Value Of Novel Biomarkers Research Articles

Emerging biomarkers for the diagnosis and monitoring of urothelial carcinoma.

Urothelial carcinoma (UC) arises extensively from the renal pelvis, ureter, urinary bladder, and urethra. UC represents a clinical and social challenge because of its incidence, post-treatment recurrence rate, and prognosis. Combinations of urine cytology, cystoscopy, and conventional imaging such as computed tomography are currently used for diagnosis and monitoring modalities of UC. Both the poor diagnostic accuracy of urine cytology and poor cost performance of cystoscopy and conventional imaging modalities emphasize the urgent need for advancement in clinical guidance for UC. Urine- and blood-based biomarkers for detection of UC of the bladder and upper urinary tract represent a considerable research area. Biomarkers can help to improve UC diagnosis with the aim of replacing cystoscopy and other imaging examinations in future and may enable individualizing risk stratification regarding therapy and follow-up. Over the decades, numerous studies have focused on the potential application of biomarkers for UC, including urine, circulating tumor DNA, RNAs, proteins, and extracellular vesicles. Although some biomarkers such as ImmunoCyt/uCyt+, UroVysion, NMP-22, bladder tumor antigen, CxBladder, and Xpert Bladder Cancer are currently available in clinical practice, few biomarkers achieve high sensitivity and specificity. Emerging biomarkers are continuously developed and reported in medical journals. However, there is a significant lack on following external validation using different cohorts. The positive results are needed to be confirmed by more studies with large-scale cohorts and long follow-up periods to prove the true value of novel biomarkers, followed by their adoption in clinical practice. The present paper provides an overview of the evidence based on high-impact studies regarding urine- and blood-based biomarkers and their clinical applications in bladder cancer and upper tract UC.

Diagnostic value of novel biomarkers for heart failure : Ameta-analysis.

The present meta-analysis examined the diagnostic value of novel biomarkers for heart failure (HF), including copeptin, galectin-3, hs-cTnT, MR-proANP, MR-proADM, and ST2. English (EMBASE, Cochrane, and PubMed) and Chinese (Wanfang data, CNKI, SinoMed) databases were searched to identify suitable studies that were published before 1December 2016. Data were extracted using standard forms. Pooled diagnostic statistics were calculated using DerSimonian-Laird random-effects models. The analysis comprised 45 studies. The pooled sensitivities of all biomarkers were 0.80-0.86, along with pooled specificities of 0.60-0.82, positive predictive values (PPVs) of 0.52-0.80, and negative predictive values (NPVs) of 0.70-0.87. Among them, hs-cTnT had the highest sensitivity (0.86 [95% CI: 0.84-0.88]), specificity (0.82 [95% CI: 0.79-0.84]), PPV (0.80 [95% CI: 0.77-0.83]), and NPV (0.87 [95% CI: 0.85-0.89]), while MR-proADM had the lowest sensitivity (0.80 [95% CI: 0.75-0.84]), specificity (0.60 [95% CI: 0.56-0.64]), and PPV (0.52 [95% CI: 0.47-0.56]). Copeptin had the lowest NPV (0.70 [95% CI: 0.66-0.74]). The positive likelihood ratio (LR+) of all biomarkers ranged from 1.97 to 3.21, and the negative likelihood ratio (LR-) from 0.20 to 0.36. MR-proADM had the lowest LR+ and highest LR-; galectin-3 had the highest LR+ and MR-proANP had the lowest LR-. The area under the curve (AUC) was as low as 0.68 for MR-proADM, while AUCs for the other biomarkers ranged from 0.83 to 0.89. The overall diagnostic accuracy of copeptin, galectin-3, hs-cTnT, MR-proANP, and ST2 was relatively good. MR-proADM had apoor capacity to confirm or exclude HF. Improving the diagnostic accuracy of HF by acombination of biomarkers could be considered in the future.

Predictive value of novel biomarkers for acute kidney injury in critically ill patients at Assiut University Hospitals

Introduction Acute kidney injury (AKI) is a clinical problem in critically ill patients, which is associated with adverse outcomes. There is a persistent need to find reliable biomarkers for the early diagnosis and prediction of AKI. Many genes are upregulated in the damaged kidneys, with the subsequent protein products appearing in the urine. Urinary liver-type fatty acid-binding protein (uL-FABP) and urinary kidney injury molecule-1 (uKIM-1) are among the promising upregulated biomarkers. Aim To assess the ability of uL-FABP in comparison with kidney injury molecule-1 for early prediction of AKI in adult critically ill patients. Patients and methods A cohort study was conducted enrolling 100 critically ill patients admitted to medical critical care units (CCUs) who had risk factors for developing AKI. Acute Physiology and Chronic Health Evaluation II score was calculated on admission. Serum creatinine was measured on admission and thereafter daily till the seventh day of CCU stay. Urine samples for uL-FABP and uKIM-1 assay were collected at the time of CCU admission, on day 3, and on day 5. Results Among critically ill patients, 60% had AKI diagnosed mostly on the second (53.3%) and third (40%) day of CCU admission. There was a significant difference in Acute Physiology and Chronic Health Evaluation II score (P Conclusion UKIM-1 was a sensitive and specific biomarker (superior to uL-FABP) for the prediction of AKI in critically ill patients.

‘Progressive MS – macro views’: The need for novel clinical trial paradigms to enable drug development for progressive MS

This article outlines the principal challenges to establish a standard phase-2 approach for progressive multiple sclerosis (PMS) and presents referring strategies to accelerate the registration process via a guidance approved by regulatory agencies. Accordingly, the contribution of ‘big datasets’ for a better understanding of the natural history of primary-progressive multiple sclerosis (PPMS) and secondary-progressive multiple sclerosis (SPMS) and of their prognostic factors and the value of novel biomarkers are discussed. The establishment of new industry–academic initiatives, such as independent consortia under the umbrella of Progressive MS Alliance (PMSA), with the endorsement of MS organizations and Scientific Societies (e.g. European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS)) may be crucial to overcome some of the current challenges. Within this frame, the continuous interaction with regulatory agencies is instrumental for the formal validation of the many developments suitable to improve clinical trialling in PMS.

Novel biomarkers predicting cardiac function after acute myocardial infarction.

Measurement of biomarkers provides a cost-effective and widely available method to estimate cardiac dysfunction and clinical outcome of patients with acute myocardial infarction (AMI). PubMed entries with terms 'myocardial infarction' and the respective biomarker. Cardiac troponins and natriuretic peptides are closely related to left ventricular dysfunction and the occurrence of adverse clinical events following AMI. The incremental value of novel biomarkers is controversial. The combination of traditional and novel biomarkers might further improve risk stratification of patients with AMI. We searched all entries on the PubMed database with the MeSH terms 'myocardial infarction' and 'cardiac troponins', 'natriuretic peptides', 'copeptin', galectin-3', 'corin', 'fetuin-A', 'adiponectin' and 'microRNA'.

16-76: Assessing the value of novel biomarkers in the prediction of clinical outcomes after cardiac resynchronization therapy

Purpose: Cardiac resynchronization therapy (CRT) improves mortality in chronic heart failure (HF) patients with ventricular dyssynchrony, although some patients do not improve clinically and pass away unexpectedly despite correct CRT indications. In this study we investigated a set of novel heart failure biomarkers associated with various pathways of heart failure pathophysiology, our purpose was to assess their ability to predict clinical outcomes after CRT. Methods: We enrolled 136 consecutive chronic HF patients undergoing CRT implantation to our prospective single-center observational study. We measured the plasma levels of fractalkine, pentraxin-3, hepatocyte growth factor, CA-125 and MMP-9 before and six months after CRT with commercially available assays. The primary endpoint of the study was five year all-cause mortality, we considered six month reverse remodelling defined as at least 15% decrease in end systolic volume as secondary end-point. Results: During five years of follow-up 58 patients (43%) deceased, 66 were considered as non-responder. From the investigated baseline clinical variables age, NYHA class III-IV and NT-proBNP were predictive of reverse remodelling. Five years all-cause mortality was significantly related to left brundle branch block, beta blocker therapy and increasing NT-proBNP levels. After adjusting to all significant baseline parameters HGF was the only independent predictor of reverse remodelling (OR: 0.54, CI for OR: 0.32-0.90, p = 0.01) and 5-year mortality (HR: 1.35, CI for HR: 1.11-1.64, p = 0.003). The reclassification analyses revealed that HGF reached a reclassification improvement of 39 % [NRI= 0.39 (0.07-0-71), p = 0.01] in reverse remodeling and 69 % [NRI= 0.69 (0.39-0.99), p < 0.0001] in 5-year mortality prediction. Moreover, discrimination development was 3 % [IDI= 0.03 (0.00-0.06), p = 0.02] in reverse remodelling and 6% [IDI = 0.06 (0.02-0.11) in 5-year mortality prediction. Conclusion: Of all studied biomarkers HGF, the pleiotropic cardioprotective agent was the only independent predictor of clinical outcomes in HF patients undergoing CRT, reclassification analyses showed that it may be useful in refining patient selection.

The incremental prognostic and clinical value of multiple novel biomarkers in heart failure.

In recent years there has been an increase in the number of biomarkers in heart failure (HF). The clinical role for these novel biomarkers in combination is not clear. The following novel biomarkers were measured from 628 patients recently hospitalized with decompensated HF; mid-regional pro-adrenomedullin (MR-proADM), mid-regional pro-atrial natriuretic peptide (MR-proANP), copeptin, high-sensitivity cardiac troponin T (hs-cTnT), ST2, galectin-3, cystatin C, combined free light chains (cFLC) and high sensitivity C-reactive protein (hsCRP). The incremental prognostic value of these novel biomarkers was evaluated within an extensive model containing established predictors of mortality. During a mean (SD) follow-up of 3.2 (1.5) years, 290 (46%) patients died. Elevated concentrations of all novel biomarkers were associated with an increased unadjusted risk of mortality but only two-thirds were independent predictors following multivariable analysis. Using dichotomized cut-points from receiver operating characteristic analysis, MR-proADM, hs-cTnT, cFLC, hsCRP, and ST2 remained independent predictors of mortality. Further dichotomization into low (0-2 elevated biomarkers) or high (at least three of the five biomarkers elevated) risk groups provided greatest incremental prognostic value (hazard ratio 2.20, 95% confidence interval 1.37-3.54; P = 0.001) and improved the performance of the model (C-statistic 0.730 from 0.721, net reclassification index 32.5%). The novel biomarkers included in this study added little, if any, incremental prognostic value on their own to a model containing established predictors of mortality. However, following dichotomization, five of the novel biomarkers provided incremental prognostic value. There was a clear gradient in the risk of death with increasing numbers of elevated novel biomarkers, with the presence of at least three identifying patients at greatest risk of mortality.

Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer

Pancreatic cancer (PC) has a high mortality rate because it is usually diagnosed late. Glycosylation of proteins is known to change in tumor cells during the development of PC. The objectives of this study were to identify and validate the diagnostic value of novel biomarkers based on N-glycomic profiling for PC. In total, 217 individuals including subjects with PC, pancreatitis, and healthy controls were divided randomly into a training group (n=164) and validation groups (n=53). Serum N-glycomic profiling was analyzed by DSA-FACE. The diagnostic model was constructed based on N-glycan markers with logistic stepwise regression. The diagnostic performance of the model was assessed further in validation cohort. The level of total core fucose residues was increased significantly in PC. Two diagnostic models designated GlycoPCtest and PCmodel (combining GlycoPCtest and CA19-9) were constructed to differentiate PC from normal. The area under the receiver operating characteristic curve (AUC) of PCmodel was higher than that of CA19-9 (0.925 vs. 0.878). The diagnostic models based on N-glycans are new, valuable, noninvasive alternatives for identifying PC. The diagnostic efficacy is improved by combined GlycoPCtest and CA19-9 for the discrimination of patients with PC from healthy controls.

No Added Value of Novel Biomarkers in the Diagnostic Assessment of Patients Suspected of Acute Coronary Syndrome.

BackgroundDespite the availability of high-sensitive troponin (hs-cTnT), there is still room for improvement in the diagnostic assessment of patients suspected of acute coronary syndrome (ACS). Apart from serial biomarker testing, which is time-consuming, novel biomarkers like copeptin have been proposed to expedite the early diagnosis of suspected ACS in addition to hs-cTnT. We determined whether placenta derived growth factor (PlGF), soluble Fms-like tyrosine kinase 1 (sFlt-1), myoglobin, N-terminal prohormone B-type Natriuretic Peptide (NT-proBNP), growth-differentiation factor 15 (GDF-15) and copeptin improved early assessment of chest pain patients.MethodsThis prospective, single centre diagnostic FAME-ER study included patients presenting to the ED with symptoms suggestive of ACS. Blood was collected to measure biomarkers, notably, hs-cTnT was retrospectively assessed. Added value of markers was judged by increase in AUC using multivariable logistic regression.ResultsOf 453 patients enrolled, 149 (33%) received a final diagnosis of ACS. Hs-cTnT had the highest diagnostic value in both univariable and multivariable analysis. PPVs of the biomarkers ranged from 23.5% (PlGF) to 77.9% (hs-cTnT), NPVs from 67.0% (PlGF) to 86.4% (hs-cTnT). Only myoglobin yielded diagnostic value in addition to clinical symptoms and electrocardiography (ECG) (AUC of clinical model 0.80) with AUC of 0.84 (p<0.001). However, addition of hs-cTnT was superior (AUC 0.89, p<0.001). Addition of the biomarkers to our clinical model and hs-cTnT did not or only marginally (GDF-15) improved diagnostic performance.ConclusionWhen assessing patients suspected of ACS, only myoglobin had added diagnostic value beyond clinical symptoms and ECG. However, when combined with hs-cTnT, it yields no additional diagnostic value. PlGF, sFlt-1, NT-proBNP, GDF-15 and copeptin had no added value to the clinical model or hs-cTnT.

Long-Term Prognosis After Coronary Artery Calcification Testing in Asymptomatic Patients: A Cohort Study.

The extent of coronary artery calcification (CAC) and near-term adverse clinical outcomes are strongly related through 5 years of follow-up. To describe the ability of CAC scores to predict long-term mortality in persons without symptoms of coronary artery disease. Observational cohort. Single-center, outpatient cardiology laboratory. 9715 asymptomatic patients. Coronary artery calcification scoring and binary risk factor data were collected. The primary end point was time to all-cause mortality (median follow-up, 14.6 years). Univariable and multivariable Cox proportional hazards models were used to compare survival distributions. The net reclassification improvement statistic was calculated. In Cox models adjusted for risk factors for coronary artery disease, the CAC score was highly predictive of all-cause mortality (P<0.001). Overall 15-year mortality rates ranged from 3% to 28% for CAC scores from 0 to 1000 or greater (P<0.001). The relative hazard for all-cause mortality ranged from 1.68 for a CAC score of 1 to 10 (P<0.001) to 6.26 for a score of 1000 or greater (P<0.001). The categorical net reclassification improvement using cut points of less than 7.5% to 22.5% or greater was 0.21 (95% CI, 0.16 to 0.32). Data collection was limited to a single center with generalizability limitations. Only binary risk factor data were available, and CAC was only measured once. The extent of CAC accurately predicts 15-year mortality in a large cohort of asymptomatic patients. Long-term estimates of mortality provide a unique opportunity to examine the value of novel biomarkers, such as CAC, in estimating important patient outcomes. None.

Prognostic value of novel biomarkers compared with detailed biochemical evaluation in patients with heart failure

The assessment of prognosis is crucial for the clinical management of patients with heart failure (HF). The aim of the study was to evaluate the usefulness of novel biomarkers for the assessment of prognosis in patients with HF, compared with a detailed assessment based on routine laboratory tests. The study included 179 patients with HF. In all patients, routine laboratory tests were performed and selected biomarkers were measured (N-terminal pro-B-type natriuretic peptide, high-sensitivity C-reactive protein, growth hormone, myeloperoxidase, metaloproteinase 9, procollagen type III, soluble toll like receptor 2, insulin growth factor, and neutrophil gelatinase-associated lipocain). The primary endpoint was death or urgent heart transplantation, while the secondary endpoints encompassed primary endpoints plus cardioverter intervention or hospitalization for HF. The mean age of the study group was 52.5 years (91% were men). Most patients had advanced HF. During a 6-month follow-up, 21 primary endpoints and 63 secondary endpoints were recorded. A multiple regression analysis showed that of all laboratory variables and biomarkers, only uric acid and sodium were independent predictors of primary endpoints, and only estimated glomerular filtration rate had a predictive value for secondary endpoints. None of the biomarkers were a significant prognostic factor in the study population. Biomarkers do not outweigh the value of standard laboratory tests. Routine laboratory workup allows to assess multiorgan damage and provides the most significant prognostic data. Biochemical tests should remain the gold standard for the assessment of prognosis in patients with HF.

The Added Value of Percentage of Free to Total Prostate-specific Antigen, PCA3, and a Kallikrein Panel to the ERSPC Risk Calculator for Prostate Cancer in Prescreened Men

BackgroundProstate-specific antigen (PSA) testing has limited accuracy for the early detection of prostate cancer (PCa). ObjectiveTo assess the value added by percentage of free to total PSA (%fPSA), prostate cancer antigen 3 (PCA3), and a kallikrein panel (4k-panel) to the European Randomised Study of Screening for Prostate Cancer (ERSPC) multivariable prediction models: risk calculator (RC) 4, including transrectal ultrasound, and RC 4 plus digital rectal examination (4+DRE) for prescreened men. Design, setting, and participantsParticipants were invited for rescreening between October 2007 and February 2009 within the Dutch part of the ERSPC study. Biopsies were taken in men with a PSA level ≥3.0 ng/ml or a PCA3 score ≥10. Additional analyses of the 4k-panel were done on serum samples. Outcome measurements and statistical analysisOutcome was defined as PCa detectable by sextant biopsy. Receiver operating characteristic curve and decision curve analyses were performed to compare the predictive capabilities of %fPSA, PCA3, 4k-panel, the ERSPC RCs, and their combinations in logistic regression models. Results and limitationsPCa was detected in 119 of 708 men. The %fPSA did not perform better univariately or added to the RCs compared with the RCs alone. In 202 men with an elevated PSA, the 4k-panel discriminated better than PCA3 when modelled univariately (area under the curve [AUC]: 0.78 vs 0.62; p=0.01). The multivariable models with PCA3 or the 4k-panel were equivalent (AUC: 0.80 for RC 4+DRE). In the total population, PCA3 discriminated better than the 4k-panel (univariate AUC: 0.63 vs 0.56; p=0.05). There was no statistically significant difference between the multivariable model with PCA3 (AUC: 0.73) versus the model with the 4k-panel (AUC: 0.71; p=0.18). The multivariable model with PCA3 performed better than the reference model (0.73 vs 0.70; p=0.02). Decision curves confirmed these patterns, although numbers were small. ConclusionsBoth PCA3 and, to a lesser extent, a 4k-panel have added value to the DRE-based ERSPC RC in detecting PCa in prescreened men. Patient summaryWe studied the added value of novel biomarkers to previously developed risk prediction models for prostate cancer. We found that inclusion of these biomarkers resulted in an increase in predictive ability.

Key concepts and limitations of statistical methods for evaluating biomarkers of kidney disease.

Interest in developing and using novel markers of kidney injury is increasing. To maintain scientific rigour in these endeavors, a comprehensive understanding of statistical methodology is required to rigorously assess the incremental value of novel biomarkers in existing clinical risk prediction models. Such knowledge is especially relevant, because no single statistical method is sufficient to evaluate a novel biomarker. In this review, we highlight the strengths and limitations of various traditional and novel statistical methods used in the literature for biomarker studies and use biomarkers of AKI as examples to show limitations of some popular statistical methods.

The Xu′s chart for prostate biopsy: a visual presentation of the added value of biomarkers to prostate-specific antigen for estimating detection rates of prostate cancer

Elevated serum prostate-specific antigen (PSA) level is the primary indication for prostate biopsy for detection of prostate cancer (PCa) in the modern era. The detection rate of PCa from biopsy is typically below 30%, especially among patients with PSA levels at 4–10 ng ml−1. In the past several years, additional biomarkers, such as Prostate Health Index, PCA3 and genetic risk score (GRS) derived from multiple PCa risk-associated single nucleotide polymorphisms (SNPs) have been shown to provide added value to PSA in discriminating prostate biopsy outcomes. However, the adoption rate of these novel biomarkers in clinics is low, largely due to poor understanding of the added value of novel biomarkers. To address this matter, we developed a chart to visually present (i) expected detection rates of PCa from biopsy with respect to PSA levels, and more importantly, (ii) a range of PCa detection rates at the same PSA levels when novel biomarkers are considered. This chart, called the Xu's chart for prostate biopsy, is not a formal risk prediction model; rather, a simple visual tool for urologists to communicate with their patients an initial evaluation of PCa detection rate based on their PSA levels and a possible recommendation for additional biomarkers. A more comprehensive evaluation of PCa risk using existing risk assessment tools such as nomograms can be followed once additional biomarkers are measured. The current version of the chart is only a prototype and should be further developed to include the detection rate of aggressive PCa, and validated in larger studies.

Relation of genetic profile and novel circulating biomarkers with coronary plaque phenotype as determined by intravascular ultrasound: rationale and design of the ATHEROREMO-IVUS study

The European Collaborative Project on Inflammation and Vascular Wall Remodeling in Atherosclerosis - Intravascular Ultrasound (ATHEROREMO-IVUS) study aims to investigate the relations of genetic profile and novel circulating biomarkers with coronary plaque phenotype and vulnerability as determined by intravascular ultrasound (IVUS). ATHEROREMO-IVUS is a prospective, observational cohort study of 846 patients with stable angina pectoris or acute coronary syndrome (ACS) who are referred for coronary angiography. Prior to the catheterisation procedure, blood samples are drawn for biomarker measurements and genetic analyses. During the catheterisation procedure, IVUS is performed in a non-culprit coronary artery. The primary endpoint is the presence of vulnerable plaque as determined by IVUS virtual histology. Secondary endpoints include the incidence of major adverse cardiac events during long-term follow-up. Results from ATHEROREMO-IVUS are expected to improve our knowledge of the role of genetic profile and circulating biomarkers in relation to the development of atherosclerosis and vulnerable plaques. Assessment and early validation of the prognostic value of novel biomarkers and intracoronary imaging techniques will be performed. (ClinicalTrials.gov number: NCT01789411).

Acute kidney injury after cardiac arrest of ventricular fibrillation and asphyxiation swine model

PurposesThe purposes of the study are to investigate the renal function in ventricular fibrillation (VF) and asphyxiation cardiac arrest in a swine model and to estimate the value of novel biomarkers in the acute kidney injury (AKI) after cardiac arrest. MethodThirty-two healthy inbred Wu-Zhi-Shan miniature piglets were randomized into 2 groups (n = 16 per group). Cardiac arrest was induced by programmed electric stimulation and clamping the endotracheal tube in the VF group and asphyxiation group, respectively. Cardiopulmonary resuscitation was done for return of spontaneous circulation (ROSC). ResultsOne hundred percent (16/16) ROSC was observed in the VF group, and 50% (8/16) in the asphyxiation group (P < .01). All AKI biomarkers elevated significantly after ROSC. The novel biomarkers changed much earlier than the creatinine. The concentration of novel biomarkers in the asphyxiation group was higher than the VF group. Live animals had an oliguria and developed AKI. Characteristic morphological injuries in renal tissues were observed under light microscope and transmission electron microscope and were more serious in the asphyxiation group. ConclusionsAcute kidney injury at early stage of postresuscitation is common in different causes of cardiac arrest. Asphyxiation has more severe kidney injury and gets worse prognosis.

The potential of novel biomarkers to improve risk prediction of type 2 diabetes

The incidence of type 2 diabetes can be reduced substantially by implementing preventive measures in high-risk individuals, but this requires prior knowledge of disease risk in the individual. Various diabetes risk models have been designed, and these have all included a similar combination of factors, such as age, sex, obesity, hypertension, lifestyle factors, family history of diabetes and metabolic traits. The accuracy of prediction models is often assessed by the area under the receiver operating characteristic curve (AROC) as a measure of discrimination, but AROCs should be complemented by measures of calibration and reclassification to estimate the incremental value of novel biomarkers. This review discusses the potential of novel biomarkers to improve model accuracy. The range of molecules that serve as potential predictors of type 2 diabetes includes genetic variants, RNA transcripts, peptides and proteins, lipids and small metabolites. Some of these biomarkers lead to a statistically significant increase of model accuracy, but their incremental value currently seems too small for routine clinical use. However, only a fraction of potentially relevant biomarkers have been assessed with regard to their predictive value. Moreover, serial measurements of biomarkers may help determine individual risk. In conclusion, current risk models provide valuable tools of risk estimation, but perform suboptimally in the prediction of individual diabetes risk. Novel biomarkers still fail to have a clinically applicable impact. However, more efficient use of biomarker data and technological advances in their measurement in clinical settings may allow the development of more accurate predictive models in the future.

Predictive value of novel biomarkers for response to medical treatment in systolic heart failure

Purpose: Although large scale clinical trials have demonstrated the efficacy and safety of pharmacological treatment for systolic heart failure (HF), HF treatment non-response was a common clinical observation. We sought to evaluate the role of HF biomarkers in prediction of HF treatment response. Methods: The participating sites from 3 countries have recruited a total of 646 patients with systolic HF, of which 299 patients have completed 6-months follow-up. HF treatment was defined as death, re-hospitalization for HF, and/or reduction of left ventricular end-systolic volume of <10% in 6 months despite standard HF medication therapy. 25 biomarkers related to inflammation, fibrosis or myocyte damage were compared between Responders and Non-responders. Results: Of 299 patients enrolled during the reporting period, 169 (53.5%) were HF treatment while 130 (46.5%) were 5 of the 25 biomarkers including N-terminal prohormone of Brain Natriuretic Peptide (NT-proBNP), ST2 receptor, Midregional pro-adrenomedullin (MRproADM), Growth differentiation factor 15 (GDF15) and High sensitivity Troponin T (Hs-TNT) were much higher in Non-responders than in Responders. Repeated-measure ANOVA showed differences in the serial changes in response to HF treatment for NT-proBNP, ST2 receptor and MRproADM between Responders and Non-Responders (All P<0.05). (Figure) In multiple regression analysis, Hs-TNT [Odds Ratios (OR): 1.004, 95% Confidential Interval (CI) 1.000-1.008, p=0.04] and ST2 receptor (OR 1.007, 95% CI 1.000-1.013, p=0.04) were independent predictors of HF treatment Non-responders. ![Figure][1] Conclusions: Hs-TNT and ST2 receptor are potentially useful biomarkers to identify treatment in mid-term follow-up of HF patients. [1]: pending:yes

918 ADDED VALUE OF NOVEL BIOMARKERS IN TYPE 2 DIABETES PREDICTION

Objective: To summarize the literature assessing the added value of novel biomarkers for predicting the occurrence of type 2 diabetes Design: Systematic review and qualitative synthesis. Data Sources: MEDLINE and EMBASE databases searched from January 2000 to July 2011. Study selection: Published studies in English assessing the improvement of type 2 diabetes risk prediction subsequent to adding novel biomarkers to traditional risk factors in prediction models. Data Extraction: Independent, duplicate identification of studies, data extraction and quality assessment conducted by two reviewers using standardized forms, with discrepancies resolved by consensus or a third reviewer. Extracted data was on study methods and metrics used for evaluating the incremental predictive values of novel biomarkers. Results: We included 28 publications from 25 studies that assessed the incremental predictive ability of novel biomarkers. All the studies reported a change in the area under the receiver-operating characteristic curve, which was modest, ranging from 0 to 0.1, with claims of statistically significant improvement in eight studies. The net reclassification index was evaluated in seven studies, and ranged from -0.03% to 10.2% after inclusion of genetic markers in four studies (statistically significant in two cases), and from -0.5 % to 11.8% after inclusion of non-genetic markers in three studies (non-significant). The integrated discrimination index (0.0015 to 2.4) was reported in five studies, being statistical significant in only three of these. Conclusions: Currently known novel biomarkers do not significantly improve T2DM risk prediction above and beyond the ability of known traditional risk factors.

Comparison of the various lipid ratios and indices for risk assessment in patients of myocardial infarction

Coronary artery disease (CAD) has emerged as the major cause of morbidity and mortality among Asian Indians in the recent past. The following study was undertaken to assess the predictive value of novel biomarkers of dyslipidemia for risk assessment for CAD in the Indian population. The study group comprised of 100 clinically assessed patients of myocardial infarction and 100 age and sex matched healthy controls. Apolipoprotein-A (Apo-AI) and Apolipoprotein-B (Apo-B) were estimated and small dense LDL was derived mathematically. The cases showed significantly high levels of total serum cholesterol, triglycerides, LDL cholesterol, Apo-B, sdLDL, and non-HDL cholesterol. On carrying out multivariate regression analysis, Lp(a)/HDL ratio emerged as the best determinant of CAD risk The above data clearly underlines the role of these novel biomarkers in the risk assessment for CAD in the Indian context.