PATH-03. FERROPTOSIS-RELATED LONG NON-CODING RNA SIGNATURES PREDICT PROGNOSIS IN PATIENTS WITH GLIOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi115-vi115
Author(s):  
Lai ◽  
Xiaojia Zuo ◽  
Xintong Yang ◽  
Yanjun Zheng ◽  
Baoyu Duan ◽  
...  
Keyword(s):  
Risk Score ◽  
Proportional Hazards Model ◽  
Risk Group ◽  
Characteristic Curve ◽  
Malignant Gliomas ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Genome Atlas

Abstract Ferroptosis, with iron-dependent and ROS-dependent, is a novel type of cell death in a variety of diseases and some studies confirmed that ferroptosis-related lncRNAs are involved in the occurrence and development of several cancers. However, the ferroptosis-related lncRNA in the role of gliomas is unclear. Here, we constructed a prognostic scoring model of ferroptosis-related lncRNAs in gliomas. Data were downloaded from the Chinese glioma genome atlas (CGGA), the cancer genome atlas, and FerrDb database. In this study, we found 1051 lncRNAs associated with ferroptosis by Spearman's rank correlation analysis in CGGA653, and 547 lncRNAs were related to prognosis in gliomas. Subsequently, we identified 9 ferroptosis-related signatures (AC010729.2, AC062021.1, FAM225B, FAM66C, HOXA-AS2, LINC00662, LINC00665, MIR497HG, and TMEM72-AS1) by least absolute shrinkage and selection operator and Cox proportional hazards model. Next, all glioma patients were divided into high- and low-risk groups based on the median risk score based on these signatures, and the low-risk group had better prognosis significantly than the high-risk group by Kaplan-Meier curve. Moreover, the risk score can predict survival status with high sensitivity and specificity by receiver operating characteristic curve (area under the curve at 1, 3, 5 years: 0.791, 0.84, 0.856, respectively). In addition, some pathways (cell cycle, p53 signaling pathway, apoptosis, and oxidative phosphorylation) significantly enriched in KEGG enrichment pathway, and a nomogram was constructed by integrating some independent prognostic clinicopathological features to predict the overall survival in gliomas (C-index: 0.786). In summary, these 9 ferroptosis-related signatures have potential prognostic value and could be crucial factors for treating malignant gliomas.

Proliferation-dominant high-grade astrocytoma: survival benefit associated with extensive resection of FLAIR abnormality region

2020 ◽  
Vol 132 (4) ◽  
pp. 998-1005 ◽  
Author(s):  
Haihui Jiang ◽  
Yong Cui ◽  
Xiang Liu ◽  
Xiaohui Ren ◽  
Mingxiao Li ◽  
...  
Keyword(s):  
Survival Benefit ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Characteristic Curve ◽  
Extent Of Resection ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
High Grade ◽  
Extensive Resection ◽  
High Grade Astrocytoma

OBJECTIVEThe aim of this study was to investigate the relationship between extent of resection (EOR) and survival in terms of clinical, molecular, and radiological factors in high-grade astrocytoma (HGA).METHODSClinical and radiological data from 585 cases of molecularly defined HGA were reviewed. In each case, the EOR was evaluated twice: once according to contrast-enhanced T1-weighted images (CE-T1WI) and once according to fluid attenuated inversion recovery (FLAIR) images. The ratio of the volume of the region of abnormality in CE-T1WI to that in FLAIR images (VFLAIR/VCE-T1WI) was calculated and a receiver operating characteristic curve was used to determine the optimal cutoff value for that ratio. Univariate and multivariate analyses were performed to identify the prognostic value of each factor.RESULTSBoth the EOR evaluated from CE-T1WI and the EOR evaluated from FLAIR could divide the whole cohort into 4 subgroups with different survival outcomes (p < 0.001). Cases were stratified into 2 subtypes based on VFLAIR/VCE-T1WIwith a cutoff of 10: a proliferation-dominant subtype and a diffusion-dominant subtype. Kaplan-Meier analysis showed a significant survival advantage for the proliferation-dominant subtype (p < 0.0001). The prognostic implication has been further confirmed in the Cox proportional hazards model (HR 1.105, 95% CI 1.078–1.134, p < 0.0001). The survival of patients with proliferation-dominant HGA was significantly prolonged in association with extensive resection of the FLAIR abnormality region beyond contrast-enhancing tumor (p = 0.03), while no survival benefit was observed in association with the extensive resection in the diffusion-dominant subtype (p=0.86).CONCLUSIONSVFLAIR/VCE-T1WIis an important classifier that could divide the HGA into 2 subtypes with distinct invasive features. Patients with proliferation-dominant HGA can benefit from extensive resection of the FLAIR abnormality region, which provides the theoretical basis for a personalized resection strategy.

Histologic Evaluation Using the Robarts Histopathology Index in Patients With Ulcerative Colitis in Deep Remission and the Association of Histologic Remission With Risk of Relapse

2022 ◽  
Author(s):  
Jin Park ◽  
Soo Jin Kang ◽  
Hyuk Yoon ◽  
Jihye Park ◽  
Hyeon Jeong Oh ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Proportional Hazards Model ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
Fecal Calprotectin ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Clinical Relapse ◽  
Endoscopic Remission ◽  
Risk Of Relapse

Abstract Background This study prospectively evaluated the risk of relapse according to the status of histologic activity in patients with ulcerative colitis (UC) who achieved deep remission. Methods Patients with UC in clinical remission (partial Mayo score ≤1) and endoscopic remission (ulcerative colitis endoscopic index of severity ≤1) were enrolled. Rectal biopsies were performed in patients, and histologic remission was defined as a Robarts histopathology index of ≤3. Receiver-operating characteristic curve analysis was conducted to determine fecal calprotectin cutoff values for histologic remission. The cumulative risk of relapse was evaluated using the Cox proportional hazards model. Results Among the 187 patients enrolled, 82 (43.9%) achieved histologic remission. The best cutoff value of fecal calprotectin for predicting histologic remission was 80 mg/kg (area under the curve of 0.646, sensitivity of 74%, and specificity of 61%). Among 142 patients who were followed up for &gt;3 months, 56 (39.4%) showed clinical relapse during a median of 42 weeks. The risk of relapse was lower in patients with histologic remission than in those with histologic activity (P = .026). In multivariable analysis, histologic remission (hazard ratio [HR], 0.551; 95% confidence interval [CI], 0.316-0.958; P = .035), elevated C-reactive protein levels (HR, 3.652; 95% CI, 1.400-9.526; P = .008), and history of steroid use (HR, 2.398; 95% CI, 1.196-4.808; P = .014) were significantly associated with clinical relapse. Conclusions In patients with UC who achieved clinical and endoscopic remission, histologic remission was independently associated with a lower risk of clinical relapse.

Mucin O-glycosylating enzyme GALNT2 facilitates the malignant character of glioma by activating the EGFR/PI3K/Akt/mTOR axis

2019 ◽  
Vol 133 (10) ◽  
pp. 1167-1184 ◽  
Author(s):  
Zhongzheng Sun ◽  
Hao Xue ◽  
Yan Wei ◽  
Chaochao Wang ◽  
Rui Yu ◽  
...  
Keyword(s):  
Matrix Metalloproteinase ◽  
Glioma Cell ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
The Cancer Genome Atlas ◽  
Matrix Metalloproteinase 2 ◽  
Migration And Invasion ◽  
Expression Levels

AbstractN-Acetylgalactosaminyltransferase 2 (GALNT2), the enzyme that regulates the initial step of mucin O-glycosylation, has been reported to play a role in influencing the malignancy of various cancers. However, the mechanism through which it influences gliomas is still unknown. In the current study, the Cox proportional hazards model was used to select genes. Data obtained from The Cancer Genome Atlas (TCGA) database and immunohistochemistry (IHC) of clinical specimens showed that increased GALNT2 expression levels were associated with an unfavorable prognosis and a higher tumor grade in human gliomas. Then, GALNT2 knockdown and overexpression were performed in glioma cell lines and verified by quantitative real-time PCR (qRT-PCR) and Western blotting. Functional assays demonstrated that GALNT2 was closely related to glioma cell proliferation, cycle transition, migration and invasion. Western blot analysis and lectin pull-down assays indicated that GALNT2 knockdown decreased the level of phosphorylated epidermal growth factor receptor (EGFR) and the expression of the Tn antigen on EGFR and affected the expression levels of p21, cyclin-dependent kinase 4 (CDK4), cyclinD1, matrix metalloproteinase 2 (MMP2) and matrix metalloproteinase 9 (MMP9) through the EGFR/PI3K/Akt/mTOR pathway. GALNT2 overexpression had the opposite effects. In vivo, the growth of orthotopic glioma xenografts in nude mice was distinctly inhibited by the expression of GALNT2 shRNA, and the tumors with GALNT2 shRNA exhibited less aggressiveness and reduced expression of Ki67 and MMP2. Overall, GALNT2 facilitates the malignant characteristics of glioma by influencing the O-glycosylation and phosphorylation of EGFR and the subsequent downstream PI3K/Akt/mTOR axis. Therefore, GALNT2 may serve as a novel biomarker and a potential target for future therapy of glioma.

scholarly journals Development of a digitally-obtainable 10-year all-cause mortality risk score based on data from 497,712 UK Biobank participants

2021 ◽  
Author(s):  
Michele Colombo ◽  
Nikola Dolezalova ◽  
Aleksa Despotovic ◽  
Angus B Reed ◽  
Davide Morelli ◽  
...  
Keyword(s):  
Feature Selection ◽  
Survival Analysis ◽  
Risk Score ◽  
Proportional Hazards Model ◽  
Selection Process ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Uk Biobank ◽  
Modifiable Factors ◽  
All Cause Mortality

Background: All-cause mortality (ACM) scores are a useful tool for identifying individuals with decreased life expectancy. An interpretable score consisting of smartphone-obtainable variables could allow for long-term management of individual health and support the next generation of healthcare monitoring and preventative practices. The aim of this study was to develop a 10-year ACM risk score using the UK Biobank dataset, using only digitally-obtainable variables. Methods: The models were developed using the full UK Biobank cohort comprising nearly 500,000 individuals. We extracted 399 features from the dataset and, through a data-driven feature selection process with subsequent clinical review, identified 34 features for the final model. As part of the study, we compared two survival analysis approaches: Cox proportional hazards model and DeepSurv, a deep learning-based survival analysis algorithm. Results: Before feature selection, Cox performed similarly to DeepSurv, achieving a c9index of 0.771 (95% CI 0.770-0.772) and 0.774 (95% CI 0.772-0.775) on the test dataset, respectively. Using the selected 34 features, the c-index of Cox decreased slightly to 0.770 (95% CI 0.769-0.770) and DeepSurv to 0.758 (95% CI 0.755-0.762). The models show excellent calibration at 10 years. Conclusions: This study improves on a previous smartphone-compatible score, C-Score, by incorporating non-modifiable factors in addition to variables which can be actively modified to reduce risk. This score is comprehensive, easily interpretable and actionable, and as such, could provide a powerful tool for preventative healthcare.

Pembrolizumab (pembro) plus axitinib (axi) versus sunitinib as first-line therapy for metastatic renal cell carcinoma (mRCC): Outcomes in the combined IMDC intermediate/poor risk and sarcomatoid subgroups of the phase 3 KEYNOTE-426 study.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4500-4500 ◽  
Author(s):  
Brian I. Rini ◽  
Elizabeth R. Plimack ◽  
Viktor Stus ◽  
Rustem Gafanov ◽  
Robert Hawkins ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Risk Group ◽  
Risk Groups ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
First Line ◽  
Poor Risk ◽  
First Line Therapy ◽  
Line Therapy

4500 Background: In KEYNOTE-426, pembro + axi significantly improved OS (HR 0.53, P < .0001), PFS (HR 0.69, P = .0001), and ORR (59.3% vs 35.7%, P < .0001) vs sunitinib and had manageable toxicity as first-line therapy for mRCC (NCT02853331). The pembro + axi benefit was observed across all IMDC risk groups and regardless of PD-L1 expression. We present data for the combined intermediate/poor risk group and for patients (pts) with sarcomatoid features. Methods: 861 eligible pts with clear-cell mRCC, no prior systemic therapy for mRCC, and KPS ≥70 were randomized 1:1 to pembro 200 mg IV Q3W for a maximum of 35 cycles plus axi 5 mg orally BID (N = 432) or sunitinib 50 mg orally QD (4-wk on/2-wk off) (N = 429). Primary endpoints were OS and PFS (RECIST v1.1 by blinded, independent central review [BICR]). ORR (RECIST v1.1 by BICR) was the key secondary endpoint. The intermediate/poor risk group was prespecified; the sarcomatoid group was exploratory. HRs and their 95% CIs were calculated with a Cox proportional hazards model. None of the analyses were multiplicity-controlled. Results: 592 (68.8%) of all randomized pts were of IMDC intermediate/poor risk — 294 in the pembro + axi arm, 298 in the sunitinib arm. Pembro + axi improved OS (HR 0.52, 95% CI 0.37-0.74; 12-mo rate 87.3% vs 71.3%), PFS (HR 0.67, 95% CI 0.53-0.85; median 12.6 vs 8.2 mo), and ORR (55.8% [95% CI 49.9-61.5] vs 29.5% [24.4-35.1]) in pts with intermediate/poor risk; CR rates were 4.8% (95% CI 2.6-7.9) vs 0.7% (0.1-2.4). Of the 578 pts with known status, 105 (18.2%) had sarcomatoid features — 51 in the pembro + axi arm, 54 in the sunitinib arm. Pembro + axi improved OS (HR 0.58, 95% CI 0.21-1.59; 12-mo rate 83.4% vs 79.5%), PFS (HR 0.54, 95% CI 0.29-1.00; median not reached vs 8.4 mo), and ORR (58.8% [95% CI 44.2-72.4] vs 31.5% [19.5-45.6]) in pts with sarcomatoid features; CR rates were 11.8% (95% CI 4.4-23.9) vs 0% (0.0-6.6). Conclusions: Pembro + axi provides benefit in the combined population of pts with IMDC intermediate or poor risk and in pts whose tumors had sarcomatoid features. The observed benefits were consistent with those seen in the total population. Clinical trial information: NCT02853331.

Comorbidities and Overall Survival In Myelodysplastic Syndromes (MDS): Development of a Prognostic Model Incorporating IPSS and Age with ACE-27 Comorbidity Index

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 605-605 ◽  
Author(s):  
Kiran Naqvi ◽  
Maria E Suarez-Almazor ◽  
Sagar Sardesai ◽  
Jeong Oh ◽  
Carlos Vigil ◽  
...  
Keyword(s):  
Median Survival ◽  
Prognostic Model ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Risk Group ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Kaplan Meier ◽  
Comorbidity Scores

Abstract Abstract 605 Background: Cancer patients often experience comorbidities that may affect their therapeutic options, prognosis, and outcome. Limited studies have evaluated the characteristics and impact of comorbidities in MDS. The aim of this study was to determine the effect of comorbidities on the survival of patients with MDS. Methods: We reviewed the medical records of 600 consecutive MDS patients who presented to MD Anderson Cancer Center from 01–2002 to 06–2004. The Adult Comorbidity Evaluation-27 (ACE-27), a validated 27-item comorbidity index for cancer patients, was used to assess the severity of comorbid conditions. Data on demographic characteristics, International Prognostic Scoring System (IPSS), stem cell transplant (SCT) and outcomes (leukemic transformation and survival) was collected. Kaplan-Meier methods and log-rank tests were used to assess survival. Multivariate analysis was performed using the Cox Proportional Hazards Model. A prognostic model incorporating baseline comorbidities with age and IPSS was developed to predict survival. A score point for each significant factor (age, IPSS and ACE-27 comorbidity score) was obtained by dividing respective coefficients from the multivariate model by 0.3 and rounding to the nearest integer. Results: Of the 600 patients included in this study, 400 (65.7%) were male, and 518 (87.1%) were white; median age at presentation was 66.6 years (range 17.3 – 93.5); median duration of follow-up was 14.8 months (range 0–88). The ACE-27 comorbidity scores were as follows: none, 137 patients (28.8%); mild, 254 (42.3%); moderate, 127 (21.2%); and severe, 82 (13.7%). Four hundred and fifty six (76.0%) patients died, 123 (20.5%) suffered leukemic transformation and 51 (8.5%) patients underwent SCT. Overall median survival using the Kaplan-Meier method was 18.6 months. Median survival according to ACE-27 scores was: 31.8, 16.8, 15.2 and 9.7 months for none, mild, moderate and severe comorbidity scores respectively (p < 0.0001). The adjusted hazards ratios from the multivariate Cox Proportional Hazards Model were 1.3, 1.6 and 2.3 for mild, moderate and severe comorbidity scores when adjusted for age and IPSS (p < 0.0001). A final prognostic model incorporating comorbidity score with age and IPSS was developed. A risk score was derived based on the regression coefficients from the final multivariate model. The score points assigned were: Age > 65 years=2; IPSS of Intermediate-2= 2 and High= 3; ACE-27 score of mild or moderate= 1 and Severe= 3. Based upon their risk scores, patients were categorized into 3 groups: low (0 - 1), intermediate (2 - 4) and high (5 – 8). Almost 50% of the patients in our study were noted to be in the intermediate category with a median survival of 23 months. The model confirmed a better survival in patients in low risk group of 43 months versus 9 months in the high risk group (p < 0.001). Conclusion: Comorbidities had a significant impact on the survival of patients with myelodysplastic syndrome. Patients with higher ACE-27 comorbidity scores had a shorter survival than those with no comorbidity, independent of their age and the IPSS risk group. A comprehensive assessment of comorbidity is therefore needed to determine the prognosis in patients with MDS. Our newly developed prognostic model helps predict survival in such patients based on their comorbidities. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Prognostic Value of Phosphotyrosine Phosphatases in Hepatocellular Carcinoma

2018 ◽  
Vol 46 (6) ◽  
pp. 2335-2346 ◽  
Author(s):  
Guangyan Zhangyuan ◽  
Yin Yin ◽  
Wenjie Zhang ◽  
WeiWei Yu ◽  
Kangpeng Jin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
The Cancer Genome Atlas ◽  
Expression Levels ◽  
Hazards Model ◽  
Kaplan Meier ◽  
Phosphotyrosine Phosphatases

Background/Aims: During the occurrence and progression of hepatocellular carcinoma (HCC), phosphotyrosine phosphatases (PTPs) are usually described as tumor suppressors or proto-oncogenes, and to some degree are correlated with the prognosis of HCC. Methods: A total of 321 patients from the Cancer Genome Atlas (TCGA) database and 180 patients from our validated cohort with hepatocellular carcinoma were recruited in this study. Kaplan-Meier, univariate and multivariate Cox proportional hazards model were used to evaluate the risk factors for survival. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) were applied to detect the expression levels of PTP genes. Results: After screening the data of TCGA, we identified five PTPs as HCC overall survival related PTP genes, among which only three (PTPN12, PTPRN, PTPN18) exhibited differential expression levels in our 180 paired HCC and adjacent tissues (P< 0.001). Further analysis revealed that expression of PTPN18 was positively, but PTPRN was negatively associated with prognosis of HCC both in TCGA cohort and our own cohort. As to PTPN12, results turned out to be opposite according to HBV status. In detail, higher expression of PTPN12 was associated with better outcome in HBV group but worse prognosis in Non-HBV group. Conclusion: Our results suggested that PTPN12, PTPRN and PTPN18 were independent prognostic factors in HCC.

scholarly journals Development and validation of Pyroptosis‑related lncRNAs prediction model for bladder cancer

2022 ◽  
Author(s):  
Thongher Lia ◽  
Yanxiang Shao ◽  
Parbatraj Regmi ◽  
Xiang Li
Keyword(s):  
Bladder Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis

Bladder cancer is one of the highly heterogeneous disorders accompanied by a poor prognosis. This study aimed to construct a model based on pyroptosis‑related lncRNA to evaluate the potential prognostic application in bladder cancer. The mRNA expression profiles of bladder cancer patients and corresponding clinical data were downloaded from the public database from The Cancer Genome Atlas (TCGA). Pyroptosis‑related lncRNAs were identified by utilizing a co-expression network of Pyroptosis‑related genes and lncRNAs. The lncRNA was further screened by univariate Cox regression analysis. Finally, 8 pyroptosis-related lncRNA markers were established using Lasso regression and multivariate Cox regression analysis. Patients were separated into high and low-risk groups based on the performance value of the median risk score. Patients in the high-risk group had significantly poorer overall survival (OS) than those in the low-risk group (p &lt; 0.001), and In multivariate Cox regression analysis, the risk score was an independent predictive factor of OS ( HR&gt;1, P&lt;0.01). The area under the curve (AUC) of the 3- and 5-year OS in the receiver operating characteristic (ROC) curve were 0.742 and 0.739 respectively. In conclusion, these 8 pyroptosis-related lncRNA and their markers may be potential molecular markers and therapeutic targets for bladder cancer patients.

scholarly journals Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data

Biomedicines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1502
Author(s):  
Cong Pian ◽  
Mengyuan He ◽  
Yuanyuan Chen
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Transcriptomic Data ◽  
Cancer Types ◽  
The Individual ◽  
Pathway Deregulation

The occurrence of cancer is closely related to the deregulation of certain pathways. Based on pathway deregulation scores (PDS) inferred by the Pathifier algorithm, we analyzed transcriptomic data of 13 different cancer types in The Cancer Genome Atlas database to identify cancer-specific deregulated pathways and prognostic pathways. The results showed that the individual-specific pathway deregulation scores can clearly distinguish different cancer types and their tumor-adjacent tissues. In addition, the cancer-specific deregulated pathways and prognostic pathways of different cancer types had high heterogeneity, and the identified cancer prognostic pathways have been reported to be closely related to the corresponding cancers. Furthermore, we also found that cancers with more deregulation pathways tend to be malignant and have worse prognoses. Finally, a Cox proportional Hazards model was constructed based on the prognostic pathways; this model successfully predicted survival and prognosis based on data from cancer samples. In addition, the performance of the breast cancer prognostic model was validated with an independent data set in the METABRIC database. Therefore, the prognostic pathways we identified have the potential to become targets for the treatment of cancer.

N-terminal pro-B-type natriuretic peptide complements the GRACE risk score in predicting early and late mortality following acute coronary syndrome

2009 ◽  
Vol 117 (1) ◽  
pp. 31-39 ◽  
Author(s):  
Sohail Q. Khan ◽  
Hafid Narayan ◽  
Kelvin H. Ng ◽  
Onkar S. Dhillon ◽  
Dominic Kelly ◽  
...  
Keyword(s):  
Natriuretic Peptide ◽  
Risk Score ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Receiver Operating Curve ◽  
Risk Scores ◽  
Late Mortality ◽  
Coronary Syndrome ◽  
Grace Risk Score

The GRACE (Global Registry of Acute Coronary Events) risk score has been shown to offer predictive power with regard to death and AMI (acute myocardial infarction) in patients with ACS (acute coronary syndromes). NT-proBNP (N-terminal pro-B-type natriuretic peptide) has also been found to be useful in predicting mortality following ACS. In the present study, we sought to investigate the use of the GRACE score and NT-proBNP levels at predicting risk of early and late deaths following ACS. We studied 1033 patients (740 men, mean age 66.5±12.7 years) with AMI. Blood was drawn once within 24 h following the onset of chest pain. The plasma concentration of NT-proBNP was determined using an in-house non-competitive immunoassay. Patients were GRACE risk scored. The 30-day mortality was 3.7% and the 6-month mortality was 7.8%, and all were related to higher GRACE risk scores (P=0.001 for trend). Higher NT-proBNP levels were also related to increased mortality (P<0.0001). In a Cox proportional hazards model, independent predictors of 30-day and 6-month mortality included NT-proBNP levels and the GRACE risk score. The receiver-operating curve for the GRACE risk score was complemented by NT-proBNP levels for prediction of 30-day mortality [AUC (area under the curve), 0.85] and 6-month mortality (AUC, 0.81). NT-proBNP gives complementary information to the GRACE risk score for predicting early and late mortality. The inclusion of the NT-proBNP blood test is useful in risk-stratifying patients after ACS.

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