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.

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 Determination of Risk Factors for Venous Thromboembolism by an Adapted Caprini Scoring System in Surgical Patients

2019 ◽  
Vol 9 (3) ◽  
pp. 36 ◽  
Author(s):  
Bui My Hanh ◽  
Le Quang Cuong ◽  
Nguyen Truong Son ◽  
Duong Tuan Duc ◽  
Tran Tien Hung ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Venous Thromboembolism ◽  
Scoring System ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Assessment Model ◽  
Surgical Patients ◽  
Risk Scoring

Venous thromboembolism (VTE) is a frequent preventable complication among surgical patients. Precise risk assessment is a necessary step for providing appropriate thromboprophylaxis and reducing mortality as well as morbidity caused by VTE. We carried out this work to define the rate of VTE postoperatively, following a Caprini score, and to determine VTE risk factors through a modified Caprini risk scoring system. This multicenter, observational, cohort study involved 2,790,027 patients who underwent surgery in four Vietnamese hospitals from 01/2017 to 12/2018. All patients who were evaluated before surgery by using a Caprini risk assessment model (RAM) and monitored within 90 days after surgery. The endpoint of the study was ultrasound-confirmed VTE. Our data showed that the 90-day postoperative VTE was found in 3068 patients. Most of VTE (46.97%) cases were found in the highest risk group (Caprini score > 5). A total of 37.19% were observed in the high risk group, while the rest (15.84%) were from low to moderate risk groups. The likelihood of occurring VTE was heightened 2.83 times for patients with a Caprini score of 3–4, 4.83 times for a Caprini score of 5–6, 8.84 times for a score of 7–8, and 11.42 times for a score of >8, comparing to ones with a score of 0 to 2 (all p values < 0.05). Thus, the frequency of postoperative VTE rises substantially, according to the advanced Caprini score. Further categorizing patients among the highest risk group need delivering more appropriate thromboprophylaxis.

Comparison of Prognostic Models for Autologous Hematopoietic Stem Cell Transplantation (AHCT) for Relapsed Hodgkin Lymphoma.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 1215-1215
Author(s):  
Theresa Hahn ◽  
Philip L. McCarthy ◽  
Jeanette Carreras ◽  
Mei-Jie Zhang ◽  
Hillard M. Lazarus ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Risk Group ◽  
Patient Characteristics ◽  
Risk Groups ◽  
High Risk Group ◽  
Prognostic Models ◽  
Brier Score ◽  
Model Risk ◽  
Resistant Disease

Abstract Abstract 1215 Poster Board I-237 AHCT is standard therapy for relapsed or refractory Hodgkin Lymphoma (HL). Prognostic risk score models for HL patients receiving AHCT aim to predict post transplant outcomes based on factors measured at the time of AHCT. We performed a comparison of 3 such models from Dana-Farber Cancer Institute (DFCI), Roswell Park Cancer Institute (RPCI) and University of Minnesota (UMinn) in an independent multicenter dataset of 597 relapsed or refractory HL patients receiving AHCT from 1996-2004, reported to the CIBMTR by 150 centers. Patient characteristics at diagnosis: 60% male, 52% stage III-IV, 59% B symptoms, 33% extranodal disease. Patient characteristics at AHCT: median (range) age 32 (7-74) years; 73% KPS≥90; 19% with extranodal disease; 39% had ≥3 prior chemotherapy regimens; 18% had resistant disease; median (range) time from diagnosis to AHCT 22 (3-238) months. High dose therapy regimens were primarily BEAM (72%) or CBV (12%) with 91% receiving peripheral blood stem cells. Progression free (PFS) and overall survival (OS) estimates at 3 years were 59% and 72%, respectively. The 3 prognostic models each measured 3 prognostic variables at AHCT that were combined into a prognostic score and assigned to a risk group (low, intermediate, high). The DFCI model risk factors were: chemo-resistant disease, KPS<90, ≥1 extranodal site; with corresponding risk groups low (0 factors), intermediate, (1 factor) and high (2-3 factors). The RPCI model risk factors were: chemo-resistant disease, KPS<90, ≥3 prior regimens with risk groups low (0-1 factor) and high (2-3 factors). The UMinn model risk factors were: chemo-resistant disease, B symptoms, not in CR at BMT with risk groups low (0-1 factor), intermediate (2 factors) and high (3 factors). Only 1 factor (chemo- resistant disease) was included in all 3 models. We quantified the predictive capabilities of the models using Brier score (B) and R2 for each model. Brier score as a function of time is a measure of the accuracy of the model calculated as the average deviation between the predicted probabilities and the actual outcome. R2 measures goodness of fit based on the observed vs. predicted difference in the regression model. A smaller Brier score and a larger R2 indicate better predictive performance. The models are compared in Table 1 with regards to prediction of 36 month PFS: Table 1 DFCI Model RPCI model UMinn model Brier Score 0.2344 0.2360 0.2394 R2 3.24% 2.57% 1.17% The high risk group PFS (Figure 1) was similar for the DFCI and RPCI models but the DFCI model separated a low and intermediate risk group which were not significantly different from each other. The UMinn model high risk group had a higher PFS than either of the other 2 models' high risk group and the intermediate group in this model was not significantly different from the high risk group. The relative incremental change in R2 was 26% higher for the DFCI than the RPCI model and 120% higher for the RPCI than the UMinn model. From the B and R2 values, the DFCI model had marginal superiority over RPCI model while both performed better than the UMinn model. Newer prognostic systems incorporating other prognostic variables are needed to distinguish lower and intermediate risk patients. Figure 1 Figure 1. Disclosures: No relevant conflicts of interest to declare.

Pharmacogenomic Prediction of Anthracycline-Induced Cardiotoxicity in Children

2012 ◽  
Vol 30 (13) ◽  
pp. 1422-1428 ◽  
Author(s):  
Henk Visscher ◽  
Colin J.D. Ross ◽  
S. Rod Rassekh ◽  
Amina Barhdadi ◽  
Marie-Pierre Dubé ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Genetic Variants ◽  
Risk Group ◽  
Treatment Options ◽  
Risk Groups ◽  
High Risk Group ◽  
Clinical Risk Factors ◽  
Nucleotide Polymorphisms ◽  
Clinical Risk

Purpose Anthracycline-induced cardiotoxicity (ACT) is a serious adverse drug reaction limiting anthracycline use and causing substantial morbidity and mortality. Our aim was to identify genetic variants associated with ACT in patients treated for childhood cancer. Patients and Methods We carried out a study of 2,977 single-nucleotide polymorphisms (SNPs) in 220 key drug biotransformation genes in a discovery cohort of 156 anthracycline-treated children from British Columbia, with replication in a second cohort of 188 children from across Canada and further replication of the top SNP in a third cohort of 96 patients from Amsterdam, the Netherlands. Results We identified a highly significant association of a synonymous coding variant rs7853758 (L461L) within the SLC28A3 gene with ACT (odds ratio, 0.35; P = 1.8 × 10−5 for all cohorts combined). Additional associations (P < .01) with risk and protective variants in other genes including SLC28A1 and several adenosine triphosphate–binding cassette transporters (ABCB1, ABCB4, and ABCC1) were present. We further explored combining multiple variants into a single-prediction model together with clinical risk factors and classification of patients into three risk groups. In the high-risk group, 75% of patients were accurately predicted to develop ACT, with 36% developing this within the first year alone, whereas in the low-risk group, 96% of patients were accurately predicted not to develop ACT. Conclusion We have identified multiple genetic variants in SLC28A3 and other genes associated with ACT. Combined with clinical risk factors, genetic risk profiling might be used to identify high-risk patients who can then be provided with safer treatment options.

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.

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 Background: Atherosclerosis is the main risk factor of cerebral vascular disease. Previous studies published several predictive models of asymptomatic carotid stenosis , yet they were ignored that people with lower levels of stenosis (＜50% or carotid instability plaque) who may benefit from early risk reducing medications, such as statins, antiplatelet drugs. Thus, this study determined to establish a predictive model of carotid vulnerable plaque through systematic screening of high-risk population for stroke. 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 Area under curve (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. Conclusions: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.

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.

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.

scholarly journals Comparative risk assessment for the development of cardiovascular diseases in the Hungarian general and Roma population

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Peter Piko ◽  
Zsigmond Kosa ◽  
Janos Sandor ◽  
Roza Adany
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Cardiovascular Risk ◽  
Cardiovascular Diseases ◽  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Average Risk ◽  
Cvd Risk ◽  
Roma Population

AbstractCardiovascular diseases (CVDs) are the number one cause of death globally, and the early identification of high risk is crucial to prevent the disease and to reduce healthcare costs. Short life expectancy and increased mortality among the Roma are generally accepted (although not indeed proven by mortality analyses) which can be partially explained by the high prevalence of cardiovascular risk factors (CVRF) among them. This study aims to elaborate on the prevalence of the most important CVD risk factors, assess the estimation of a 10-year risk of development of fatal and nonfatal CVDs based on the most used risk assessment scoring models, and to compare the Hungarian general (HG) and Roma (HR) populations. In 2018 a complex health survey was accomplished on the HG (n = 380) and HR (n = 347) populations. The prevalence of CVRS was defined and 10-year cardiovascular risk was estimated for both study populations using the following systems: Framingham Risk Score for hard coronary heart disease (FRSCHD) and for cardiovascular disease (FRSCVD), Systematic COronary Risk Evaluation (SCORE), ACC/AHA Pooled Cohort Equations (PCE) and Revised Pooled Cohort Equations (RPCE). After the risk scores had been calculated, the populations were divided into risk categories and all subjects were classified. For all CVD risk estimation scores, the average of the estimated risk was higher among Roma compared to the HG independently of the gender. The proportion of high-risk group in the Hungarian Roma males population was on average 1.5–3 times higher than in the general one. Among Roma females, the average risk value was higher than in the HG one. The proportion of high-risk group in the Hungarian Roma females population was on average 2–3 times higher compared to the distribution of females in the general population. Our results show that both genders in the Hungarian Roma population have a significantly higher risk for a 10-year development of cardiovascular diseases and dying from them compared to the HG one. Therefore, cardiovascular interventions should be focusing not only on reducing smoking among Roma but on improving health literacy and service provision regarding prevention, early recognition, and treatment of lipid disorders and diabetes among them.

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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