scholarly journals Prognosis Score System to Predict Survival for COVID-19 Cases: a Korean Nationwide Cohort Study

10.2196/26257 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e26257 ◽  
Author(s):  
Sung-Yeon Cho ◽  
Sung-Soo Park ◽  
Min-Kyu Song ◽  
Young Yi Bae ◽  
Dong-Gun Lee ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
High Risk ◽  
Hospital Stay ◽  
Risk Score ◽  
Validation Cohort ◽  
Length Of Hospital Stay ◽  
Risk Groups ◽  
Prognosis Score ◽  
Very High

Background As the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care. Objective In this study, we aimed to identify factors that predict the overall survival rate for COVID-19 cases and develop a COVID-19 prognosis score (COPS) system based on these factors. In addition, disease severity and the length of hospital stay for patients with COVID-19 were analyzed. Methods We retrospectively analyzed a nationwide cohort of laboratory-confirmed COVID-19 cases between January and April 2020 in Korea. The cohort was split randomly into a development cohort and a validation cohort with a 2:1 ratio. In the development cohort (n=3729), we tried to identify factors associated with overall survival and develop a scoring system to predict the overall survival rate by using parameters identified by the Cox proportional hazard regression model with bootstrapping methods. In the validation cohort (n=1865), we evaluated the prediction accuracy using the area under the receiver operating characteristic curve. The score of each variable in the COPS system was rounded off following the log-scaled conversion of the adjusted hazard ratio. Results Among the 5594 patients included in this analysis, 234 (4.2%) died after receiving a COVID-19 diagnosis. In the development cohort, six parameters were significantly related to poor overall survival: older age, dementia, chronic renal failure, dyspnea, mental disturbance, and absolute lymphocyte count <1000/mm3. The following risk groups were formed: low-risk (score 0-2), intermediate-risk (score 3), high-risk (score 4), and very high-risk (score 5-7) groups. The COPS system yielded an area under the curve value of 0.918 for predicting the 14-day survival rate and 0.896 for predicting the 28-day survival rate in the validation cohort. Using the COPS system, 28-day survival rates were discriminatively estimated at 99.8%, 95.4%, 82.3%, and 55.1% in the low-risk, intermediate-risk, high-risk, and very high-risk groups, respectively, of the total cohort (P<.001). The length of hospital stay and disease severity were directly associated with overall survival (P<.001), and the hospital stay duration was significantly longer among survivors (mean 26.1, SD 10.7 days) than among nonsurvivors (mean 15.6, SD 13.3 days). Conclusions The newly developed predictive COPS system may assist in making risk-adapted decisions for the allocation of medical resources, including intensive care, during the COVID-19 pandemic.

scholarly journals Prognosis Score System to Predict Survival for COVID-19 Cases: a Korean Nationwide Cohort Study (Preprint)

2020 ◽  
Author(s):  
Sung-Yeon Cho ◽  
Sung-Soo Park ◽  
Min-Kyu Song ◽  
Young Yi Bae ◽  
Dong-Gun Lee ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
High Risk ◽  
Hospital Stay ◽  
Risk Score ◽  
Validation Cohort ◽  
Length Of Hospital Stay ◽  
Risk Groups ◽  
Prognosis Score ◽  
Very High

BACKGROUND As the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care. OBJECTIVE In this study, we aimed to identify factors that predict the overall survival rate for COVID-19 cases and develop a COVID-19 prognosis score (COPS) system based on these factors. In addition, disease severity and the length of hospital stay for patients with COVID-19 were analyzed. METHODS We retrospectively analyzed a nationwide cohort of laboratory-confirmed COVID-19 cases between January and April 2020 in Korea. The cohort was split randomly into a development cohort and a validation cohort with a 2:1 ratio. In the development cohort (n=3729), we tried to identify factors associated with overall survival and develop a scoring system to predict the overall survival rate by using parameters identified by the Cox proportional hazard regression model with bootstrapping methods. In the validation cohort (n=1865), we evaluated the prediction accuracy using the area under the receiver operating characteristic curve. The score of each variable in the COPS system was rounded off following the log-scaled conversion of the adjusted hazard ratio. RESULTS Among the 5594 patients included in this analysis, 234 (4.2%) died after receiving a COVID-19 diagnosis. In the development cohort, six parameters were significantly related to poor overall survival: older age, dementia, chronic renal failure, dyspnea, mental disturbance, and absolute lymphocyte count &lt;1000/mm<sup>3</sup>. The following risk groups were formed: low-risk (score 0-2), intermediate-risk (score 3), high-risk (score 4), and very high-risk (score 5-7) groups. The COPS system yielded an area under the curve value of 0.918 for predicting the 14-day survival rate and 0.896 for predicting the 28-day survival rate in the validation cohort. Using the COPS system, 28-day survival rates were discriminatively estimated at 99.8%, 95.4%, 82.3%, and 55.1% in the low-risk, intermediate-risk, high-risk, and very high-risk groups, respectively, of the total cohort (<i>P</i>&lt;.001). The length of hospital stay and disease severity were directly associated with overall survival (<i>P</i>&lt;.001), and the hospital stay duration was significantly longer among survivors (mean 26.1, SD 10.7 days) than among nonsurvivors (mean 15.6, SD 13.3 days). CONCLUSIONS The newly developed predictive COPS system may assist in making risk-adapted decisions for the allocation of medical resources, including intensive care, during the COVID-19 pandemic.

scholarly journals A Peri-Implant Disease Risk Score for Patients with Dental Implants: Validation and the Influence of the Interval between Maintenance Appointments

2019 ◽  
Vol 8 (2) ◽  
pp. 252 ◽  
Author(s):  
Miguel de Araújo Nobre ◽  
Francisco Salvado ◽  
Paulo Nogueira ◽  
Evangelista Rocha ◽  
Peter Ilg ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Disease Risk ◽  
Disease Incidence ◽  
Risk Groups ◽  
Risk Profile ◽  
Moderate Risk ◽  
C Statistic ◽  
Disease Risk Score ◽  
Very High

Background: There is a need for tools that provide prediction of peri-implant disease. The purpose of this study was to validate a risk score for peri-implant disease and to assess the influence of the recall regimen in disease incidence based on a five-year retrospective cohort. Methods: Three hundred and fifty-three patients with 1238 implants were observed. A risk score was calculated from eight predictors and risk groups were established. Relative risk (RR) was estimated using logistic regression, and the c-statistic was calculated. The effect/impact of the recall regimen (≤ six months; > six months) on the incidence of peri-implant disease was evaluated for a subset of cases and matched controls. The RR and the proportional attributable risk (PAR) were estimated. Results: At baseline, patients fell into the following risk profiles: low-risk (n = 102, 28.9%), moderate-risk (n = 68, 19.3%), high-risk (n = 77, 21.8%), and very high-risk (n = 106, 30%). The incidence of peri-implant disease over five years was 24.1% (n = 85 patients). The RR for the risk groups was 5.52 (c-statistic = 0.858). The RR for a longer recall regimen was 1.06, corresponding to a PAR of 5.87%. Conclusions: The risk score for estimating peri-implant disease was validated and showed very good performance. Maintenance appointments of < six months or > six months did not influence the incidence of peri-implant disease when considering the matching of cases and controls by risk profile.

scholarly journals A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Yan ◽  
Wenjiang Zheng ◽  
Boqing Wang ◽  
Baoqian Ye ◽  
Huiyan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Performance ◽  
Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

A Risk Score Combined Clinical and Molecular Profiles Identifies a High-Risk Subgroup within AML1-ETO-Positive Acute Myeloid Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 19-19
Author(s):  
Min Yang ◽  
Yi Zhang ◽  
Jinghan Wang ◽  
Lixia Liu ◽  
Chengcheng Wang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
High Risk ◽  
Risk Score ◽  
Myeloid Leukemia ◽  
Validation Cohort ◽  
Concordance Index ◽  
Scoring Model ◽  
Mutation Burden ◽  
Acute Myeloid

Background: AML1-ETO-positive acute myeloid leukemia, is classified as a favorable leukemia subtype according to the European Leukemia Net (ELN) risk stratification. Nevertheless, studies show the biology and prognosis within the AML1-ETO-positive AML are highly different, which suggests that more prognostic factors are needed to be identified. Aims: This study mainly revealed the genomic mutation characteristics and explored more factors which affect the prognosis of Chinese AML1-ETO-positive AML patients. Methods: A total of 167 AML1-ETO-positive patients who diagnosed and treated in Zhejiang Institute of Hematology had cryopreserved DNA for deep target 185-gene regional sequencing. Variants were detected with a variant allele frequency (VAF) cutoff of 0.5%. We used a LASSO Cox regression model to build risk score for predicting overall survival. A nomogram was constructed to display the risk of death in individuals. The discrimination of the risk score was measured by the concordance index (C-index) and areas under time-dependent receiver-operating characteristics (ROC) curves (AUCs), and the calibration of the risk score was explored graphically by calibration plots. Patients (n=75) from other hospital were used as a validation cohort. Results: The median age in analyzed patients was 42(6-78) years. The most common recurrent mutations occurred in KIT(n=84,50%), ASXL2(n=46,28%), NRAS(n=37,22%), FLT3-ITD(n=35,21%) and TET2(n=30,18%). We observed that high KIT mutant allele burden predicts for poor outcome in t(8:21) AML. High KIT VAF(≥15%) correlated with shortened overall survival compared to the other KIT mutated cases including low VAF and wild-type KIT (3-year OS 26.6% vs 59.0% vs 69.6%, HR 1.50, 95%CI 0.78-2.89, P=0.0005). In addition, we also identified some other mutated genes influence the prognosis of patients with t (8;21), such as FLT3-ITD high mutation burden(VAF≥44% vs other cases, 3-year OS 30.0% vs 56.2%, HR 2.94, 95%CI 0.43-20.18, P=0.056), TET2 high mutation burden (VAF≥43% vs other cases, 3-year OS 33.3% vs 56.5%, HR 2.87, 95%CI 0.66-12.46, P=0.018) and DHX15 high mutation burden (VAF≥22% vs other cases, 3-year OS 15.0% vs 58.3%, HR 2.65, 95%CI 0.81-8.73, P=0.011). In univariate analyses for OS, age&gt;42 (3-year OS 46.3% vs 64.4%, HR 1.91, 95%CI 1.14-3.14, P=0.012), WBC&gt;27.1×109/L(3-year OS 34.3% vs 60.0%, HR 2.59, 95%CI 1.13-5.9, P=0.001), BM blast&gt;20% (3-year OS 52.2% vs 92.8%, HR 6.36, 95%CI 2.7-14.97, P =0.035), LDH &gt; 504U/L (3-year OS 44.1% vs 67.1%, HR 2.62, 95%CI 1.50-4.59, P=0.0007), PLT≤28×109/L (3-year OS 47.1% vs 66.9%, HR 1.89, 95%CI 1.13-3.17, P=0.019), HB≤87g/L (3-year OS 49.4% vs 73.8%, HR 2.20, 95%CI 1.27-3.84, P=0.019) were significantly associated with poor OS. Six variables were incorporated in our scoring model by LASSO, including age, WBC, PLT, KIT mutation, FLT3-ITD mutation and TET2 mutation. A risk scoring model was developed incorporating the weighted coefficients of these variables. The risk score grouped AML1-ETO AML patients into two subgroup: low risk (LR, n=68) and high risk (HR, n=86) groups. The 3-year OS for LR and HR groups were 72.7% and 43.0% (P&lt;0.0001, Figure A). The similar results were also observed in validation cohort (3-year OS 79.1% vs 49.5%, P= 0.01; Figure B). Concordance index [train: 0.708, 95% CI (0.680, 0.736), validation: 0.722, 95% CI (0.666, 0.778)] demonstrated well discrimination power and calibration plots showed that the nomograms did well compared with an ideal model. Conclusion: In this study, our findings indicate that the prognostic effect of gene mutation in de novo t(8:21) AML may be influenced by the relative abundance of the mutated allele. A novel scoring model was developed and validated that incorporated molecular and clinical profiles. According to our score model, AML1-ETO AML patients could be further stratified into two subgroups with distinct clinical outcomes. Our data can serve as a basis for guided and risk-adapted treatment strategies for CBF-AML patients. The results are needed to be validated in other independent cohorts and prospective studies before implementation into clinics. Disclosures No relevant conflicts of interest to declare.

A Risk Score to Predict CMV Viremia within the First 100 Days after Allogeneic Stem Cell Transplantation Based on Pre-Transplant Parameters

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3877-3877
Author(s):  
Feras Alfraih ◽  
John Kuruvilla ◽  
Naheed Alam ◽  
Anna Lambie ◽  
Vikas Gupta ◽  
...  
Keyword(s):  
Risk Factors ◽  
Stem Cell ◽  
High Risk ◽  
Risk Score ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Cmv Infection ◽  
Allogeneic Hsct ◽  
Very High

Abstract Introduction: Cytomegalovirus (CMV) is a major infectious complication following allogeneic hematopoietic stem cell transplantation (HSCT). Risk of CMV infection varies between patients and individualized strategies for monitoring and therapy for CMV are needed. In this study, we attempted to establish a clinical score based on patient and transplant characteristics in order to predict the probability for early CMV viremia (CMV-V) within the first 100 days after HSCT. Methods: A total of 548 patients were evaluated after receiving HSCT between 2005 and 2012 at Princess Margaret Cancer Centre. CMV sero-negative recipients with CMV sero-negative donors (R-D-) were excluded. CMV-V was diagnosed in peripheral blood samples obtained on two occasions either by PCR (>200 IU/ml) or antigenemia testing (>2 positive cells/100000). A total of 378 patients were included into the study. Uni- and multivariable analyses were performed to identify risk factors for CMV-V. A weighted score was assigned to each factor based on the odds ratios determined by the multivariable analysis. A total score was calculated for each patient and used for assignment into one of 4 risk categories, the low risk (score 0-1), the intermediate (score 2-3), the high (score 4-5) and the very high (score 6-8). Median age for all patients was 51 years (range 17-71) and 173 (46%) were female. Matched related donors were used for two hundred fifteen patients (57%). Two hundred forty-three patients (64%) were transplanted for myeloid and 108 (29%) for lymphoid malignancies. One hundred thirteen patients (30%) were CMV sero-positive with a negative donor (R+D-) while 191 (51%) were recipient and donor CMV sero-positivity (R+D+). Graft versus host disease (GVHD) prophylaxis included CSA/MMF (n=200, 52%), and CSA/MTX (n=178, 48%). Myeloablative conditioning regimens were administered to 220 patients (58%), 158 patients (42%) were treated with a reduced intensity regimen. Three hundred-thirty seven patients (89%) received peripheral blood stem cells as a stem cell source. In vivo T cell depletion (TCD) with alemtuzumab was used in 138 (37%). Results: CMV-V occurred in 246 (64%) patients by day 100 post HSCT. The impact of patient and HSCT characteristics on the risk of CMV-V was assessed by multivariable analysis. The significant factors were CMV sero-status R+D- and R+D+, TCD, GVHD prophylaxis with MMF administration of myeloablative preparative regimens (Table 1). Table 1. Multivariate analysis for risk factors of CMV infection following allogeneic HSCT Table 1. Multivariate analysis for risk factors of CMV infection following allogeneic HSCT CMV-V rates on the 4 new risk categories amounted to 93% in the very high-risk, 78% in high-risk, 41% in intermediate-risk and 11% in low-risk group (Fig 1). The risk score was also predictive for the occurrence of multiple CMV-V reactivations with rates of 71%, 45%, 19% and 4% for the very high, high, intermediate and low-risk groups, respectively. The overall survival (OS) rate at 2 years was 33%(n=56) in the very high-risk group compared to 50% in other-risk groups (n=147) (P=0.01) (Fig 2). Non-relapse mortality (NRM) was 53% in the very high-risk versus 33% in other-risk groups (P<0.001). However, there was no difference on cumulative incidence of relapse between the groups (P=0.3). The cumulative incidence of grades 1-4 acute GVHD, grades 2-4, grades 3-4 at day 120 and overall chronic GVHD at 2 years was 68%, 47%, 25% and 39% in very high-risk group versus 65%, 52%, 21% and 52% in other-risk groups, suggesting slightly lower incidence of chronic GVHD in very high-risk vs other-risk groups. Conclusion: We present a new clinical scoring system to stratify the risk of early CMV viremia after allogeneic HSCT based on patients and HSCT characteristics. Identifying the risk for each patient would facilitate decision making with respect to strategies including CMV prophylaxis, pre-emptive treatment or inclusion into clinical trials, as well directing the CMV monitoring policy post-transplant. In addition, the risk score was associated with higher risk of overall mortality and NRM in the very high-risk versus other-risk groups. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.

scholarly journals A Novel Four-Gene Signature Associated With Immune Checkpoint for Predicting Prognosis in Lower-Grade Glioma

2020 ◽  
Vol 10 ◽  
Author(s):  
Youchao Xiao ◽  
Gang Cui ◽  
Xingguang Ren ◽  
Jiaqi Hao ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Risk Groups ◽  
Gene Signature ◽  
Low Risk ◽  
Lower Grade ◽  
Lower Grade Glioma ◽  
Risk Patients

The overall survival of patients with lower grade glioma (LGG) varies greatly, but the current histopathological classification has limitations in predicting patients’ prognosis. Therefore, this study aims to find potential therapeutic target genes and establish a gene signature for predicting the prognosis of LGG. CD44 is a marker of tumor stem cells and has prognostic value in various tumors, but its role in LGG is unclear. By analyzing three glioma datasets from Gene Expression Omnibus (GEO) database, CD44 was upregulated in LGG. We screened 10 CD44-related genes via protein–protein interaction (PPI) network; function enrichment analysis demonstrated that these genes were associated with biological processes and signaling pathways of the tumor; survival analysis showed that four genes (CD44, HYAL2, SPP1, MMP2) were associated with the overall survival (OS) and disease-free survival (DFS)of LGG; a novel four-gene signature was constructed. The prediction model showed good predictive value over 2-, 5-, 8-, and 10-year survival probability in both the development and validation sets. The risk score effectively divided patients into high- and low- risk groups with a distinct outcome. Multivariate analysis confirmed that the risk score and status of IDH were independent prognostic predictors of LGG. Among three LGG subgroups based on the presence of molecular parameters, IDH-mutant gliomas have a favorable OS, especially if combined with 1p/19q codeletion, which further confirmed the distinct biological pattern between three LGG subgroups, and the gene signature is able to divide LGG patients with the same IDH status into high- and low- risk groups. The high-risk group possessed a higher expression of immune checkpoints and was related to the activation of immunosuppressive pathways. Finally, this study provided a convenient tool for predicting patient survival. In summary, the four prognostic genes may be therapeutic targets and prognostic predictors for LGG; this four-gene signature has good prognostic prediction ability and can effectively distinguish high- and low-risk patients. High-risk patients are associated with higher immune checkpoint expression and activation of the immunosuppressive pathway, providing help for screening immunotherapy-sensitive patients.

Gestational trophoblastic disease: 25-year experience at the Instituto Nacional de Enfermedades Neoplasicas (INEN)

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 16031-16031
Author(s):  
L. Mas Lopez ◽  
M. Olivera ◽  
L. Casanova ◽  
C. Santos ◽  
S. Neciosup ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
High Risk ◽  
Complete Remission ◽  
Risk Score ◽  
Gestational Trophoblastic Disease ◽  
Low Risk ◽  
Overall Survival Rate ◽  
Trophoblastic Disease ◽  
Results Of Treatment

16031 Background: To evaluate the clinical behavior and results of treatment of gestational trophoblastic disease at INEN between 1980 to 2005. Methods: This is a retrospective analysis of patients with gestational trophoblastic disease, clinical characteristics, results of treatment, toxicity, objective response and survival from January 1980 to December 2005. Descriptive statistics and Kaplan-Meier for survival analysis were performed. Results: Since Jan 1980 to Dec 2005. 595 patients were admitted at INEN; Hydatidiform mole 254 (42.7%) choriocarcinoma 201 (33.8%) invasive mole 41(6.8%). FIGO scoring System, high risk (score >6): 247 (41.5%), low risk (score 1–6): 348 (58.5%). Age ranged from 14 to 54 years, with 255 (44%) cases between 20 to 29 years. The sities of metastasis: lung 67.3%, vaginal 17.9%, brain 8.7%, liver 5.1%. The patients with low risks received treatment with Metotrexate 0.4mg/kg x day x 5 days po, reach disease control with a mean course of 6 (1 - 14), complete remission in 66.1% cases and 97% the overall survival rate to 20 years. Patients with high risk received treatment with: MAC 77 patients, MEC 19 patients, EMACO 48 patients and BEP 14 patients and achieved complete remission in 32.5%, 36.8%, 50% and 25% respectively. On the high risk group we detected two groups according to score > 12 and < 12, with diferent probability of survival at 20 years, for the group with score <12, 80% and the group with score >12, 48%. 98 patients were identified with score >12, and the age of these patients ranged from 15 to 51 years, with a mean age of 36.5 years. The blood B- HCG titers of these patients ranged from 198 to 6710,500. Liver and brain metastasis in 26 cases, number metastasis mayor 8 in 78 cases. Conclusions: Gestational trofhoblastic disease is highly curable. Patients of low risk achieved a 97% overall survival rate to 20 years. There are differences in the overall survival rate between patients of high risk with a score < 12 (80%) and score >12 (48%). This group presented with brain and liver metastasis, and it is important to define the best treatment for this group of patients No significant financial relationships to disclose.

Proposal of A Prognostic Score for Previously Untreated Patients with Chronic Lymphocytic Leukemia Based on An Overall Survival Analysis of Three German CLL Study Group Phase III Trials

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2831-2831
Author(s):  
Jasmin Bahlo ◽  
Natali Pflug ◽  
Thomas Elter ◽  
Kathrin Bauer ◽  
Barbara Eichhorst ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Research Funding ◽  
Prognostic Score ◽  
Phase Iii ◽  
Mutational Status ◽  
Phase Iii Trials ◽  
Binet Stage ◽  
Very High

Abstract Abstract 2831 Introduction Prognosis and need of treatment in CLL is currently determined by clinical staging systems of Binet and Rai. Recent research has focused on prognostic factors that may predict a poor prognosis independent of the clinical stage. Markers which have shown independent prognostic information are serum parameters and genetic factors (genomic aberrations, IgHV and p53 mutational status). To investigate the relevance of these different factors, we performed a pooled analysis using the data of three multicenter German CLL Study Group phase III trials (CLL1, CLL4 and CLL8). Based on this analysis we propose a prognostic score for previously untreated patients with early and advanced CLL. Material and Methods Patients were recruited between 1997 and 2006 into three phase III trials: 715 in CLL1 (“watch and wait” versus fludarabine (F)), 362 in CLL4 (F versus F and cyclophosphamide (FC)) and 817 patients in the CLL8 trial (FC versus FC and rituximab (FCR)). Serum parameters and genetic factors were centrally analyzed prior to treatment. The main end point of all statistical analyses was overall survival. First, univariate analyses were performed including variables of different groups such as baseline characteristics, stage of disease, laboratory results, molecular cytogenetics, mutational status and serum parameters. Next, multivariate Cox regressions were applied including all parameters that showed a significant association with overall survival in univariate analyses. To create a prognostic score we developed a weighted grading algorithm for independent factors based on ranges of hazard ratios. Finally, a prognostic score was defined as the sum of single ratings of adverse factors. According to this score, four different risk groups for overall survival could be identified. Results In total 1948 patients were eligible for the pooled analysis with a median age of 60 years (range, 30 to 81 years). After a median observation time of 63.4 months 485 deaths were reported. At study entry, 799 patients (42.4%) were at Binet stage A, 717 (38.0%) at Binet stage B and 370 (19.6%) at Binet stage C. Almost all considered variables were significantly associated with outcome and therefore included in the multivariate analysis. Based on the data of 1223 patients for whom all parameters were available, multivariate Cox regressions were performed and identified gender, age, ECOG score, del(17p), del(11q), IgHV mutational status, serum β2-microglobulin and serum thymidine kinase as independent factors for overall survival. Deletion 17p was the strongest adverse factor. Neither the clinical staging (Rai, Binet) nor the treatment modality were independent prognostic factors for overall survival. Similarly, the time interval between first diagnosis and study entry was not an independent prognostic factor. Due to the great differences between hazard ratios of independent factors, we developed a weighted grading system based on a simple algorithm to assign an individual grade to each adverse factor. By using this weighted grading, four different prognostic groups could be separated: low risk (score 0 – 2), intermediate risk (score 3 – 5), high risk (score 6 – 10) and very high risk (score 11 – 14) (figure 1). Overall survival rates were significantly different for these four groups with 95.2%, 86.9%, 67.7% and 18.7% survival after 5 years for the low, intermediate, high and very high risk group, respectively (p<0.0001). Moreover, within the group of patients showing a deletion 17p the score could distinguish patients of a high risk and a very high risk group (p<0.0001). Finally, the score could predict the individual risk for short overall survival independent of and within the different Binet or Rai stages (p<0.0001) (figure 2). Conclusion While Binet and Rai staging systems may remain important for the initial clinical assessment due to their simplicity, our prognostic score using a weighted combination of genetic and serum markers is superior to predict the overall survival of CLL patients. Disclosures: Pflug: Hoffmann-la Roche: Travel grant; Mundipharma: Travel grant. Eichhorst:Hoffmann La Roche: Honoraria, Research Funding, Travel Grants; Mundipharma: Research Funding, Travel Grants; Gilead: Consultancy. Bergmann:Celgene: Honoraria. Döhner:Hoffmann-la Roche: Research Funding. Stilgenbauer:Hoffmann La Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Travel Grants. Fischer:Hoffmann La Roche: Travel Grants. Hallek:Hoffmann-la Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.

scholarly journals Academic Centers Are Associated with Improved Survival Outcomes in High Risk Diffuse Large B-Cell Lymphoma Patients

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4747-4747
Author(s):  
Daniel A. Ermann ◽  
Victoria Vardell Noble ◽  
Avyakta Kallam ◽  
James O. Armitage
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Median Survival ◽  
Risk Score ◽  
B Cell Lymphoma ◽  
Risk Groups ◽  
Low Risk ◽  
Survival Outcomes ◽  
Intermediate Risk ◽  
Hazard Ratios

Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma, and is characterized as a heterogenous disease associated with varying outcomes. The International Prognostic Index (IPI) has been the standard for baseline prognostic assessment in these patients. In this study we aimed to determine the impact of treatment facility (academic versus non-academic centers) on overall survival outcomes in DLBCL patients stratified by IPI score risk groups, with a focus on high risk disease as this is associated with poorer outcomes. Methods: The 2018 National Cancer Database (NCDB) was utilized for patients diagnosed with DLBCL between 2004-2015. Patients were then stratified based on IPI risk score from low to high risk. Four risk groups were formed: low (0-1), low-intermediate (2), high-intermediate (3), and high (4-5). Overall survival was calculated using Kaplan-Meyer analysis with bivariate cox proportional hazard ratios to compare survival by facility type (academic or community centers) within these risk groups. Results: A total of 160,137 patients were identified. Of these cases 31.8% were classified as low risk, 21.9% were low-intermediate risk, 22.2% were high-intermediate risk, and 24% were high risk. 59.3% of patients were treated at a community center and 40.7% were treated at academic centers. Treatment at academic centers was associated with a significantly improved overall survival (OS) for each risk category. Median survival (in months) for high risk IPI score DLBCL was 47.9 months in community and 61.1 months in academic centers (p<.0001). Median survival for high-intermediate risk score was 48.3 months in community and 87.3 months in academic centers (p<.0001). Median survival for low-intermediate score was 90.3 months in community and 122.8 months in academic centers (p<.0001). Median survival for low risk score was 132 months in community and 148 months in academic centers (p<.0001). Hazard ratios for academic center versus community center for high risk, high-intermediate, low-intermediate and low risk are 0.768, 0.71, 0.848 and 0.818 respectively (p<.0001). Conclusions: Facility type is significantly associated with improved survival outcomes across all IPI based risk groups for DLBCL. This benefit is especially significant in higher risk disease where positive outcomes are less common, suggesting treatment at academic centers may be particularly beneficial in these patients. Some of the possible reasons for this difference may include provider experience, increased access to resources, and opportunity for clinical trials. Further investigations into the factors contributing to such disparities should be done to help standardize care and improve outcomes. Disclosures No relevant conflicts of interest to declare.

scholarly journals WT1 mRNA Expression in the Peripheral Blood of Patients with MDS Yields Additional Prognostic Information within the IPSS-R Risk Categories "Very Low", "Low" and "Intermediate"

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1827-1827
Author(s):  
Christina Rautenberg ◽  
Sabrina Pechtel ◽  
Norbert Gattermann ◽  
Rainer Haas ◽  
Ulrich Germing ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Peripheral Blood ◽  
Research Funding ◽  
Risk Groups ◽  
Prognostic Information ◽  
Expression Status ◽  
Very High ◽  
Risk Categories ◽  
Who 2008

Abstract Introduction: The revised version of the International Prognostic Scoring System, (IPSS-R), is an accepted standard for assessing the prognosis of patients with MDS. Its usefulness may be further improved by integrating molecular findings. However, such efforts are impeded by limited access to molecular diagnostics, lack of standardized methodology, and a relatively low frequency of individual gene mutations in MDS. The Wilms' Tumor-1 (WT1) gene is overexpressed on mRNA level in the peripheral blood (PB) in about 50% of patients with MDS. The aim of this analysis was to determine whether PB WT1 expression status yields additional prognostic information. Methods: For this purpose, PB WT1 mRNA expression was measured in 91 newly diagnosed patients with MDS (WHO: MDS del5q, n=7; RARS, n=1; RCUD, n=4; RCMD, n=37; RAEB-I, n=16; RAEB-II, n=23; MDS/MPN unclassifiable, n=3 / IPSS-R: very low risk, n=3; low risk, n=28; intermediate risk, n=27; high risk, n=13; very high risk, n=20), using the Ipsogen® WT1 ProfileQuant® Kit. This standardized, commercially available assay uses a validated cut-off level of 50 WT1 copies/104ABL copies for discrimination between normal and overexpression of WT1 in PB. MDS patients in our study cohort were stratified accordingly (normal WT1 expression with <50 WT1 copies versus overexpression with >50 WT1 copies). WT1 expression status was correlated with clinical parameters and outcome. Results: Overall, 53 MDS patients (58%) showed WT1 overexpression, which correlated significantly with WHO 2008 disease category and IPSS-R risk groups, as indicated by both the absolute WT1 levels (correlation with WHO 2008 type, p=0.0028, and IPSS-R, p=0.0075) and the frequency of WT1-overexpressing patients within the respective MDS subgroup (correlation with WHO 2008 type, p=0.0029, and IPSS-R, p=0.0027). Regarding the entire cohort, patients with elevated WT1 expression had a significantly lower progression-free survival (PFS) and overall survival (OS) compared to those with normal WT1 expression (p<0.0001 and p=0.0306). Furthermore, within the IPSS-R risk groups 'very low', 'low' and 'intermediate', PFS differed significantly between patients showing normal vs. elevated WT1 expression status (IPSS-R very low/low: median PFS 30.1 months vs. not reached, for WT1 high vs normal, respectively, p=0.0127; IPSS-R intermediate: median PFS 14.4 months vs. 59.5 months, for WT1 high vs. normal, respectively p=0.0240). These differences in PFS retained their prognostic significance in multivariate analysis after adjusting for IPSS-R (HR 0.306; 95% CI 0,156-0,598, p=0.001). However, they did not translate into a difference in overall survival, which was probably due to a relevant number of patients proceeding to allogeneic stem cell transplantation. Given the large proportion of patients displaying WT1 overexpression in the IPSS-R high and very high risk groups, it was not surprising that no significant prognostic subdivision by WT1 expression level was seen in these risk categories. Conclusion: Our results show that PB WT1 expression offers additional prognostic information in patients belonging to the IPSS-R risk groups 'very low', 'low' and 'intermediate'. Assessment of WT1 expression status at diagnosis is a relatively time and cost efficient method that can be performed without patient discomfort and may help to identify MDS IPSS-R low and intermediate patients at risk for early progression. Disclosures Rautenberg: Celgene: Honoraria. Germing:Janssen: Honoraria; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Kobbe:Roche: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Other: Travel Support, Research Funding. Schroeder:Celgene: Consultancy, Honoraria, Research Funding.

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