Aggregate Clinical and Biomarker-Based Model Predicts Adverse Outcomes in Patients With Coronary Artery Disease.

Despite guideline-based therapy, patients with coronary artery disease (CAD) are at widely variable risk for cardiovascular events. This variability demands a more individualized risk assessment. Herein, we evaluate the prognostic value of 6 biomarkers: high-sensitivity C-reactive protein, heat shock protein-70, fibrin degradation products, soluble urokinase plasminogen activator receptor, high-sensitivity troponin I, and B-type natriuretic peptide. We then develop a multi-biomarker-based cardiovascular event prediction model for patients with stable CAD. In total, 3,115 subjects with stable CAD who underwent cardiac catheterization at Emory (mean age 62.8 years, 17% Black, 35% female, 57% obstructive CAD, 31% diabetes mellitus) were randomized into a training cohort to identify biomarker cutoff values and a validation cohort for prediction assessment. Main outcomes included (1) all-cause death and (2) a composite of cardiovascular death and nonfatal myocardial infarction (MI) within 5 years. Elevation of each biomarker level was associated with higher event rates in the training cohort. A biomarker risk score was created using optimal cutoffs, ranging from 0 to 6 for each biomarker exceeding its cutoff. In the validation cohort, each unit increase in the biomarker risk score was independently associated with all-cause death (hazard ratio 1.62, 95% confidence interval [CI] 1.45 to 1.80) and cardiovascular death/MI (hazard ratio 1.52, 95% CI 1.35 to 1.71). A biomarker risk prediction model for cardiovascular death/MI improved the c-statistic (∆ 6.4%, 95% CI 3.9 to 8.8) and net reclassification index by 31.1% (95% CI 24 to 37), compared with clinical risk factors alone. Integrating multiple biomarkers with clinical variables refines cardiovascular risk assessment in patients with CAD.

Relation of High-sensitivity Cardiac Troponin I Elevation With Exercise to Major Adverse Cardiovascular Events in Patients With Coronary Artery Disease.

High sensitive cardiac troponin I (hs-cTnI) increases with inducible myocardial ischemia in patients with coronary artery disease (CAD). We aimed to assess if the change in hs-cTnI levels with exercise stress testing is associated with major adverse cardiac events (MACE). A cohort of 365 (age 62 ± 9 years, 77% men) patients with stable CAD underwent 99mTc sestamibi myocardial perfusion imaging with treadmill testing. Plasma hs-cTnI level was measured at rest and at 45 min after stress. Multivariable Fine & Gray's subdistribution hazards models were used to determine the association between the change in hs-cTnI and MACE, a composite end point of cardiovascular death, myocardial infarction, and unstable angina requiring revascularization. During a median follow-up of 3 years, 39 (11%) patients experienced MACE. After adjustment, for each two-fold increment in hs-cTnI with stress, there was a 2.2 (95% confidence interval 1.3-3.6)-fold increase in the hazard for MACE. Presence of both a high resting hs-cTnI level (>median) and ≥ 20% stress-induced hs-cTnI elevation was associated with the highest incidence of MACE (subdistribution hazards models 4.6, 95% confidence interval 1.6 to 13.0) compared with low levels of both. Risk discrimination statistics significantly improved after addition of resting and change in hs-cTnI levels to a model including traditional risk factors and inducible ischemia (0.67 to 0.71). Conversely, adding inducible ischemia by SPECT did not significantly improve the C-statistic from a model including traditional risk factors, baseline and change in hs-cTnI (0.70 to 0.71). In stable CAD patients, higher resting levels and elevation of hs-cTnI with exercise are predictors of adverse cardiovascular outcomes beyond traditional cardiovascular risk factors and presence of inducible ischemia.

Soluble Urokinase-Type Plasminogen Activator Receptor and High-Sensitivity Troponin Levels Predict Outcomes in Nonobstructive Coronary Artery Disease.

Background Multiple biomarkers have been independently and additively associated with major adverse cardiovascular events in patients with coronary artery disease. We investigated the prognostic value of suPAR (soluble urokinase-type plasminogen activator receptor) and hsTnI (high-sensitivity troponin I) levels in symptomatic patients with no obstructive coronary artery disease. We hypothesized that high levels of these biomarkers will be associated with the risk of future adverse outcomes. Methods and Results Plasma levels of suPAR and hsTnI were measured in 556 symptomatic patients with no obstructive coronary artery disease. A biomarker risk score was calculated by counting the number of biomarkers above the median in this cohort (suPAR>2523 pg/mL and hsTnI>2.7 pg/mL). Survival analyses were performed with models adjusted for traditional risk factors. All-cause death and major adverse cardiovascular events (cardiovascular death, myocardial infarction, stroke, and heart failure) served as clinical outcomes over a median follow-up of 6.2 years. Mean age was 57±10 years, 49% of the cohort patients were female, and 68% had a positive stress test. High suPAR and hsTnI levels were independent predictors of all-cause death (hazard ratio=3.2 [95% CI, 1.8-5.7] and 1.3 [95% CI, 1.0-1.7], respectively; both P<0.04) and major adverse cardiovascular events (hazard ratio=2.7 [95% CI, 1.4-5.4] and 1.5 [95% CI, 1.2-2.0], respectively; both P<0.002). Compared with a biomarker risk score of 0, biomarker risk scores of 1 and 2 were associated with 19- and 14-fold increased risk of death and development of major adverse cardiovascular events, respectively. Conclusions Among symptomatic patients with no obstructive coronary artery disease, higher levels of suPAR and hsTnI were independently and additively associated with an increased risk of adverse events. Whether modification of these biomarkers will improve risk in these patients needs further investigation.

A Novel Online Calculator Based on Serum Biomarkers to Detect Hepatocellular Carcinoma among Patients with Hepatitis B.

BACKGROUND: Early detection of hepatocellular carcinoma (HCC) among hepatitis B virus (HBV)-infected patients remains a challenge, especially in China. We sought to create an online calculator of serum biomarkers to detect HCC among patients with chronic hepatitis B (CHB). METHODS: Participants with HBV-HCC, CHB, HBV-related liver cirrhosis (HBV-LC), benign hepatic tumors, and healthy controls (HCs) were recruited at 11 Chinese hospitals. Potential serum HCC biomarkers, protein induced by vitamin K absence or antagonist-II (PIVKA-II), α-fetoprotein (AFP), lens culinaris agglutinin A-reactive fraction of AFP (AFP-L3) and α-l-fucosidase (AFU) were evaluated in the pilot cohort. The calculator was built in the training cohort via logistic regression model and validated in the validation cohort. RESULTS: In the pilot study, PIVKA-II and AFP showed better diagnostic sensitivity and specificity compared with AFP-L3 and AFU and were chosen for further study. A combination of PIVKA-II and AFP demonstrated better diagnostic accuracy in differentiating patients with HBV-HCC from patients with CHB or HBV-LC than AFP or PIVKA-II alone [area under the curve (AUC), 0.922 (95% CI, 0.908-0.935), sensitivity 88.3% and specificity 85.1% for the training cohort; 0.902 (95% CI, 0.875-0.929), 87.8%, and 81.0%, respectively, for the validation cohort]. The nomogram including AFP, PIVKA-II, age, and sex performed well in predicting HBV-HCC with good calibration and discrimination [AUC, 0.941 (95% CI, 0.929-0.952)] and was validated in the validation cohort [AUC, 0.931 (95% CI, 0.909-0.953)]. CONCLUSIONS: Our results demonstrated that a web-based calculator including age, sex, AFP, and PIVKA-II accurately predicted the presence of HCC in patients with CHB. CLINICALTRIALSGOV IDENTIFIER: NCT03047603.

Machine Learning to Predict the Likelihood of Acute Myocardial Infarction.

BACKGROUND: Variations in cardiac troponin concentrations by age, sex, and time between samples in patients with suspected myocardial infarction are not currently accounted for in diagnostic approaches. We aimed to combine these variables through machine learning to improve the assessment of risk for individual patients. METHODS: A machine learning algorithm (myocardial-ischemic-injury-index [MI3]) incorporating age, sex, and paired high-sensitivity cardiac troponin I concentrations, was trained on 3013 patients and tested on 7998 patients with suspected myocardial infarction. MI3 uses gradient boosting to compute a value (0-100) reflecting an individual's likelihood of a diagnosis of type 1 myocardial infarction and estimates the sensitivity, negative predictive value, specificity and positive predictive value for that individual. Assessment was by calibration and area under the receiver operating characteristic curve. Secondary analysis evaluated example MI3 thresholds from the training set that identified patients as low risk (99% sensitivity) and high risk (75% positive predictive value), and performance at these thresholds was compared in the test set to the 99th percentile and European Society of Cardiology rule-out pathways. RESULTS: Myocardial infarction occurred in 404 (13.4%) patients in the training set and 849 (10.6%) patients in the test set. MI3 was well calibrated with a very high area under the receiver operating characteristic curve of 0.963 [0.956-0.971] in the test set and similar performance in early and late presenters. Example MI3 thresholds identifying low- and high-risk patients in the training set were 1.6 and 49.7, respectively. In the test set, MI3 values were <1.6 in 69.5% with a negative predictive value of 99.7% (99.5-99.8%) and sensitivity of 97.8% (96.7-98.7%), and were ≥49.7 in 10.6% with a positive predictive value of 71.8% (68.9-75.0%) and specificity of 96.7% (96.3-97.1%). Using these thresholds, MI3 performed better than the European Society of Cardiology 0/3-hour pathway (sensitivity, 82.5% [74.5-88.8%]; specificity, 92.2% [90.7-93.5%]) and the 99th percentile at any time point (sensitivity, 89.6% [87.4-91.6%]); specificity, 89.3% [88.6-90.0%]). CONCLUSIONS: Using machine learning, MI3 provides an individualized and objective assessment of the likelihood of myocardial infarction, which can be used to identify low- and high-risk patients who may benefit from earlier clinical decisions. CLINICAL TRIAL REGISTRATION: URL: https://www.anzctr.org.au. Unique identifier: ACTRN12616001441404.

Global Adoption of High-Sensitivity Cardiac Troponins and the Universal Definition of Myocardial Infarction.

BACKGROUND: The universal definition of myocardial infarction (UDMI) standardizes the approach to the diagnosis and management of myocardial infarction. High-sensitivity cardiac troponin testing is recommended because these assays have improved precision at low concentrations, but concerns over specificity may have limited their implementation. METHODS: We undertook a global survey of 1902 medical centers in 23 countries evenly distributed across 5 continents to assess adoption of key recommendations from the UDMI. Respondents involved in the diagnosis and management of patients with suspected acute coronary syndrome completed a structured telephone questionnaire detailing the primary biomarker, diagnostic thresholds, and clinical pathways used to identify myocardial infarction. RESULTS: Cardiac troponin was the primary diagnostic biomarker at 96% of surveyed sites. Only 41% of centers had adopted high-sensitivity assays, with wide variation from 7% in North America to 60% in Europe. Sites using high-sensitivity troponin more frequently used serial sampling pathways (91% vs 78%) and the 99th percentile diagnostic threshold (74% vs 66%) than sites using previous-generation assays. Furthermore, high-sensitivity institutions more often used earlier serial sampling (≤3 h) and accelerated diagnostic pathways. Fewer than 1 in 5 high-sensitivity sites had adopted sex-specific thresholds (18%). CONCLUSIONS: There has been global progress toward the recommendations of the UDMI, particularly in the use of the 99th percentile diagnostic threshold and serial sampling. However, high-sensitivity assays are still used by a minority of sites, and sex-specific thresholds by even fewer. Additional efforts are required to improve risk stratification and diagnosis of patients with myocardial infarction.

High-Sensitivity Cardiac Troponin I Levels in Normal and Hypertensive Pregnancy.

PURPOSE: The purpose of this study was to examine the association of circulating concentrations of high-sensitivity cardiac troponin I (hs-cTn) in the various trimesters of pregnancy in patients with and without hypertension. METHODS: This was a prospective cross-sectional study of pregnant and postnatal women aged between 18-35 years with no coexisting diseases. Serum samples were analysed for hs-TnI. RESULTS: A total of 880 women (mean age = 29.1 years [standard deviation = 5.1 years]) were recruited with 129 (14%), 207 (24%), and 416 (47%) patients in the first, second, and third trimesters, respectively. Ninety (10%) participants were recruited in the postnatal period. During pregnancy 28 (3%) patients were classified as having pregnancy-induced hypertension and 10 (1%) as preeclampsia. High-sensitivity cardiac troponin I was measurable in 546 (62%) participants with a median of 1 ng/L (range 0 to 783 ng/L). Troponin concentrations were above the 99th percentile in 19 (2%) individuals. Patients with pregnancy-induced hypertension and preeclampsia had higher concentrations of hs-TnI (median 11 ng/L [interquartile range (IQR) 6 to 22 ng/L] vs 12ng/L [IQR 3 to 98 ng/L] vs 1 ng/L [IQR 0 to 1 ng/L]). In logistic regression modeling hs-cTnI concentration remained an independent predictor of pregnancy-induced hypertension or preeclampsia in both unadjusted and adjusted models (odds ratio 9.3 [95% confidence interval 5.8 to 16.3] and 11.5 [95% confidence interval 6.3 to 24.1], respectively, per doubling of hs-TnI concentrations). CONCLUSIONS: Cardiac troponin measured using a high-sensitivity assay is quantifiable in the majority of young pregnant women with 2% of individuals having concentration above the 99th percentile sex-specific threshold. Patients with pregnancy-induced hypertension or preeclampsia had higher cardiac troponin concentrations. Cardiac troponin was a strong independent predictor of pregnancy-induced hypertension or preeclampsia in pregnant and postnatal women.

Comparison of the Association Between High-Sensitivity Troponin I and Adverse Cardiovascular Outcomes in Patients With Versus Without Chronic Kidney Disease.

It is unknown whether the association of high-sensitivity troponin I (hs-TnI) with adverse cardiovascular outcomes varies by the presence of chronic kidney disease (CKD). We examined the association of hs-TnI with adverse cardiovascular outcomes in those with and without CKD in 4,107 (mean age, 64 years; 63% men; 20% black) patients from the Emory Cardiovascular Biobank who underwent coronary angiography. CKD (n = 1,073) was defined as estimated glomerular filtration rate <60 ml/min/1.73 m2 or urine albumin/creatinine ratio >30 mg/g at baseline. Cox regression was used to compute hazard ratios (HR) for the association between hs-TnI levels (per doubling of hs-TnI: log2[hs-TnI] + 1) and death, cardiovascular death, and major adverse cardiac events (MACE), separately. Hs-TnI was a stronger predictor of death (CKD: HR 1.23, 95% confidence interval [CI] 1.15 to 1.31; no CKD: HR 1.11, 95% CI 1.05 to 1.17, p-interaction = 0.023), cardiovascular death (CKD: HR 1.24, 95% CI 1.14 to 1.34; no CKD: HR 1.15, 95% CI 1.07 to 1.22, p-interaction = 0.12), and MACE (CKD: HR 1.18, 95% CI 1.11 to 1.25; no CKD: HR 1.11, 95% CI 1.06 to 1.16, p-interaction = 0.095) in CKD compared with non-CKD. The association between hs-TnI and death in patients with CKD was stronger for patients without obstructive coronary artery disease (no obstructive coronary artery disease: HR 1.60, 95% CI 1.27 to 2.01; obstructive coronary artery disease: HR 1.19, 95% CI 1.11 to 1.27, p-interaction = 0.041). In conclusion, hs-TnI is a stronger predictor of adverse cardiovascular events in patients who have CKD than those without, even in the absence of obstructive coronary artery disease. Hs-TnI may identify CKD patients who are high risk for adverse cardiovascular outcomes in whom aggressive risk factor modification strategies are warranted.

Serum ARCHITECT PIVKA-II reference interval in healthy Chinese adults: Sub-analysis from a prospective multicenter study.

BACKGROUND: Protein induced by vitamin K absence or antagonist-II (PIVKA-II) has been widely used as a biomarker for liver cancer diagnosis in Japan for decades. However, the reference intervals for serum ARCHITECT PIVKA-II have not been established in the Chinese population. Thus, this study aimed to measure serum PIVKA-II levels in healthy Chinese subjects. METHODS: This is a sub-analysis from the prospective, cross-sectional and multicenter study (ClinicalTrials.gov Identifier: NCT03047603). A total of 892 healthy participants (777 Han and 115 Uygur) with complete health checkup results were recruited from 7 regional centers in China. Serum PIVKA-II level was measured by ARCHITECT immunoassay. All 95% reference ranges were estimated by nonparametric method. RESULTS: The distribution of PIVKA-II values showed significant difference with ethnicity and sex, but not age. The 95% reference range of PIVKA-II was 13.62-40.38 mAU/ml in Han Chinese subjects and 15.16-53.74 mAU/ml in Uygur subjects. PIVKA-II level was significantly higher in males than in females (P < 0.001). The 95% reference range of PIVKA-II was 15.39-42.01 mAU/ml in Han males while 11.96-39.13 mAU/ml in Han females. CONCLUSIONS: The reference interval of serum PIVKA-II on the Architect platform was established in healthy Chinese adults. This will be valuable for future clinical and laboratory studies performed using the Architect analyzer. Different ethnic backgrounds and analytical methods underline the need for redefining the reference interval of analytes such as PIVKA-II, in central laboratories in different countries.

High-Sensitivity Troponin I Levels and Coronary Artery Disease Severity, Progression, and Long-Term Outcomes.

BACKGROUND: The associations between high-sensitivity troponin I (hsTnI) levels and coronary artery disease (CAD) severity and progression remain unclear. We investigated whether there is an association between hsTnI and angiographic severity and progression of CAD and whether the predictive value of hsTnI level for incident cardiovascular outcomes is independent of CAD severity. METHODS AND RESULTS: In 3087 patients (aged 63±12 years, 64% men) undergoing cardiac catheterization without evidence of acute myocardial infarction, the severity of CAD was calculated by the number of major coronary arteries with ≥50% stenosis and the Gensini score. CAD progression was assessed in a subset of 717 patients who had undergone ≥2 coronary angiograms >3 months before enrollment. Patients were followed up for incident all-cause mortality and incident cardiovascular events. Of the total population, 11% had normal angiograms, 23% had nonobstructive CAD, 20% had 1-vessel CAD, 20% had 2-vessel CAD, and 26% had 3-vessel CAD. After adjusting for age, sex, race, body mass index, smoking, hypertension, diabetes mellitus history, and renal function, hsTnI levels were independently associated with the severity of CAD measured by the Gensini score (log 2 ß=0.31; 95% confidence interval, 0.18-0.44; P<0.001) and with CAD progression (log 2 ß=0.36; 95% confidence interval, 0.14-0.58; P=0.001). hsTnI level was also a significant predictor of incident death, cardiovascular death, myocardial infarction, revascularization, and cardiac hospitalizations, independent of the aforementioned covariates and CAD severity. CONCLUSIONS: Higher hsTnI levels are associated with the underlying burden of coronary atherosclerosis, more rapid progression of CAD, and higher risk of all-cause mortality and incident cardiovascular events. Whether more aggressive treatment aimed at reducing hsTnI levels can modulate disease progression requires further investigation.