in patients with CML (p = 0.024), however no differences were observed in ALL. - The identification of VUS is not associated to poor prognosis and these variants could not confer resistance to ITK. Disclosures Sevilla: Rocket Pharmaceuticals, Inc.: Honoraria, Patents & Royalties: Inventor on patents on lentiviral vectors filled by CIEMAT, CIBERER and F.J.D and may be entitled to receive financial benefits from the licensing of such patents; NOVARTIS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Rocket: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sobi: Membership on an entity's Board of Directors or advisory committees; Miltenyi Biotech: Honoraria. Steegmann:Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. García Gutiérrez:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Incyte: Honoraria, Research Funding.

Background . In clinical practice, tapering off thrombopoietin receptor agonists (TPO-RA) in immune thrombocytopenia (ITP) is considered if therapy is no longer needed due to a decrease in the disease activity favoring sustained treatment-free responses (TFR). To date, there are no predictors to identify when this approach is likely to be successful, other than earlier start of TPO-RA, and robust platelet responses. Aim. To evaluate clinical predictors of TFR in a real-world cohort of ITP patients treated with TPO-RA by dealing with confounding variables that could be minimized at the stage of the analysis. Methods. In this retrospective, multicenter study from 19 secondary and tertiary Spanish hospitals, patients aged >18 years with chronic ITP who had initiated TPO-RA (eltrombopag [EPG] or romiplostim [ROM]) between January 2012 and December 2014 were included. Data were collected from medical records (November 2016 to January 2018) on patient characteristics, history of disease and previous therapies, TPO-RA administration, response and discontinuation. Results. A total of 82 patients with a median age of 63 years (range 19-90 years), 59.9% females initiated TPO-RA (ROM, n=37; EPG, n=45). The median time from diagnosis of ITP to therapy with TPO-RA was 5.5 years (1.1-50.3 years). In all cases the TPO-RA was started with intention to treat indefinitely; the median initial doses of EPG were 350 mg/week (175-525 mg/week), and those of ROM 2.0 μg/kg/week (1.0-7.0 μg/kg/week). The median time on TPO-RA treatment was 2.9 years (0.1 to 5.6 years), and the median follow-up from start of TPO-RA until collection of data was of 3.9 years (1.3 to 5.6 years). A total of 29 patients (35.4%) switched TPO-RA during follow-up. The most frequent cause for switching was lack of efficacy (44.8% of cases -in all cases the initial TPO-RA was EPG-). Due to switching, 58 patients received ROM, and 53 were treated with EPG, yielding 122.3, and 100.8 patient-years of total exposure, respectively. During follow-up almost one half of the patients (47.6%, n=39) stopped TPO-RA. After a median of 1.4 years (0.1-3.3 yrs) under TPO-RA treatment, 19 patients (23.2% of the whole cohort) maintained TFR defined as platelet counts >50x109/l for a median follow-up of 2.8 years (1.5-4.4 years) in the absence of any platelet increasing drug. Remarkably, while the specific TPO-RA that was discontinued did not influence the probability to achieve TFR (P=0.582), there was a trend towards receiving ROM as first TPO-RA and attaining sustained responses (P=0.073), while switching TPO-RA negatively predicted TFR (P=0.010). In univariate analysis with logistic regression, switching TPO-RA was associated with a 6.4 risk of not achieving TFR (P= 0.019). The overall comparison of the Kaplan-Meier curves indicated an association (log-rank P=0.041) among the initial TPO-RA that was prescribed and the probability of TFR (Fig 1A), but the estimated median time to achieve TFR was not reached for either TPO-RA. When switching and initial TPO-RA were considered, patients receiving ROM and not experiencing switching were the best performing group in terms of achieving TFR; the median time to taper off the drug and sustain platelet responses was 3.3 years (95% CI 2.7-4.0 years) (Fig. 1B). Conclusion. In this observational research analysis, we have tried to minimize the possible bias of some studies that could mistakenly attribute TPO-RA induced TFR, when in fact it may be the natural course of the underlying disease. By analyzing a group of chronic ITP patients with a particularly poor baseline prognosis (median time from diagnosis 5.5 years) we address potential confounding variables by disease severity. Our data show that assuring that long duration under TPO-RA therapy is provided (median of 3.3 years), one half of chronic ITP patients treated with ROM and not undergoing switching can achieve TFR. Disclosures Mingot-Castellano: Roche: Consultancy; Bayer: Consultancy; Novartis: Consultancy; Takeda: Consultancy; Sobi: Consultancy; Amgen: Consultancy; Novonordisk: Consultancy; CSL Behring: Consultancy. Jarque:Abbie: Consultancy, Speakers Bureau; Alexion: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Grifols: Consultancy; Gilead: Consultancy, Speakers Bureau; CellTrion: Consultancy; Celgene: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Servier: Speakers Bureau; Roche: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; MSD: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Shire: Consultancy, Speakers Bureau; Shionogi: Consultancy, Speakers Bureau. Campos:Novartis: Speakers Bureau; Amgen: Speakers Bureau. Lopez Fernandez:Amgen: Consultancy, Speakers Bureau. Casado:Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau. Álvarez Roman:Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Bayer: Consultancy, Speakers Bureau; Pfizer: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; CSL Behring: Consultancy, Speakers Bureau; Sobi: Consultancy, Speakers Bureau; Takeda: Research Funding; NovoNordisk: Consultancy, Speakers Bureau.