Discrimination slope and integrated discrimination improvement – properties, relationships and impact of calibration

No abstract is available for this paper.

• Publication year

  2017

• Venue

  Statistics in Medicine

• Publication date

  2017-12-10

• Fields of study

  Mathematics, Medicine

• Identifiers
  DOI 10.1002/sim.7139PMID 27699818
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• A calibration hierarchy for risk models was defined: from utopia to empirical data.

  2016cited by this paper
• Predictive accuracy of novel risk factors and markers: A simulation study of the sensitivity of different performance measures for the Cox proportional hazards regression model

  2015cited by this paper
• Net reclassification improvement and integrated discrimination improvement require calibrated models: relevance from a marker and model perspective

  2014cited by this paper
• A note on the evaluation of novel biomarkers: do not rely on integrated discrimination improvement and net reclassification index

  2014influential reference
• Understanding increments in model performance metrics

  2012cited by this paper
• A Unified View of Performance Metrics: Translating Threshold Choice into Expected Classification Loss C` Esar Ferri

  2012cited by this paper
• Quantifying discrimination of Framingham risk functions with different survival C statistics

  2012cited by this paper
• Several methods to assess improvement in risk prediction models: Extension to survival analysis

  2011cited by this paper
• Relations of Biomarkers of Distinct Pathophysiological Pathways and Atrial Fibrillation Incidence in the Community

  2010influential reference
• Coefficients of Determination in Logistic Regression Models—A New Proposal: The Coefficient of Discrimination

  2009influential reference
• Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond

  2008cited by this paper
• Comments on ‘Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond’ by M. J. Pencina et al., Statistics in Medicine (DOI: 10.1002/sim.2929)

  2008cited by this paper
• PAV and the ROC convex hull

  2007cited by this paper
• Strictly Proper Scoring Rules, Prediction, and Estimation

  2007cited by this paper
• Loss Functions for Binary Class Probability Estimation and Classification: Structure and Applications

  2005cited by this paper
• Loss Functions for Binary Class Probability Estimation

  2003cited by this paper
• Regression Modeling Strategies

  2003cited by this paper
• The Area under the ROC Curve and Its Competitors

  1991influential reference
• Order restricted statistical inference

  1988cited by this paper
• External correspondence: Decompositions of the mean probability score

  1982influential reference
• VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY

  1950cited by this paper

• Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance.

  2025cites this paper
• Personalized Treatment of Patients with Coronary Artery Disease: The Value and Limitations of Predictive Models

  2025cites this paper
• Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models

  2025cites this paper
• Development and validation of survival nomograms in elder triple-negative invasive ductal breast carcinoma patients

  2024cites this paper
• The clinical applications of ensemble machine learning based on the Bagging strategy for in-hospital mortality of coronary artery bypass grafting surgery

  2024cites this paper
• Predicting risk of peripartum blood transfusion during vaginal and cesarean delivery: A risk prediction model

  2023cites this paper
• Machine-learning predictions for acute kidney injuries after coronary artery bypass grafting: a real-life muticenter retrospective cohort study

  2023cites this paper
• Number of positive lymph nodes combined with the logarithmic ratio of positive lymph nodes predicts long-term survival for patients with node-positive parotid gland carcinoma after surgery: a SEER population-based study

  2023cites this paper
• Net Reclassification Index Statistics Do Not Help Assess New Risk Models.

  2022cites this paper
• A machine learning–Based model to predict early death among bone metastatic breast cancer patients: A large cohort of 16,189 patients

  2022cites this paper
• A Comparison of Clinical Prognostic Indices in Elderly Patients with Diffuse Large B-Cell Lymphoma Treated with a Pegylated Liposomal Doxorubicin Combination Regimen in China

  2022cites this paper
• Predictive Ability of European Heart Surgery Risk Assessment System II (EuroSCORE II) and the Society of Thoracic Surgeons (STS) Score for in-Hospital and Medium-Term Mortality of Patients Undergoing Coronary Artery Bypass Grafting

  2021cites this paper
• Radiomics model based on shear-wave elastography in the assessment of axillary lymph node status in early-stage breast cancer

  2021cites this paper
• Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer

  2020cites this paper
• Predicting 1-Year Mortality After Cardiac Surgery Complicated by Prolonged Critical Illness: Derivation and Validation of a Population-Based Risk Model.

  2020cites this paper
• Calibration slope versus discrimination slope: shoes on the wrong feet.

  2020cites this paper
• Estimation of Atherosclerotic Cardiovascular Disease Risk Among Patients in the Veterans Affairs Health Care System

  2020cites this paper
• TRIPOD statement: a preliminary pre-post analysis of reporting and methods of prediction models

  2020cites this paper
• Measures for evaluation of prognostic improvement under multivariate normality for nested and nonnested models

  2019cites this paper
• Nomogram For The Prediction Of Malignancy In Small (8–20 mm) Indeterminate Solid Solitary Pulmonary Nodules In Chinese Populations

  2019cites this paper
• CMAR_A_225739 9439..9448

  2019cites this paper
• Early identification of preterm neonates at birth with a Tablet App for the Simplified Gestational Age Score (T-SGAS) when ultrasound gestational age dating is unavailable: A validation study

  2019cites this paper
• Comments on “Net reclassification index at event rate: Properties and relationships”

  2019cites this paper
• Developing Implementable Risk Prediction Models with Electronic Health Records Data

  2019cites this paper
• Single‐number summary and decision analytic measures can happily coexist

  2019cites this paper
• Relation of Serum and Urine Renal Biomarkers to Cardiovascular Risk in Patients with Type 2 Diabetes Mellitus and Recent Acute Coronary Syndromes (From the EXAMINE Trial).

  2019cites this paper
• Early Identification of Preterm Neonates at Birth With a Tablet App for the Simplified Gestational Age Score (T-SGAS) When Ultrasound Gestational Age Dating Is Unavailable: Protocol for a Validation Study

  2019cites this paper
• A comparison of statistical learning methods for deriving determining factors of accident occurrence from an imbalanced high resolution dataset.

  2019cites this paper
• The power‐integrated discriminant improvement: An accurate measure of the incremental predictive value of additional biomarkers

  2019cites this paper
• Body mass index versus bioelectrical impedance analysis for classifying physical function impairment in a racially diverse cohort of midlife women: the Study of Women’s Health Across the Nation (SWAN)

  2019cites this paper
• Kidney Biomarkers and Decline in eGFR in Patients with Type 2 Diabetes.

  2018cites this paper
• Assessing markers from ambulatory laboratory tests for predicting high-risk patients.

  2018cites this paper
• Early Identification of Preterm Neonates at Birth With a Tablet App for the Simplified Gestational Age Score (T-SGAS) When Ultrasound Gestational Age Dating Is Unavailable: Protocol for a Validation Study (Preprint)

  2018cites this paper
• Quantifying the added value of new biomarkers: how and how not

  2018cites this paper
• Comparison of Duke Activity Status Index with cardiopulmonary exercise testing in cancer patients

  2018cites this paper
• First things first: risk model performance metrics should reflect the clinical application

  2017cites this paper
• Clinical risk reclassification at 10 years

  2017cites this paper
• Event rate net reclassification index and the integrated discrimination improvement for studying incremental value of risk markers

  2017influential citation
• Genetic Drivers of von Willebrand Factor Levels in an Ischemic Stroke Population and Association With Risk for Recurrent Stroke

  2017cites this paper
• Authors' response to comments

  2017cites this paper
• Asymptotic distribution of ∆AUC, NRIs, and IDI based on theory of U‐statistics

  2017cites this paper
• Risk assessment with newer statistical metrics

  2017cites this paper