| scholarly article | Q13442814 |
| P50 | author | John Ioannidis | Q6251482 |
| Ioanna Tzoulaki | Q63378793 | ||
| P2093 | author name string | George Liberopoulos | |
| P2860 | cites work | Clinical Utility of Different Lipid Measures for Prediction of Coronary Heart Disease in Men and Women | Q57308696 |
| Improvement of Risk Prediction by Genomic Profiling: Reclassification Measures Versus the Area Under the Receiver Operating Characteristic Curve | Q57364788 | ||
| Evaluation of risk prediction updates from commercial genome-wide scans | Q57364888 | ||
| Prediction of Coronary Heart Disease Using Risk Factor Categories | Q22241923 | ||
| General and Abdominal Adiposity and Risk of Death in Europe | Q22250882 | ||
| Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III) | Q27860959 | ||
| A model to predict survival in patients with end-stage liver disease | Q28199900 | ||
| The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure<SUBTITLE>The JNC 7 Report</SUBTITLE> | Q28204197 | ||
| Use of multiple biomarkers to improve the prediction of death from cardiovascular causes | Q28280099 | ||
| Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond | Q29614697 | ||
| Quantitative Synthesis in Systematic Reviews | Q29614894 | ||
| Predictive value of brachial flow-mediated dilation for incident cardiovascular events in a population-based study: the multi-ethnic study of atherosclerosis | Q30435137 | ||
| Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort study | Q30491056 | ||
| Inflammatory markers and poor outcome after stroke: a prospective cohort study and systematic review of interleukin-6. | Q30878935 | ||
| Carotid artery intima-media thickness, carotid plaque and coronary heart disease and stroke in Chinese | Q33377448 | ||
| Critical appraisal of CRP measurement for the prediction of coronary heart disease events: new data and systematic review of 31 prospective cohorts | Q33377856 | ||
| Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study | Q33592543 | ||
| Improving global vascular risk prediction with behavioral and anthropometric factors. The multiethnic NOMAS (Northern Manhattan Cohort Study) | Q33613171 | ||
| The potential of genes and other markers to inform about risk | Q33718762 | ||
| Comparative validity of 3 diabetes mellitus risk prediction scoring models in a multiethnic US cohort: the Multi-Ethnic Study of Atherosclerosis | Q33880878 | ||
| Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality: a meta-analysis | Q34100632 | ||
| Importance of treadmill exercise time as an initial prognostic screening tool in patients with systolic left ventricular dysfunction | Q34380854 | ||
| Quantitative electrocardiographic measures and long-term mortality in exercise test patients with clinically normal resting electrocardiograms | Q34425217 | ||
| Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project | Q34534248 | ||
| Diagnosis of osteoporosis and assessment of fracture risk | Q34678969 | ||
| Hyponatremia and mortality among patients on the liver-transplant waiting list | Q34820619 | ||
| Genotype score in addition to common risk factors for prediction of type 2 diabetes | Q34884376 | ||
| Clinical risk factors, DNA variants, and the development of type 2 diabetes | Q34884389 | ||
| Novel and conventional biomarkers for prediction of incident cardiovascular events in the community | Q34960396 | ||
| Assessing the value of risk predictions by using risk stratification tables | Q34969023 | ||
| The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults | Q34991895 | ||
| Assessment of claims of improved prediction beyond the Framingham risk score | Q35015499 | ||
| Almost all articles on cancer prognostic markers report statistically significant results | Q36991618 | ||
| Cardiovascular disease risk prediction with and without knowledge of genetic variation at chromosome 9p21.3. | Q37069329 | ||
| Lipoprotein particle profiles by nuclear magnetic resonance compared with standard lipids and apolipoproteins in predicting incident cardiovascular disease in women | Q37146755 | ||
| Prediction of incident hypertension risk in women with currently normal blood pressure | Q37165226 | ||
| Reasons or excuses for avoiding meta-analysis in forest plots | Q37195565 | ||
| Postprandial glucose improves the risk prediction of cardiovascular death beyond the metabolic syndrome in the nondiabetic population. | Q37319194 | ||
| Ascites improves upon [corrected] serum sodium plus [corrected] model for end-stage liver disease (MELD) for predicting mortality in patients with advanced liver disease. | Q37343682 | ||
| Prognostic value of multiple biomarkers in American Indians free of clinically overt cardiovascular disease (from the Strong Heart Study). | Q37350726 | ||
| Predicting the 30-year risk of cardiovascular disease: the framingham heart study | Q37356527 | ||
| C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men. | Q37363683 | ||
| Prognostic value of biomarkers in heart failure: application of novel methods in the community | Q37413803 | ||
| Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures | Q37435521 | ||
| Development of a nomogram for individualizing hip fracture risk in men and women | Q38506588 | ||
| Assessing prostate cancer risk: results from the Prostate Cancer Prevention Trial | Q39752227 | ||
| Common genetic markers and prediction of recurrent events after ischemic stroke in young adults. | Q39950517 | ||
| Inflammatory biomarkers and the prediction of coronary events among people at intermediate risk: the EPIC-Norfolk prospective population study | Q39964508 | ||
| The additive prognostic value of end-systolic pressure-volume relation in patients with diabetes mellitus having negative dobutamine stress echocardiography by wall motion criteria | Q39982594 | ||
| Congestive heart failure is associated with lipoprotein components in statin-treated patients with coronary heart disease Insights from the Incremental Decrease in End points Through Aggressive Lipid Lowering Trial (IDEAL). | Q39991771 | ||
| Chromosome 9p21.3 coronary heart disease locus genotype and prospective risk of CHD in healthy middle-aged men. | Q40126925 | ||
| Association of very highly elevated C-reactive protein concentration with cardiovascular events and all-cause mortality | Q43250055 | ||
| Does acute hyperglycemia add prognostic value to the GRACE score in individuals with non-ST elevation acute coronary syndromes? | Q43266928 | ||
| Reclassification calculations for persons with incomplete follow-up | Q43679277 | ||
| Enhancement of absolute fracture risk prognosis with genetic marker: the collagen I alpha 1 gene. | Q43686744 | ||
| Use of serum homocysteine to predict stroke, coronary heart disease and death in ethnic Chinese. 12-year prospective cohort study. | Q44186212 | ||
| Several methods to assess improvement in risk prediction models: Extension to survival analysis | Q44667332 | ||
| Prognosis and prognostic research: Developing a prognostic model | Q45768539 | ||
| Contribution of novel biomarkers to incident stable angina and acute coronary syndrome: the PRIME Study | Q45796818 | ||
| Anemia for risk assessment of patients with acute coronary syndromes | Q45892224 | ||
| How much does HDL cholesterol add to risk estimation? A report from the SCORE Investigators. | Q45927317 | ||
| Impact of gender on risk stratification by stress echocardiography | Q46094610 | ||
| Lipoprotein predictors of cardiovascular events in statin-treated patients with coronary heart disease. Insights from the Incremental Decrease In End-points Through Aggressive Lipid-lowering Trial (IDEAL). | Q46152808 | ||
| Continuous relationships between non-diabetic hyperglycaemia and both cardiovascular disease and all-cause mortality: the Australian Diabetes, Obesity, and Lifestyle (AusDiab) study. | Q46171495 | ||
| PSA kinetics provide improved prediction of survival in metastatic hormone-refractory prostate cancer | Q46474880 | ||
| Prognosis and prognostic research: application and impact of prognostic models in clinical practice | Q46516876 | ||
| Evaluation of the Framingham risk score in the European Prospective Investigation of Cancer-Norfolk cohort: does adding glycated hemoglobin improve the prediction of coronary heart disease events? | Q46549322 | ||
| A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study | Q46564797 | ||
| Polymorphisms associated with cholesterol and risk of cardiovascular events | Q46691746 | ||
| Relationships between lipoprotein components and risk of myocardial infarction: age, gender and short versus longer follow-up periods in the Apolipoprotein MOrtality RISk study (AMORIS). | Q46734939 | ||
| Association of kidney function and albuminuria with cardiovascular mortality in older vs younger individuals: The HUNT II Study | Q46856822 | ||
| Prognostic value of biomarkers during and after non-ST-segment elevation acute coronary syndrome | Q48520047 | ||
| Predicting outcome after acute and subacute stroke: development and validation of new prognostic models | Q48638450 | ||
| Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study | Q51470643 | ||
| The effect of including C-reactive protein in cardiovascular risk prediction models for women | Q51797108 | ||
| What makes a good predictor?: the evidence applied to coronary artery calcium score | Q51829443 | ||
| The effect of including quantitative heel ultrasound in models for estimation of 10-year absolute risk of fracture | Q57306132 | ||
| P433 | issue | 4 | |
| P304 | page(s) | 1094-1105 | |
| P577 | publication date | 2011-02-16 | |
| P1433 | published in | International Journal of Epidemiology | Q6051393 |
| P1476 | title | Use of reclassification for assessment of improved prediction: an empirical evaluation | |
| P478 | volume | 40 |
| Q50318034 | A methodology review on the incremental prognostic value of computed tomography biomarkers in addition to Framingham risk score in predicting cardiovascular disease: the use of association, discrimination and reclassification |
| Q45343601 | A minimal net reclassification improvement to assess predictions of intensive care mortality |
| Q40809666 | Activated factor VII-antithrombin complex predicts mortality in patients with stable coronary artery disease: a cohort study. |
| Q89338036 | Application of net reclassification index to non-nested and point-based risk prediction models: a review |
| Q45232818 | Assessing improvement in disease prediction using net reclassification improvement: impact of risk cut-offs and number of risk categories |
| Q45388848 | Biomarkers in sepsis |
| Q38165077 | Bleeding risk prediction models in atrial fibrillation. |
| Q35232523 | Cardiac biomarkers and acute kidney injury after cardiac surgery |
| Q35165334 | Commentary: Reporting standards are needed for evaluations of risk reclassification |
| Q38223336 | Design and analysis of metabolomics studies in epidemiologic research: a primer on -omic technologies |
| Q42138242 | Further insight into the incremental value of new markers: the interpretation of performance measures and the importance of clinical context |
| Q84330546 | New Metrics for Assessing Diagnostic Potential of Candidate Biomarkers |
| Q46988536 | Novel and established anthropometric measures and the prediction of incident cardiovascular disease: a cohort study |
| Q34448829 | Predicting risk of mortality in dialysis patients: a retrospective cohort study evaluating the prognostic value of a simple chest X-ray |
| Q37220830 | Predicting risk of type 2 diabetes mellitus with genetic risk models on the basis of established genome-wide association markers: a systematic review |
| Q30559655 | Prediction of vascular risk after stroke - protocol and pilot data of the Prospective Cohort with Incident Stroke (PROSCIS). |
| Q24289043 | Prognostic effect size of cardiovascular biomarkers in datasets from observational studies versus randomised trials: meta-epidemiology study |
| Q93090933 | Reclassification calibration test for censored survival data: performance and comparison to goodness-of-fit criteria |
| Q33917180 | Reclassification of risk of death with the knowledge of D-dimer in a cohort of treated HIV-infected individuals |
| Q36171681 | Risk reclassification analysis investigating the added value of fatigue to sickness absence predictions |
| Q47436259 | Simpson's paradox in the integrated discrimination improvement |
| Q43650485 | The accuracy of predicting cardiovascular death based on one compared to several albuminuria values |
| Q51150112 | Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement |
| Q51152907 | Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement |
| Q34837497 | Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement |
| Q51150478 | Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement |
| Q51157282 | Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement |
| Q34978306 | Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group |
| Q44249154 | What to expect from net reclassification improvement with three categories |
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