scholarly journals MRI-Based Texture Features as Potential Prognostic Biomarkers in Anaplastic Astrocytoma Patients Undergoing Surgical Treatment

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Yang Zhang ◽  
Chaoyue Chen ◽  
Yangfan Cheng ◽  
Danni Cheng ◽  
Fumin Zhao ◽  
...  
Keyword(s):  
Surgical Treatment ◽  
Anaplastic Astrocytoma ◽  
Cox Regression ◽  
Texture Feature ◽  
Texture Features ◽  
Prognostic Biomarkers ◽  
Rank Test ◽  
Operating Characteristics ◽  
Surgical Interventions ◽  
Cox Regression Analysis

Objectives. The purpose of this study was to investigate whether texture features from magnetic resonance imaging (MRI) were associated with the overall survival (OS) of anaplastic astrocytoma (AA) patients undergoing surgical treatment. Methods. A total of 51 qualified patients who were diagnosed with AA and underwent surgical interventions in our institution were enrolled in this retrospective study. Patients were followed up for at least 30 months or until death. Texture features derived from histogram-based matrix (HISTO) and grey-level co-occurrence matrix (GLCM) were extracted from preoperative contrast-enhanced T1-weighted images. Each texture feature was dichotomized based on its optimal cutoff value calculated by receiver operating characteristics curve analysis. Kaplan–Meier analysis and log rank test were conducted to compare the 30-month OS between the dichotomized subgroups. Multivariate Cox regression analysis was performed to determine independent prognostic factors. Results. Three HISTO-derived features (HISTO-Energy, HISTO-Entropy, and HISTO-Skewness) and five GLCM-derived features (GLCM-Contrast, GLCM-Energy, GLCM-Entropy, GLCM-Homogeneity, and GLCM-Dissimilarity) were found to be significantly correlated with 30-month OS. Moreover, GLCM-Homogeneity (p=0.001, hazard ratio = 6.351) was suggested to be the independent predictor of the patient survival. Conclusion. MRI-based texture features have the potential to be applied as prognostic biomarkers in AA patients undergoing surgical treatment.

Predictive Model for Live Birth at 12 Months After Starting In-Vitro Fertilization Treatment

MedPharmRes ◽  
2018 ◽  
Vol 2 (2) ◽  
pp. 5-20
Author(s):  
Vu Ho ◽  
Toan Pham ◽  
Tuong Ho ◽  
Lan Vuong
Keyword(s):  
In Vitro Fertilization ◽  
Live Birth ◽  
Cox Regression ◽  
Financial Burden ◽  
Oocyte Retrieval ◽  
Operating Characteristics ◽  
Vitro Fertilization ◽  
Cox Regression Analysis ◽  
Significant Difference

IVF carries a considerable physical, emotional and financial burden. Therefore, it would be useful to be able to predict the likelihood of success for each couple. The aim of this retrospective cohort study was to develop a prediction model to estimate the probability of a live birth at 12 months after one completed IVF cycle (all fresh and frozen embryo transfers from the same oocyte retrieval). We analyzed data collected from 2600 women undergoing in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) at a single center in Vietnam between April 2014 and December 2015. All patients received gonadotropin-releasing hormone (GnRH) antagonist stimulation, followed by fresh and/or frozen embryo transfer (FET) on Day 3. Using Cox regression analysis, five predictive factors were identified: female age, total dose of recombinant follicle stimulating hormone used, type of trigger, fresh or FET during the first transfer, and number of subsequent FET after the first transfer. The area under the receiver operating characteristics curve for the final model was 0.63 (95% confidence interval [CI] 0.60‒0.65) and 0.60 (95% CI 0.57‒0.63) for the validation cohort. There was no significant difference between the predicted and observed probabilities of live birth (Hosmer-Lemeshow test, p > 0.05). The model developed had similar discrimination to existing models and could be implemented in clinical practice.

scholarly journals Predictive impact of PVL assessments on clinical outcomes in patients undergoing TAVR

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
K Matsushita ◽  
B Marchandot ◽  
M Kibler ◽  
C Sato ◽  
J Heger ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Cox Regression ◽  
Adenosine Diphosphate ◽  
Rank Test ◽  
Multicenter Studies ◽  
Cox Regression Analysis ◽  
Paravalvular Leakage ◽  
Transcatheter Aortic Valve ◽  
Log Rank Test ◽  
Cerebrovascular Events

Abstract Introduction Paravalvular leakage (PVL) following transcatheter aortic valve replacement (TAVR) is associated with greater mortality. In clinical practice, determining PVL severity after TAVR remains challenging and often requires multiparametric assessment. Purpose This study sought to evaluate the respective value of various modalities of PVL assessments, including transthoracic echocardiography (TTE), cine-angiography, aortic regurgitation index (ARI), and closure time with adenosine diphosphate (CT-ADP), in the prediction of adverse clinical outcomes. Methods We included 1044 patients from our prospective TAVR registry between February 2010 and May 2019. Major adverse cardiac and cerebrovascular events (MACCE) was defined as a composite of all-cause death, myocardial infarction, stroke, and heart failure hospitalization within 1-year. Established cutoff values of ARI (<25) and CT-ADP (>180 sec) were used to assess the presence of PVL after TAVR. Results Moderate to severe PVL occurred in 14.2% and 5.2% of patients as measured by TTE and angiography. The rate of patients with ARI <25 and CT-ADP >180 sec were 36.5% and 24.9%, respectively. Among the four modalities, PVL evaluated by angiography predicted poorer clinical outcomes (Log rank test; p=0.001), whereas TTE, ARI <25, and CT-ADP >180 sec were not associated with 1-year MACCE. By multivariate Cox regression analysis, moderate to severe PVL by angiography was an independent predictor of 1-year MACCE (hazard ratio: 1.96; 95% confidence interval: 1.22–3.00; p=0.007). Conclusions Paravalvular leakage measured by angiography was evidenced as the most meaningful modality in the prediction of adverse clinical outcomes. Future multicenter studies are warranted to ensure these findings in the current TAVR era. Figure 1 Funding Acknowledgement Type of funding source: None

scholarly journals Survival and community care use by care home residents in England: does mental health matter?

2021 ◽  
pp. 1-15
Author(s):  
Apostolos Tsiachristas ◽  
Antoinette Broad ◽  
Alice Coates ◽  
Surya Singh ◽  
Jane Fossey
Keyword(s):  
Mental Health ◽  
Community Care ◽  
Cox Regression ◽  
Care Home ◽  
Care Homes ◽  
Health Conditions ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Mental Health Conditions ◽  
Care Costs

Abstract The aim was to provide evidence of mortality and community care costs of people living in care homes and to investigate its association with mental health based on the Mental Health Clustering Tool (MHCT). In an observational study, 5,782 residents living in 104 care homes were followed from 2014 to 2016. Residents were categorised into four groups using the MCHT: three with mental health conditions, ‘non-psychotic’, ‘psychotic’ or ‘organic’; and one without mental health conditions, ‘non-clustered’. Generalised estimating equations were used to explore associations between mean community care costs over 6 months per patient and the clustering of residents into the four groups. Differences in survival rates of residents were plotted using Kaplan–Meier curves and tested with the log-rank test and Cox regression analysis. Community care costs were similar among residents with dementia (£431) and without mental health conditions (£407), while costs were higher among residents with non-psychotic (£762) and psychotic (£1,724) mental health conditions. After adjusting for patient and care home characteristics, residents with dementia were 30 per cent less likely to die compared with residents without mental health conditions. Similarly, residents with psychotic conditions and residents with non-psychotic conditions were 25 and 20 per cent less likely to die, respectively, than residents without mental health conditions. The MHCT seems to provide an informative stratification of care home residents with regards to survival and community care use.

Exploratory circulating biomarker analyses: lenvatinib + pembrolizumab (L + P) in a phase 1b trial in unresectable hepatocellular carcinoma (uHCC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 4084-4084
Author(s):  
Andrew X. Zhu ◽  
Josep M Llovet ◽  
Masahiro Kobayashi ◽  
Masafumi Ikeda ◽  
Marc Pracht ◽  
...  
Keyword(s):  
Cox Regression ◽  
Objective Response ◽  
Rank Correlation ◽  
Study Drug ◽  
Complete Response ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Clinical Endpoints ◽  
Spearman’S Rank Correlation ◽  
Phase 1B

4084 Background: In a phase 1b trial (NCT03006926), L + P had promising antitumor activity as first-line (1L) therapy in uHCC. We present exploratory biomarker analyses of circulating angiogenic factors and cytokines/chemokines related to the mechanism of action of L + P (ie, pharmacodynamic [PD] biomarkers), as well as biomarker correlations with clinical outcomes in patients (pts) with uHCC, from this trial. Methods: Pts received lenvatinib 12 mg/d (bodyweight [BW] >60 kg) or 8 mg/d (BW < 60 kg) PO + pembrolizumab 200 mg IV Q3W. Tumors were assessed using mRECIST or RECIST v1.1 per independent imaging review. Peripheral blood samples were collected before administration of study drug at baseline, cycle (C) 2, day (D) 1, C3D1, C4D1, and off-treatment. 43 Biomarkers were assayed in serum from 100 1L uHCC pts (excluding 4 pts from the dose-limiting toxicity part of the trial with prior sorafenib). Of these 43, 31 biomarkers (for which ≤20% of samples had measurements above/below the quantification limit of the assay) were included in the analyses. Changes in biomarker levels from baseline were evaluated via 1-sample Wilcoxon signed-rank test. Associations were explored between changes in biomarker levels and maximum tumor shrinkage (MTS) via the Spearman’s rank correlation test, objective response (OR; complete response + partial response) via the Wilcoxon rank sum test, and PFS via Cox regression analysis and log rank test. Data cutoff date for clinical endpoints was 7 August 2020. Results: Levels of PD biomarkers related to angiogenic signaling (VEGF increase/ANG2 decrease), FGF signaling (increase in FGF23/FGF19), and IFNγ signaling (increase in IFNγ, CXCL9/10/11) were changed significantly (adjusted P< 0.05) with L + P (C2D1–C4D1; except for FGF19 at C3D1). Significant decreases of TIMP1 and increases of MCP1 were observed at C4D1 during treatment; these were associated with greater MTS. Greater decreases in TIMP1 and greater increases in MCP1 were observed in pts with OR vs others. Changes in levels of the PD biomarkers ANG2, IL10, and VEGFR2 were found to be associated with PFS by dichotomized analysis. With tertile 2 cutoff, median PFS for pts in the group with greater decreases of ANG2 was 13.9 months vs 9.6 months for pts in the group with lesser decreases of ANG2 (unadjusted P= 0.002; HR 2.65, 95% CI 1.39–5.08). Conclusions: These are the first exploratory biomarker analyses for the single-arm study of L + P in pts with uHCC. Changes in serum biomarkers associated with angiogenic-, FGF-, and IFNγ-signaling pathways indicated target engagement of L + P. Decreases in TIMP1 and increases in MCP1 were associated with MTS and OR. Associations were found between longer PFS and a greater decrease in levels of ANG2. Angiogenesis inhibition and modulation of cancer immune response were observed with L + P. Further validation from independent studies is warranted. Clinical trial information: NCT03006926.

scholarly journals Tertiary Gleason Pattern 5 is An Independent Risk Factor for Prostate Cancer with GS 7: A Retrospective Study from China.

2021 ◽  
Author(s):  
Desheng Cai ◽  
Zixin Wang ◽  
Yu Fan ◽  
Lin Cai ◽  
Kan Gong
Keyword(s):  
Prostate Cancer ◽  
Risk Factor ◽  
Independent Risk Factor ◽  
Cox Regression ◽  
Prostate Volume ◽  
Surgical Margin ◽  
Rank Test ◽  
Positive Surgical Margin ◽  
Cox Regression Analysis ◽  
Gleason Pattern

Abstract Background: Tertiary Gleason pattern 5 (TGP5) was found to be prognostic in prostate cancer (PCa) after radical prostatectomy (RP), but related data from China was rare. Our study was aimed at finding out the effect of TGP5 on PCa with Gleason score (GS) 7 and supplementing data from China in this field.Methods: A total of 229 cases met with inclusion criteria during Jan. 2014 to Dec. 2018 were reviewed. Cases were divided into GS 7 without TGP5 and GS 7 with TGP5. We compared age at diagnosis, preoperative PSA level, prostate volume, PSA density (PSAD), GS variation, clinical T staging, pathological T staging, T staging variation, extra-prostatic extension (EPE), positive surgical margin (PSM) and seminal vesicle invasion (SVI) between the groups. Effects of TGP5 on prognosis of PCa with GS 7 were evaluated using biochemical recurrence (BCR) as the primary end point.Results: TGP5 was related to higher PSM rate (P=0.001) and BCR rate (P=0.009) but not related to higher preoperative PSA level, larger prostate volume, higher PSAD, GS upgrade, poorer clinical/pathological T staging, T upstaging, EPE and SVI (all P>0.05). The median follow-up time was 24 months (interquartile range 17.5-45.5). TGP5 was an independent risk factor to PCa with GS 7 after RP using Kaplan-Meier log-rank test (P=0.018). Both univariable and multivariable cox-regression analysis pointed out that TGP5 increased the incidence of BCR in PCa with GS 7 (P<0.05). Stratified analyses were also done.Conclusion: TGP5 is an independent risk factor predicting of BCR after RP in PCa with GS 7 from China. TGP5 is related to higher PSM rate and BCR incidence. It is time to renew the contemporary Grading Group system with the consideration of TGP.

scholarly journals Tumor Volume Reduction Rate to Induction Chemotherapy Is a Prognostic Factor for Locally Advanced Head and Neck Squamous Cell Carcinoma: a Retrospective Cohort Study

2021 ◽  
Author(s):  
Chi-hsien Huang ◽  
Ting-Chun Lin ◽  
Ming-Yu Lien ◽  
Fu-Ming Cheng ◽  
Kai-Chiun Li ◽  
...  
Keyword(s):  
Tumor Volume ◽  
Cox Regression ◽  
Reduction Rate ◽  
Volume Reduction ◽  
Cancer Site ◽  
Rank Test ◽  
Primary Cancer ◽  
Cox Regression Analysis ◽  
Log Rank Test ◽  
Tumor Volume Reduction

Abstract BackgroundAim of this study was to evaluate the prognostic of tumor volume reduction rate (TVRR) status post induction chemotherapy (IC) in LA-HNSCC.MethodsPatients with newly diagnosed LA-HNSCC from year 2007 to 2016 at a single center were included in this retrospective study. All patients had received IC as TPF (taxotere, platinum, fluorouracil) followed by daily definitive intensity-modulated radiotherapy (IMRT) for 70 Gy in 35 fractions concurrent with or without cisplatin-based chemotherapy. Tumor volume reduction rate of the primary tumor (TVRR-T) and lymph node (TVRR-N) was measured and calculated by contrast-enhanced CT images at diagnosis, and one month after final IC cycle, and analyzed though a univariate and multivariate Cox regression model.ResultsNinety patients of the primary cancer sites at hypopharynx (31/90, 34.4%), oropharynx (29/90, 32.2%), oral cavity (19/90, 21.1%) and larynx (11/90, 12.2%) were included in this study, with a median follow-up time interval of 3.9 years. In univariate Cox regression analysis, the TVRR-T as the only variable showed a significant difference for disease-free survival (DFS) (hazard ratio [HR] 0.77, 95% confidence interval (CI) 0.63 to 0.96; P = 0.02), aside from cancer site, RECIST, age and IC dose. In multivariate Cox regression analysis, The TVRR-T was also an independently significant prognostic factor for DFS (HR 0.77, 95% CI 0.62 to 0.97; P = 0.02). At a cutoff value using TVRR-T of 50% in Kaplan-Meier survival analysis, the DFS was significant higher with TVRR-T ≥ 50% group (log-rank test, p = 0.024), and also a trend of improved OS. (log-rank test, p = 0.069).ConclusionsTVRR-T was related to improved DFS and trend of improved OS. Other factors including patient’s age at diagnosis, the primary cancer site, and RECIST, were not significantly related to DFS.

scholarly journals Clinical Value of lncRNA LUCAT1 Expression in Liver Cancer and its Potential Pathways

2019 ◽  
Vol 28 (4) ◽  
pp. 439-447 ◽  
Author(s):  
Yan Jiao ◽  
Yanqing Li ◽  
Bai Ji ◽  
Hongqiao Cai ◽  
Yahui Liu
Keyword(s):  
Liver Cancer ◽  
Roc Curve ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Rank Test ◽  
P Value ◽  
Rna Seq ◽  
Cox Regression Analysis

Background and Aims: Emerging studies indicate that long noncoding RNAs (lncRNAs) play a role as prognostic markers in many cancers, including liver cancer. Here, we focused on the lncRNA lung cancer-associated transcript 1 (LUCAT1) for liver cancer prognosis. Methods: RNA-seq and phenotype data were downloaded from the Cancer Genome Atlas (TCGA). Chisquare tests were used to evaluate the correlations between LUCAT1 expression and clinical features. Survival analysis and Cox regression analysis were used to compare different LUCAT1 expression groups (optimal cutoff value determined by ROC). The log-rank test was used to calculate the p-value of the Kaplan-Meier curves. A ROC curve was used to evaluate the diagnostic value. Gene Set Enrichment Analysis (GSEA) was performed, and competing endogenous RNA (ceRNA) networks were constructed to explore the potential mechanism. Results: Data mining of the TCGA -Liver Hepatocellular Carcinoma (LIHC) RNA-seq data of 371 patients showed the overexpression of LUCAT1 in cancerous tissue. High LUCAT1 expression was associated with age (p=0.007), histologic grade (p=0.009), T classification (p=0.022), and survival status (p=0.002). High LUCAT1 patients had a poorer overall survival and relapse-free survival than low LUCAT1 patients. Multivariate analysis identified LUCAT1 as an independent risk factor for poor survival. The ROC curve indicated modest diagnostic performance. GSEA revealed the related signaling pathways, and the ceRNA network uncovered the underlying mechanism. Conclusion: High LUCAT1 expression is an independent prognostic factor for liver cancer.

scholarly journals Identification and Analysis of Three Hub Prognostic Genes Related to Osteosarcoma Metastasis

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jianye Tan ◽  
Haofeng Liang ◽  
Bingsheng Yang ◽  
Shuang Zhu ◽  
Guofeng Wu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Survival Rates ◽  
Prognostic Biomarkers ◽  
Messenger Rnas ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Expression Levels ◽  
Kaplan Meier ◽  
Before And After

Osteosarcoma (OS) often occurs in children and often undergoes metastasis, resulting in lower survival rates. Information on the complexity and pathogenic mechanism of OS is limited, and thus, the development of treatments involving alternative molecular and genetic targets is hampered. We categorized transcriptome data into metastasis and nonmetastasis groups, and 400 differential RNAs (230 messenger RNAs (mRNAs) and 170 long noncoding RNAs (lncRNAs)) were obtained by the edgeR package. Prognostic genes were identified by performing univariate Cox regression analysis and the Kaplan–Meier (KM) survival analysis. We then examined the correlation between the expression level of prognostic lncRNAs and mRNAs. Furthermore, microRNAs (miRNAs) corresponding to the coexpression of lncRNA-mRNA was predicted, which was used to construct a competitive endogenous RNA (ceRNA) regulatory network. Finally, multivariate Cox proportional risk regression analysis was used to identify hub prognostic genes. Three hub prognostic genes (ABCG8, LOXL4, and PDE1B) were identified as potential prognostic biomarkers and therapeutic targets for OS. Furthermore, transcriptions factors (TFs) (DBP, ESX1, FOS, FOXI1, MEF2C, NFE2, and OTX2) and lncRNAs (RP11-357H14.16, RP11-284N8.3, and RP11-629G13.1) that were able to affect the expression levels of genes before and after transcription were found to regulate the prognostic hub genes. In addition, we identified drugs related to the prognostic hub genes, which may have potential clinical applications. Immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (qRT-PCR) confirmed that the expression levels of ABCG8, LOXL4, and PDE1B coincided with the results of bioinformatics analysis. Moreover, the relationship between the hub prognostic gene expression and patient prognosis was also validated. Our study elucidated the roles of three novel prognostic biomarkers in the pathogenesis of OS as well as presenting a potential clinical treatment for OS.

Abstract 2284: Non-invasively Determined Ventricular Elastance as a predictor of cardiovascular mortality in Patients With acute myocardial infarction and Preserved ejection fraction: Data from Infarction Prognosis Study (IPS) registry

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Sung Ai Kim ◽  
Jong-Won Ha ◽  
Hyeon Chang Kim ◽  
Sungha Park ◽  
Eui-Young Choi ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Ejection Fraction ◽  
Cardiovascular Mortality ◽  
Cox Regression ◽  
Left Ventricular ◽  
Volume Index ◽  
Rank Test ◽  
Preserved Ejection Fraction ◽  
Cox Regression Analysis ◽  
Acute Mi

Background : Previous studies of the prognosis of myocardial infarction (MI) have focused primarily on patients with left ventricular (LV) systolic dysfunction. Little is known about the prognosis of patients with MI and preserved ejection fraction (EF), which is increasing. Since the ratio of mitral inflow (E) and annular velocity (E′) to stroke volume (E/E′/SV) has been reported as an index of diastolic elastance (Ed), we hypothesized that Ed has prognostic implication in patients with acute MI and preserved EF. Method : Between May 2005 and January 2007, a total of 421 patients with acute MI were prospectively enrolled in Infarction Prognosis Study (IPS) registry. Among 358 patients who had comprehensive echocardiographic study, 42 patients with significant valvular heart disease or coexisted cardiomyopathy and 50 patients with decreased EF (<40%) were excluded. This left a total of 266 patients, who constituted the study population. The primary end-point was cardiovascular mortality. Results : Median follow-up duration was 12 months. Of 266 patients, cardiovascular death occurred in 11 (4.1%) patients. Age (p< 0.001), LA volume index (p=0.001), the severity of diastolic dysfunction (grade ≥ 2, p=0.04), Ed (p=0.003) were univariate predictors of cardiovascular mortality. However, in multivariate Cox regression analysis, age (p=0.008, HR; 1.14, 95% CI; 1.03–1.25) and Ed (p=0.009, HR; 1.72, 95% CI; 1.14 –2.58) were found to be independent predictors for cardiovascular mortality in patients with acute MI and preserved EF. Cut-off value of Ed for cardiovascular mortality determined by Kaplan-Meier method (p<0.001 by log-rank test) and ROC curve (AUC 0.87, sensitivity 90%, specificity 74%) was 0.25. Conclusion : Non-invasively determined ventricular diastolic elastance is a novel and powerful independent predictor of cardiovascular mortality in patients with acute MI and preserved EF.

Cardiovascular Risk Based on ASCVD and KDIGO Categories in Chinese Adults: A Nationwide, Population-Based, Prospective Cohort Study

2021 ◽  
pp. ASN.2020060856
Author(s):  
Yu Xu ◽  
Mian Li ◽  
Guijun Qin ◽  
Jieli Lu ◽  
Li Yan ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Cohort Study ◽  
Risk Prediction ◽  
Cox Regression ◽  
Rank Test ◽  
Atherosclerotic Cardiovascular Disease ◽  
Cvd Risk ◽  
Cox Regression Analysis ◽  
Ascvd Risk ◽  
Risk Categories

BackgroundThe Kidney Disease Improving Global Outcomes (KDIGO) clinical practice guideline used eGFR and urinary albumin-creatinine ratio (ACR) to categorize risks for CKD prognosis. The utility of KDIGO’s stratification of major CVD risks and predictive ability beyond traditional CVD risk prediction scores are unknown.MethodsTo evaluate CVD risks on the basis of ACR and eGFR (individually, together, and in combination using the KDIGO risk categories) and with the atherosclerotic cardiovascular disease (ASCVD) score, we studied 115,366 participants in the China Cardiometabolic Disease and Cancer Cohort study. Participants (aged ≥40 years and without a history of cardiovascular disease) were examined prospectively for major CVD events, including nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death.ResultsDuring 415,111 person-years of follow-up, 2866 major CVD events occurred. Incidence rates and multivariable-adjusted hazard ratios of CVD events increased significantly across the KDIGO risk categories in ASCVD risk strata (all P values for log-rank test and most P values for trend in Cox regression analysis <0.01). Increases in c statistic for CVD risk prediction were 0.01 (0.01 to 0.02) in the overall study population and 0.03 (0.01 to 0.04) in participants with diabetes, after adding eGFR and log(ACR) to a model including the ASCVD risk score. In addition, adding eGFR and log(ACR) to a model with the ASCVD score resulted in significantly improved reclassification of CVD risks (net reclassification improvements, 4.78%; 95% confidence interval, 3.03% to 6.41%).ConclusionsUrinary ACR and eGFR (individually, together, and in combination using KDIGO risk categories) may be important nontraditional risk factors in stratifying and predicting major CVD events in the Chinese population.

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