European LeukemiaNet 2017 risk stratification for acute myeloid leukemia: validation in a risk-adapted protocol

The 2017 European LeukemiaNet (ELN 2017) guidelines for the diagnosis and management of acute myeloid leukemia (AML) have become fundamental guidelines to assess the prognosis and postremission therapy of patients. However, they have been retrospectively validated in few studies with patients included in different treatment protocols. We analyzed 861 patients included in the Cooperativo Para el Estudio y Tratamiento de las Leucemias Agudas y Mielodisplasias-12 risk-adapted protocol, which indicates cytarabine-based consolidation for patients allocated to the ELN 2017 favorable-risk group, whereas it recommends allogeneic stem cell transplantation (alloSCT) as a postremission strategy for the ELN 2017 intermediateand adverse-risk groups. We retrospectively classified patients according to the ELN 2017, with 327 (48%), 109 (16%), and 245 (36%) patients allocated to the favorable-, intermediate-, and adverse-risk group, respectively. The 2- and 5-year overall survival (OS) rates were 77% and 70% for favorable-risk patients, 52% and 46% for intermediate-risk patients, and 33% and 23% for adverse-risk patients, respectively. Furthermore, we identified a subgroup of patients within the adverse group (inv(3)/t(3;3), complex karyotype, and/or TP53 mutation/17p abnormality) with a particularly poor outcome, with a 2-year OS of 15%. Our study validates the ELN 2017 risk stratification in a large cohort of patients treated with an ELN-2017 risk-adapted protocol based on alloSCT after remission for nonfavorable ELN subgroups and identifies a genetic subset with a very poor outcome that warrants investigation of novel strategies

Formulación de un plan de mejoramiento basados en la metodología ITIL 4 para la mejora continua de los procesos de servicios de software y mantenimiento de sistemas en la empresa colombiana SOFTMANAGEMENT S.A. en la ciudad de Bogotá D.C.

Las organizaciones hoy en día buscan estar al margen del mercado con el fin de potenciar sus servicios y productos, además que la interacción con el cliente sea más cercana, buscando generar el máximo valor de negocio. Es por esto por lo que los marcos de referencia como ITIL tienen gran popularidad en la gestión de servicios del lado de las organizaciones y del cliente. La empresa colombiana SOFTMANAGEMENT S.A. se dedica a la prestación de servicios de desarrollo, fabricación y construcción de software, soporte y mantenimiento de sistemas a nivel nacional, por este motivo la compañía cuenta con gran variedad de operación tecnológica en el negocio en áreas de desarrollo de mantenimiento e infraestructura. Además, es una empresa que se caracteriza por estar en cada momento de los proyectos al lado de los clientes, y tomar el acompañamiento como una filosofía que los caracteriza, para ello tienen los más altos estándares de Calidad, que les permite que los proyectos realizados, lleguen a ser exitosos, productivos y con un alto grado de satisfacción. Este proyecto se ha enfocado en la mejora del sistema de gestión de servicios para la empresa SOFTMANAGEMENT S.A, utilizando lineamientos indicados por la NORMA TECNICA NTC-ISO Colombiana 20000-1 y el marco de referencia ITIL 4, estableciendo requerimientos necesarios para lograr la buena gestión de los procesos y establecer el modelo de trabajo requerido para cumplir con la filosofía de mejora continua. Actualmente la organización presenta oportunidades de mejora frente a la gestión de servicios debido a que no cuenta con estándares sólidos en los procesos de registro y soporte de servicios, llevando a que se presente baja satisfacción del cliente por incumpliendo en los requerimientos pactados. Es por ello que se ha decidido contemplar un plan de mejoramiento en el sistema de gestión de servicios que permita lograr mayor eficiencia en la gestión de sus procesos y cumplir con los requerimientos establecidos por sus clientes internos y externos, llevando a la organización a reafirmar y mejorar su posición de liderazgo.GLOSARIO,-- INTRODUCCION,-- 1. DESCRIPCION DEL PROBLEMA, -- 1.1 PLANTEAMIENTO DEL PROBLEMA, -- 1.2 OBJETIVOS DEL PROBLEMA, -- 1.2.1Objetivo general,-- 1.2.2 Objetivos específicos,-- 2. MARCOS DE REFERENCIA,-- 2.1 MARCO TEORICO, -- 2.2 MARCO INSTITUCIONAL, -- 2.2.1 Plataforma estratégica de la empresa SOFTMANAGEMENT S.A., -- 2.2.2 Políticas y principios de SOFTMANAGEMENT S.A., -- 2.2.3 Líneas de servicio o productos, -- 3. METODOLOGIA, -- 3.1 POBLACION, -- 3.2 TECNICA PARA LA RECOLECCION Y ANALISIS DE LA INFORMACION, -- 3.3 TECNICAS, HERRAMIENTAS Y METODOS PARA EL DISEÑO E IMPLEMENTACION DE LOS SISTEMAS DE GESTION TECNOLOGICA, -- 4. DIAGNOSTICO DE LAS CONDICIONES ACTUALES DE LA COMPAÑÍA SOFTMANAGEMENT S.A., -- 4.1 ESTADO DE LAS CONDICIONES ACTUALES, -- 4.2 DETERMINACIÓN DE FACTORES CRÍTICOS, -- 4.3 IDENTIFICACIÓN DE HALLAZGOS SIGNIFICATIVOS, -- 5. FORMULACIÓN DE PLAN DE MEJORAMIENTO EN LA EMPRESA SOFTMANAGEMENT S.A. BASADO EN LA APLICACIÓN DEL MARCO DE REFERENCIA ITIL 4 EN LA CIUDAD DE BOGOTÁ, -- 5.1 PLAN DE MEJORAMIENTO, -- CONCLUSIONES, -- RECOMENDACIONES, -- [email protected]@campusucc.edu.c

Oligomonocytic and overt chronic myelomonocytic leukemia show similar clinical, genomic, and immunophenotypic features

Oligomonocytic chronic myelomonocytic leukemia (OM-CMML) is defined as those myelodysplastic syndromes (MDSs) or myelodysplastic/myeloproliferative neoplasms, unclassifiable with relative monocytosis (≥10% monocytes) and a monocyte count of 0.5 to 94% classical monocytes (MO1s) and CD56 and/or CD2 positivity in peripheral blood monocytes, was similar to overt CMML. The MO1 percentage >94% method showed high accuracy for predicting CMML diagnosis (sensitivity, 90.7%; specificity, 92.2%), even when considering OM-CMML as a subtype of CMML (sensitivity, 84.9%; specificity, 92.1%) in our series of 233 patients (39 OM-CMML, 54 CMML, 23 MDS, and 15 myeloproliferative neoplasms with monocytosis and 102 reactive monocytosis). These results support the consideration of OM-CMML as a distinctive subtype of CMML

The Complete Mutatome and Clonal Architecture of Del(5q)

Abstract Cytogenetic abnormalities are found in around half of MDS patients (pts) and have both clinical impact and may be subtype-defining, e.g. in 5q-syndrome. Interstitial deletion of the long arm of chr.5 [del(5q)] is the most common aberration (almost 20% of cases with abnormal cytogenetics). Del(5q) is heterogeneous, occurring as a sole abnormality or in combination, with the deleted region often truncated within or extended and/or beyond the CDR boundaries. Isolated del(5q) is frequently shorter and confers a more favorable prognosis with regard to survival and lenalidomide (LEN) responsiveness, while del(5q) in the context of a complex karyotype (CK) imparts a poor prognosis. In addition to chromosomal lesions, somatic mutations can contribute to the pathogenesis of MDS, including del(5q). We theorized that recognition of molecular defects in MDS with del(5q) may clarify the pathogenic mechanisms behind this lesion and help explain the clinical heterogeneity. We analyzed 225 pts with myeloid neoplasia and del(5q) using WES (n= 107 samples) and targeted multiplexed PCR (top 60 most frequently mutated genes) (n =133 samples); serial analysis was performed in 15 pts studied at ≥2 time points, 11 during LEN therapy and 4 upon relapse/progression. A total of 116 samples had a CK with other lesions such as -7/del(7q) found in 31% cases, and 18% had -17/del(17p). WES (average depth >60x) was followed by a bioanalytic pipeline, detecting ≥1 mutated gene in 71% of cases. Candidate somatic alterations were found in 357 genes and selected for further analysis. When focused on hemizygous mutations within the retained 5q allele, CSNK1A1 mutations were the most common, found in 4 pts, while other genes were only sporadically affected. Among heterozygous mutations on the non-deleted portion of del(5q) and other chromosomes (Chr), we found several novel mutations, in addition to TP53 (n=26), DNMT3A (n=8), PRPF8 (n =8), RUNX1 (n=5), TET2 (n=5), and ASXL1 (n=4), among others. Furthermore, LOH/haploinsuffciency of genes on 7q (e.g., LUC7L2, CUX1, EZH2 and MLL3) appears to be a common defect seen in pts with non-isolated del(5q), suggesting synergistic functional defects. When functionally grouping gene mutations, DNA methylation family (8 cases) and transcription factor mutations (29 cases) were associated with advanced disease (AD) and a CK. Heterozygous mutations in TP53 (34%) or deletions involving the TP53 locus (23%) resulted in total of 42% of cases carrying either TP53 LOH or mutation. TP53 lesions were more common in pts with AD vs. low risk. (21 vs. 5 p =.0008). In contrast, TP53 mutations are found in 8-10% of cases of MDS. A total of 34 pts were treated with LEN and subgrouped into responders (n=17) vs. refractory (n=9) with an overall response rate of 65%. When mutational profiles were compared, the presence of TP53 mutations did not preclude responsiveness to LEN. CK was present in 12% of responders vs. 67% of refractory pts. The most frequent Chr abnormalities were -7/7q (0% vs. 67% in responders vs. refractory) and 17p-(6% vs. 67% in responders vs. refractory) suggestive of their role in LEN resistance. In addition to cross sectional analysis, our WES study using paired Germline/tumor samples followed by deep sequencing facilitated analyses of clonal architecture by examining clonal dynamics over time. Assessment of del(5q) clone size by allelic imbalance combined with clonal burden by VAF allowed us to reconstruct the clonal hierarchy: in 73% of cases, del(5q) appeared to be the initial defect followed by subsequent mutations (e.g., TP53, DNMT3A, IDH2). In contrast, in 24% of cases, TP53, RUNX1, JARID2, were the primary defect followed by a subclonal del(5q) events. Serial samples collected before and after therapy demonstrated that responses were associated with decreased clonal burden for del(5q) but persistence of certain mutations. In refractory cases, persistent subclonal lesions and the appearance of new lesions were associated with progression. For example, pts with TP53, LAMB4, EPHA6 progressed and acquired additional lesions such as CSMD2 or KCND2, and did not see the disappearance of TP53 alterations upon treatment. In conclusion, no unifying somatic defect was found in pts with del(5q) regardless if the deletion event was primary or subclonal. Most commonly associated lesions were not present on the retained 5q alleles but rather other chr yet modified clinical behavior, including responsiveness to LEN. Disclosures Bejar: Celgene: Consultancy, Honoraria; Alexion: Other: ad hoc advisory board; Genoptix Medical Laboratory: Consultancy, Honoraria, Patents & Royalties: MDS prognostic gene signature. Sekeres:Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; TetraLogic: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees

An Analysis of Prognostic Markers and the Performance of Scoring Systems in 1837 Patients with Therapy-Related Myelodysplastic Syndrome - a Study of the International Working Group (IWG-PM) for Myelodysplastic Syndromes (MDS)

Abstract Background: The International Prognostic Scoring System (IPSS) for MDS has recently been revised (IPSS-R). However both scoring systems were developed after exclusion of therapy-related cases and data on its usefulness in treatment-related MDS (tMDS) is limited. Aims and Methods: We analyzed 1837 pts from Spanish, German, Swiss, Austrian, US, Italian, and Dutch centers diagnosed 1975-2015. Complete data to calculate the IPSS/-R was available in 1511 pts. The impact of prognostic features was analyzed by uni- and multivariable models and estimated by a measure of concordance for censored data (Dxy). Results: Median age was 68 years. 1% of pts had 5q-syndrome, 13% RCUD, 4% RARS, 27% RCMD/-RS, 18% RAEB 1, 18% RAEB 2, 4% CMML 1, 2% CMML 2, 3% MDS-U, and 7% AML (RAEB-T) according to WHO-classification. Regarding cytogenetics 38% exhibited good, 14% intermediate, and 48% poor-risk according to IPSS, and 2% very good, 36% good, 17% intermediate, 15% poor, and 31% very poor according to IPSS-R. Prognostic risk groups were 12% IPSS low, 34% int 1, 36% int 2, and 18% high, while the IPSS-R was very low in 8%, low in 20%, intermediate in 17%, high in 23%, and very high in 32%. The most frequent primary diseases were NHL 28%, breast cancer 16%, myeloma 6%, prostate cancer 6%, Hodgkins disease 5%, and 4% gastrointestinal tumors. Patients received chemotherapy in 75% and radiotherapy in 47%. Regarding chemotherapeutic drugs, most pts received combination regimens containing alkylating agents in 65%, topoisomerase inhibitors in 44%, antitubulin agents in 26%, and antimetabolites in 26%. Median follow-up from MDS diagnosis was 59 months, median survival 16 months. Since a disease altering treatment is, at least in higher risk disease, which is overrepresented in tMDS, standard of care, we decided to analyze treated as well as untreated pts to avoid a selection bias. This included stem cell transplantation in 16% with a median survival of 24 months. Features with influence on survival and time to AML in univariable analysis included FAB, WHO, IPSS, IPSS-R, cytogenetics, hb, platelets, marrow and peripheral blasts, ferritin, LDH, fibrosis, ß2-microglobulin, and use of alkylating agents for the treatment of primary disease. For hemoglobin, platelets, LDH, fibrosis, and ß2-microglobulin the influence was stronger on survival. Year of diagnosis, age, gender, neutrophil count, WBC, use of chemo or radiotherapy as well as other chemotherapeutic agents had no marked influence on both outcomes. According to our results, both the IPSS (Dxy 0.29 for survival, 0.32 for AML) and IPSS-R (Dxy 0.34, 0.32 for AML) perform moderately in tMDS, but not as well as in primary MDS (pMDS). Therefore, existing prognostic models need to be adjusted to tMDS. However, this appears to be not without difficulties. The scores tested, as well as most prognostic variables themselves perform inferior compared to pMDS. It becomes even more complicated since tMDS in itself is even more heterogeneous than pMDS. Scores and variables perform differently depending on the primary disease or therapy. The IPSS/-R and its variables perform for example better in pts with solid tumors compared to hematologic diseases or in pts who have received radio- instead of chemotherapy, but also in pts after prostate compared to breast cancer. In addition to the integration of further variables, new cutoffs, or the weighting of existing variables, we are currently testing the possibility of separate score versions for different tMDS subgroups. Separate score versions for survival and time to AML would also give differing weights to most features. Hemoglobin, platelets and cytogenetics would get more weight for survival, while marrow blasts would be more important regarding AML. Conclusion: In contrast to early descriptions of tMDS, with poor risk cytogenetics in the vast majority of pts and a uniformly poor prognosis, surprisingly we find good risk karyotypes in a relatively large number of pts. Although, poor risk cytogenetics are still overrepresented, this indicates, different types of tMDS exist. Our analysis shows that many variables exhibit prognostic influence in tMDS and the IPSS or preferably IPSS-R can be applied in these pts. However, the prognostic power of both scores is inferior compared to pMDS, making an optimized tMDS score reasonable. Currently data from further IWG centers is integrated in our database and further analyses are performed to propose a tMDS specific score. Figure 1. Figure 1. Disclosures Komrokji: Novartis: Research Funding, Speakers Bureau; Pharmacylics: Speakers Bureau; Incyte: Consultancy; Celgene: Consultancy, Research Funding. Sekeres:TetraLogic: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Steensma:Celgene: Consultancy; Incyte: Consultancy; Amgen: Consultancy; Onconova: Consultancy. Valent:Novartis: Consultancy, Honoraria, Research Funding; Ariad: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Celgene: Honoraria. Platzbecker:Boehringer: Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Esteve:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria

Therapy-Related MDS Can be Separated into Different Risk-Groups According to Tools for Classification and Prognostication of Primary MDS

Abstract The current classification system for Myelodysplastic Syndromes lumps all therapy-related (tMDS) into one subgroup assuming all tMDS had the same poor prognosis. We have put together a database including 2032 patients with a diagnosis of tMDS from several different IWG centers and the MDS clinical research consortium. With the idea of developing an individual scoring system for tMDS, we decided to start by optimizing the cytogenetic part of the IPSSR. First, we did an extensive review of karyotypes. Finally, 1245 patients had complete data and correct ISCN formula to be used for score development. We could show regarding karyotypes there are very limited differences between primary and tMDS. Mainly the distribution of risk groups differs with complex occurring more (37%) and normal karyotypes occurring less frequent, although still accounting for 30%. There are few exceptions that are relatively special for tMDS, like translocations including 11q23. A few karyotypes are less frequent; therefore, we could not evaluate the value of IPSS-R cytogenetics for all karyotypes. However, if we apply IPSS-R cytogenetics to our patient cohort, we can separate 5 different risk groups as in pMDS. We tested the performance of the score by using the Dxy. As main endpoint we chose transformation-free survival giving better information about the severity of the disease compared to the single endpoints survival and AML transformation that where calculated for completeness as well. The Dxy for the IPSS-R cytogenetic part is 0.31 for transformation-free survival. This indicates an effective prognostic performance although not as good as in pMDS. Several attempts were done to develop a tMDS specific cytogenetic score. The best draft scoring component achieves a Dxy of 0.33. Counting the number of aberrations achieves a score of 0.30. If normal clone present or not is added, the performance of this very simple model is improved with a Dxy of 0.32. As we could show, all these different approaches lead to a comparable performance. One can argue that still regarding a few karyotypes the prognostic impact is slightly different between p and tMDS (e.g. +8). On the other hand, the most practical approach seems to be to adopt the original cytogenetic part of the IPSS-R for further score development since clinicians do not need to use different scoring systems for different MDS subtypes. While the final analyses for the development of a tMDS specific risk score are currently under way, extensive calculations regarding the performance of different scores like WHO- (Dxy 0.24), FAB-classification (Dxy 0.19), WPSS-R (Dxy 0.35), IPSS-R (Dxy 0.37), and IPSS-R+age (Dxy 0.36), show all these systems can separate different risk groups within our cohort. However, these results also show an inferior performance of the scoring systems in t compared to pMDS. There are multiple possible reasons for this. The most important seem to be tMDS patients are often not cured from the primary disease and its disease specific risk of death should ideally be considered. Unfortunately, we don't have that data. And second, we included treated as well as untreated patients. It seems not to be feasible otherwise since the selection bias for old unfit patients would be unacceptable. We could show already in pMDS that the score performances are considerably worse if we analyze treated patients and the score performance in our cohort is better if limited to untreated patients. To conclude, we can say existing classification and scoring systems work in tMDS and can separate groups with clearly different risk for death and transformation. Although we could not develop a tMDS specific cytogenetic score this could be seen positively since it underlines tMDS do not seem to be much different regarding disease specific risk. This should initiate a discussion of a revision of the WHO-classification and encourage clinicians to use the existing tools for risk assessment and treatment decisions. A simple solution could be to use the WHO classification for pMDS and precede each subgroup with a t, like tMDS-SLD, and so on. Such an approach would be of importance for patients falsely classified as tMDS. After all this classification is done according to anamnestic information only and sporadic cases cannot be excluded. Until now, in the first analyzes performed with the final tMDS-database, we did not find any indication that risk factors established in pMDS would lose or change their meaning in tMDS. Figure. Figure. Disclosures Komrokji: Celgene: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees. List:Celgene: Research Funding. Roboz:Orsenix: Consultancy; Eisai: Consultancy; Novartis: Consultancy; Celltrion: Consultancy; Astex Pharmaceuticals: Consultancy; Argenx: Consultancy; Janssen Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Consultancy; Argenx: Consultancy; Janssen Pharmaceuticals: Consultancy; Pfizer: Consultancy; Cellectis: Research Funding; Daiichi Sankyo: Consultancy; Sandoz: Consultancy; Otsuka: Consultancy; Daiichi Sankyo: Consultancy; Eisai: Consultancy; Pfizer: Consultancy; Roche/Genentech: Consultancy; Novartis: Consultancy; Celltrion: Consultancy; Celgene Corporation: Consultancy; Cellectis: Research Funding; Orsenix: Consultancy; Aphivena Therapeutics: Consultancy; Otsuka: Consultancy; Jazz Pharmaceuticals: Consultancy; Sandoz: Consultancy; Roche/Genentech: Consultancy; Aphivena Therapeutics: Consultancy; AbbVie: Consultancy; Bayer: Consultancy; Bayer: Consultancy; Astex Pharmaceuticals: Consultancy; Celgene Corporation: Consultancy; AbbVie: Consultancy. Döhner:Jazz: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Pfizer: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Celator: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Valent:Pfizer: Honoraria; Novartis: Honoraria; Incyte: Honoraria. Platzbecker:Celgene: Research Funding. Lübbert:TEVA: Other: Study drug; Celgene: Other: Travel Support; Cheplapharm: Other: Study drug; Janssen: Honoraria, Research Funding. Díez-Campelo:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Stauder:Celgene: 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; Teva: Research Funding. Germing:Janssen: Honoraria; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding

Frequency and Prognostic Significance of Cytogenetic Abnormalities in 1269 Patients with Therapy-Related Myelodysplastic Syndrome - a Study of the International Working Group (IWG-PM) for Myelodysplastic Syndromes (MDS)

Abstract To develop a prognostic scoring system tailored for therapy-related myelodysplastic syndromes (tMDS), we put together a database containing 1933 patients (pts) with tMDS from Spanish, German, Swiss, Austrian, US, Italian, and Dutch centers diagnosed between 1975-2015. Complete data to calculate the IPSS and IPSS-R were available in 1603 pts. Examining different scoring systems, we found that IPSS and IPSS-R do not risk stratify tMDS as well as they do primary MDS (pMDS), thereby supporting the need for a tMDS-specific score (Kuendgen et al., ASH 2015). The current analysis focuses on cytogenetic information as a potential component of a refined tMDS score, based on this large, unique patient cohort. Of the 1933 pts, 477 had normal karyotype (KT), 197 had missing cytogenetics, while 467 had a karyotype not readily interpretable. Incomplete karyotype descriptions will be reedited for the final evaluation. Of the remaining 1269 pts the most frequent cytogenetic abnormalities (abn) were: -7, del(5q), +mar, +8, del(7q), -5, del(20q), -17, -18, -Y, del(12p), -20, and +1 with >30 cases each. Frequencies are shown in Table 1. Some abn were observed mostly or solely within complex KTs, such as monosomies, except -7. Others, like del(20q) or -Y, are mainly seen as single or double abn, while del(5q), -7, or del(7q) are seen in complex as well as non-complex KTs. The cytogenetic profile overlapped with that of pMDS (most frequent abn: del(5q), -7/del(7q), +8, -18/del(18q), del(20q), -5, -Y, -17/del(17p), +21, and inv(3)/t(3q) (Schanz et al, JCO 2011)), with notable differences including overrepresentation of complete monosomies, a higher frequency of -7 or t(11q23), and a more frequent occurrence of cytogenetic subtypes in complex KTs, which was especially evident in del(5q) occurring as a single abn in 16%, compared to 70% within a complex KT. IPSS-R cytogenetic groups were distributed as follows: Very Good (2%), Good (35%), Int (17%), Poor (15%), Very Poor (32%). Regarding the number of abn (including incomplete KT descriptions) roughly 30% had a normal KT, 20% 1, 10% 2, and 40% ≥3 abn, compared to pMDS: 55% normal KT, 29% 1, 10% 2, and 6% ≥3 abn. To be evaluable for prognostic information, abn should occur in a minimum of 10 pts. As a single aberration this was the case for -7, +8, del(5q), del(20q), del(7q), -Y, and t(11;varia) (q23;varia). Of particular interest, there was no apparent prognostic difference between -7 and del(7q); del(5q) as a single abn was associated with a relatively good survival, while the prognosis was poor with the first additional abn; t(11q23) occurred primarily as a single abn and was associated with an extremely poor prognosis, and prognosis of pts with ≥4 abn was dismal independent of composition (Table 1). To develop a more biologically meaningful scoring system containing homogeneous and prognostically stable groups, we will further combine subgroups with different abn leading to the same cytogenetic consequences. For example, deletions, unbalanced translocations, derivative chromosomes, dicentric chromosomes of 17p, and possibly -17 all lead to a loss of genetic material at the short arm of this respective chromosome affecting TP53. Further information might be derived from analyses of the minimal common deleted regions. For some abn, like del(11q), del(3p), and del(9q), this can be refined to one chromosome band only (table 1). Conclusion: Development of a robust scoring system for all subtypes of tMDS is challenging using existing variables. This focused analysis on the cytogenetic score component shows that favorable KTs are evident in a substantial proportion of pts, in contrast to historic data describing unfavorable cytogenetics in the majority of pts. Although complex and monosomal KTs are overrepresented, this suggests the existence of distinct tMDS-subtypes, although some of these cases might not be truly therapy-induced despite a history of cytotoxic treatment. The next steps will be to analyze the prognosis of the different groups, develop a tMDS cytogenetic score, and examine minimal deleted regions to identify candidate genes for development of tMDS, as well as to describe the possible influence of different primary diseases and treatments (radio- vs chemotherapy, different drugs) on induction of cytogenetic subtypes. Our detailed analysis of tMDS cytogenetics should reveal important prognostic information and is likely to help understand mechanisms of MDS development. Disclosures Komrokji: Novartis: Consultancy, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Sole:Celgene: Membership on an entity's Board of Directors or advisory committees. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees. Roboz:Cellectis: Research Funding; Agios, Amgen, Amphivena, Astex, AstraZeneca, Boehringer Ingelheim, Celator, Celgene, Genoptix, Janssen, Juno, MEI Pharma, MedImmune, Novartis, Onconova, Pfizer, Roche/Genentech, Sunesis, Teva: Consultancy. Steensma:Amgen: Consultancy; Genoptix: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Millenium/Takeda: Consultancy; Ariad: Equity Ownership. Schlenk:Pfizer: Honoraria, Research Funding; Amgen: Research Funding. Valent:Amgen: Honoraria; Deciphera Pharmaceuticals: Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Ariad: Honoraria, Research Funding; Deciphera Pharmaceuticals: Research Funding. Giagounidis:Celgene Corporation: Consultancy. Giagounidis:Celgene Corporation: Consultancy. Platzbecker:Celgene Corporation: Honoraria, Research Funding; TEVA Pharmaceutical Industries: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Janssen-Cilag: Honoraria, Research Funding; Amgen: Honoraria, Research Funding. Lübbert:Janssen-Cilag: Other: Travel Funding, Research Funding; Celgene: Other: Travel Funding; Ratiopharm: Other: Study drug valproic acid