MD Anderson Scoring System (MDACC) Predicts Outcomes After Hematopoietic Stem Cell Transplantation (HSCT) Better Than Other Prognostic Classifications In MDS

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3340-3340
Author(s):  
Piyanuch Kongtim ◽  
Uday R Popat ◽  
Marcos de Lima ◽  
Guillermo Garcia-Manero ◽  
Elias J. Jabbour ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Risk Group ◽  
Univariate Analysis ◽  
Scoring Systems ◽  
Risk Groups ◽  
High Risk Group ◽  
Risk Scores ◽  
Hematopoietic Stem ◽  
Very High

Abstract MDS is a heterogeneous group of hematopoietic stem cell disorders. Various prognostic models have been established to categorize patients with MDS including the International Prognostic Scoring System (IPSS), the Revised-IPSS (r-IPSS) and MDACC Scoring System. In this analysis, we compared those three classification schemas for their outcome predictability after HSCT. We analyzed 291 MDS patients with a median age of 55 (interquartile range (IQR) 47-60.7 years) who underwent HSCT between January 2001 and December 2011. Histology by WHO classification included RA/RARS 48 (16.5%), RCMD 28 (9.6%), RAEB-1 59 (20.2%), RAEB-2 63 (21.7%), MDS unclassified 67 (23%), and CMML 26 (9%). Of 291, 117 patients (40.2%) had therapy related MDS (t-MDS). Conditioning regimen was myeloablative in 201 patients (69.1%) and reduced intensity in 90 patients (30.9%). Donors were matched related (MRD), matched unrelated (MUD), mismatched (MMD) in 131 (45%), 114 (39.2%) and 46 (15.8%) patients respectively. Risk categorization was performed by IPSS, r-IPSS and MDACC scoring systems at the time of diagnosis. IPSS, r-IPSS and MDACC scoring systems could be assessed in 239 (82.1%), 241 (82.8%) and 231 (79.4%) patients respectively. The median follow up time of 109 survivors was 45 months. The median time from diagnosis to HSCT was 7.3 months (IQR 4.6-12.4 months). Three-year overall survival (OS) was 38.1% (95%CI 32.3-43.9) with 3-year event free survival (EFS) of 34.2% (95%CI 28.4-40). Cumulative relapse incidence (RI) at 3-year was 28.8% (95%CI 23.3-34.5). Cumulative incidence of treatment related mortality (TRM) at 3 year post-transplant was 27.9% (95%CI 22.6-33.6). In univariate analysis, IPSS and r-IPSS were able to differentiate 2 risk groups for OS and EFS. High risk group per IPSS and very high risk group per r-IPSS had lower OS with hazard ratio (HR) of 2.4 to 3.1, lower EFS with HR of 2.2 to 2.7. While IPSS could not predict RI, very high risk group by r-IPSS had higher RI with HR of 3.6 compared with lower risk groups. Both IPSS and r-IPSS did not identify different risk groups for TRM. On the other hand, MDACC scoring system was able to identify 4 different risk groups for EFS and OS in univariate analysis. Three-year OS was 68%, 46.1%, 30.3% and 11.4% for patients with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 respectively (p<0.001) (figure1). Three-year EFS with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 was 61.7%, 40.8%, 28.1% and 7.4% respectively (p<0.001). For RI and TRM, only MDACC risk scores of ≥9 was associated with poor outcomes with 3-year RI of 38.9% and 3-year TRM of 41.7% compared with 13.3% and 15.5% in risk scores of 0-4 (p=0.01 and p=0.01 respectively). In multivariate analysis, MDACC score, matched unrelated and mismatched donors were associated with inferior OS (table1). As a summary, MDACC risk scoring system for MDS better differentiates prognostic groups than IPSS or r-IPSS. Considering the high frequency of t-MDS among transplanted MDS patients, we propose that MDACC scoring system should be used for prognostic classification for hematopoietic transplantation. Disclosures: No relevant conflicts of interest to declare.

Prediction of Survival in Patients with Myelodysplastic Syndrome According to WHO Classification-Based Prognostic Scoring System (WPSS).

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4617-4617
Author(s):  
Jun Ho Jang ◽  
Kihyun Kim ◽  
Chul W. Jung ◽  
Keon Woo Park
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Risk Scores ◽  
The Mean ◽  
Very High

Abstract Background Based upon the classification of FAB criteria, International Prognostic Scoring System(IPSS) has been a standard prognostic model to predict survival and progression in MDS. In 2000, the WHO has formulated a new classification of myelodysplastic syndrome(MDS). The aim of this study was to evaluate the prognostic value of WHO classification-based prognostic scoring system(WPSS) in MDS. Patients and methods One hundred forty-nine patients who were diagnosed as having de novo MDS at the Division of Hematology-Oncology, Samsung medical center, Seoul, Korea, between Dec. 1994 and Feb. 2007, were evaluated retrospectively for clinical and hamatologic features at diagnosis, transfusion dependence, overall survival(OS), and progression to leukemia(LFS). Risk group stratifications in MDS patients were done according to IPSS and WPSS. Results 18 patients(12.1%), 93 patients (62.4%), 29 patients(29%) and 9 patients(6%) had IPSS risk scores of low, intermediate-1(Int-1), intermediate-2(Int-2) and high, respectively. According to WPSS risk scores, 8 patients(5.4%), 30 patients(20.1%), 41 patients(27.5%), 57 patients(38.3%) and 13 patients(8.7%) were classified to very low, low, intermediate, high and very high risk group, respectively. In IPSS, median OSs of low, Int-1, Int-2 and high subgroup were 65.2, 32.9, 14.3 and 9.1 months respectively (p<0.001). According to WPSS, median OSs of very low, low, intermediate, high and very high risk subgroup were not reached, 55.4, 27.4, 19.0 and 6.2 months respectively (p<0.001). Between subgroups classified according to WPSS, significant differences in OS were noted in low vs. intermediate risk group (p=0.047), in intermediate vs. high risk group (p=0.046) and in high vs. very high risk group(p=0.003) but statistically not significant difference in OS was observed between very low and low risk group (p=0.08). The mean and median OS of the lowest risk group(low risk) in IPSS are 65.33 and 55.43 months, respectively. The mean and median OS of the lowest risk group(very low risk) in WPSS are 102.8 months and not reached, respectively. Conclusion These data show that WPSS with five risk groups might provide more refined prognostic stratifications of MDS than IPSS with four risk groups. Especially, new prognostic system appears to discriminate a subset of patients with very low risk, who could have long term survival.

The Utility Of Newer Risk Models In Predicting Outcomes Of Patients (pts) With Higher-Risk (HR) Myelodysplastic Syndromes (MDS) Treated With Azactidine (aza)

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2771-2771
Author(s):  
Amer M. Zeidan ◽  
Najla H Al Ali ◽  
Mohamed A. Kharfan-Dabaja ◽  
Eric Padron ◽  
Ling Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Research Funding ◽  
Goodness Of Fit ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Information Criteria ◽  
Prognostic Groups ◽  
Very High

Abstract Background While aza is the only drug shown to prolong survival in MDS, only half of aza-treated pts achieve objective responses (10-20% complete remission), and 4-6 months might be needed before a response is seen. Therefore the ability to select pts with high and low likelihoods of benefit from aza therapy is a clinical and a research priority. No clinical or laboratory parameter consistently predicts response or survival with aza therapy. A French prognostic scoring system (FPSS) was proposed to predict survival among aza-treated pts with HR-MDS. We sought to compare the relative prognostic discriminatory power of the FPSS with that of the revised IPSS (IPSS-R) and the global MD Anderson prognostic scoring system (MDAPSS) in a large cohort of aza-treated pts with IPSS HR-MDS. Methods The MDS database at Moffitt Cancer Center (MCC) was used to identify patients with HR-MDS (International Prognostic Scoring System [IPSS] intermediate-2 [INT-2] and high-risk) who received aza therapy. Kaplan-Meier curves were used to depict survivals, and the log-rank test was used to compare median overall survival (OS). Akaike information criteria (AIC) were used to assess the relative goodness of fit of the models. Results We identified 259 patients HR-MDS (74.1% with INT-2 and 25.9% with high IPSS) treated with aza at the MCC. The median duration of follow up since diagnosis was 53 months (M) (95% confidence interval [CI], 49-59 M). The median number of aza cycles was 5 (range 1-72), with 75% of pts receiving 4 cycles of therapy or more. The median time from diagnosis to aza initiation was 1.5 M. The median OS for the entire cohort was 19 M (95%CI, 16-22 M), 64% of pts were males, 91% were white, 80% were older than 60 years, and 25% had therapy-related MDS. For the IPSS, the median OS was 23.5 M (CI, 18.4-28.6 M) for INT-2 and 15.9 M (CI, 13.6-18.2 M) for high-risk group (P=0.004). For the FPSS, the median OS was 29.5 M (CI, 14.1-44.9 M) for low risk (LR), 21.1 M (CI, 16.4-26.0 M) for intermediate risk (IR), and 14.1 M (CI, 8.7-19.5 M) for HR (P=0.001). For the MDAPSS the median OS was not reached (NR) for low, 53.5 M (CI, 37.5-69.4 M) for INT-1, 29.5 M (CI, 18.3-40.6 M) for INT-2, and 16.1 M (CI, 14.5-17.7 M) for high risk groups (P<0.0001). For the IPSS-R, the median OS 40.6 M (CI, 22.8-58.4 M) for low, 44.7 M (CI, 25.0-64.4 M) for INT, 23.5 M (CI, 20.3-26.8 M) for high, and 15.2 M (CI, 13.7-16.8 M) for very-high risk groups (P<0.0001). Scores generated using AIC to assess the relative goodness of fit (lower is better) were 1453 (IPSS-R), 1480 (MDAPSS), 1512 (FPSS), and 1522 (IPSS). The IPSS could not refine any of the other models. All three newer models refined IPSS INT-2 but not IPSS high-risk. The IPSS did not refine any of the newer models. The MDAPSS refined the FPSS LR and IR and the IPSS-R high and very-high groups. The FPSS refined IPSS-R very high risk group but not the not the MDAPSS. The R-IPSS did not refine the MDAPSS or the FPSS. Response rates were not statically significantly different within the prognostic groups in any of the scoring systems. Conclusions The IPSS-R, MDAPSS, and the FPSS all functioned well to separate aza-treated pts with IPSS HR-MDS into prognostic groups with different survivals, but the IPSS-R and MDAPSS appear superior to the FPSS. None of the prognostic systems predicted response to aza therapy. HR-MDS patients with poor projected survival with aza therapy might be considered for experimental approaches. Disclosures: Off Label Use: entinostat for MDS. Lancet:Celgene: Research Funding. List:Celgene: Research Funding. Komrokji:Celgene: Research Funding, Speakers Bureau.

Chemotherapy-associated thrombosis in cancer outpatients: Risk factors and decision making of a prophylactic approach.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e20647-e20647
Author(s):  
Martina Torchio ◽  
Benvenuto Franceschetti ◽  
Carla Cavali ◽  
Sonia Zanirato ◽  
Angelo Olgiati ◽  
...  
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
High Risk ◽  
Scoring System ◽  
Risk Group ◽  
Venous Catheter ◽  
Risk Groups ◽  
High Risk Group ◽  
Factors Analysis ◽  
Negative Predictor

e20647 Background: Venous thromboembolism (VTE), is a negative predictor of survival in pts with advanced cancer. International guidelines don’t recommend routine prophlaxis but suggest to consider pts, undergoing chemotherapy (CT), with high risk of VTE. Many clinical risk factors for cancer-associated VTE have been evaluated in a 5 parameter-based (body mass index, platelet and leucocyte counts, hemoglobin value and tumor site) scoring system, the Khorana score, utilized to indicate a prophylactic approach. We prospectively applied this score in cancer outpts beginning CT and an implementation based on 6 addictional factors analysis (sex, age, central venous catheter, CT-agents, antiangiogenetic drugs, erithropoiesis stimulating agent) to evaluate their impact in pts assignment into risk groups. Methods: We studied adult pts, followed at our Department from August 2011 to December 2012, with advanced cancers (breast, NSCLC, colorectal, pancreatic/gastric, urogenital, LNH, Hodgkin's disease, HD, and MM), receiving a first or second line standard CT. We stratified pts into three risk groups (score 0= low; score 1-2=intermediate; score 3-4-5=high) considering both the Khorana scoring system and its implementation. Results: We analyzed 169 pts (103F/66M, median age 62.3, range 35-80 yrs), pt population included: 38 breast, 32 colorectal, 31 LNH, HD and MM, 27 urogenital, 22 NSCLC and 19 pancreatic/gastric. With the Khorana score 49 pts were assigned to the low risk, 87 pts to the intermediate risk (57 with score=1, 28 with score=2), 16 pts (9.4%) to the high risk group (9 with score=3, 4 with score=4, 3 with score=5). When we considered 11 parameters 37 pts (21.8%) were assigned to the high risk group. Conclusions: A more comprehensive quantification of VTE risk, also considering new independent factors, is mandatory for a correct decision making of an antithrombotic-prophylactic approach.

Varying Importance of Prognostic Factors in Subgroups of Myelodysplastic Syndromes Defined by Blast Count, Cytogenetic Risk Group, or WHO Classification.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2776-2776
Author(s):  
Andrea Kuendgen ◽  
Corinna Strupp ◽  
Kathrin Nachtkamp ◽  
Barbara Hildebrandt ◽  
Rainer Haas ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
Univariate Analysis ◽  
Risk Groups ◽  
High Risk Group ◽  
Intermediate Risk ◽  
Blast Count

Abstract Abstract 2776 Poster Board II-752 Introduction: We wondered whether prognostic factors have similar relevance in different subpopulations of MDS patients. Methods: Our analysis was based on patients with primary, untreated MDS, including 181 RA, 169 RARS, 649 RCMD, 322 RSCMD, 79 5q-syndromes, 290 RAEB I, 324 RAEB II, 266 CMML I, 64 CMML II, and 209 RAEB-T. The impact of prognostic variables in univariate analysis was compared in subpopulations of patients defined by medullary blast count, namely <5%, ≥5% (table), ≥10%, and ≥20% (not shown), as well as 3 subpopulations defined by the cytogenetic risk groups according to IPSS (table). Multivariate analysis of prognostic factors was performed for cytogenetically defined subgroups and WHO-subtypes. Results: Strong prognostic factors in all blast-defined subgroups were hemoglobin, transfusion dependency, increased WBC, age, and LDH. However, all variables became less important in patients with ≥20% blasts (RAEB-T) and increased WBC was rare. Platelet count and cytogenetic risk groups were relevant in patients with <5%, ≥5%, and ≥10% marrow blasts, but not in RAEB-T. Marrow fibrosis was important in patients with <5% or ≥5% blasts, but not ≥10%. Gender and ANC <1000/μl were significant only in patients with a normal blast count. Furthermore, we looked for the effect of the karyotypes, relevant for IPSS scoring (-Y, del5q, del20q, others, del7q/-7, complex), and found a comparable influence on survival, irrespective whether patients had < or ≥5% marrow blasts. In subpopulations defined by cytogenetic risk groups, several prognostic factors were highly significant in univariate analysis, if patients had a good risk karyotype. These included hemoglobin, sex, age, LDH, increased WBC, transfusion need, and blast count (cut-offs 5%, 10%, and 20%). In the intermediate risk group only LDH, platelets, WBC, and blasts were significant prognostic factors, while in the high risk group only platelets and blast count remained significant. Multivariate analysis was performed for the cytogenetic risk groups and for subgroups defined by WHO subtypes. The analysis considered blast count (</≥5%), hemoglobin, platelets, ANC, cytogenetic risk group, transfusion need, sex, and age. In the subgroup including RA, RARS, and 5q-syndrome, LDH, transfusion, and age in descending order were independent prognostic parameters. In the RCMD+RSCMD group, karyotype, age, transfusion, and platelets were relevant factors. In the RAEB I+II subgroup, the order was hemoglobin, karyotype, age, and platelets, while in CMML I+II only hemoglobin had independent influence. In RAEB-T none of the factors examined was of independent significance. Looking at cytogenetic risk groups, in the favorable group, several variables independently influenced survival, namely transfusion, blasts, age, sex, and LDH (in this order). Interestingly, in the intermediate and high risk group, only blast count and platelets retained a significant impact. Conclusion: Univariate analysis showed prognostic factors (except ANC) included in IPSS and WPSS are relevant in most subgroups defined by marrow blast percentage. However, they all lose their impact if the blast count exceeds 20%. Regarding cytogenetic risk groups, several prognostic factors lose their influence already in the intermediate risk group. This underscores the prognostic importance of MDS cytogenetics. Multivariate analysis showed MDS subpopulations defined by WHO types also differ with regard to prognostic factors. In particular, CMML and RAEB-T stand out against the other MDS types. Disclosures: Kuendgen: Celgene: Honoraria. Hildebrandt:Celgene: Research Funding. Gattermann:Novartis: Honoraria, Participation in Advisory Boards on deferasirox clinical trials. Germing:Novartis, Celgene: Honoraria, Research Funding.

scholarly journals Comprehensive Clinical-Molecular Transplant Risk Model for Myelofibrosis Undergoing Allogeneic Stem Cell Transplantation

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 689-689 ◽  
Author(s):  
Nico Gagelmann ◽  
Markus Ditschkowski ◽  
Rashit Bogdanov ◽  
Marie Robin ◽  
Bruno Cassinat ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Research Funding ◽  
Triple Negative ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Risk Groups ◽  
Karnofsky Performance Score ◽  
Very High ◽  
Reduced Intensity

Abstract Background The dynamic International Prognostic Scoring System (DIPSS) is commonly applied to predict survival among patients with primary myelofibrosis (PMF) but has been shown to perform less precisely in secondary myelofibrosis (SMF) and after transplantation. Furthermore, the prognostic relevance of mutation profile resulted in the mutation-enhanced IPSS (MIPSS) in PMF, as well as in a model specific to SMF (MYSEC-PM) after essential thrombocythemia (ET) or polycythemia vera (PV). The aim of the current study was to develop a comprehensive prognostic system including clinical and molecular information, specifically in myelofibrosis undergoing transplantation. Methods Previously published methods were used to sequence myelofibrosis-associated genes (i.a. CALR1/2, JAK2, MPL,ASXL1, SRSF2, EZH2, IDH1/2, DNMT3A, TET2, TP53). Outcome was calculated from date of transplant (95% confidence interval). Variables associated with overall survival (OS) constructed a Cox regression with a stepwise selection procedure. Hazard ratios (HR) were used as weights for model development. Validation was done using repeated random subsampling. Performance of the model was verified via Harrel's concordance index C and was also tested in predefined cohorts: disease (PMF, SMF), conditioning, and ruxolitinib pretreatment. Results Population. The total cohort consisted of 361 patients from four different centers in Germany and France (260 PMF, 101 SMF). Median age at transplant was 57 years (range, 22-75), 58% were male and 42% had a Karnofsky performance score (KPS) <90. The median follow-up was 62 months and was similar between PMF and SMF (p=0.50). Overall 5-year OS was 60% (54-67) being similar in PMF (63%) and SMF after ET (59%) and slightly lower after PV (45%). Most frequent mutations were: JAK2 V617F (57%), CALR (20%; types 1/2/other 66%/23%/11%), MPL (5%), ASXL1 (31%), TET2 (19%), SRSF2 (9%), DNMT3A (6%), TP53 (6%). Two or more mutations were present in 60%. Most transplants were received from matched unrelated (46%), mismatched unrelated donors (MMUD, 27%), identical siblings (27%), and mismatched siblings (1%). Reduced intensity was given more frequently (64%) than myeloablative conditioning (36%). Frequencies at transplant were 9% (low), 29% (intermediate-1), 48% (intermediate-2), 14% (high) according to DIPSS and 3% (low), 40% (intermediate), and 57% (high) for MIPSS. Factors on outcome. In univariate analysis, mutations in CALR and MPL showed better OS (79% and 76%) vs. JAK2 (53%) and triple negative (50%; p=0.001). Outcome was similar according to CALR type (p=0.99). ASXL1 and DNMT3A mutations also entered the multivariate model. The following eight clinical, molecular and transplant-related variables were identified (corresponding HR): leukocytes >25x109/l (1.71), platelets <150x109/l (1.53), KPS <90 (1.63), age >57 years (1.69), recipient/donor CMV serostatus (+/- vs. other, 1.68), ASXL1 (1.74), JAK2/triple negative (2.10), and MMUD (2.11). Myelofibrosis Transplant Scoring System (MTSS). A weighted score of 1 was assigned to leukocytosis, thrombocytopenia, KPS <90, age >57, recipient/donor CMV serostatus (+/-), and ASXL1 mutation, whereas 2 points were assigned to JAK2/triple negative and MMUD. Four risk groups constructed the MTSS: low (score 0-2), intermediate (score 3-4), high (score 5-6), and very high (score 7-9). The 5-year OS according to risk groups was 88%, 71%, 50%, and 20% (Figure 1). The hazard for death (with low-risk as reference) was 2.36 for intermediate-risk, 4.65 for high-risk, and 9.72 for very high-risk. The score was predictive of OS overall as well as for PMF and SMF (p<0.001, respectively). The MTSS showed overall C statistics of 0.718 (0.707-0.730) after cross-validation yielding a median of 0.727 in PMF and 0.708 in SMF indicating improved performance and replicability vs. DIPSS (0.572), MIPSS (0.577), and MYSEC-PM (0.601). The system was also predictive of OS in different conditioning settings (reduced intensity and myeloablative) and in patients with ruxolitinib pretreatment (p<0.001, respectively). Conclusions The new MTSS includes modern disease- and transplant-associated risk variables pertinent to both PMF and SMF. This proposed system consistently predicts outcome facilitating posttransplant decision-making and can be applied to different conditioning settings and to patients receiving ruxolitinib pretreatment. Figure 1. Figure 1. Disclosures Beelen: Medac: Consultancy, Other: Travel Support. Kroeger:Novartis: Honoraria, Research Funding; Riemser: Honoraria, Research Funding; Neovii: Honoraria, Research Funding; Sanofi: Honoraria; JAZZ: Honoraria; Celgene: Honoraria, Research Funding.

Validation of Updated Cytogenetic Risk Classification in Patients with Myelodysplastic Syndrome: Retrospective Study at Single Institution.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 4837-4837
Author(s):  
Jina Yun ◽  
Jee Hyun Kong ◽  
Jung A. Kim ◽  
Dong Hwan Dennis Kim ◽  
Jun Ho Jang ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Conflicts Of Interest ◽  
Risk Group ◽  
Medical Center ◽  
High Risk Group ◽  
Risk Classification ◽  
International Prognostic Scoring System ◽  
Prognostic Impact ◽  
Very High

Abstract Abstract 4837 Introduction The International Prognostic Scoring System (IPSS) or the WHO Classification-Based Prognostic Scoring System (WPSS) are considered as gold standard to evaluate the patients with MDS in terms of their clinical courses. Recently, a new prognostic cytogenetic risk classification, defined as favorable (5q-, 12p-, 20q-, +21, -Y, 11q-, t(11)(q23), normal, 2 abnormalities including 5q-), intermediate-1 (+1q, 3q21/q26-abnormalities, +8, t(7q), +19, -21, any other single, any other double), intermediate-2 (-X, -7/7q-, 2 abnormalities incl. -7/7q-, complex = 3 abnormalities) or unfavorable risk group (Complex >3 abnormalities), has been reported through 3 large, well-characterized international investigations (German-Austrian (GA), Spanish MDS-registry, IMRAW). This new cytogenetic classification system showed better discrimination of patients according to their prognosis with respect to overall survival and leukemic transformation. The current study attempted to evaluate the new prognostic cytogenetic risk classification in patients with MDS, retrospectively. Patients and methods Between 1996 and 2007, 180 patients with MDS, who were diagnosed and treated at the Samsung medical center, Seoul, Korea, were enrolled into the study. One hundred seventy one patients were analyzed, 115 patients receiving best supportive care were included in the present analysis. Clinical characteristics were as follows; age 59 years (median, range 16-83), male 72%; 3 patients (pts) has 5q-; 1 patient (pt), 12p-; 3 pts, 20q-; 5 pts, -Y; 1 pt, 11q-; 1 pt, t(11)(q23); 80 pts, normal; 2 pts, 2 abnormalities including 5q-; 1 pt, +1q; 1 pt, 3q21/q26-abnormalities; 18 pt, +8; 16 pts, any other single; 19 pts, any other double; 2 pts, -7/7q-; 6 pts, complex = 3 abnormalities; 12 pts, complex >3 abnormalities. Results According to IPSS, 10 patients (9%) were at low risk, 77 patients (67%) at intermediate-1 (Int-1) risk, 22 patients (19%) at intermediate-2 (Int-2) risk and 6 patients (5%) at high risk. According to WPSS, 10 patients (9%) were at very low, 25 patients (22%) at low, 36 patients (31%) at intermediate, 31 patients(27%) at high and 13 patients(11%) at very high risk group. According to new cytogenetic risk classification, 66 patients (57%) were at favorable, 34 patients (30%) at intermediate-1 (Int-1), 9 patients (8%) at intermediate-2 (Int-2) and 6 patients (5%) at unfavorable subgroup. The median OS in overall population was 23.2 months. According to the IPSS, median OS in the Low, Int-1, Int-2 and High subgroup was 37.8, 27.5, 14.8 and 11.6 months, respectively (p<0.001). According to the WPSS, median OS in the subgroup of Very low, Low, Intermediate, High and Very high risk was 54.6, 43.1, 27.5, 16.5 and 11.9 months, respectively (p<0.001). By the new cytogenetic risk classification, median OS in the Favorable, Int-1, Int-2 and Unfavorable subgroup was 23.8, 24.1, 13.0 and 9.1 months (p=0.035). Sixteen cases (13.9%) showed documented leukemic evolutions with median 9.2 months of onset. It was difficult to analyze of leukemic evolution risk due to small number of sample size. Discussion In the present study, the new cytogenetic risk classification does not seem to be validated retrospective series of patients, we couldn't validate that the new cytogenetic subgroups are powerful predictor of prognosis as good as IPSS or WPSS. To warrant availability of the new cytogenetic risk classification, large data sets should be necessary. Also, we should be consider review about the prognostic impact of the karyotype in MDS. Disclosures No relevant conflicts of interest to declare.

scholarly journals A model for predicting carotid instability plaque in high risk group of stroke individuals

2019 ◽  
Author(s):  
Junxiong Yin ◽  
Chuanyong Yu ◽  
Hongxing Liu ◽  
Mingyang Du ◽  
Feng Sun ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Predictive Model ◽  
Doppler Ultrasound ◽  
Scoring System ◽  
Risk Group ◽  
High Risk Group ◽  
High Risk Population ◽  
Auc Value ◽  
Validation Set

Abstract Objective: To establish a predictive model of carotid vulnerable plaque through systematic screening of high-risk population for stroke.Patients and methods: All community residents who participated in the screening of stroke high-risk population by the China National Stroke Screening and Prevention Project (CNSSPP). A total of 19 risk factors were analyzed. Individuals were randomly divided into Derivation Set group and Validation Set group. According to carotid ultrasonography, the derivation set group patients were divided into instability plaque group and non-instability plaque group. Univariate and multivariable logistic regression were taken for risk factors. A predictive model scoring system were established by the coefficient. The AUC value of both derivation and validation set group were used to verify the effectiveness of the model.Results: A total of 2841 high-risk stroke patients were enrolled in this study, 266 (9.4%) patients were found instability plaque. According to the results of Doppler ultrasound, Derivation Set group were divided into instability plaque group (174 cases) and non-instability plaque group (1720 cases). The independent risk factors for carotid instability plaque were: male (OR 1.966, 95%CI 1.406-2.749)，older age (50-59, OR 6.012, 95%CI 1.410-25.629; 60-69, OR 13.915, 95%CI 3.381-57.267;≥70, OR 31.267, 95%CI 7.472-130.83) , married(OR 1.780, 95%CI 1.186-2.672)，LDL-c(OR 2.015, 95%CI 1.443-2.814), and HDL-C(OR 2.130, 95%CI 1.360-3.338). A predictive scoring system was created, range 0-10. The cut-off value of prediction model score is 6.5. The AUC value of derivation and validation set group were 0.738 and 0.737.Conclusion：For a high risk group of stroke individual, We provide a model that could distinguishing those who have a high probability of having carotid instability plaque. When resident’s predictive model score exceeds 6.5, the incidence of carotid instability plaque is high, carotid artery Doppler ultrasound would be checked immediately. This model can be helpful in the primary prevention of stroke.

scholarly journals A Novel Ferroptosis-Related Gene Signature Robustly Predicts Clinical Prognosis And Tumor Immunity in Patients With Kidney Renal Clear Cell Carcinoma

2021 ◽  
Author(s):  
Wei Song ◽  
Weiting Kang ◽  
Qi Zhang
Keyword(s):  
High Risk ◽  
Clear Cell ◽  
Risk Group ◽  
Gene Signature ◽  
Renal Clear Cell Carcinoma ◽  
High Risk Group ◽  
Risk Scores ◽  
Related Gene ◽  
Clinical Prognosis ◽  
Validation Set

Abstract Objective: This study aimed to construct a ferroptosis-related gene signature to predict clinical prognosis and tumor immunity in patients with kidney renal clear cell carcinoma (KIRC).Methods: The mRNA expression profiles and corresponding clinical data of KIRC patients were downloaded from The Cancer Genome Atlas (TCGA), which were randomly divided into training (398 patients) and validation set (132 patients). The iron death related (IDR) prediction model was constructed based on training set and 60 ferroptosis-related genes from previous literatures, followed by prognostic performance evaluation and verification using the validation set. Moreover, functional enrichment, immune cell infiltration, metagene clusters correlation, and TIDE scoring analyses were performed. Results: In total, 23 ferroptosis-related genes were significantly associated with overall survival (OS). The IDR prediction model (a 10-gene signature) was then constructed to stratify patients into two risk groups. The OS of KIRC patients with high-risk scores was significantly shorter than those with low-risk scores. Moreover, the risk score was confirmed as an independent prognostic predictor for OS. The positive and negative correlated genes with this model were significantly enriched in p53 signaling pathway, and cGMP-PKG signaling pathway. The patients in the high-risk group had higher ratios of plasma cells, T cells CD8, and T cells regulatory Tregs. Furthermore, IgG, HCK, LCK, and Interferson metagenes were significantly correlated with risk score. By TIDE score analysis, patients in the high-risk group could benefit from immunotherapy.Conclusions: The identified ferroptosis-related gene signature is significantly correlated with clinical prognosis and immune immunity in KIRC patients.

scholarly journals Establishment of an immune-related gene pairs model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene

Abstract Background Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma(COAD) is the main pathological type of colon cancer. There is a lot of evidence describing the correlation between the prognosis of COAD and the immune system. The objective of the current study was the development of a robust prognostic immune-related gene pairs (IRGPs) model for estimating overall survival of COAD. Methods The gene expression profiles and clinical information of patients with colon adenocarcinoma come from TCGA and GEO databases and are divided into training and validation cohorts. Immune genes were selected which show significantly association with prognosis. Results Among 1647 immune genes, a 17 IRGPs model was built which was significantly associated with OS in the training cohort. In the training and validation data set, the IRGPs model divided patients into high-risk groups and low-risk groups, and the prognosis of the high-risk group was significantly worse( P <0.001). Univariate and multivariate Cox proportional hazard analysis confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways in high-risk groups were up-regulated. T cells regulatory and Macrophage M0 were significantly highly expressed in the high-risk group. Conclusion We successfully constructed an IRGPs model that can predict the prognosis of COAD, which provides new insights into the treatment strategy of COAD.

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